PhD Germain Arribarat
email: germain.arribarat@inserm.fr

MD, PhD Ofer Pasternak

MD Amaury De Barros

MD Monique Galitzky

MD, PhD Oliver Rascol

PhD Patrice Péran

Substantia nigra locations of iron-content, free-water and mean diffusivity abnormalities in moderate stage Parkinson's disease

Keywords: Parkinson's disease, Substantia Nigra, MRI, Iron, Free-water

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

I Introduction

A key pathophysiological characteristic of Parkinson disease (PD) is the loss of the dopaminergic neurons of the substantia nigra (SN) [START_REF] Damier | The substantia nigra of the human brain. II. Patterns of loss of dopamine-containing neurons in Parkinson's disease[END_REF], particularly in the SN pars compacta (SNc). Clinically, conventional magnetic resonance imaging (MRI) has been useful primarily for excluding underlying pathologies (e.g., vascular lesions). Because it is non-invasive and more widely available than other nuclear neuroimaging modalities, MRI has also been an advantageous technology for investigating potential biomarkers of PD onset and progression.

Postmortem histology [START_REF] Galvan | Pathophysiology of parkinsonism[END_REF] and in vivo MRI analyses [START_REF] Péran | Magnetic resonance imaging markers of Parkinson's disease nigrostriatal signature[END_REF] have demonstrated iron deposition in the SN of PD patients. Iron deposition can be quantitated with the T2* relaxation rate (R2*) measure in MRI data. R2* mapping studies have confirmed elevated iron content in the SN of PD patients, compared to levels in healthy controls (HCs) [START_REF] Péran | Magnetic resonance imaging markers of Parkinson's disease nigrostriatal signature[END_REF], [START_REF] Martin | Midbrain iron content in early Parkinson disease: a potential biomarker of disease status[END_REF]. However, iron accumulation in the SN seems not to be specific to sporadic PD because it has been found in patients with multiple system atrophy as well [START_REF] Barbagallo | Multimodal MRI assessment of nigro-striatal pathway in multiple system atrophy and Parkinson disease[END_REF], [START_REF] Péran | MRI supervised and unsupervised classification of Parkinson's disease and multiple system atrophy[END_REF].

Two longitudinal studies with the aim of characterizing PD progression reported conflicting R2* results among themselves. The first showed an increase SN signals [START_REF] Ulla | Is R2* a new MRI biomarker for the progression of Parkinson's disease? A longitudinal follow-up[END_REF] whereas the second failed to detect a change [START_REF] Wieler | Longitudinal midbrain changes in early Parkinson's disease: Iron content estimated from R2*/MRI[END_REF]. This discrepancy in results could be related to inconsistency in the definition of the spatial localization of the SN. Some studies have used manual segmentation of the whole SN with average markers as indices [START_REF] Péran | Magnetic resonance imaging markers of Parkinson's disease nigrostriatal signature[END_REF], [START_REF] Barbagallo | Multimodal MRI assessment of nigro-striatal pathway in multiple system atrophy and Parkinson disease[END_REF], whereas others have used manual definition of regions-of-interest (ROIs) in the SN [START_REF] Martin | Midbrain iron content in early Parkinson disease: a potential biomarker of disease status[END_REF], [START_REF] Ulla | Is R2* a new MRI biomarker for the progression of Parkinson's disease? A longitudinal follow-up[END_REF], [START_REF] Du | Distinct progression pattern of susceptibility MRI in the substantia nigra of Parkinson's patients[END_REF], [START_REF] Vaillancourt | High-resolution diffusion tensor imaging in the substantia nigra of de novo Parkinson disease[END_REF].

Diffusion MRI sensitizes the MRI signal to the displacement of water molecules. Diffusion tensor imaging (DTI) is a popular diffusion MRI analysis method that provides several measures including fractional anisotropy (FA), which is sensitive to the directionality of the molecule displacement, and mean diffusivity (MD), which is sensitive to molecule displacement amplitude. DTI studies have reported reduced FA of the SN in PD patients compared to HCs subjects [START_REF] Vaillancourt | High-resolution diffusion tensor imaging in the substantia nigra of de novo Parkinson disease[END_REF], [START_REF] Lehéricy | Magnetic resonance imaging of the substantia nigra in Parkinson's disease[END_REF], which may reflect the loss of dopaminergic neurons.

However, a meta-analysis found no significant FA differences between PD patients and HCs in any SN regional analyses [START_REF] Schwarz | Diffusion tensor imaging of nigral degeneration in Parkinson's disease: A region-of-interest and voxel-based study at 3 T and systematic review with meta-analysis[END_REF]. A new diffusion MRI analysis method based on the calculation of a two-tensor model has been introduced [START_REF] Ofori | Free water improves detection of changes in the substantia nigra in parkinsonism: A multisite study[END_REF], wherein the fractional volume of free-water (FW) within a voxel is estimated. FW analysis has produced promising results with respect to the observation of higher values for the posterior SN in PD patients compared to HCs in single-and multi-site cohorts [START_REF] Ofori | Increased free water in the substantia nigra of Parkinson's disease: A single-site and multi-site study[END_REF].

Both diffusion MRI

II Materials and methods

Subjects

Thirty-nine subjects participated in this study between 2014 and 2016, including 21 HCs (each individual's data were collected in a single session) and 18 PD patients, whose data were collected at two visits separated by approximately 2 years [mean interscan interval ± standard deviation (SD), 24.5 ± 4.4 months] (Table 1). PD patients were enrolled from outpatient clinics of the Toulouse PD Expert Center with the following inclusion criteria: [START_REF] Damier | The substantia nigra of the human brain. II. Patterns of loss of dopamine-containing neurons in Parkinson's disease[END_REF] diagnosis of PD according to international diagnostic criteria [START_REF] Hughes | Accuracy of clinical diagnosis of idiopathic Parkinson's disease: A clinico-pathological study of 100 cases[END_REF] [START_REF] Folstein | Mini-mental state'. A practical method for grading the cognitive state of patients for the clinician[END_REF]]; [START_REF] Barbagallo | Multimodal MRI assessment of nigro-striatal pathway in multiple system atrophy and Parkinson disease[END_REF] no deep brain stimulation treatments received; [START_REF] Péran | MRI supervised and unsupervised classification of Parkinson's disease and multiple system atrophy[END_REF] no evidence of movement artifacts, vascular brain lesions, brain tumors, or marked cortical or subcortical atrophy on MRI scans. Two radiologists with substantial clinical experience examined all MRI series for the patients considered for this study to exclude any patients with potential brain abnormalities evident in conventional fluidattenuated inversion recovery and T1-weighted images. Motor disabilities were assessed by way of Motor Examination scores of the Unified Parkinson's Disease Rating Scale (UPDRS-III). Written informed consent was obtained from all patients. This study was conducted according to the ethical principles of the Declaration of Helsinki and approved by the Toulouse Ethics Committee.

Acquisition

We used a mMRI protocol similar to our previous study [START_REF] Péran | Magnetic resonance imaging markers of Parkinson's disease nigrostriatal signature[END_REF] i.e. T1, T2 relaxometry, diffusion tensor imaging (DTI) (further details in Supplementary files).

Image analysis

Image processing was performed using FSL v5 (www.fmrib.ox.ac.uk/fsl/). Head movement parameters (rotation/translation) were estimated between Parkinson's patients and healthy subjects. FW markers and FW corrected diffusion tensor markers were calculated with a custom MATLAB R2013a code [START_REF] Ofori | Free water improves detection of changes in the substantia nigra in parkinsonism: A multisite study[END_REF]. R2* markers were calculated with a custom MATLAB R2013a code [START_REF] Péran | Voxel-based analysis of R2* maps in the healthy human brain[END_REF] (for more details see Supplementary files). As a result of this processing, the FW, FAT, FA, MDT, MD and R2* maps were generated in the MNI space.

Spatial definition of the SN

The regions of interest (ROIs) were hand-drawn for each subject in MNI space by two trained raters, blinded to the map, subject groups, and visit.

Posterior and anterior SN subregions

The ROIs were hand drawn in the substantia nigra based upon the b0 images, in MNI space.

The red nucleus was used as a reference because it is anatomically close to the substantia nigra and is located on the same slice as the dorsal substantia nigra. Each ROI included 8 voxels that spanned two axial slices on each image. The dorsal region contained a square ROI of four voxels (2 × 2) and the ventral ROI consisted of a square ROI of four voxels (2 × 2), based on previous work [START_REF] Ofori | Increased free water in the substantia nigra of Parkinson's disease: A single-site and multi-site study[END_REF], [START_REF] Vaillancourt | Effects of aging on the ventral and dorsal substantia nigra using diffusion tensor imaging[END_REF]. ROIs were drawn on the left and right anterior and posterior regions of the SN. The posterior ROIs were in voxels largely lateral to the anterior ROIs. Across subjects, the MNI coordinates for the SN ROIs were as follows: posterior right x = -12 to -14, y = 20 to 22, and z = -10 to -12; posterior left, x = 10 to 12, y = 22 to 24, z = -10 to -12; anterior right x = -6 to -8.0, y = 14 to 16, and z = -10 to -12; and anterior left, x = 6.0 to 8.0, y = 14 to 16, z = -10 to -12. (see Fig. 1).

Whole SN

The whole SN was identified as a T2* hypo-intensity band in the midbrain, as described previously [START_REF] Péran | Magnetic resonance imaging markers of Parkinson's disease nigrostriatal signature[END_REF], [START_REF] Barbagallo | Multimodal MRI assessment of nigro-striatal pathway in multiple system atrophy and Parkinson disease[END_REF] (see Fig. 1).

Voxel-based analysis

The R2*, MD, FA, FW, MDT, and FAT values were compared with a whole SN binary mask using two-sample unpaired t-tests. The mask was defined in the standard MNI space. This analysis was performed with the tool "randomize" from the FSL group. The number of permutations used was 5000. P-values (<0.05) were corrected with the family-wise error rate method for multiple comparisons. Uncorrected P-values (<0.05) were also examined.

Statistical analysis

For each subject and each ROI, we calculated mean values. We used the Shapiro-Wilk test of normality distributions to verify the appropriateness of analyzing sample means of the dependent variables (P-values >0.05). To determine MRI parameter sensitivity to group differences, mean ROI values were compared between PD patients and HCs with two-sample t-tests. To determine MRI parameter sensitivity to disease progression within the PD group, mean ROI values were compared between baseline and 2-year follow-up time points with paired t-tests. For voxel-based longitudinal analysis, only MRI parameters that showed significant group differences were submitted to the analysis. To explore relationships of putative MRI markers with clinical scales, we performed multiple regression analysis for age, disease duration, Montreal Cognitive Assessment score, and UPDRS motor score for mean imaging parameter values by SN region and subregions.

III Results

Demographic and clinical information

The participants' demographic and clinical characteristics are summarized and compared across the PD and HCs groups in Table I. The groups were similar with respect to age and sex. From the baseline time point to the year 2 times point, MDS-UPDRS Part III scores increased significantly; no other parameters changed significantly.

ROI selection

Absolute inter-and intra-rater agreement was > 94% (kappa>0.81, P-values<0.001). No difference in head movements were found, either for rotation or translation (T2*_Rot: Pvalues =0.13. T2*_Trans: P-values = 0.48; DTI_Rot P-values = 0.67. DTI_Trans P-values = 0.76), between Parkinson's patients and healthy subjects. When the SN was defined by the whole structure, PD patients displayed significantly higher R2* values than HCs, but there were no significant group differences for diffusion MRI markers (Table II). With selection of the posterior SN, PD patients had significantly higher FW, MD, and MDT values than HCs, but there were no significant group differences for R2*, FA, or FAT (Table II). With selection of the anterior SN, PD patients had significantly higher R2* values than HCs, with no significant differences for diffusion MRI markers in the anterior region (Table II). Voxel-based analysis in the SN revealed significant R2* cluster (n = 42) (see Fig. 2), FW and MD cluster (n=11 and n = 15) in the SN between the PD and HCs groups, with uncorrected p values. With corrected-p, only one significant R2* cluster (n = 11) is revealed.

T2* versus diffusion imaging

The two SN subpart selections had different outcomes for the T2* and diffusion MRI markers. When the anterior part of the SN was defined, only the R2* data yielded significant differences between the PD and HCs groups (see Fig. 3). Conversely, when the posterior part of the SN was defined, several diffusion parameters (FW, MD, and MDT) differed significantly between the PD and HCs groups (see Fig. 3), but there was no difference in R2*.

In summary, the T2* and diffusion MRI measures produced group differences selectively for the anterior SN and posterior SN, respectively.

DTI versus FW

When the posterior SN was defined, PD patients had significantly increased FW and MDT values compared with HCs. With conventional DTI, MD was significantly increased in the PD group relative to HCs. FA as well as FAT did not show significant group difference.

Longitudinal analysis

The markers found to have group differences for the whole SN, or for the subregions of the SN did not significantly differ between the baseline and 2-year follow-up time points for the PD group.

MRI parameters & clinical scales

In the PD cohort, none of the baseline MRI parameters in the SN (with any kind of ROI) correlated with clinical score changes from baseline to the 2-year follow-up time point.

IV Discussion

We collected a unique dataset that allowed comparisons of iron-related and diffusion markers in the SN and thus enabled us to determine their relative sensitivities. We found that, relative to HCs, PD patients had increased R2* in the anterior SN and increased FW and MD in the posterior SN, findings suggestive of potentially distinct pathologies in the different SN subparts as well as distinct roles for these MRI markers in PD.

Diagnostic markers: the role of SN spatial definition

Our finding of increased R2* in PD patients compared to HCs in the anterior SN was confirmed in part by voxel-based analysis. An overlap between the anterior SN and the coordinates of significant voxels was obtained. The cluster found by voxel-based analysis seemed to correspond to the anterior medial SNc, in agreement with previous histochemical studies demonstrating elevated iron in PD specifically in the SNc [START_REF] Ayton | Nigral iron elevation is an invariable feature of Parkinson's disease and is a sufficient cause of neurodegeneration[END_REF], [START_REF] Dexter | Alterations in the levels of iron, ferritin and other trace metals in Parkinson's disease and other neurodegenerative diseases affecting the basal ganglia[END_REF]. One possible explanation for the detection of iron depositions in the anterior parts of the SN may be due to the absence of nigrosome degeneration in this area. The absence of partial volume with extracellular water due to the neuronal degeneration does not perturb the iron-related T2* signal. Our finding of FW increases in the posterior SN in PD patients compared to HCs is consistent with previous studies [START_REF] Ofori | Longitudinal changes in free-water within the substantia nigra of Parkinson's disease[END_REF], [START_REF] Planetta | Free-water imaging in Parkinson's disease and atypical parkinsonism[END_REF]. In addition, we found increased MD and MDT in the posterior SN of PD patients. As demonstrated by Mishra et al., 2015, FW can be linearly mapped to MD and could explain both extracellular and cellular changes [START_REF] Mishra | Toward tract-specific fractional anisotropy (TSFA) at crossing-fiber regions with clinical diffusion MRI[END_REF]. The location of posterior SN appears to correspond to the location of the nigrosome-1 [START_REF] Blazejewska | Visualization of nigrosome 1 and its loss in PD: pathoanatomical correlation and in vivo 7 T MRI[END_REF]. Its absence could explain the increase of FW and MD. FW identifying atrophy/cellular deterioration, versus T2* identifying iron depositions. The specific increase of R2* in the anterior SN concomitant with the specific increase of FW in posterior SN suggests a complementary aspect of the two parameters and, perhaps, different underlying pathophysiological processes. This potential complementarity is not surprising considering previous interpretations of PD-related changes wherein SN R2* increases are classically interpreted as increased iron content due to neurotoxicity [START_REF] Zecca | Iron, brain ageing and neurodegenerative disorders[END_REF], while FW and MD increases are classically interpreted as a rarefaction of the cells [START_REF] Ofori | Increased free water in the substantia nigra of Parkinson's disease: A single-site and multi-site study[END_REF], [START_REF] Planetta | Free-water imaging in Parkinson's disease and atypical parkinsonism[END_REF].

The role of SN spatial definition is crucial for PD, particularly for SNc. At the time of the onset of PD symptoms, a significant portion of neurons containing neuromelanin (NM) were lost. Iron deposition occurs at the same time as this loss. T2/T2*-weighted images are not sensitive to NM and therefore localization of the SNc. Neuromelanin-sensitive MRI (MRI-NM) can generate a contrast to NM [START_REF] Trujillo | Contrast mechanisms associated with neuromelanin-MRI[END_REF], [START_REF] Sulzer | Neuromelanin detection by magnetic resonance imaging (MRI) and its promise as a biomarker for Parkinson's disease[END_REF]. Some studies have demonstrated that the SN observed in T2/T2* contrasts is spatially non-conform to the NM-MRI [START_REF] Lehéricy | 7 tesla magnetic resonance imaging: A closer look at substantia nigra anatomy in Parkinson's disease[END_REF]. The T2/T2* sequences, should be spatially correlated with the NM-MRI, to assess the potential impact of neuromelanin and its potential role in iron disease mechanisms, particularly in a sub-regional approach. When SNpc is defined by neuromelanin-sensitive MRI, Langley et al. showed that the mean value of R2* is significantly increased in PD [START_REF] Langley | Reproducible detection of nigral iron deposition in 2 Parkinson's disease cohorts[END_REF]. We assume that in the future, it will be interesting to compare the topographic aspect of the R2*/MD/FW biomarkers studied in SN of patients with intermediate PD with neuro-melanin imaging.

Disease progression marker

We found no significant change over time in FW/MD/R2* maps in patients with PD, despite the use of different ROI types to describe the SN. Our lack of significant changes over time could be a ceiling effect for iron content due to advanced disease stage. Indeed, our PD patient group had a disease duration of about 7 years on average, a duration corresponding to advanced PD. The current findings are consistent with Guttuso et al., [START_REF] Guttuso | Substantia Nigra Free Water Increases Longitudinally in Parkinson Disease[END_REF], with a baseline mean idiopathic Parkinson disease duration of 7.1 years. Hopes et al. (2016) observed R2* changes in the SN over 2 years in early-stage PD patients, but this same study did not show differences in SN R2* when early and advanced patient were analyzed together, consistent with the ceiling effect interpretation. R2* in the anterior SN and FW in the posterior SN seem to be sensitive enough to detect cross-sectional differences (PD patients versus HCs) but not to detect progression in advanced PD patients. The prior free-water longitudinal findings [START_REF] Ofori | Longitudinal changes in free-water within the substantia nigra of Parkinson's disease[END_REF] were observed in early stage PD with a different cohort, which was not the case of the present study. In addition, this prior work showing longitudinal free-water changes in early PD has been replicated in the Parkinson's Progression Markers Initiative (PPMI) cohort in early stage PD [START_REF] Burciu | Progression marker of Parkinson's disease: a 4-year multi-site imaging study[END_REF]. In addition, other groups have also found FA changes longitudinally in the substantia nigra in early stage PD [START_REF] Loane | Aberrant nigral diffusion in Parkinson's disease: A longitudinal diffusion tensor imaging study[END_REF].

Previous data have demonstrated changes in SN pigmentation and iron deposition with healthy aging [START_REF] Vaillancourt | Effects of aging on the ventral and dorsal substantia nigra using diffusion tensor imaging[END_REF]. Therefore, a longitudinal evaluation of PD appears to require simultaneous evaluation of the same imaging sequences in HC, particularly for early stage evaluation of the disease. With this approach, the inclusion of an atypical cohort would allow comparison of imaging methods based on R2*/diffusion measurements for SN, in the anterior and posterior parts.

The lack of longitudinal change sensitivity could be also explained by a relative highresolution acquisition using in this current study compared to previous studies (e.g. FW: [START_REF] Ofori | Longitudinal changes in free-water within the substantia nigra of Parkinson's disease[END_REF]; T2*: [START_REF] Péran | Magnetic resonance imaging markers of Parkinson's disease nigrostriatal signature[END_REF]) that decrease signal on noise ratio. In addition, diffusion multi-shell acquisitions are preferred to obtain bi-tensor fit more stable [START_REF] Mishra | Toward tract-specific fractional anisotropy (TSFA) at crossing-fiber regions with clinical diffusion MRI[END_REF].

MRI markers of PD-related SN pathophysiology

Gerlach, Double, Youdim, and Riederer (2006) proposed several hypotheses to explain iron accumulation in the SN of PD patients, including increased iron in dopaminergic neurons as well as microglial activation, which may be undetectable at an advanced stage. This hypothesis is aligned with our results and with Devos' research group's study [START_REF] Hopes | Magnetic Resonance Imaging Features of the Nigrostriatal System: Biomarkers of Parkinson's Disease Stages?[END_REF] demonstrating a lack of longitudinal R2* changes in advanced PD patients and a lack R2* differences between early and advanced patients. Even if R2* is not specific to only one iron-bound protein [START_REF] Gerlach | Potential sources of increased iron in the substantia nigra of parkinsonian patients[END_REF], the R2* relaxometry method has convincing histochemical results in postmortem brain tissue studies [START_REF] Galvan | Pathophysiology of parkinsonism[END_REF].

Pasternak and colleagues have demonstrated that FW mapping provides some information about tissue microstructure, including changes related to atrophy, neuroinflammation, and cellular density [START_REF] Guttuso | Substantia Nigra Free Water Increases Longitudinally in Parkinson Disease[END_REF]. This increase, in the SN posterior parts, has been interpreted as cell rarefaction, an interpretation which can also explain concomitant MD increases. This delineation of the SN may correspond to the dorsolateral SNc, a site of dopaminergic neuron degeneration.

Cross-sectional analysis of diffusion MRI and T2* markers did not reveal a relationship of R2* or FW values in the SN with motor deficit. This lack of a correlation between MRI markers and direct indexes of clinical disability (UPDRS-III score) in the PD group may be due to the patients being assessed while on dopaminergic medications alleviating their symptoms [START_REF] Péran | Magnetic resonance imaging markers of Parkinson's disease nigrostriatal signature[END_REF], [START_REF] Hopes | Magnetic Resonance Imaging Features of the Nigrostriatal System: Biomarkers of Parkinson's Disease Stages?[END_REF], [START_REF] Du | Imaging nigral pathology and clinical progression in Parkinson's disease[END_REF]. The aforementioned ceiling effect in advanced PD patients could also help to explain the lack of correlation.

A potential limitation of this study could be the number of patients included. Our monocentric longitudinal study makes it difficult to recruit a large cohort of PD patients but enables us to avoid confounding factors related to multicenter studies (e.g., center and sequence effects).

The study design was appropriate for confirming previously highlighted results and evaluating the different SN definitions with a variety of imaging markers. Secondly, our study investigated advanced PD patients on medication. Longitudinal studies on de novo untreated PD patients will be crucial to confirming the potential utility of R2*/MD/FW markers for diagnosis and disease progression monitoring. The possibility of a larger cohort will also clarify the relationship between the sexes regarding the deposition and metabolism of iron in the brain, particularly over time. Also, it would be interesting to include a longitudinal group of HC to assess physiological variability and a better appreciation of the biomarker topography.

Conclusion

The specific increase in R2* in the anterior SN concomitant with the specific increase in FW in the posterior SN suggests a complementary aspect of the two parameters and, possibly, different underlying pathophysiological processes. The boundaries between SNr and SNc are difficult to define, due to the groups of SNc neurons deeply embedded in the SNr. The small size of the SNr and its position make it difficult to obtain a clear image with current methods.

  and T2* relaxation studies have shown promise in differentiating PD from HCs brains. Comparison of these two sequences may help to clarify the relationship between microstructural features and iron accumulation in the SN and provide additional information regarding PD pathology. The present study is a cross-sectional and longitudinal analysis comparing T2* relaxation and diffusion MRI data, while also comparing different spatial definitions of the SN. We collected diffusion and T2* imaging data, placed them in a standard space, and compared averages of each parameter according to two different SN spatial definitions: Péran et al.'s (2010) definition employed in T2* experiments, and Vaillancourt et al.'s (2009) definition used in FW diffusion experiments. Additionally, we used a voxel-based method to investigate the SN with a data-driven approach.

  These results demonstrate the need for high resolution imaging in the substantia nigra allowing the distinction of new patients with Parkinson's disease (PD) at an early stage from healthy individuals. Specific image processing techniques, such as noise reduction and super-resolution reconstruction, can improve image quality. Finally, with the possibility of obtaining phase imaging without adding time acquisition, it could be interesting to compare a multi-contrast acquisition collection (R2*/QSM/SWI) with multishell diffusion imaging and neuromelaninsensitive imaging data.

Table II : Region of interest

 II 567.08 4219.16 417.12 4166.63 376.65 4059.95 419.43 ns ns Anterior SN MD 648.68 93.25 652.28 77.35 646.30 78.48 656.23 100.18 ns ns Anterior SN FAT 4754.59 486.26 4706.70 394.66 4644.42 346.58 4602.45 300.55 ns ns Anterior SN MDT 499.10 43.81 501.54 42.37 498.44 45.34 491.96 25.99 ns ns MD: (× 10 -3 mm 2 /s). The variables are multiplied (x10 -FW, x1000 -MD and MDT, x10000 -FA and FAT) for a better statistical representation. All values correspond to the mean values of ROI. SD = Standard Deviation. ns = not significant.. Significant p-values are indicated in bold (**:p<0.01; ***:p<0.001).

		Healthy Controle N=21	Parkinson's Patients Baseline (N=18) Baseline (N=15) Year 2 (N=15)	PD Baseline vs Healthy Subject	PD Baseline vs PD Year 2
		Mean	DS	Mean	SD	Mean	SD	Mean	SD	p-value	p-value
	Posterior SN R2star	25.02	2.14	25.96	3.12	26.01	3.36	26.66	3.09	ns	ns
	Posterior SN FW	10.99	4.52	15.65	4.93	14.97	4.78	15.13	3.53	0.004**	ns
	Posterior SN FA	4578.55 564.03 4426.59 554.56 4473.69 575.53 4378.7 322.27	ns	ns
	Posterior SN MD	673.32 78.93 744.00 79.48 730.68 77.36 732.52 74.91	0.008**	ns
	Posterior SN FAT	5160.39 522.75 5249.99 450.03 5266.06 472.55 5170.30 295.67	ns	ns
	Posterior SN MDT	538.41 29.23 557.75 29.05 551.62 27.97 551.41 30.79	0.04*	ns
	Anterior SN R2star 27.26	2.97	31.05	3.61	31.43	3.74	31.72	3.86	0.001**	ns
	Anterior SN FW	11.82	4.86	11.81	3.35	11.59	3.27	12.68	6.01	ns	ns
	Anterior SN FA 4231.21 Whole SN R2star 29.96	2.97	34.47	3.03	34.74	3.27	35.81	3.33 < 0.001***	ns
	Whole SN FW	12.17	4.19	12.99	2.28	12.14	2.40	12.67	2.50	ns	ns
	Whole SN FA	4520.67 388.71 4470.71 360.34 4388.07 310.21 4413.88 240.69	ns	ns
	Whole SN MD	668.57 77.13 672.37 50.18 669.72 53.38 657.83 41.21	ns	ns
	Whole SN FAT	5123.94 377.30 5126.74 381.99 5040.17 331.30 5032.79 205.39	ns	ns
	Whole SN MDT	506.66 28.40 502.33 28.13 497.10 27.27 491.03 16.39	ns	ns
	R2*: s -1 ;

Acknowledgments

This study was supported by a "Recherche clinique translationnelle" grant from INSERM-DGOS 2013-2014. We thank the Centre d'Investigation Clinique (CIC) for the global coordination of the clinical study and the Inserm/UPS UMR1214 Technical Platform for the MRI acquisitions.

The study was sponsored by Inserm and funded by a "Recherche clinique translationnelle" grant from INSERM-DGOS (2013-2014).

Authors' Roles


Silvia Lasala
email: silvia.lasala@univ-lorraine.fr

Romain Privat

Philippe Arpentinier

Jean-Noël Jaubert
email: jean-noel.jaubert@univ-lorraine.fr

Note on the inconsistent definition assigned in the literature to the heat capacity of the so-called "equilibrium hydrogen

Keywords: Equilibrium hydrogen, para-hydrogen, ortho-hydrogen, heat capacity

In classical chemical engineering thermodynamics, constant-pressure heat capacity has a rigorous -non-negotiable -definition. With this communication we aim to make researchers aware of a thermodynamically inconsistent definition assigned, in the literature, to the heat capacity of equilibrium gaseous mixtures of reacting ortho-hydrogen and para-hydrogen (the so-called "equilibrium-hydrogen mixtures"). Along this note we show that in order to define its heat capacity, the equilibrium reacting mixture is inconsistently assimilated to a pseudo pure component having the same enthalpy as the reacting mixture of p-H2 and o-H2 at chemical equilibrium. In so doing, the pseudo-component heat capacity aggregates not only sensibleheat effects but also thermal effects due to compositional changes.

INTRODUCTION

In nature, molecular hydrogen exists in the form of a mixture of two nuclear isomeric forms, ortho-hydrogen and para-hydrogen [START_REF] Farkas | Orthohydrogen, parahydrogen and heavy hydrogen[END_REF], in the proportions dictated by the temperature of the system, its dynamic variation and the kinetic characteristics of the (slow) reaction o-H2 ⇌ p-H2. More specifically, "equilibrium hydrogen" denotes, in the literature, the reactive system characterized by the proportion of ortho-and para-hydrogen dictated by the condition of thermodynamic equilibrium.

Since the 1930', many authors have been mentioning or treating the problem of computing the thermodynamic properties of equilibrium hydrogen under the assumption of perfect gas mixture.

In the context of a research project focused on the study of hydrogen liquefaction and storage, we came across the dissemination, in the literature, of an inconsistent presentation of the heat capacity of the equilibrium hydrogen mixture. Indeed, although modelled as perfect gas system, equilibrium hydrogen is surprisingly presented as a mixture whose specific heat capacity, at some temperatures, does not take an intermediate value between the ones of the two pure components that form the mixture, ortho-hydrogen and para-hydrogen [START_REF] Farkas | Orthohydrogen, parahydrogen and heavy hydrogen[END_REF][START_REF] Giauque | The entropy of hydrogen and the third law of thermodynamics the free energy and dissociation of hydrogen[END_REF][START_REF] Dennison | A note on the specific heat of the hydrogen molecule[END_REF][START_REF] Haar | Ideal gas thermodynamic functions and isotope exchange functions for the diatomic hydrides, deuterides, and tritides. monograph 20[END_REF][START_REF]Specific heats at low temperatures[END_REF][START_REF] Le Roy | Accurate thermodynamic properties of the six isotopomers of diatomic hydrogen[END_REF][START_REF] Valenti | The influence of the thermodynamic model of equilibrium-hydrogen on the simulation of its liquefaction[END_REF][START_REF] Valenti | Hydrogen liquefaction and liquid hydrogen storage[END_REF][START_REF] Leachman | Hydrogen[END_REF][START_REF] Vaytet | On the role of the H 2 ortho:para ratio in gravitational collapse during star formation[END_REF]. Such a result is unquestionably in contradiction with well-established mathematical relationships that apply to perfect gas mixtures.

To our knowledge, only Pitzer [START_REF] Pitzer | Thermodynamics[END_REF] tried to explain the occurrence of such a behavior, by saying that the "heat capacity of the equilibrium mixture includes a term for the heat of conversion […]". According to such an explanation, the reason of the deviation from the expected trend of the specific heat capacity of equilibrium hydrogen has to be sought in the occurrence of the chemical reaction which characterizes hydrogen at thermodynamic equilibrium, o-H2 ⇌ p-H2. However, Pitzer's statement clearly does not explain why a quantity, which does not verify the thermodynamic definition of the specific heat capacity of a mixture, is designated in the literature "specific heat capacity of equilibrium hydrogen". It is, indeed, neither theoretically correct, nor of common practice to include the heat of reaction directly in the specific heat capacity of a reactive system. In front of a hodgepodge of undigested thoughts available in the open literature, this note aims at clarifying how were defined the properties of "equilibrium hydrogen" and especially its heat capacity.

DISCUSSION

From classical chemical-engineering thermodynamics, the specific heat capacity of a mixture (of known mole-fraction vector z, temperature T and pressure p) is defined as:

( ) ( ) , , ,
, ,

p mix T p p h T p T c =  ∂    ∂   z z z (1)
(where h denotes the specific enthalpy of the mixture). In case of a nc-component perfect gas mixture, the constant pressure specific heat capacity results to be given by:

( ) ( ) • , • , mix T p h T T c =   ∂   ∂     z z z (2)
as the enthalpy of a perfect gas mixture is pressure-independent. Note that symbol "•" designates a perfect gas property. Analogously, by remembering that the heat-capacity change on mixing ( )

M p c
is zero for a perfect gas mixture, one has:

( ) ( ) • • 1 , mix pure i nc p p i i T c z c T = = ∑ z ( 3
)
where:

( ) ( )

• • pure i pure i T p dh T dT c = (4)
is the specific heat capacity of pure perfect-gas i. According to Eq. ( 3), the specific heat capacity of any binary mixture takes an intermediate value between the specific heat capacity of the components which form that mixture. For completeness, the equilibrium composition of the system o-H2 ⇌ p-H2 -that can be determined by well-known theoretical considerations [START_REF] Farkas | Orthohydrogen, parahydrogen and heavy hydrogen[END_REF][START_REF] Atkins | Atkins' physical chemistry[END_REF] -is a function of the temperature only. Fig. 1 shows the graphical evolution of this function. An approximate correlation for this curve is reported by Wilhelmsen et al. [START_REF] Wilhelmsen | Reducing the exergy destruction in the cryogenic heat exchangers of hydrogen liquefaction processes[END_REF]. Published values for specific heat capacities of equilibrium hydrogen follow the curve named "Literature equilibrium hydrogen" in Fig. 2. Consistently with Eq. (1) (i.e., the rigorous definition of a heat capacity, coincident with Eq. ( 4) for a pure fluid), it is possible to show from the quantic theory [START_REF] Pitzer | Thermodynamics[END_REF] that the specific heat capacities of pure para-hydrogen and ortho-hydrogen follow the dashed curves represented in Fig. 1. Moreover, Fig. 1 shows the specific heat capacity of the equilibrium hydrogen mixture calculated accordingly to the uncontested Eq. (3) (namely, "Actual equilibrium hydrogen"), considering the determined composition of the equilibrium mixture (Fig. 1) and the specific heat capacities of pure ortho-hydrogen and para-hydrogen.

Being equilibrium hydrogen a binary mixture of ortho-hydrogen and para-hydrogen, its specific heat capacity should be, by definition, between that of these two pure components and should coincide with the curve labeled "Actual equil. hydrogen" in Fig. 2.

Figure 2. Reduced specific heat capacity of para-hydrogen, ortho-hydrogen, literature 'equilibrium-hydrogen' and actual equilibrium hydrogen.

From the above, it is possible to conclude that the specific heat capacity of "literature equilibrium hydrogen" totally disagrees with the theory. To clarify this discrepancy, we need to go back to the definition of "Literature equilibrium hydrogen" specific heat capacity.

The heat capacity of "Literature equilibrium-hydrogen" is calculated, under the assumption of perfect gas, as:

• , ( ) ( ) • equilibrium mix p T T T dh dT c     = equ. z (5)
Differently from the rigorous definition given in Eq. ( 2), Eq. ( 5) is unquestionably a derivative of the enthalpy of the mixture with respect to temperature but evaluated along the equilibrium path, i.e., at variable (rather than constant) composition. Indeed, as previously discussed (see Fig. 1), composition of the equilibrium mixture is temperature-dependent. We can conclude that Eq. ( 5) is thus not the correct -thermodynamically consistent -definition of the specific heat capacity of the mixture o-H2 ⇌ p-H2. What is titled, in the literature, "equilibrium hydrogen heat capacity" is, in fact, the heat capacity of a fictive pure component having the same enthalpy as a reacting mixture of para-hydrogen and orthohydrogen at chemical equilibrium. In other words, the term represented by Eq. ( 5) is actually a pure-component quantity aggregating the sensible-heat and reaction thermal effects of an equilibrium hydrogen mixture:

( ) ( ) 2 2 - - , . (5)
In support to such a conclusion, we observe that the molar thermal power, Q n , exchanged by the equilibrium hydrogen mixture along its isobaric cooling from inlet temperature, in T , to the outlet temperature, out T , can be equivalently calculated either treating such a system as a fictive pure component characterized by the specific heat capacity curve named in Fig. 2 "Lit. equilibrium hydrogen": ( )

Q c T n ⋅ = ∫ (7)
or according to the rigorous method:

( ) ( ) ( ) ( ) ( ) 2 2 2 2 • , - - • , - - out in out in T eq in p pure p H p H T T eq in p pure o H o H T R out Q z T c T dT n z T c T dT H T n ξ + + + + ∆ °= ∫ ∫ (8)
where n ξ is the extent of reaction specific to the molar flow, which can be determined by the knowledge of the equilibrium composition [START_REF] Wilhelmsen | Reducing the exergy destruction in the cryogenic heat exchangers of hydrogen liquefaction processes[END_REF], and

( ) R out H T ∆ °
the enthalpy of reaction at the outlet temperature:

( ) ( ) ( ) ( ) ( ) 2 2 2 2 - - • , - • , - out ref out ref p H o H T R out p pure p H f ref T T p pure o H f ref T H T H T c T dT H T c T dT               -      ∆ °∆ + ∆ + = ∫ ∫ o o (9) being ( )
i f ref H T ∆ o
the standard enthalpies of formation of ortho-hydrogen and para-hydrogen, at the reference temperature. Furthermore, we would like to highlight that the design of the heat capacity of a fictive pure fluid being thermally equivalent to a reactive mixture at thermodynamic equilibrium is possible only when the mixture behaves as a perfect gas and if the reaction does not involve a variation of the number of moles of the reactive system, i.e., if:

i i NR NP i i υ υ =
∑ ∑ , that is:

0 NC i i υ = ∑ (10)
where NR and NP denote the number of reactants and products, respectively, and υi is the stoichiometric coefficient of each i-th species involved in the reaction. Indeed, for these types of reactive systems, the composition, z, at chemical equilibrium and thus the corresponding enthalpy ( )

• equilibrium 1 h pure i nc i i h z T • =     = ⋅     ∑ is only function of temperature.
Proof can be obtained by writing the condition of thermodynamic equilibrium (see Eq. [START_REF] Pitzer | Thermodynamics[END_REF] in which the mathematical expression of the temperature-dependent equilibrium constant only depends on the equilibrium composition):

. . (10) ( )

i NC i i i i NC i i NC i i NC i i perf gas Eq f K T p p z p z υ υ υ υ     °      °  = = = ∑ ∏ ∏ ∏ ( 11
)
i f is the fugacity of the i-th pure component and p° is standard-state pressure.

The composition at chemical equilibrium and the corresponding enthalpy ( )

• equilibrium 1 h pure i nc i i h z T • =     = ⋅    
∑ depending only on temperature, application of Eq. ( 5) makes it possible to design the heat capacity of a fictive pure perfect gas thermally equivalent to the reactive mixture. For different types of reactive systems, the variation of the equilibrium composition with pressure would entail the necessity of defining the heat capacity of a fictive pure perfect gas for each pressure level. Such an approach would thus loose its peculiar simplification feature, which is the reason at the basis of its application. Finally, insist on the physical difference between the constant-pressure calorimetric quantities treated in this work, we would like to stress that calorimetric measurements performed on reactive fluids characterized by non-negligible reaction rates would lead to measure the calorimetric quantity represented by Eq. ( 5), which contains the contribution of the heat of reaction. In particular, in the ideal case of a perfectly catalyzed reaction between o-H2 and p-H2, such calorimetric measurement would lead to obtain the curve labeled "Lit. equil.-hydrogen" in Fig. 2. On the other side, in the absence of a catalyzer, the reaction between o-H2 and p-H2 is so slow that the effect of the reaction is negligible in the characteristic time of these experimental measurements. As a consequence, calorimetric measurements at constant-pressure on such a system would lead to measured quantities which respond to Eq.

(3): the actual specific heat capacity of mixtures composed by o-H2 and p-H2, in their timeinvariant proportion fixed by the initial composition of the system under analysis.

Figure 1 .

 1 Figure 1. Mole fraction of para-hydrogen in perfect gas equilibrium hydrogen.

  ,

	c	mix p	Eq	T	=	reacti o H ve mixture p H enthalpy as the having the same p fictive pure fluid c	T

ACKNOWLEDGEMENTS

The French company AIR LIQUIDE, is gratefully acknowledged for sponsoring this research.


domain: sdv chim

text:
Jiaqi Luo
email: jiaqi.luo@uni-saarland.de

Christina Hein

Jaafar Ghanbaja

Jean-François Pierson

Frank Mücklich

Bacteria accumulate copper ions and inhibit oxide formation on copper surface during antibacterial efficiency test

Keywords: copper, oxidation, ions, ICP-MS, EDS, E. coli

Copper surface after antibacterial test against E. coli was examined in the aspect of corrosion. Results from scanning electron microscope (SEM), grazing incidence X-ray diffractometer (GIXRD) and Raman spectroscopy together confirmed less oxidation on copper surface with the presence of E. coli. The inhibition of the cuprous oxide (Cu2O) layer instead ensured the continuous exposure of copper surface, letting localised corrosion attacks observable and causing a stronger release of copper ions. These phenomena are attributed to the fact that E. coli act as ions reservoirs where high amount of copper accumulation were found by energy dispersive X-ray spectroscopy (EDS).

Introduction

Copper has been drawing the attention of microbiologists in the recent years [START_REF] Vincent | Contact killing and antimicrobial properties of copper[END_REF][START_REF] Turner | Metal-based antimicrobial strategies[END_REF][START_REF] Rock | Innovative Methods of Hospital Disinfection in Prevention of Healthcare-Associated Infections[END_REF][START_REF] Muller | Antimicrobial surfaces to prevent healthcare-associated infections: a systematic review[END_REF]. Copper and its ions, copper oxides as well as oxide nanoparticle, all of them have shown the toxicity against various bacteria or virus [START_REF] Rosenberg | Rapid in situ assessment of Cu-ion mediated effects and antibacterial efficacy of copper surfaces[END_REF][START_REF] Rotini | Salinity-Based Toxicity of CuO Nanoparticles, CuO-Bulk and Cu Ion to Vibrio anguillarum[END_REF]. This antimicrobial property brings copper into the hygiene market, and without a doubt, a great amount of studies have focused on this aspect. Copper or copper contained coatings [START_REF] Wu | Preparation, antibacterial effects and corrosion resistant of porous Cu-TiO2 coatings[END_REF][START_REF] Souli | Reduction of Environmental Contamination With Multidrug-Resistant Bacteria by Copper-Alloy Coating of Surfaces in a Highly Endemic Setting[END_REF], particles [START_REF] Gilbertson | Shape-Dependent Surface Reactivity and Antimicrobial Activity of Nano-Cupric Oxide[END_REF][START_REF] Ben-Sasson | In situ surface functionalization of reverse osmosis membranes with biocidal copper nanoparticles[END_REF], fabrics [START_REF] Dhineshbabu | Antibacterial activity of hybrid chitosan-cupric oxide nanoparticles on cotton fabric[END_REF][START_REF] Demir | N-Halamine-Modified Antimicrobial Polypropylene Nonwoven Fabrics for Use against Airborne Bacteria[END_REF], textiles [START_REF] Irene | Copper-coated textiles: armor against MDR nosocomial pathogens[END_REF][START_REF] Turalija | Copper(i)oxide microparticles -synthesis and antimicrobial finishing of textiles[END_REF], composites [START_REF] Usman | Enhanced mechanical, thermal and antimicrobial properties of poly(vinyl alcohol)/graphene oxide/starch/silver nanocomposites films[END_REF][START_REF] Kara | Structural and Antibacterial Properties of PP/CuO Composite Filaments Having Different Cross Sectional Shapes[END_REF] are being fabricated and widely investigated, in terms of their antimicrobial efficiencies the relevant applications.

To determine the antimicrobial efficiency of a certain material, or more specifically of a surface, a certain method has to be applied. It allows us to measure the survival of microbe, to quantify the antibacterial efficacy, and in the end, to compare them. Most of these methods could be grouped into two main types that worth being briefly introduced. One is where no suspension with bacteria needs to be prepared, for instance, in the inhibition zone determination [START_REF] Usman | Enhanced mechanical, thermal and antimicrobial properties of poly(vinyl alcohol)/graphene oxide/starch/silver nanocomposites films[END_REF][START_REF] Cano | Copper sulfate-embedded and copper oxide-embedded filter paper and their antimicrobial properties[END_REF]. The coupon to be tested will be placed on a nutrient agar plate already covered with bacteria. Since the antibacterial agents could release and further diffuse from the coupon, a gradient of antibacterial substance is supposed to form from the centre of the coupon outwards. After certain incubation periods, there should be a zone around the coupon where no obvious growth of colony is observed. The antibacterial efficiency can be thus compared by the size or radius of these zones. Moreover, this method may tell better the diffusion rate of the corresponding antibacterial substance on the agar plate. It is fairly popular in research especially in testing novel antibacterial composites or fabrics.

In another type of method, a drop of suspension composed of bacteria and buffer solution needs to be applied on the coupon. After several designed time points, part of the suspension is withdrawn. There are a number of approach to determine the bacterial survival in the suspension. One way to do this is by fluorescence microscopy [START_REF] Wu | Role of the Surface Nanoscale Roughness of Stainless Steel on Bacterial Adhesion and Microcolony Formation[END_REF][START_REF] Ellinas | Is There a Threshold in the Antibacterial Action of Superhydrophobic Surfaces?[END_REF], which is also often called Live/Dead staining test. In this test, a red-fluorescent indicator (often propidium iodide) is used to label the DNA after membrane damage happens, so as to distinguish whether bacteria are intact or not. Therefore the change of colour directly tells the killing effect of a substance. Another popular approach is to count the colony-forming unit (CFU) [START_REF] Santo | Bacterial Killing by Dry Metallic Copper Surfaces[END_REF][START_REF] Tripathy | Enhancing the Bactericidal Efficacy of Nanostructured Multifunctional Surface Using an Ultrathin Metal Coating[END_REF]. The withdrawn suspension will be first properly diluted in series and then plated on an agar plate. The cultivable bacteria will grow as colonies that could be big enough to be identified and directly counted. This method not only produces highly statistical and reproducible results, but also allows to track the details of antibacterial efficiency as a function of time. This is why it has been chosen in most of our recent studies [START_REF] Luo | Killing of bacteria by copper, cadmium, and silver surfaces reveals relevant physicochemical parameters[END_REF][START_REF] Hans | Laser cladding of stainless steel with a copper-silver alloy to generate surfaces of high antimicrobial activity[END_REF][START_REF] Hans | Role of Copper Oxides in Contact Killing of Bacteria[END_REF], and again applied in this study.

Although all the methods listed above offer almost sufficient information of the survival of bacteria, nevertheless, there is a hidden respect not being considered: the coupons themselves. The bacteria are inactivated by the antibacterial agents, which are released from the specific surface in most of the cases. This indicates that the surface itself is also under a series of change along the time. In the case of copper, it is corrosion that should be further considered [START_REF] Zhao | Effect of surface passivation on corrosion resistance and antibacterial properties of Cu-bearing 316L stainless steel[END_REF][START_REF] Liu | Corrosion of antibacterial Cu-bearing 316L stainless steels in the presence of sulfate reducing bacteria[END_REF]. Furthermore, the corrosion phenomena occurring on the surface, in fact, also alter the surface itself during these antibacterial efficiency tests.

In other words, these methods are not always charactering the initial surface, in contrary, a constantly changing surface. Take this into account have two main advantages: one is to know exactly the actual surface being characterised, the other one is to start exploring its potential aging effects when it comes to the daily life applications.

Oxidation is certainly drawing attention among the common corrosion phenomena. By mainly electrochemical means, copper oxides growth on copper or its alloys in buffer solution [START_REF] Toparli | State of the Surface of Antibacterial Copper in Phosphate Buffered Saline[END_REF] or synthetic perspiration [START_REF] Foster | Corrosion of Cu-5Zn-5Al-1Sn (89% Cu, 5% Zn, 5% Al, 1% Sn) Compared to Copper in Synthetic Perspiration During Cyclic Wetting and Drying: The Fate of Copper[END_REF] are recently reported.

Different types of oxides (Cu2O, CuO), hydroxide (Cu(OH)2) or other corrosion products (Cu2Cl(OH)3) could be identified.

Their thickness and in-depth distribution were correlated with different experimental conditions, such as the chemical composition of the original surface, the components of the applied solution and the contact period. However, there is a few research that has considered the aging of copper surface in a bacterial suspension, not to mention to probe the role of bacteria in this corrosion system. On the other hand, how bacteria interact with or influence by various kinds of metallic ions or particles have been extensively investigated, in terms of the transportation of ions and the accumulation in different organelles [START_REF] Carter | Fluorescent Sensors for Measuring Metal Ions in Living Systems[END_REF][START_REF] Hohle | Bacterial outer membrane channel for divalent metal ion acquisition[END_REF]. But again, bacterial influence on the surface through these effects are not the focus in these studies.

One recent research [START_REF] Wakshlak | Antibacterial activity of silver-killed bacteria: the "zombies" effect[END_REF] revealed the re-release of silver from the silver-killed bacteria back to the solution. It offers a hint about the interaction between ions enriched bacteria and their effect on the environment. Here in the current study, we extended the focus from the solution back to the initial ions releaser: the copper surface itself. The main question we aim to answer is: during the copper release process that kills bacteria, does the existence of these bacteria affect the corrosion process as well? Therefore we investigated the role of E. coli in copper surface chemical changes during the antibacterial efficiency test. Ex-situ approaches were performed to distinguish the changes in morphology and composition in the outermost copper surface. The inhibition effect of oxides was described and its possible causes were put forward, taking account of the role of bacteria on the amount of copper ion in suspension.

Materials and Methods

Materials

Coupons of copper (99.99%, K09, Wieland) were first ground with a silicon carbide sandpaper (end with grit number as P600), then they were cleaned by an ultrasonic bath with ethanol and finally dried by air.

Solutions

Phosphate-buffered saline (PBS) was prepared with NaH2PO4. 1H2O (Merck, Germany, final concentration 0.01 M), NaCl (VWR, Germany, final concentration 0.14 M) and pure water for analysis (Merck, Germany). Its pH value was adjusted by adding NaOH to 7.4, sterilised by an autoclave after preparation. The preparation of PBS with bacteria could also be referred to the antibacterial efficiency determination in previous publication [START_REF] Molteni | Killing of Bacteria by Copper Surfaces Involves Dissolved Copper[END_REF]. In brief, the E. coli K12 strain was grown aerobically overnight in Lysogeny broth (LB) medium at 37 ⁰C in a water bath with a speed of 220 rpm. The stationary cells from 5 mL culture were collected by centrifugation for 15 min at 5000 x g, washed and centrifuged three times with PBS, and finally resuspended in 5 mL of the same type of buffer solution. The initial average cell count was around 3 X 10 9 to 5 X 10 9 CFU/ml.

For the suspension S. cohnii, the Tryptic soy broth (Fluka) medium was chosen.

Corrosion protocol

Coupons of copper were placed in a water-saturated atmosphere at room temperature when 20 µL of various solutions were applied on them with a pipette. After certain exposure time (30 minutes, 1 hours, 3 hours and 6 hours), these solutions were withdrawn with a pipette and the coupons were dried in a ventilated room. These steps are chosen in order to keep it as similar as the antibacterial efficiency tests as described in our other research [START_REF] Luo | Killing of bacteria by copper, cadmium, and silver surfaces reveals relevant physicochemical parameters[END_REF][START_REF] Hans | Role of Copper Oxides in Contact Killing of Bacteria[END_REF].

Surface corrosion characterization

Scanning electron microscope (SEM, Helios NanoLab600, FEI) was used to compare the morphology of copper surfaces after various corrosion experiments. The chemical composition was obtained by Energy dispersive X-ray spectroscopy (EDS) with an acceleration voltage as 5 kV. For further confirmation of corrosion products covering the surfaces as well as the form of copper in bacteria, Raman spectroscopy (Raman, laser source with 633 nm, inVia, Renishaw) with a 50X optical microscopy (OM) and high resolution grazing incidence X-ray diffractometer (GIXRD, Cu Kα with 1 degree grazing angle, PANalytical X'Pert PRO-MPD) were applied. All these images and spectra were obtained within 24 hours after corrosion treatment.

pH values measurements

The pH values were obtained from pH-indicator strips (Merck, Germany), designed for a range from 6.5 to 10.0, with 5 gradations between 7.1 and 8.1, namely 7.1, 7.4, 7.7, 7.9 and 8.1. During the withdrawal process described in section 2.3, 10 µL of various solutions were separated and applied again on these strips.

Copper content determination

For the samples (PBS or PBS with E. coli) to be directly measured, following almost every step in the corrosion protocol, only whenever the exposure time is reached, 10 µL samples were withdrawn by repetitive pipetting and diluted in 2.990 mL 1 wt% nitric acid (Merck, Germany). For the measurement of supernatant, every three 10 µL samples were transferred and mixed in SafeSeal 1.5 mL tubes. After being centrifuged for 5 min at 5 krpm, 10 µL of supernatant were collected and diluted in nitric acid as mentioned above. For all samples, before measured by inductively coupled plasma mass spectrometry (ICP-MS, 7500cx, Agilent), 3 µl of 10 mg/l scandium and caesium internal standard solutions were added to the samples. For calibration, standards with 0.1, 0.5, 2.5, 10, 50, 250 and 1000 µg/L of copper were used. After obtaining the results with a unit of ppb, the final values with a unit of µM were calculated with the fold of dilutions and molar mass 63.55 g/mol for copper. The average values and standard deviation were obtained by three independent experiments.

Bacteria imaging and chemical mapping

Scanning transmission electron microscopy (STEM) mode of transmission electron microscopy (TEM, JEM-ARM 200F, JEOL) was applied with a voltage of 200 kV. The bacteria were treated with copper surface for 3 hours as described above.

Before having them transferred on a Ni grid, they were diluted 1:10 with pure water for analysis.

Results and Discussion

Evolution of surface morphology always reflects the corrosion behaviours. Therefore, to directly observe the corrosion phenomena on copper surface, high resolution SEM images were taken and shown in Figure 1. After 3 hours in pure PBS, granular sub-micron formation were found on the copper surface. Consequently, the as-ground morphology becomes less obvious. However, with the addition of E. coli, similar corrosion products can hardly be found. In addition to the remained bacteria, some area were suffering localised corrosion attacks, resulting in sub-micron scale pits. No other SEM observable features that can be identified on this bacterial treated surface. On the other side, it almost kept the original morphology of the untreated as-ground copper surface (SI, Figure 1).

To further identify these corrosion products, GIXRD were applied to collect the near surface phase information presented in Figure 2 (a). The range of diffraction peak of (111) planes of Cu2O was chosen, since it is expected to be the strongest peak of the Cu2O without any preferential orientation growth. A clear peak is recorded from the surface corroded by pure PBS, confirming the main corrosion products described above as crystallised Cu2O. By contrast, the diffractogram from the coupon treated with E. coli suspension is rather flat.

Since no copper oxides related diffraction peaks could be assigned, Raman was applied owing to its higher sensitivity, where a slight oxidation is shown (Figure 2 (b)). Comparatively, these oxides signals are with lower background and less obvious oxides' peaks, especially around 149 cm -1 and 216 cm -1 . In addition, compared to the relatively large detection zone of GIXRD, Raman results could be correlated with more localised features. For example in Figure 2 (c), some dark areas found in OM are confirmed by SEM as the positions where localised corrosion attacks occurred. In these positions, higher Raman signal of Cu2O were recorded and shown in Figure 2 (d). Although these localised corrosion sites are far smaller than the macroscopic pits that could be observed directly in OM, they do match the features described traditional pitting corrosion theories [START_REF] Hoeppner | Pitting corrosion: morphology and characterization[END_REF]. They describe the formation of corrosion products around the opening (cathode) of these cavities (anode). These product could gradually seal the pits, which has not yet been observed on our experiments though. Apart from small difference, all the abovementioned findings confirm the considerable changes on copper surface after adding E. coli into PBS: the Cu2O formation becomes less dominant and more non-uniform on copper surface.

Corrosion behaviour of a certain material is never an independent phenomenon: it is closely correlated to the surrounding environment which is applied, that is to say, the solutions (PBS or bacterial suspensions) on copper coupons. It is known from the Poubaix diagram of copper, that Cu2O formation favours alkaline environment, while acidity increases, it dissolves and exists as cupric ions [START_REF] Toparli | State of the Surface of Antibacterial Copper in Phosphate Buffered Saline[END_REF]. For this reason, although PBS is defined and prepared as a buffer solution, it would still be helpful to know whether the actual condition in these corrosion tests already exceeds the buffer capacity. Therefore, the pH values of the samples were checked and given in Table 1. For the original PBS, no matter with or without bacterial addition, their pH values were 7.4 as designed. However, in both cases, this value rose after corrosion tests, indicating an alkaline shift. Most importantly, when E. coli was added, the solution became even more alkaline, which theoretically should be more beneficial to the formation of Cu2O. Therefore, there must be other reasons instead of the acidity that inhibit the oxide growth in bacterial condition.

To preliminarily verify if E. coli could interactive with Cu2O actively, another case was designed to place E. coli PBS suspension on pure PBS treated copper surface (therefore with existing Cu2O). Their GIXRD results (SI, Figure 2) show that the previously formed Cu2O layer does not change obviously after bacterial suspension treatment, suggesting that E. coli do not act as an active role in deteriorating Cu2O layer.

After the examination of the corrosion products on these surfaces, we then shifted the interest to the solution, namely the withdrawn droplets. Copper content in pure PBS and E. coli PBS suspension were measured and plotted in Figure 3. In pure PBS, the concentration of copper has quickly reached a plateau in 30 minutes, which at least lasted for 3 hours. With E. coli addition, on the other hand, the curve evidently follows another trend: it significantly becomes higher in the whole period.

The variety of these two patterns could be ascribed to the barrier effect of copper oxides coverage. As fewer oxides were found in the latter case, a bigger portion of bare copper was exposed to the solution, that is to say, can still be corroded by the solution. For this reason, release of copper ion can be thus less hindered and therefore copper content gradually increase could be observed. In addition, the shown copper content data can also be transferred into weight loss of the original surface if needed. Because for pure copper coupons, the amount of copper measured in solution should be equal to the weight loss.

However, it should be noted that the contribution from the oxide growth will not be considered in this way as they are still attached to the original surface.

But why did the oxide growth rate slowdown so distinctly? Similar trends of copper content were also reported with S. cohnii addition [START_REF] Hahn | Pure and Oxidized Copper Materials as Potential Antimicrobial Surfaces for Spaceflight Activities[END_REF]. S. cohnii is a type of bacteria with less mobility, as shown in SI Figure 3, its PBS suspension has rather similar corrosive influence on the copper surface: no obvious oxide layer could be found in 3 hours. This helps us to exclude the potential effects induced by bacterial mobility that may change the local near-surface circumstance, such as substance concentration and fluid flow rate. Now back to the rise of copper content, which was previously ascribed to the bonding effect of complexing agents [START_REF] Hahn | Pure and Oxidized Copper Materials as Potential Antimicrobial Surfaces for Spaceflight Activities[END_REF].

Inspired by this aspect, another test was designed to detect the amount of copper in supernatant (green curve in Figure 3). This result implies another possibility. These values represent the amount of free copper ions in the suspension. They are relatively low, fewer than those in PBS by almost a factor around 5, in spite of the slight increase along the time. It could probably mean that the concentration of free copper ions are still far away from its equilibrium that leads to oxides formation.

Apparently, the following question needs to be answer could be: where are the rest of the huge amount of copper? Logically, if they are not in the supernatant, then they could only be with bacteria. Figure 4 presents the copper treated E. coli observed by SEM. Prolonging the treatment time, in the first place, the shape of bacteria becomes more regular. However, since no fixation or drying steps were adopted in order to preserve the potential copper ion accumulation within bacteria, morphology of these bacteria might not be interpreted as their original state.

On the other hand, local elemental analysis done by EDS further provides more interesting information. First of all, the main elemental composition of E. coli itself is always considered as a combination of C, H, O and N [START_REF] Stockar | Does microbial life always feed on negative entropy? Thermodynamic analysis of microbial growth[END_REF]. Other elements should be thus considered to have an environmental source. Therefore, the actual EDS on untreated E. coli (shown in SI Figure 4) also revealed certain amounts of Na and P, which could come from the compositions of LB growth medium or PBS.

Besides, signal of Si comes from the silicon substrate that is supporting the bacteria. The most significant finding belongs to those Cu peaks. Not only have their signal been successfully collected, their intensity also progressively increases proportional to treatment time. This trend indeed represents the copper amount accumulated by the bacteria, confirming both our results and the latest reported results obtained from ICP-MS measurements [START_REF] Hahn | Antimicrobial properties of ternary eutectic aluminum alloys[END_REF].

As generally reported, 3-hour is a period already assures at least 99.9% E. coli in PBS can be killed on copper surface due to the released copper ions [START_REF] Hans | Role of Copper Oxides in Contact Killing of Bacteria[END_REF]. Interestingly, this accumulation process still continued after 3 hours, as the intensity from Cu peak reached another higher value in 6 hours. A similar test with sterile E. coli instead of viable E. coli was carried out, where bacteria were found with high copper content as well (shown in SI Figure 5). This may indicate the observed accumulation process should not be considered as an active process fulfilled by the living bacteria or biofilm, but rather a passive process in this condition. Meanwhile, these results also suggest that the inhibition of oxides are not likely to be linked with the consequences of bacterial metabolism such as the consumption of oxygen.

Apart from this type of copper accumulation, the dissolved copper exists as another observable form. Figure 5 reveals this on those bacteria after treated with copper surface for 3 hours: there are some sub-micron particles with various sizes attaching on these bacteria. EDS spectra collected from these features tell more details from their composition. Position 1 represents the spectrum obtained from bacterium without particle coverage, acting as a contrast. The present elements resemble those discussed in the above section. The intensity of Cu is relatively higher, resulting from the fact that during this observation, these bacteria were still on copper surface, instead of having been transferred to silicon wafer in the previous case. Therefore this intensity also includes the characteristic X-ray excited from the copper surface under the bacterium due to its small size (more precisely, the thickness) of bacterium. On the other hand, the spectrum from position 2 centred on the sub-micron particle draws a different scene. The intensity of C, N and Na became less, based on the fact that the particle locates higher than the bacterium, and so there was less electrons reaching and exciting characteristic X-ray from the bacterium.

Whereas the other three detected elements, namely O, Cu and P, were recorded with higher intensity. They should thus be considered as the main elemental composition of these particles.

Although no exact phase composition of these particles could be indexed from the current GIXRD results, studies [START_REF] He | Spontaneous interfacial reaction between metallic copper and PBS to form cupric phosphate nanoflower and its enzyme hybrid with enhanced activity[END_REF][START_REF] Luo | Pure copper phosphate nanostructures with controlled growth: a versatile support for enzyme immobilization[END_REF] did have shown that a popular approach to produce copper phosphate nano-particle is by appropriately mixing copper or its ions with phosphate solution. Unfortunately, we cannot directly conclude whether the bacteria promote the formation of the suspected copper phosphate particles (not the scope of our current study either). Nevertheless, we could still comment that they are more likely to grow on bacteria, and it does show us one of the forms how the copper content being stabilised in the solution instead of being free ions. Furthermore, since the above ICP-MS results only could show the sum of both accumulation of copper in bacteria and copper phosphate, it will be meaningful if future experiments are designed to show the proportion. These sub-micron particles are easily found, mainly because their distribution on the surface of bacteria. However, for the dispersed copper that could only be detected by EDS, it is still yet to know whether they entered the bacteria or only attached with the outer membrane. STEM mode in TEM was therefore applied so as to collect the information of the elemental distribution, as shown in Figure 6. BF image outlines the profile of bacteria better. While in the ADF image, it could already be observed that the sub-micron particles contain elements with higher atomic number, since higher intensity from these locations were recorded. This information is further confirmed by EDS mapping, where O, Cu and P were found highly concentrated in those regions. Another important fact could be extracted from the EDS mapping, is the distribution of copper in a bacterium. It is true that for a 2D top-view of a 3D object (the bacterium), it's hard to tell where the copper exactly are.

However, one could still suppose that if the situation was that the copper only anchored on the outer membrane of a bacterium.

In this case, the copper amount should be found a significant increase from the centre of the bacterium to its edge. This is because from a 2D top-view, the edge of a bacterium consists of overlap of the membrane in top-view that should have resulted in a higher copper content. But this has not been observed in the current result, suggesting that it is highly possible that those dispersed copper were located within the bacteria. To further investigate the more precise locations of copper, further work could be done by combing other more localised techniques such as NanoSIMS, with almost 100 nm lateral resolution [START_REF] Kraft | Phase Separation of Lipid Membranes Analyzed with High-Resolution Secondary Ion Mass Spectrometry[END_REF] combining with depth profiling. Another equally interesting information is about the state of these copper contents. Thus far have we applied GIXRD and Raman on the copper treated bacteria (shown in SI, Figure 6), unfortunately no (or not enough) crystalline phase could be indexed.

With these observations, the role of bacteria in the antibacterial efficiency test (copper-PBS system) is summarised in Figure 7. The first phase is the release of copper ions when the contact of suspension and copper surface begins, which leads to an increase of copper content in suspension. The existence of bacteria does not essentially alter this initial phase. However, when these ions "meet" the bacteria, they begin to be accumulated by the bacteria, with two main paths confirmed: one is through the absorption of the bacteria. It is not the first time to report that the microbe may act as a reservoir of metal ions [START_REF] Veglio | Removal of metals by biosorption: a review[END_REF][START_REF] Wang | Biosorbents for heavy metals removal and their future[END_REF], but to link this behaviour not only to the surrounding solution environment but also another object (in this case: copper surface) sharing the same environment is still seldom considered. Another path is the formation of copper phosphate sub-micron particles. As the bacteria begin to collect free copper ions from the solution, the amount of the actual copper ions in the solution has been gradually consumed. This process keeps the amount of free copper ion low, favouring less the oxide formation. Exposure of copper surface without fully oxides coverage enables the continuous corrosion, explaining why the total amount of copper in the whole suspension is much higher.

At last, there are a few concerns that should be noticed basing on the current observations. For example, due to the additional effect introduced by bacteria, we should now realise the importance of interpreting the each corresponding scenario also with bacteria. In other words, although analysis of interaction between pure buffers and surface can help, but does not necessarily represent the actual situation (e.g. copper content level). On the other hand, the ion accumulation and its effects on corrosion process could be better validated, for instance, by well-defined experiments where copper content in the bacterial suspension can be precisely regulated. Moreover, further work should focus on the details of corrosion phenomenon on antibacterial copper as well as its consequences. Attempts to investigate how these changes could affect the antibacterial behaviour could also be meaningful.

Conclusions

This study focuses on copper surface evolution during the antibacterial efficiency test. The environmental components as well as the role of bacteria in buffer suspension were considered. Several concluding remarks are listed below:

Copper surface oxidation in PBS is inhibited as the presence of E. coli in the suspension, confirmed by GIXRD and Raman. In contrast, without the Cu2O coverage, localised corrosion attacks are much visible on the copper surface.

Due to the absence of Cu2O layer as an ion release barrier, the amount of copper ions released by the metallic surface strongly grows, where no plateau has been reached in 3 hours exposure.

The released copper ions are found to be stored inside the bacteria and forming copper phosphate sub-micron particles outside the bacteria. These two main paths on one hand enhance the capacity of copper storage of the suspension, on the other hand, reduce the free copper ions in the suspension. This accumulation is a passive process where viable bacteria is not the necessary condition.

Table Captions

Table 1 The pH values of different solutions before and after 3 hours corrosion tests on copper surface.

Figure 1 Typical

 1 Figure 1 Typical SEM images of copper surfaces after 3 hours of exposure to PBS (a-b) and PBS with E. coli (c-d). The dashed squares in (a) and (c) indicate the positions of the following higher magnification images (b) and (d). The arrows indicate localised corrosion attacks.

Figure 2 ( a )

 2a Figure 2 (a) High resolution grazing incidence X-ray diffractograms in the range of (111) planes of Cu2O (#75-1531) and (b) typical Raman spectra obtained from copper surfaces after 3 hours exposure to PBS and PBS with E. coli. (c) OM images and SEM images of two typical features obtained from the bacterial treated surface and (d) their Raman spectra from the same areas.

Figure 3 Concentration

 3 Figure 3 Concentration of copper content in PBS, PBS with E. coli and its supernatant following various exposure periods. The error bars indicate the standard deviations calculated from three independent measurements.

Figure 4 Typical

 4 Figure 4 Typical SEM images and EDS spectra from copper surface treated E. coli following various exposure periods, after being transferred to silicon wafer: (a-c) 1 hour; (d-f) 3 hours and (g-i) 6 hours. The dashed squares indicates the position of the following higher magnification images. The cross shape indicators point out the positions where the corresponding spectra were collected.

Figure 5 Typical

 5 Figure 5Typical SEM images (a-b) and EDS spectra (c) from 3 hours copper surface treated E. coli, on the original copper surface.The dashed squares indicates the position of the following higher magnification image. The cross shape indicators point out the positions where the corresponding spectra were collected.

Figure 6 Typical

 6 Figure 6 Typical STEM observation from copper surface treated E. coli for 3 hours: (a) BF image; (b) ADF image. The dashed squares indicate the position of the following chemical mapping: (c) carbon; (d) oxygen; (e) phosphorus and (f) copper.

Figure 7

 7 Figure 7

Figure 7

 7 Figure 7

Table 1

 1

	Solution	Before corrosion	After corrosion
	PBS	7.4	7.7
	PBS with E. coli	7.4	7.9
	PBS with S. cohnii	7.4	7.9

Acknowledgements

This study was supported by Erasmus Mundus Joint European Doctoral Programme in Advanced Materials Science and Engineering (DocMASE) and the Deutsch-Französische PhD-Track-Programme (PhD02-14). The ICP-MS experiments were supported by Dr. Ralf Kautenburger from the chair of Inorganic Solid State Chemistry. The authors acknowledge Prof. Volker Presser and Leibniz Institute for New Materials for the access of Raman spectrometer. Dr. Javad Najafi helped a lot to understand the concept of bacterial mobility. Prof. Gert-Wieland Kohring and Dr. Fabio Pereira from Department of Microbiology in Saarland University offer valuable instruction in centrifugation.

Data availability

The data that support the findings of this study are available from the corresponding author on request.

Declarations of interest

None.