Ewelina Kosior
email: ewelina.kosior@esrf.fr

Sylvain Bohic

Heikki Suhonen

Richard Ortega

Guillaume Devès

Asuncion Carmona

Florence Marchi

Jean Francois Guillet

Peter Cloetens
email: peter.cloetens@esrf.eu

Combined use of hard X-ray phase contrast imaging and X-ray

Keywords: X-ray fluorescence, phase contrast imaging, synchrotron, trace elements

Introduction

Metals present as trace elements in biological systems play an important role in the cell metabolism [START_REF] Meares | Metal chelates as probes of biological systems[END_REF], [START_REF] Bush | Twenty years of metallo-neurobiology: where to now?[END_REF]. In any organism most of the intracellular processes are regulated by metals, such as proteins containing metal cofactors which catalyze biochemical reactions. Present in enzymes, they are involved in important biosynthetic pathways including the conversion of electrochemical to chemical energy, the biosynthesis of DNA, and an array of important metabolites [START_REF] Sundberg | Interactions of histidine and other imidazole derivatives with transition metal ions in chemical and biological systems[END_REF]. The number of studies on trace elements is growing and nowadays their role in human health both in their natural occurance and via therapeutic drugs is recognized as crucial. Compounds containing metals are used for the diagnoses and treatment of diseases such as Alzheimer, Parkinson, cancer (treatment with cisplatin-based drugs in chemotherapy [START_REF] Lippard | Principles of Bioinorganic Chemistry[END_REF]) and to develop nanocomposites for gene therapy. Quantitative study of the distribution of trace elements at the sub-cellular level provides important information for the study of the functions and pathways of metalloproteins and therapeutic approaches, especially in connection with the local chemical state of the element. To answer fundamental questions on the role of metal ions in these systems requires combination of different approaches across the multidisciplinary fields of biology, chemistry and physics. The relevant information about trace elements in biological specimens increases with the sampling resolution. To probe the sub-cellular complexity of metal ion homeostasis mechanisms, one requires sub-micrometer resolution together with a sub-femtogram absolute detection limits due to the decreasing quantity of sample probed. X-ray fluorescence (XRF) analysis with a nanoprobe is the most direct and sensitive method to quantify the distribution of metals and other elements at the sub-cellular level [START_REF] Bohic | Synchrotron hard x-ray microprobe: fluorescence imaging of single cells[END_REF], [START_REF] Ortega | Cobalt distribution in keratinocyte cells indicates nuclear and perinuclear accumulation and interaction with magnesium and zinc homeostasis[END_REF]. It provides high sensitivity for transition metals and other relevant trace elements together with the capability of penetrating and mapping whole cells. Most of the details of cells are undetectable in hard X-ray microscopy due to the weak absorption contrast between structures with similar transparency. However the various organelles show wide variation in refractive index, that is, the tendency of the materials to bend light, providing an opportunity to distinguish them. The technique exploiting the refractive index (its real part) is phase contrast imaging. Methods based on phase contrast provide complementary information about cells by mapping the electron density. Information about the electron density combined with the average density of the sample allows to calculate its thickness, value which can be compared with alternative techniques (Scanning Transmission Ion Microscopy, Atomic Force Microscopy). We use such comparison for validating the method described in this article. In this work we limit our investigations to the 2D regime. Therefore the quantitative values are averaged over the sample thickness. The local concentrations would be accessible by combining the proposed method with 3D tomography techniques. Without going to the full 3D investigation the proposed method allows to avoid misinterpretations of X-ray fluorescence maps, which would result from the inability to distinguish if a change in fluorescence signal is due to a change in concentration or a change in sample thickness. Our method (combining XRF with phase contrast imaging) yields the projected concentrations at the sub-cellular level after the sample preparation and thus it is sensitive to it. This represents possible future approach -to study at the sub-cellular level the influence of different sample preparation techniques on the cell integrity. Although, not discussed in the present paper, another interesting possibility would be to investigate the radiation damages of the sample and to correct for any possible mass loss due to irradiation.

Methods

Sample preparation

Certified particles size standard -polystyrene spheres (Duke Scientific Corp, Palo Alto, CA) and PC12 cells were analysed. Polystyrene spheres were of four different diameters (400 nm, 1µm, 5 µm, 10 µm). The commercial solution was diluted 5 to 10 times, deposited on a silicon nitride (Si 3 N 4 ) membrane, spin coated and air dried at room temperature. PC12 cells, a clonal catecholaminergic cell line derived from rat pheochromocytoma [7] were cultured in RPMI 1640 medium supplemented with 10% (v/v) heat-inactivated horse serum, 5% (v/v) fetal bovine serum, penicillin (25 µg/mL) and streptomycin (25 µg/mL). Cultures were maintained according to standard protocols at 37 • C in a 95% humidified incubator with 5% CO 2 as already described [START_REF] Carmona | Quantitative micro-analysis of metal ions in subcellular compartments of cultured dopaminergic cells by combination of three ion beam techniques[END_REF]. The cells were cultured directly on gelatin gel coated thin polycarbonate foil (2 µm thick). These targets were subsequently fastly cryofixed in liquid nitrogen, chilled isopentane (-160 • C) and further lyophilized. PC12 cells synthesize and store dopamine in neurovesicles. In the presence of nerve growth factor (NGF), these cells develop an extensive network of neuronal-like projections, that is accepted as a model of catecholaminergic neurons and often used as an in vitro model for Parkinson's disease. The cells labelled B,C in this work, were exposed to 300 µM of Mn and cell A was exposed to 300 µM of Mn and brefeldin A, a molecule known to cause the apparent collapse of the Golgi stacks [START_REF] Carmona | Manganese accumulates within Golgi apparatus in dopaminergic cells as revealed by synchrotron X-Ray fluorescence nano-imaging[END_REF].

X-ray fluorescence

X-ray fluorescence is a phenomenon in which the material exposed to X-rays emits radiation, which has an energy characteristic of the atoms present. It allows studying the chemical composition of the sample. X-ray fluorescence analysis was performed at the nano-imaging station ID22NI (Fig. 1), using the intrinsic monochromaticity of the undulators of about δλ/λ ≃ 0.01. The experimental station is located at a distance of 63 m from the undulator source and at 37 m from the high power slits used as secondary source in the horizontal direction (25 µm slit opening).The synchrotron radiation is focused by an X-ray optical device consisting of two elliptically shaped mirrors acting in two orthogonal planes using the so-called Kirkpatrick-Baez geometry [START_REF] Hignette | Efficient sub 100nm focusing of hard x rays[END_REF]. The mirrors are coated with a graded multi-layer. No other monochromator is used in the setup, resulting in a very high and unique X-ray flux (up to 10 12 photons/s) at energies between 15 and 29 keV. In this work, the energy of the pink photon beam was set to 17.5 keV for all experiments. The focused beam was characterized by translation of a gold stripe of a nano-fabricated test pattern (Xradia, USA) recording both the transmitted intensity by a diode and the Au -L α fluorescence emission line by a silicon drift detector (vortex-EX, SII NanoTechnology Inc., USA). The X-ray spot size was measured to be 76 nm horizontally by 84 nm vertically (FWHM). The samples were positioned in the focal plane of the KB system and translated by piezo-stages in the directions perpendicular to the beam. The X-ray fluorescence spectra of several samples were collected by the silicon drift energy dispersive detector positioned in the horizontal plane at 75 • of the incoming X-ray beam. Based on the X-ray fluorescence energy spectrum, the areal mass (A mass ) of the element can be calculated through a fitting procedure. The samples being scanned were deposited on 3 x 3 mm 2 membranes made of 500 nm thick silicon nitride (Si 3 N 4 ) (Silson, Blisworth, U.K.). A step-size of 150 nm was used and the dwell time varied from 150 to 250 ms.

Phase contrast imaging

When X-rays pass through an object, two scenarios, according to the refractive index n, are considered

n = 1 -δ + iβ (1)
The x-rays can be absorbed, which effect is determined by imaginary part of the refractive index, β. Image contrast is thus entirely due to absorption differences (emphasis is put on the corpuscular nature of photons) and the amplitude of the radiation changes. The X-rays can also be retarded in the object. This phenomenon is used in phase contrast imaging, where the effects due to the decrement of the real part of the refractive index, δ, are exploited. A difference in the δ value between an object and the background results in a phase shift between the wave transmitted through and outside the object. Due to this phase shift an interference pattern appears upon propagation. Emphasis is thus put on the wave nature of x-rays. The phase shift induced by the object can be described as

φ(x, y) = -(2π/λ) δ(x, y, z)dz ( 2
)
where z is the propagation direction and λ the wavelength. Far from the absorption edges and considering the fact that the elemental content is dominated by the cellular architecture, comprised of light elements (C, N, H, O) in biological systems, the real part of the refractive index is approximately proportional to the density of the object, ρ.

δ ≈ 1.36 × 10 -6 ρ[g/cm 3 ]λ 2 [Å] (3)
thus the equation 2 can be simplified

φ = α ρ T ( 4
)
where α is a known constant, ρ is the mean density and T is the thickness of the object, ρ T represents also the areal mass density of the cellular ultrastructure, denoted hereafter the projected mass.

Combining the information from the X-ray fluorescence map (the areal elemental mass) with the projected mass measured by the phase contrast one can calculate the projected elemental concentration:

C i = A i mass / ρ T (5)
where C i is a projected concentration of the element i averaged over the sample thickness. The same experimental setup as described in 2.2 was used for the magnified phase contrast imaging but the sample was put downstream of the focus in the divergent beam (see Fig. 1). Projection microscopy, which uses partial coherence of the incident beam is a simple way of phase contrast imaging through propagation [START_REF] De Jonge | Quantitative phase imaging with a scanning transmission x-ray microscope[END_REF], [START_REF] Fabrizio | Diffractive optical elements for differential interference contrast x-ray microscopy[END_REF]. Samples were put at different distances (29 mm, 30 mm, 34 mm, 44 mm) downstream of the X-ray focus resulting in magnified Fresnel patterns collected by a highly sensitive charge-coupled device (CCD) camera. The need of multiple distances is related to the phase retrieval procedure [START_REF] Mokso | Nanoscale zoom tomography with hard x rays using Kirkpatrick-Baez optics[END_REF]. The pixel size varied depending on the distance focus-sample, being set to 53 nm for the first distance (while the pixel size of the detector was 0.96 µm).

Atomic Force Microscopy (AFM) measurement

Atomic Force Microscopy allows imaging the surface morphology at nanoscale resolution and measuring the force at nano-Newton scale. AFM can investigate thin and thick film coatings, synthetic and biological membranes, metals, polymers, semiconductors and study locally the electric, magnetic or mechanical properties of the sample [START_REF] Marchi | Characterisation of trapped electric charge carriers behavior at nanometer scale by electrostatic force microscopy[END_REF]. Thanks to its versatility, AFM became a tool of choice in biophysics [START_REF] Alessandrini | AFM: a versatile tool in biophysics[END_REF]. Our measurements were performed in Tapping mode under ambient conditions on an Asylum MFP-3D AFM instrument equipped with acoustic box. In this MFP-3D AFM the planar scan relies on an (X,Y) scanner in closed loop while an independent piezoelectric element drives the Z displacement of the probe according to the open feedback loop control. A standard Tapping probe was used with a measured resonant frequency of 325 kHz and a cantilever stiffness of about 45 N/m (average value provided by the manufacturer data sheet). The AFM topographic images were recorded with a numerical resolution of 256 x 256 pixels. The tapping mode allows high-resolution topographic imaging of surfaces that are easily damaged or not hold tightly to their substrate. The Tapping mode is implemented in ambient air by exciting the cantilever assembly near the cantilevers resonant frequency using a dedicated piezoelectric crystal. Thanks to this mechanical excitation, the cantilever oscillates with amplitude of typically few tens of nanometers; this amplitude is modulated when the tip comes into contact with the surface. The AFM measurement was performed on polystyrene spheres of 5 µm diameter at the Surface Science Laboratory of the ESRF.

Scanning Transmission Ion Microscopy (STIM)

Scanning Transmission Ion Microscopy is based on measurement of the energy loss of accelerated ions after passing through the specimen. This slowing down of the charged particles occurs during inelastic collisions with electronic shells and is proportional to the stopping power of the sample and describes its atomic density. The experiment was performed at AIFIRA ion beam facility on nanobeam line [START_REF] Barberet | Technical description of the CENBG nanobeam line[END_REF]. Charged particles delivered by a 4 MV Cockroft-Walton electrostatic accelerator are focused onto the sample surface by an electromagnetic lens down to a beam spot size of 200 nm. The beam is scanned over the surface in order to measure local ion energy loss using a passivated implanted planar silicon (PIPS) detector placed on the beam axis very close behind the sample. This geometry results in increased detection efficiency, which enables drastic lowering of the beam current down to a few hundreds of particles per second. Therefore, the sample does not suffer any mass loss during ion interaction and one can access the projected mass of the sample [START_REF] Devès | Scanning transmission ion microscopy mass measurements for quantitative trace elements analysis within biological samples and validation using atomic force microscopy thickness measurements[END_REF].

Data analysis 2.6.1. X-ray fluorescence

For X-ray fluorescence analysis we used PyMCA, a free available software, which was developed at the European Synchrotron Radiation Facility [21]. The program allows interactive as well as batch processing of large data sets and is well suited for X-ray fluorescence imaging. Quantification of the elemental areal masses is based on a fitting procedure of the recorded fluorescence spectra. The algorithms employed are described in detail elsewhere [

Calibration of the fluorescence data

The Standard Reference Material (SRM) of bovine liver was used to calibrate the fluorescence spectra. This material is intended primarily for use as a control material and in evaluating analytical methods for the determination of major, minor and trace elements in animal tissue and other biological matrices. The certified values for the constituent elements and the experimental values are given in Tab.1. Certified values are based on results obtained by definitive methods of known accuracy, or alternatively, from results obtained by two or more independent analytical methods. The grand mean was computed using the weighting scheme of Paule and Mandel [22]. The bovine liver sample was scanned through the focal plane and the spectrum of emitted fluorescence was recorded. The elemental content is calculated assuming the fundamental parameters (flux, detector characteristics) to be known except for the distance between the focus and the detector. This distance is not precisely known but it's evaluated by comparison of the calculated and known elemental content in the bovine liver sample. Three elements were chosen as representative (Fe, Cu, Zn) and three distances close to the physical one. Using PyMCA the content of the chosen elements were obtained and used in the formula:

Y(x) = i (c st i -c exp i (x)) 2 , i = Fe, Cu, Zn (6)
where x is the distance between the focus and the detector, c st i is a content of the element i from the standard values, c exp i (x) is a content of the element i measured in the experiment. The cost function Y(x) was fitted with a second order polynomial and the value of x giving the minimum was taken to be true focus to detector distance.

Phase imaging

To analyze phase contrast data we used free, available ImageJ software and the phase retrieval code developed at the ESRF and implemented under GNU Octave ( [START_REF] Cloetens | Holotomography: Quantitative phase tomography with micrometer resolution using hard synchrotron radiation x rays[END_REF], [START_REF] Langer | Quantitative comparison of direct phase retrieval algorithms in in-line phase tomography[END_REF]). The results obtained by using the phase retrieval algorithm allow to calculate the thickness of a certain area (as described in 2.3). This value can be compared with the alternative methods (AFM, STIM).

Results

Reference samples

Certified polystyrene spheres of well known diameter were used for validation of the phase retrieval algorithm. Samples were put at four distances as explained in 2.3. The phase retrieval algorithm provides relative phase maps (Fig. 2). We draw profiles across the spheres to get information on the projected phase that can be used to calculate the thickness of the sample (as described in 2.3). By introducing the density of the certified polystyrene spheres that is 1.05 g/cm 3 we obtained the results shown in Tab.2. It provides the nominal values of the spheres diameter (certified values), the experimental values and the relative differences. It can be observed that the experimental values are systematically underestimated and that the relative difference is bigger for the smaller spheres. The sample that consists of 5 µm polystyrene spheres was also imaged by AFM and STIM, as they represent alternative methods for the thickness measurement. The results are presented in Fig. 3 with associated profiles through one sphere. The same figure shows also a comparison between the different experimental results (phase, AFM, STIM) and the theoretical profile. STIM quantification of projected mass was performed using Paparamborde software [START_REF] Devès | Scanning transmission ion microscopy mass measurements for quantitative trace elements analysis within biological samples and validation using atomic force microscopy thickness measurements[END_REF]. Projected mass calculation is made by considering the slowing down of incoming particles through the bead and associated stopping power variation along the ion path. The ion path is shematically divided into elementary sub-layers with constant energy loss where stopping power and corresponding mass can be calculated. Total projected mass is then calculated giving weight to every sub-layer according to the total transmitted energy spectra. In the case of the polystyrene sphere calculation, the Si 3 N 4 contribution to the total energy loss was measured directly on transmitted map and used as a fixed parameter for sphere projected mass calculation. Accuracy in STIM mass measurement is driven by the nature of sample and background and remains here under 16% for the less favourable case (5 µm sphere on Si 3 N 4 layer).

Element mapping in PC12 cells

PC12 cells were imaged by synchrotron X-ray fluorescence and X-ray phase contrast imaging. After scanning the sample (as described in 2.2) and fitting the emitted spectra, the intracellular distribution of the accessible chemical elements can be determined at a spatial resolution corresponding to the beam size (100 nm). By applying the phase retrieval algorithm, the relative phase maps were generated. The potassium (K) and zinc (Zn) X-ray fluorescence map and phase contrast images after phase retrieval reconstruction acquired on typical NGF-differentiated PC12 cells are presented in Fig. 4. Fig. 6 shows images of the same PC12 cell obtained using the STIM method and both X-ray fluorescence and X-ray phase contrast imaging. For every cell we calculated the minimal and maximal areal mass of the selected elements; potassium which is known to have a rather uniform distribution within the cell and zinc. The results are collected in Table 3. Using data from the reconstructed phase maps, similarly to what has been done for Cells K Zn min (g/cm 2 ) max (g/cm 2 ) min (g/cm 2 ) max (g/cm 2 ) cell A 15.0 • 10 -9 1.9 the reference samples, we can calculate the thickness of the PC12 cells analysed. The profiles along selected lines (shown in Fig. 4,6) were used for calculation. Applying an average density of the dry cells of 1.218 g/cm 3 [START_REF] Snyder | Report of the Task Group on Reference Men[END_REF], [START_REF] Carmona | Quantitative micro-analysis of metal ions in subcellular compartments of cultured dopaminergic cells by combination of three ion beam techniques[END_REF] we calculate the maximum thickness of the cell A (along the selected profile) to be 2.87 µm. For the cell B we selected 2 profiles, one going through the cell (profile 2) and one going through a thin neuritic process between 2 cells (profile 3). The thickness of these areas are respectively: 6.17 µm and 1.28 µm. For the Zn fluorescence map of the cell B we selected also region of significant content of Zn, visible on the Fig. 4 and the corresponding region of high projected mass. We used this region to calculate the local areal mass of Zn (51.16 • 10 -9 g/cm 2 ) and the thickness of this part (7.59 µm). These numbers will be used to calculate the absolute projected concentration of Zn in this region of the cell. Also for the cell C we selected 2 profiles, one going through the cell (profile 4) and one going through the lower part of the cell (profile 5). The thickness of these areas are respectively: 4.77 µm and 0.82 µm.

On the STIM map of the cell C we selected 3 areas that were used for areal mass calculation. The area X was selected in one of the thinnest parts of the cell (similarly like profile 5 on the corresponding phase map) and it gave the result of 88 µg/cm 2 while the result obtained by using the phase map gives 100 µg/cm 2 . The area Y goes through the nucleus of the cell (similarly like profile 4 on the corresponding phase map) and it yields 524 µg/cm 2 . The similar area selected on the phase map gives a result of 581 µg/cm 2 . As a curiosity we also calculate the areal mass in area Z, which goes through the cytoplasm, the result is 114 µg/cm 2 (with 150 µg/cm 2 calculated from the phase map). After combining the information from X-ray fluorescence maps and phase contrast maps it is possible to calculate the absolute projected concentration for elements Zn and K in the cells (as described in the section 2.3). For these calculations and for easier comparison we used the maximal value of the areal mass and the thickness of the cell (along the selected profiles), although full quantitative maps can be derived combining both types of images (see Fig. 5). The results are presented in the absolute projected concentration of Zn at the level of 55.3 µg/g. In the Fig. 5 we present the quantitative map of the projected concentration of Zn in cell B. By using the X-ray fluorescence map of Zn and the phase contrast map of the cell B (Fig. 4) it is possible to access the projected concentration by dividing both maps pixel by pixel. Before the division we used cross correlation techniques to align the images and we applied small distortion corrections. It should be noted that it is not necessary to calculate the thickness of the sample in order to determine the projected concentrations of a given element as this information is accessible by dividing X-ray fluorescence and phase contrast images pixel by pixel (see equations [START_REF] Lippard | Principles of Bioinorganic Chemistry[END_REF][START_REF] Bohic | Synchrotron hard x-ray microprobe: fluorescence imaging of single cells[END_REF]. By doing the above calculations and comparing the results obtained by our method in terms of sample thickness and areal mass with an alternative method such as STIM, we validate our method.

Discussion

An important application of X-ray fluorescence microscopy is the determination of the distribution of the chemical elements at the sub-cellular level. Indeed, XRF analysis is a multi-element analytical technique that allows the simultaneous quantification of almost all elements in an unknown sample. The case of cells or thin sections of tissue is ideal in the way that corrections for absorption and enhancement effects are not necessary resulting in linearity between fluorescence intensity and the projected mass of a given element. However, the mapping of true element concentration at the sub-cellular level is a difficult task. Locally, the composition and the density or the thickness of different sub-cellular compartments can vary. Indeed, cell organelles are a mixture of structures with different size, weight and shape. The region of the cell nucleus is a few microns thick while some parts of the cytoplasm can be only 100 nm thick. It has been reported using combined STIM and AFM method that within a same cell specific densities vary between 1.06 to 1.86 [START_REF] Devès | Scanning transmission ion microscopy mass measurements for quantitative trace elements analysis within biological samples and validation using atomic force microscopy thickness measurements[END_REF]. This should be taken into account for true elemental quantification at subcellular level. To address this problem, X-ray fluorescence sub-cellular mapping and propagation-based X-ray phase contrast imaging for mass normalization were combined, for the first time, to provide high-resolution, truly quantitative, elemental distribution maps in cells. Phase-contrast imaging with a partially coherent beam produces Fresnel interference fringes, which make it possible to image samples with small variations in mass density. These variations would be undetectable in absorption contrast. Alternatively scanning differential phase contrast imaging has been performed by measuring the deviation of the beam by the sample with a position sensitive detector [START_REF] De Jonge | Quantitative phase imaging with a scanning transmission x-ray microscope[END_REF]. The authors have demonstrated a very good sensitivity of this approach using scanning transmission X-ray microscopy on 5 microns polystyrene spheres. Although, they did not use it yet for mass normalization for X-ray fluorescence quantitative analysis, the results obtained were done at low energy (2.5 keV) that limits the range of elements accessible. Recently the studies on Zernike Phase Contrast have shown the possibility of obtaining the projected phase in scanning mode [START_REF] Holzner | Zernike phase contrast in scanning microscopy with X-rays[END_REF]. Compton to Rayleigh scattering analysis has been used to obtain more accurate quantification in 2D [START_REF] Vincze | A General Monte-Carlo simulation of ED-XRF spectrometers: Part II, Polarized Monochromatic Radiation, homogeneous samples[END_REF] or 3D [START_REF] Golosio | Internal elemental microanalysis combining X-ray fluorescence, Compton and transmission tomography[END_REF] measurements. There is limitation to this approach, so far the matrix mean atomic number is estimated from calculated Compton/Rayleigh intensity ratios as a function of the average atomic number in various samples which not necessarily match the sample matrix studied. In addition the thickness needs to be determined from thickness calibration curves on the basis of the total Compton scatter intensity. On the overall these average values based on Compton signal seem not suited to provide absolute quantification at the sub-cellular level. The projection X-ray microscopy method used in our paper is optimized for relatively high energies (17 keV-29 keV) that match well with efficient excitation of the X-ray fluorescence. As a fullfield CCD based approach our method is more dose efficient, provides a larger field of view and is much faster than scanning methods to obtain the phase information. For comparison, the phase images are acquired with a few seconds of exposure time and contain 4 million pixels (1 µs/pixel), whereas the fluorescence scanning data requires about 6 hours of exposure time for 100000 pixels (250 ms /pixel). However the phase data is not recorded simultaneously with the XRF data as it is in [START_REF] Holzner | Zernike phase contrast in scanning microscopy with X-rays[END_REF]. Therefore to normalize the fluorescence data the alignment of the two different data sets is required. The higher energy of excitation for X-ray fluorescence allows not only a better sample penetration but allows also to reach almost all element with Z > 13 with the advantage to work with K emission lines for higher fluorescence yield and better energy resolution. Ion beam techniques have shown clear assets to obtain true elemental quantification by combining particle induced X-ray emission (PIXE) with Rutherford backscattering and/or STIM. The sensitivity and spatial resolution are much poorer than synchrotron-based XRF microscopy. Recently, efforts have been done towards the quantification of trace elments on cell cultures [START_REF] Carmona | Quantitative micro-analysis of metal ions in subcellular compartments of cultured dopaminergic cells by combination of three ion beam techniques[END_REF]. STIM allows to map with sub-micrometer resolution the variation in mass densities within single cells with calculated thicknesses in good agreement with AFM measurements [START_REF] Devès | Scanning transmission ion microscopy mass measurements for quantitative trace elements analysis within biological samples and validation using atomic force microscopy thickness measurements[END_REF]. In this work, first a comparison between reference techniques (AFM, STIM) was made on polymer microspheres to mimic, in size and composition, a typical biological specimen such as a cell. The X-ray phase imaging after the application of a phase retrieval reconstruction algorithm provides a map of the projection of the mass density of the sample that was converted to thickness knowing the polystyrene density. The calculated thickness profile for 5 microns spheres was found to be slightly underestimated using X-ray phase imaging. This can be explained by the shape of the background of the profile extracted from the X-ray phase signal and that is not corrected for. The varying background is the direct consequence of the sensitivity of differential phase contrast methods for low frequency noise. This problem can be solved by improving the quality and stability of the beamline optics, resulting in a better correction for inhomogeneities of the incoming X-ray beam. The STIM data matches more closely the theoretical profile of the sphere. Here, microspheres were deposited on 500 nm thick silicon nitride membranes. The 2 layers, i.e the sphere and the silicon nitride membrane were separated using STIM calculation modified in accordance. There is not much discrepancy between STIM -phase -and theoretical profile as shown in Fig 3 . The AFM topographic image provides two complementary measurements through the profile: a 4 µm in height and 5.1 µm for lateral dimension (measured at the half height of the microsphere, i.e 2 µm where the tip-object convolution effect can be neglected). These differences in height and lateral dimensions could be due to the absence of non-linearity correction of the piezoelectric element in Z direction while the planar scanner is corrected thanks to the closed feedback loop. Indeed, the AFM instrument is dedicated to accurate height measurements at sub-micronic scale where the non-linearity behavior can be neglected. For this reason, in our measurements, the lateral one is the more reliable. Based on this assumption, the lateral dimension matches with the diameter specification of the sphere data sheet. The thickness measurements using X-ray phase images were in good agreement (within 5% except for the smallest spheres) when compared to the certified values for the sphere. We attribute the increased relative error for the smallest spheres to a spatial resolution effect: in the phase retrieval step we didn't take into account the finite point spread function of the detector. The quantitative measurements on single 400 nm spheres are encouraging for subcellular applications. Indeed, this typically matches the size of some organelles (lysosome, mitochondria) or some thin cellular processes (neurites, filopodia). This is well exemplified when PC12 cells were analyzed. These cells were differentiated into neuronal-like cells which, expands neuritic processes. The X-ray phase reconstructed images provide useful structural details giving evidence for sub-cellular compartments of various densities and a cell nucleus that can be well delineated. Further work will be needed for better identification of the structural details obtained in the phase images by coupling to fluorescence microscopy and organelle staining. We observed inside some PC12 cells denser regions, micrometric in size. The X-ray fluorescence signal of zinc was found much higher in these regions. While the zinc distribution can be first misinterpreted, the association of X-ray phase images (for mass normalization) to X-ray fluorescence quantification results in a projected zinc concentration that remains rather similar to the one in other parts of the cell (see Fig. 5). The potassium signal is found homogeneous as expected [START_REF] Carmona | Quantitative micro-analysis of metal ions in subcellular compartments of cultured dopaminergic cells by combination of three ion beam techniques[END_REF]. This indicates that the cell integrity was preserved during the sample preparation. The areal mass obtained on PC12 cells through STIM and X-ray phase measurements are in good agreement both for a thick part of the cells like the nucleus and for thinner parts like neurites. These direct comparisons on the same cellular regions support the use of X-ray phase imaging for mass normalization in X-ray fluorescence quantification. The same cells were imaged by STIM, then by X-ray phase imaging followed by X-ray fluorescence measurements. Despite short acquisition times (150-250 ms) and low attenuation at high X-ray energies, the high X-ray photon flux delivered by the nanoprobe results in non-negligible radiation damage. It is suggested that some mass loss occurs and our approach could be used to better characterize these effects. X-ray fluorescence microscopy is a unique tool for the quantification of trace elements at the sub-cellular level and it can be applied to a wide variety of biological studies. On the overall this work is encouraging the use of X-ray phase imaging to improve the elemental quantification in 2D and 3D X-ray fluorescence imaging.

Figure 1 :

 1 Figure 1: Scheme of the experimental setup of the nano-imaging station ID22NI

Figure 2 :

 2 Figure 2: Relative phase maps generated after applying phase retrieval procedure to the certified polystyrene spheres of following diameters: 10.03 ± 0.05 µm, 4.987 ± 0.040 µm, 0.994 ± 0.021 µm, 400 ± 4 nm, together with selected profiles.

Figure 3 :

 3 Figure 3: Comparison between different imaging techniques of the 5 µm spheres. a. the AFM image of the 5µm spheres, b. STIM image of the 5 µm sphere, c. comparison between experimental profiles (phase, AFM and STIM) and the theoretical prediction.

Figure 4 :

 4 Figure 4: X-ray fluorescence (color) and phase contrast (black-white) maps of PC12 cells A and B. Dashed, white squares on phase contrast maps indicate the corresponding region on fluorescence map. The cell nuclei are highlighted in red. White square on Zn fluorescence map of the cell B was selected due to significant content of Zn (fluorescence map -a) and thickness (phase map -b); c. Profile 2, through the cell B; d. Profile 3, through the neuritic process. The colors depicting elemental content in each map are scaled to the maximum value for that map. The scanning size of the cell A was 307 x 308 pixels with dwell time 250 ms while for the cell B 194 x 176 pixels with dwell time of 150 ms

Figure 5 :

 5 Figure 5: Fully quantitative map showing the projected concentation of Zn in the cell B. The calibration bar is in ppm. The map was created by combining the X-ray fluorescence map of Zn and the phase map of the cell B by dividing both images pixel by pixel.

Figure 6 :

 6 Figure 6: X-ray fluorescence (a), phase contrast (b) and STIM (c) map of the cell C. The cell nucleus is highlighted in red. On the phase map there are 2 areas selected for the thickness calculation; d. Profile 4 through the cell C, e. Profile 5 through the lower part of the cell. On the STIM map there are 3 selected areas X, Y, Z, which were chosen to calculate the areal mass. The colors depicting elemental content in each map are scaled to the maximum value for that map. The scanning size was 225 x 411 pixels and dwell time 200 ms.

Table 1 :

 1 21]. Certified Values of Constituent Elements of the NIST SRM 1577B bovine liver together with the experimental values and their statistical uncertainties and the percentage of difference

	Element	Standard value (µg/g) Experimental value (µg/g) Difference (%)
	Potassium	9940 ± 20	7200 ± 9	-27.6
	Copper	160 ± 8	169 ± 0.2	5.6
	Iron	184 ± 15	166 ± 0.3	-9.8
	Zinc	127 ± 16	128 ± 0.2	0.8

Table 2 :

 2 The nominal and experimental values obtained on the polystyrene spheres together with their statistical uncertainties and the percentage of difference

	diameters nominal (µm) experimental (µm) difference (%)
	0.4 µm	0.4 ± 0.004	0.357 ± 0.021	-10.75
	1 µm	0.994 ± 0.021	0.95 ± 0.06	-4.43
	5 µm	4.987 ± 0.04	4.91 ± 0.42	-1.54
	10 µm	10.03 ± 0.05	9.77 ± 1.07	-2.59

Table 3 :

 3 Values of areal mass of K and Zn in PC12 cells.

Table 4 .

 4 For the region of the cell B (significant content of Zn) mentioned above we calculate

		K (%) Zn (µg/g)
	cell A	0.54	46.9
	cell B	0.97	89.3
	cell C	4.82	146.3

Table 4 :

 4 Projected concentration of K and Zn in PC12 cells obtained by dividing the maximal value of areal mass by the thickness of certain area.

Acknowledgements

We would like to thank the European Synchrotron Radiation Facility for providing the beamtime. This work was supported in part by the ANR Program PIRIBIO (ANR-09-PIRI-0029-01).


Alexandre Boisson

Jérôme Perrin

Amélie Dausse

Shakeel Ahmed

Shakeel Ahmed Assessing

Assessing Water Use Efficiency With Hydrodynamic Of Paddy Cultivation And Return Flow Using Tracer Tests

come

L'archive ouverte

5th World Aqua Congress, New Delhi, India, November [16][17][18]2011

ASSESSING WATER USE EFFICIENCY WITH HYDRODYNAMIC OF PADDY CULTIVATION AND RETURN FLOW USING TRACER TESTS

Boisson Alexandre 1 ., Perrin Jérôme 2 , Dausse Amélie 1 and Ahmed

Abstract

India has the largest paddy output in the world and is one of the largest exporter of rice. This cultivation has an important impact on the water quantity and quality. Return flow from irrigation in some regions as Andhra Pradesh may lead to water salinization as it enhances concentration of elements as fluoride. Infiltration and solute transport in paddy fields are driven by a strong soil heterogeneity including cracks. Although these processes have been observed further investigations are needed on the hydrodynamics of paddy fields to fully understand solute transport. We assess infiltration using a water balance methodology by indirect measurements and we compare it with direct measurements from a tracer test experiment using bromide as a non-reactive tracer to observe infiltration velocity on the upper 2m of the soil.

Tracer is recovered using porous cups during one month. The tracer is driven by more the 20 irrigation cycles. This experiment is coupled with regular tensiometer monitoring and irrigation water level. Soil structure is composed by black clay to dark brown sandy clayed sand in the first 50 cm and by sandy soil from 0.5m to 2m depth. Coupling of tensiometric measurements, water level, irrigation time shows a daily five steps behavior of the entire system. The hydrodynamics are mainly controlled by the plow pan. Results from the tracer test show an important heterogeneity on the flow velocity up to 2 m/day with various responses depending on the depth. While fast velocities are observed and concentrations are within the same range at each investigated depth, spreading is different depending on the soil structure. Results show that hydrodynamics is controlled by cracks and retention zones. Tracer test indicates that part of the solutes are retained in the first centimeter of the soil and then slowly diffuse to the underneath layers. Although porous cups have limitation to assess fastest velocities, the methodology is reliable to have an integrated information on the infiltration dynamics in paddy soil. Comparative study shows that although mass balance and mean tracer test velocities are in the same range, the solute transport through tracer test exhibit a larger complexity.

These observations are of importance to understand the behavior of geogenic contaminants such as fluoride and anthropic contaminants such as nitrates.


Agnès Brenot

Philippe Négrel

Romain Millot
email: r.millot@brgm.fr

Clotilde Bertin
email: c.bertin@brgm.fr

Philippe Negrel
email: p.negrel@brgm.fr

Stable (O, H) and Sr isotope tracing of the Narces de la Sauvetat peatland (Massif Central, France) water fluxes

teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire

Increasing efforts were engaged to restore degraded or lost wetlands and to manage wetlands sustainably in order to assess their multiple benefits during the past decades. In this context, important knowledge on the water cycle in the wetlands is required to manage specific actions to restore and preserve these areas. In this study, we propose to use chemical and multi-isotopic approaches combined with hydrological measurements (piezometric level and stream flow measurements) to trace the fluxes of water and dissolved element involved in the "Narces de la Sauvetat" peatland (France) and for the stream draining the area. Aims are to evaluate the water status of this ecosystem as well as the origin of dissolved elements and possible anthropogenic impacts. These approaches clearly demonstrated their effectiveness to improve the knowledge on the hydrological functioning of wetlands ecosystems.

Main results are (1) at least three fluxes with distinct chemical and isotopic signatures are providing water supplies to peatland, (2) water flow that comes out of the peatland through the stream is certainly negligible and 3) water within the peat land exhibits isotopes values consistent with carbonate amendments inputs used in local agriculture.

The outcomes of this study are that peatland ecosystem water balance is poorly affected by its outlet but are strongly controlled by groundwater replenishment. This could lead to a better adjustment of decision maker choices to maintain the water balance of the peatland, which is essential for the preservation of this fragile ecosystem.


I Gmati

M Missikoff

S Nurcan

A Systematic Method for the Intentional Modelling and Verification of Business Applications

Recently, we have witnessed a growing need to involve business people in the early stages of Enterprise Information Systems development. The MAP methodology appears to be a good candidate for involving business people in the early modelling of business applications, reducing the risk of business-IT systems misalignment. Furthermore, in the context of Model Driven Engineering, such a methodology perfectly fits in the upper CIM level. In this paper we revisit the MAP to propose a formal approach capable of providing solid basis to it, necessary when developing automatic tools aimed at supporting the modelling activity and the verification of the produced map diagrams.

Introduction

In the recent period, there has been the increasing need to foster the direct involvement of business experts in the development and maintenance of enterprise information systems (EIS), aiming at reducing the gap in the alignment of information systems and business needs. To bridge this gap, the OMG 3 has proposed the Model Driven Architecture (MDA) [START_REF] Bézivin | MDA components: Challenges and Opportunities[END_REF] approach that places the modelling activities at the centre of the EIS development. MDA is organised along three main modelling levels: CIM (Computational Independent Model), PIM (Platform Independent Model), and PSM (Platform Specific Model), with a progression that goes form business oriented models (CIM) to technology oriented models (PSM) of the enterprise software.

Traditionally, the intermediate level, PIM, has been characterised by extensive modelling, aimed at software design specifications. The top level, CIM, concerning the business modelling activities, is mainly expressed in an intuitive, 1 Univ. La Sorbonne, Paris1 2 CNR-IASI, Rome 3 Object Management Group, a major international standardization organization participated by all the primary computer industries informal fashion, with a prevalence of textual documents, often incomplete and ambiguous. Such imprecise specifications are among the causes of problems in the alignment of business requirements and EIS [10].

Experience proved that the early introduction of formal methods in business modelling has little success. It is better to start modelling business in an intuitive way and then progressively introduce precision and rigour, with an incremental approach. Along this line is positioned the MAP method [START_REF] Rolland | A Multi-Model View of Process Modeling[END_REF], where a business application is modelled in terms of intentions (goals) and strategies (activities) represented in a diagrammatic form, as nodes and arcs, respectively. The MAP method has been adopted and fruitfully used since long time. In this paper we revisit it, starting from a previous work [START_REF] Rolland | Combining Intention-Oriented and State-Based Process Modeling[END_REF] to further elaborate a formal framework and a new approach to model the contexts, i.e., the involved business objects with their states. Another key contribution of this paper is represented by the use of IF-THEN production rules to model MAP sections. Finally, having introduced an explicit representation of the pre-and post-conditions of a MAP section, we propose a formal approach aimed at a systematic validation of MAP models.

Related work

In the literature, there are several methods for early modelling of enterprise knowledge, such as Zachman [START_REF] Pereira | A Method to Define an Enterprise Architecture[END_REF] or TOGAF [START_REF] Saha | Analysing The Open Group Architecture Framework from the GERAM Perspective[END_REF]. They extensively model an enterprise but they are mainly conceived to be used by people, not by computers. When focusing on enterprise strategies, there are approaches based on "meansend" trees, representing goals and means to reach such goals, in an hierarchical decomposition structure [START_REF]Goal Based Requirements Analysis[END_REF]. Another approach is represented by the i* method [START_REF] Estrada | A Serviceoriented Approach for the i*Framework[END_REF], where goals are categorised into soft and hard ones, and it is possible to specify the actors and resources necessary to achieve such goals, in a network of dependencies. All these methods are essentially 'structural', in the sense that they do not capture the sequencing of goals and strategies (describing the business logic), as the MAP method does. Another important added value of the MAP methodology is on the explicit modelling of business objects that are involved in different strategies.

The rest of the paper is organised as follows. In Section 2 we introduce a running example, used throughout the paper. In section 3, we provide a first description of the MAP methodology, while in Section 4 we provide a preliminary proposal of a formal framework for its core part, including the principles for the systematic verification of MAP diagrams validity. Finally, Section 5 concludes the paper.

A practical example of MAP usage

In this section a business case is first reported in a narrative, textual form and then as a Map diagram, with a number of associated tables, Section Specification Table (SST), that allow the business context to be represented, i.e., the result of the enactment of a path, in terms of involved business objects with their states.

The business case: loan handling in a bank

Our business case refers to the loan handling process in a bank. A customer presents a loan request to a loan service clerk, in charge of setting up a file with the corresponding information (loan amount, rate, customer account situation, etc.). Then, the clerk performs a first formal check on the loan request and if it evidently exhibits a high risk then it is not further processed. In case the first filter is passed, the request needs to be evaluated, either by the loan service clerk himself (in the simple cases) or by the experts of the financial department (if an advanced evaluation is needed). The outcome of the evaluation is analysed by the loan manager who has the possibility either (i) to accept the loan request, or (ii) to ask the loan service clerk to further review it, or (iii) to ask an extensive reevaluation to the financial department. If the final decision is positive, the clerk assistant sends to the customer a proposal of loan, specifying the amount, the duration, and the refunding modalities. Then, the customer has to sign the contract in the indicated time span, otherwise the offer is cancelled. When the decision is negative, the clerk assistant notifies the customer with a refusal letter.

This brief text represents a typical preliminary description performed by a business expert. Then, starting from such a kind of statement, the business is modelled by a MAP diagram (a map, for short) as shown below.

A MAP diagram

The Figure 1 represents the business case just illustrated, where the strategies and intentions are respectively indicated by arcs and nodes of a directed multi-graph. In the MAP diagram we also have sections. A section is represented by a source and a target intention, and a strategy connecting the two. Finally, it is necessary to indicate when a section will be activated and what are the effects induced: such knowledge is expressed by pre-and post-conditions, respectively. A Section Specification Table (SST) complements the map diagram.

A Section Specification Table

To complete the specification of a Map diagram we need to provide further knowledge, concerning the objects, with their states, that characterise the different intentions and the involved sections. This knowledge is structured in the Section Specification Tables (SST, one for each section) which are organised in two parts: one part specifies the (source and target) intentions description, with their objects and states; the other part is related to the description of section's preconditions and post conditions. We consider the example of SST1 which reports the knowledge associated to the section S1. A table is an intuitive structure easy to be filled and managed by a business expert. In the next Section 3 we will provide a more precise and rigorous specification of the core elements of the MAP methodology.

The MAP Methodology

The MAP 4

Meta model

The MAP methodology allows business people to model the high level objectives and strategies of an enterprise, expressed in intentional terms. A MAP diagram represents a first specification of a business application; it contains a finite number of paths from 'Start' to 'Stop', each of which describes a way to develop a business product (for instance a service to be delivered). Such an application, at a later stage, will be modelled by Business Process diagrams.

An intention represents a desired state of the world, modelled in terms of a set of object states and, at the same time, a starting point for the activation of a strategy necessary to achieve the next intention. A strategy is used to achieve an intention, producing (part of) the desired object states. Since there can be multiple edges entering a node, the MAP is capable of representing different strategies that can be used for achieving, either fully or partially, an intention. Such strategies can be complementary (if more than one is needed to fulfil the intention) or alternative.

A map consists of several sections, each of which encapsulate a strategy, according to a five-tuple: S = <prc, psc, I i , I j , C ij >, where I i is the source intention, I j , is the target intention, C ij is the strategy linking the two intentions, and prc and psc are the pre-and post-conditions, respectively. There are two distinct pre-defined intentions, called Start and Stop, that represent the intentions to start navigating in the map and to stop doing so, respectively. In general, there are several paths in a map diagram from Start to Stop.

The pre-and post-conditions of a section are both defined in the form of Boolean expressions over object states. A section can be activated if its prc is verified. Then, after a finite time, the section is enacted, ensuring that the postconditions is true. Please note that in this paper we consider a simplified view in which: (i) all the preconditions must be verified before a section is activated, therefore we do not accept delayed pre-conditions, becoming true during the course of actions; (ii) we assume an optimistic approach, therefore when a section is activated it will eventually terminate, producing the effects specified in the postcondition. In essence, at this stage we are not dealing with notions such as exceptions, failures, or abort conditions. In general, the achievement of a target intention, using a strategy from a source intention (i.e. the enactment of a section), produces a state change on the involved objects, the creation of new objects, or the destruction of existing objects, according to the post-condition of the said section. We also assume that what is not explicitly indicated will remain as it was before the activation of the strategy (here we wish to recall the 'frame problem' [START_REF] Scherl | Knowledge, Action, and the Frame Problem[END_REF], guaranteeing the absence of 'hidden' side effects).

It is useful to introduce the notion of a context as a coherent set of object instances with their states. Each time a section terminates, the context evolves into a new state. The evolution over the time of the context takes place following the navigation through the map. In Fig. 2 the meta-model of map is reported.

Fig. 2. The MAP Meta-model

The MAP as an intentional process model

As a concrete example, the map shown in Figure 1 where and how. A strategy is an approach, a manner to achieve an intention (typically implemented by a business process). In Figure 1, we have the section: S1 = <prc, psc, Start, RegisterLoanRequest, InformationCaptureStrategy>, which links a source intention (Start) to a target intention (RegisterLoanRequest) through a strategy (InformationCaptureStrategy). Furthermore, we assume for instance that prc = 'Loan request has arrived' and psc = 'Loan Request Registered'.

A section of a map can be refined into a more detailed map. This happens when it can be decomposed into more refined intentions and associated strategies. This feature will not be dealt with in this paper. Detailed information can be found in [START_REF] Rolland | A Multi-Model View of Process Modeling[END_REF] and [START_REF] Nurcan | A strategy driven business process modelling approach[END_REF].

Towards a formal specification of MAP

Motivation

In this section we will revisit the MAP methodology with the objective of proposing a formal framework covering its core modelling notions. Such a formal framework will support the map developer on two levels. Firstly in the design process providing a rigorous, unambiguous grounding when building a complex map diagram. Secondly, a formal representation is needed to develop computer supported services; for instance for the simulation of a map diagram, even at a preliminary development stage, or for checking its validity.

In the following, the key notions of the MAP methodology, such as intentions, strategies, sections, pre-and post-conditions, will be formally specified. Def: Business Object (BO). It is the conceptual specification of a passive entity that characterizes a given Business Domain (BD) or application. They appear in a business scenario (BS). A BO specification includes a set of attributes that, when fully instantiated, define a business object instance. The attributes of an object are also used to define the object states (see later).

MAP Basic definitions

Def: Business Object State (BOS).

It is an intentional notion represented by a pair: (BO,sdef), where the state definition (sdef) is a labelled Boolean expression defined over the properties of one or more 5 BOSs. For short, when possible, we will use a synthetic label, bos, to indicate a Business Object State pair. A BOS is in fact a condition that can be checked against a BO instance, therefore: bos(oi) is true, if and only if the BO instance oi is in the sdef state 6 . Example BOS = {(request, underEval), (loan, granted) }; For conciseness, we may adopt for the BOS pair the following compact syntax: BOS = {request::underEval, loan::granted }.

Def: Intention. It represents a (intermediate) goal, a desired state of affairs defined by a set of business object states 7 , typically used in a conjunctive Boolean expression (Bex). When there are more than one set of object states (SOS) that satisfy an intention, its Boolean expression is disjunctive 8 . Example: DecideOnLoanOffer = { (LoanReq::accepted, LoanOffer::issued), (LoanReq::refused, RefusalLetter::sent }. This is an example of a disjunctive Intention, where the goal is achieved if one (or more) section produces the first pair or the second pair.

Def: Strategy and Section.

A strategy is the active element of a map, capable of achieving a goal. It contributes to define a Section that includes the source and target intentions, and the pre-and post-conditions (prc and psc), respectively. A strategy starts from an input context (satisfying the section's pre-conditions) and produces a new context satisfying the section's post-conditions.

In our proposal, a Section can be represented by a labeled (non-deterministic) production rule S, of the form: S = IF prc THEN C AND psc Applying the above rule pattern to the third section of our running example we have the following Example: S3 = IF LoanReq::registered THEN SimpleEvaluationStg AND (LoanReq::accepted, LoanOffer::issued) OR (LoanReq::refused, LoanOffer::cancelled) Def: Context. A context is a coherent set of object instances with their states. It is updated by strategies and evolves while a map diagram is traversed. There is an initial Context that then evolves according to the state of affairs determined by the enactment of a sequence of strategies. Each time a strategy terminates, the context is updated with the new object states produced by the former (according to its post-conditions).

The sections' sequencing between the Start and Stop intentions constitutes a "path" in the map. The "context" evolves with the enactment of a path. The context is thus the set of BOS resulting of a path enactment.

Having completed the definition of the key notions of a map model, in the following section we will address issues concerning the verification of validity of the built map.

Verification of a MAP Diagram

There are two main approaches to map diagram verification: a static and a dynamic one. The former is performed by statically analysing the sections with their pre-and post-conditions (as reported in the SSTs) and the intention definitions. In fact, not all possible diagrams, with strategies and intentions, are valid map models. There are a number of basic validity rules to be respected, as reported in [START_REF] Rolland | Eliciting Gaps in Requirements Change[END_REF] and [START_REF] Rolland | Matching ERP system functionality to customer requirements[END_REF], sketchily recapped below:

• Every intention in a map is the source of a strategy except the Stop intention. • Every intention in a map is the target of a strategy except the Start intention. • Two contiguous intentions are always connected by (at least) a strategy.

Therefore:

• Maps are connected graphs; there is no isolated intention or dangling strategies. • There is always (at least) a path from Start to Stop.

• Any section belongs at least to a path between Start and Stop (i.e., there are no extra 'sink' or 'source' nodes). • No strategy in the map can be defined as a sub-part of another strategy.

• No intention in the map can be defined as a sub-part of another intention.

• Intentions having as result the same part of product should be merged. Focusing on intentions, according to the definitions given above, we can provide further MAP validity rules [START_REF] Rolland | Combining Intention-Oriented and State-Based Process Modeling[END_REF], to be used in the validity verification method:

• No intention should have object states that do not belong to a precondition of an outgoing strategy (except the "stop" intention).

• No intention should have object states that are not produced by an incoming strategy (except the "start" intention). The latter requires that we adopt an operational view and then we analyse the diagram by traversing it, with a "enactment" logic. In this perspective the idea is that the control is initially positioned in the Start node and then the navigation (enacting sections) evolves until the Stop node is reached. By traversing a map diagram we have a sort of "live" validation of the correct sequencing of goals and strategies. This validation is mainly done by business experts who can confirm that the business actually behaves (or it is wished it does) according to the map. Here we report a sketch of an algorithmic method for the verification that all the intentions of a given map are achievable.

Begin

Forall intentions I i in map do Extract the business object states SOS i Forall SST j having I i as the target intention do Extract the post-condition psc j ProdOS i = ∪ j psc j If SOS i -ProdOS i = φ then intention I i is achievable else intention I i is not achievable fi od od End The above validation method addresses only one dimension of the map validation requirements, in particular the last bullet of the list of criteria reported above. Another dimension is represented by the possibility of an interactive validation performed by the business experts. Having introduced a rule-based formalization, it is possible to use a Rule System (such as Drools 9 ) to support the dynamic validation. This Rule System approach is based on two concepts: (i) the context and (ii) the production rules.

Conclusion

In this paper we presented a first approach towards a formalization of the MAP methodology, based on production rules to represent sections and a set-theoretic method to represent intentions and contexts. The formal approach is useful to (i) provide a formal semantics to map diagrams and (ii) to lay the basis for the development of automatic tools aimed at their verification and validation. Future activities will concentrate on the formalization of additional parts of the MAP methodology, excluded here for sake of space, and on the implementation of a first prototype aimed at map diagrams validation, along the line of the method represented in the Figure 3 of the previous section,

Fig. 1 .

 1 Fig. 1. The business map: Manage loan requests

  has 'Register the loan request' and 'Decide on the loan offer' as intentions. Both express what is wanted, a sequence of expected results, disregarding the considerations about who, when,

  Def: Map. A map is a business application model expressed in intentional terms. It provides a business logic driven representation based on a non-deterministic ordering of intentions (I), strategies (C), and sections (S) [3]: Map = (I, C, S). Example: I = (RegisterTheLoanRequest, MakeTheLoanOffer, Start, Stop) C = (InformationCaptureStrategy, ExpertEvaluationStrategy, …) S = (<prc1, psc1, Start, InformationCaptureStrategy, RegisterTheLoanRequest>, …)

Fig. 3 .

 3 Fig. 3. The map method for intentions' achievability validation

Table 1 .

 1

		the specification of Section 1 (SST1)
	SST	Intentions	Objects	States
	S1	(source) Start	loanReq	Arrived
		(target) Register the loan	loanReq	Registered
		request
		Strategy	Precond	Postcond
		By information capture	LoanReq::arrived	loanReq::registered

Please note that we will use the term MAP (full capital) to denote the methodology, while the term "map" will be used to denote a specific MAP diagram.

Note that the state of an object may be endogenous, depending on its own attribute(s), or exogenous, depending on the state of another object. E.g., a LoanRefusal depends on the LoanEval.

In other terms, the predicate bos = (bo, sdef) can test if the oi is of type bo and its attribute values satisfy the sdef.

Please note the compact syntax: <object>::<state> to represent an object state

Please note that in case of disjunction the objects of each SOS must be related, i.e., there is a unique set of BO for each Intention, and the alternatives are based on alternative states of the same objects.


Agnès Brenot

Emmanuelle Petelet-Giraud

Groundwater contribution to riverine wetlands in

teaching and research institutions in France or abroad, or from public or private research centers.

Agnès Brenot and Emmanuelle Petelet-Giraud BRGM, Avenue C. Guillemin, BP 36009, 45060 Orléans Cedex 02, France

The understanding of surface water and groundwater interactions and especially the role of groundwater in the context of wetlands is required for water quantity and quality preservation.

The present study proposed a geochemical and multi-isotopes approach to characterise the role of groundwaters from chalk aquifers on the quality of surface water draining riverine wetlands.

The studied area on located in the Austreberthe river basin, a tributary of the Seine River near Rouen (France). The Austreberthe River is fed by only one permanent tributary (Suffimbec) and numerous springs disseminated along the river course. The substratum is mainly composed of Cretaceous chalk, with the Santonian white chalk (up to 30-40 m thick), Coniacian white-grey chalk in the lower part of the basin, Turonian grey-white chalk with some flints in the upper part of the basin and Cenomanian glauconitic grey chalk in the Suffimbec valley.

Due to tectonic and climatic variations, the chalk has been affected by numerous accidents (faults ....) and subjected to alterations resulting in the development of karstic systems. Chalk is a mixed medium: porous, fissured and karstified. When the chalk is compact (in the plateaus and deep), water flows in the intergranular pores of about one micron. Groundwater flow in the aquifer is about 1 to 10 meters per year. Whereas within the millimetric crack, the water speed can reach several tens or hundreds of meters per year.

The system functioning was constrain trough geochemical (major and trace elements) and isotopic ( 87 Sr/ 86 Sr, δ 11 B) approaches. The isotopic tracer of water-rock interactions ( 87 Sr/ 86 Sr) shows that the river downstream is a mixture of all groundwater from the basin, reflecting the different drained lithologies. The tracers of anthropogenic impacts (nitrate, chloride, boron and δ 11 B ) trace a spatial deconvolution of the different anthropogenic pressures: agricultural inputs upstream (mainly nitrate and chloride) and urban wastewater in the downstream part of the basin (chloride and boron). The geochemical and isotopic approaches allowed go further in terms of knowledge of water and dissolved nutrients circulation trough 3 samples of the river from up-to downstream of the basin. It was shown that the evolution of the geochemistry of the river strictly follows that of groundwater contributing to surface runoff. The integrative power of the river, although expected, is clearly demonstrated; each river section reflecting the diversity of the dissolved inputs, corresponding both to natural inputs (related to water-rock interaction) and anthropogenic inputs (agricultural and urban). Thus, according to the hydrological conditions during the two sampling campaigns, i.e. no significant surface runoff, surface waters chemistry reflects almost exclusively the groundwater contribution all along the river.


MD Elisabeth Chéreau
email: elisabeth.chereau@gmail.com

MD, PhD R Rouzier

PhD S Gouy

MD G Ferron

MD F Narducci

MD C Bergzoll

MD C Huchon

MD, PhD F Lécuru

MD C Pomel

MD, PhD E Daraï

PhD E Leblanc

MD, PhD D Querleu

MD P Morice

Morbidity of diaphragmatic surgery for advanced ovarian cancer: Retrospective study of 148 cases

Keywords: ovarian cancer, diaphragmatic surgery, complete surgery, morbidity, survival

Introduction

Both retrospective and prospective reports have demonstrated that optimal cytoreduction for advanced epithelial ovarian cancer is the cornerstone of effective treatment [START_REF] Bristow | Survival effect of maximal cytoreductive surgery for advanced ovarian carcinoma during the platinum era: a meta-analysis[END_REF][START_REF] Chi | What is the optimal goal of primary cytoreductive surgery for bulky stage IIIC epithelial ovarian carcinoma (EOC)?[END_REF] . In patients with stage IIIC/IV disease (i.e., Advanced Ovarian Cancer, AOC), diaphragm involvement is very common [START_REF] Hacker | Primary cytoreductive surgery for epithelial ovarian cancer[END_REF] . Because of late diagnosis, the overall five-year survival rate for ovarian cancer is commonly approximately 30% [START_REF] Eisenkop | Optimal" cytoreduction for advanced epithelial ovarian cancer: a commentary[END_REF] . Bulky diaphragm disease had been reported as one of the most common sites of disease leading to suboptimal cytoreduction and therefore to a lower rate of survival. Surgical procedures already exist to treat diaphragm disease, which typically increase the rate of complete and optimal debulking and yield better survival compared to patients with residual disease found only in the diaphragm [START_REF] Chi | Improved optimal cytoreduction rates for stages IIIC and IV epithelial ovarian, fallopian tube, and primary peritoneal cancer: a change in surgical approach[END_REF] . Since 1986, some authors have reported their experience with diaphragmatic surgery in advanced ovarian cancer. The related reports highlighted feasibility, improvement in outcome in cases of optimal cytoreduction and specific pulmonary morbidity [START_REF] Deppe | Surgical approach to diaphragmatic metastases from ovarian cancer[END_REF][START_REF] Montz | Resection of diaphragmatic peritoneum and muscle: role in cytoreductive surgery for ovarian cancer[END_REF][START_REF] Kapnick | Occult pleural involvement in stage III ovarian carcinoma: role of diaphragm resection[END_REF][9][START_REF] Eisenhauer | Incidence and management of pleural effusions after diaphragm peritonectomy or resection for advanced mullerian cancer[END_REF][START_REF] Dowdy | Assessment of outcomes and morbidity following diaphragmatic peritonectomy for women with ovarian carcinoma[END_REF][START_REF] Devolder | Role of diaphragmatic surgery in 69 patients with ovarian carcinoma[END_REF][START_REF] Chéreau | Pulmonary morbidity of diaphragmatic surgery for stage III/IV ovarian cancer[END_REF][START_REF] Fanfani | Upper abdominal surgery in advanced and recurrent ovarian cancer: role of diaphragmatic surgery[END_REF][START_REF] Tsolakidis | Diaphragmatic surgery during primary debulking in 89 patients with stage IIIB-IV epithelial ovarian cancer[END_REF][START_REF] Gouy | Surgical procedures and morbidities of diaphragmatic surgery in patients M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT undergoing initial or interval debulking surgery for advanced-stage ovarian cancer[END_REF] . Moreover, incorporation of extensive upper abdominal procedures, such as partial liver section, distal pancreatectomy or splenectomy, may lead to improved cytoreduction [START_REF] Eisenhauer | The addition of extensive upper abdominal surgery to achieve optimal cytoreduction improves survival in patients with stages IIIC-IV epithelial ovarian cancer[END_REF][START_REF] Zivanovic | The impact of bulky upper abdominal disease cephalad to the greater omentum on surgical outcome for stage IIIC epithelial ovarian, fallopian tube, and primary peritoneal cancer[END_REF][START_REF] Aletti | Surgical treatment of diaphragm disease correlates with improved survival in optimally debulked advanced stage ovarian cancer[END_REF][START_REF] Kehoe | Upper abdominal surgical procedures: liver mobilization and diaphragm peritonectomy/resection, splenectomy, and distal pancreatectomy[END_REF][START_REF] Colombo | Aggressive surgical strategies in advanced ovarian cancer: a monocentric study of 203 stage IIIC and IV patients[END_REF][START_REF] Chi | Improved progression-free and overall survival in advanced ovarian cancer as a result of a change in surgical paradigm[END_REF][23] . Extensive surgery could increase postoperative morbidity (digestive fistula, lymphocyst or infection) [START_REF] Chéreau | Pulmonary morbidity of diaphragmatic surgery for stage III/IV ovarian cancer[END_REF][START_REF] Estes | Bowel resection at the time of primary debulking for epithelial ovarian carcinoma: outcomes in patients treated with platinum and taxane-based chemotherapy[END_REF][START_REF] Mourton | Morbidity of rectosigmoid resection and primary anastomosis in patients undergoing primary cytoreductive surgery for advanced epithelial ovarian cancer[END_REF][START_REF] Tamussino | Gastrointestinal surgery in patients with ovarian cancer[END_REF][START_REF] Houvenaeghel | Modified posterior pelvic exenteration for ovarian cancer[END_REF][START_REF] Gillette-Cloven | Bowel resection at the time of primary cytoreduction for epithelial ovarian cancer[END_REF][START_REF] Richardson | Risk factors for anastomotic leak after rectosigmoid resection for ovarian cancer[END_REF][START_REF] Gerestein | Causes of postoperative mortality after surgery for ovarian cancer[END_REF][31][32][33][34] . Therefore, radical surgery for advanced ovarian cancer could improve survival but with an increase in postoperative morbidity. To date, the studies reporting diaphragmatic surgery in AOC have included less than 90 patients, were unicentric studies, and were focused on pulmonary complications only. We conducted a retrospective, multicentric study that included 148 patients who underwent diaphragmatic surgery for AOC to investigate pulmonary and general complications due to extensive surgery.

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Materials and Methods

During the period from 2004 to 2008, 148 patients underwent diaphragmatic surgery for stage IIIC or IV ovarian cancer at six French surgical oncology departments. The individual records of all patients were reviewed and analysed. Patient and tumour characteristics, intra-operative findings, postoperative courses and outcomes were analysed. Diaphragmatic surgeries may have consisted of stripping, muscle resection or electrosurgical ablation. The mean diameter of the diaphragmatic resection was also studied. The indication of chest tube placement followed the surgeon's preference and typical practice at each centre. The chest tube was typically placed at the pleural opening, especially in the case of multiple openings. Extensive upper abdominal surgery included splenectomy, cholecystectomy, distal pancreatectomy, partial liver section and lesser omentum resection. Residual disease was reported as complete (no residual disease, R0) or incomplete 35 . Intra-operative estimated blood loss, operative time, and length of hospitalisation were all recorded. The duration of drainage, secondary pleural puncture requirement and post-operative complications such as digestive fistula, lymphocyst and infection were also recorded.

Because this study was a retrospective study, no Institutional Review Board approval was needed.

Statistical Analysis

Data were analysed using the chi-square test and Student's t-test. Differences were considered significant at a level of p < 0.05. Cox proportional hazards regression was used for multivariate analysis.

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Results

The median age of patients was 59 years (Table 1). Most patients were of stage FIGO 3C (91%) and had grade 2 (46%) or 3 (43%) lesions. The mean rate of CA 125 at the time of the diagnosis was 1588 UI/l. Eighty-one patients received neo-adjuvant chemotherapy. Initial surgery was performed in 38% of patients, interval surgery in 51% of cases and surgery for recurrent disease in 11% of cases. The histological type was more often serous (69%) or endometrioid (8%), and the mean size of ovarian tumours was 67 mm. During cytoreduction, 80% of patients had salpingo-oophorectomy, 76% had hysterectomy, 91% had omentectomy, 69% had pelvic lymph node dissection, 72% had para-aortic lymph node dissection, and 55% underwent appendectomy. Intestinal resection was performed in 68% of cases. Extensive upper abdominal surgery included lesser omentum resection (35%), splenectomy (31%), cholecystectomy (18%), distal pancreatectomy (4%), partial liver section (9%) and partial gastrectomy (3%). All patients underwent diaphragmatic surgery. On the right hemidiaphragm, coagulation was performed in 25% of cases, stripping (resection of the diaphragm peritoneum) was performed in 91% of cases, and muscle resection was performed in 62% of cases, with 51% of pleural openings (procedures may have been combined). Fewer patients underwent left hemi-diaphragm surgery (42%): coagulation was performed in 32% of cases, stripping in 74% of cases and muscle resection in 15% of cases (including 8% with pleural opening). The mean size of diaphragmatic resection was 126 mm for the right side and 74 mm for the left side. Pleural drainage was established during the surgical course for 35% of patients, and the mean duration of drainage was 5.1 days. The mean operative time was 426 minutes, and the estimated blood loss was 1465 ml. One hundred and twenty-four (84%) patients underwent complete cytoreduction (R0), and 24 underwent incomplete resection (16%).

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Details about the extent of surgery according to the timing of surgery (i.e., initial, interval or recurrence) are reported in Supplementary file 1.

Postoperative complications occurred in 102 patients (Table 2), and pulmonary complications were diagnosed in 63 patients. The complications included pleural effusions in 37% of patients, pulmonary embolisms in 5%, pneumothorax in 4% and pulmonary infections in 2%.

Sixty-two patients had non-pulmonary complications, including digestive fistulas (7%), lymphocysts (18%) and fever or infections (55%). Revision surgery was necessary for 13% of patients, secondary drainages or pleural punctures for 14% of patients and lymphocyst punctures for 11% of patients. Rehospitalisation was required for 20% of patients. Four patients died within 30 days of operation (3%), all from septic complications.

When we calculated the rate of postoperative complications (total, pulmonary or nonpulmonary) according to the number of patients managed during the study period (> or < 20 patients), there was no significant difference between the groups (Supplementary file 2).

We next compared surgical characteristics and postoperative complications between initial surgery and interval surgery. We found significant differences in the mean duration of surgery (467 min for initial surgery vs. 409 for interval surgery, p=0.019) and for the occurrence of intestinal resection (p=0.011), lymphadenectomy (p=0.04) and partial liver section (p=0.004).

Despite these results, we did not find any significant differences in the occurrence of postoperative complications or the results of the surgery.

Risk factors for pulmonary complications were the addition of extensive upper surgery to the diaphragmatic surgery (p=0.014) and the size of the diaphragmatic resection (p= 0.012). For severe complications (resulting in death or high morbidity), we identified past history of surgery (p=0.012) and intestinal resection (p=0.013) as risk factors. Time of surgery (initial or interval surgery) was not a risk factor for the occurrence of postoperative complications, regardless of type (pulmonary, non-pulmonary or severe complications).

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The median follow-up time for the group was 19.1 months. The two-year disease-free survival was 37%. The five-year overall survival and disease-free survival estimations were 45% and 10%, respectively. There were no differences for disease free survival (DFS) or overall survival (OS) between initial and interval surgeries.

M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT Discussion

For AOC, residual disease after surgery is the most relevant determining factor for survival [START_REF] Bristow | Survival effect of maximal cytoreductive surgery for advanced ovarian carcinoma during the platinum era: a meta-analysis[END_REF][START_REF] Chi | What is the optimal goal of primary cytoreductive surgery for bulky stage IIIC epithelial ovarian carcinoma (EOC)?[END_REF] . Because more than 75% of patients with advanced ovarian cancer had diaphragmatic disease on at least one side, diaphragmatic surgery is a major step in cytoreductive surgery [START_REF] Hacker | Primary cytoreductive surgery for epithelial ovarian cancer[END_REF] . However, radical surgery has its own morbidity, including both pulmonary and non-pulmonary (digestive fistula, lymphocyst, fever or infection) complications. In this study of 148 patients with diaphragmatic surgery as part of the radical cytoreductive surgery for stage-3C and stage-4 ovarian cancer, postoperative complications occurred in 69% of cases: 43% of patients had pulmonary complications, and 42% of patients had non-pulmonary complications.

Extension of radical surgery

Diaphragmatic carcinomatosis is one of the most frequent localisations in AOC. We reported patient and tumour characteristics in accordance with literature findings: the median age was 59 years, and the tumours were most often serous (49%) and grade 2 (46%) or 3 (43%). The rate of complete cytoreduction was 84%. To obtain this high rate of complete cytoreduction, extensive surgery including upper abdominal surgery and digestive resection was often performed. Moreover, this rate can be explained by the high rate of interval surgery.

In the literature, during extensive surgery with the aim of optimal resection, authors reported rates of diaphragmatic surgery ranging from 10 to 100%, intestinal resection from 20 to 100%, splenectomy from 1 to 33%, distal pancreatectomy from 0 to 11%, partial liver section from 0 to 16% and cholecystectomy from 2 to 20% [START_REF] Chi | What is the optimal goal of primary cytoreductive surgery for bulky stage IIIC epithelial ovarian carcinoma (EOC)?[END_REF][START_REF] Chi | Improved optimal cytoreduction rates for stages IIIC and IV epithelial ovarian, fallopian tube, and primary peritoneal cancer: a change in surgical approach[END_REF][START_REF] Eisenhauer | Incidence and management of pleural effusions after diaphragm peritonectomy or resection for advanced mullerian cancer[END_REF][START_REF] Chéreau | Pulmonary morbidity of diaphragmatic surgery for stage III/IV ovarian cancer[END_REF][START_REF] Chi | Improved progression-free and overall survival in advanced ovarian cancer as a result of a change in surgical paradigm[END_REF][START_REF] Mourton | Morbidity of rectosigmoid resection and primary anastomosis in patients undergoing primary cytoreductive surgery for advanced epithelial ovarian cancer[END_REF]36 . In this study, in addition to systematic diaphragmatic surgery, we performed similar rates of intestinal resection (68%), splenectomy (31%), cholecystectomy (18%), partial liver section (9%) and distal

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pancreatectomy (4%). These results suggest that diaphragmatic surgery is only one component of radical surgery. Therefore, postoperative morbidity included, in addition to pulmonary complications, other specific complications such as digestive fistula and lymphocysts.

Pulmonary complications

During diaphragmatic surgery, the pleural space was opened in 51% of cases. Rates found in others studies ranged from 7 to 52% (Table 3) [START_REF] Deppe | Surgical approach to diaphragmatic metastases from ovarian cancer[END_REF][START_REF] Montz | Resection of diaphragmatic peritoneum and muscle: role in cytoreductive surgery for ovarian cancer[END_REF][START_REF] Kapnick | Occult pleural involvement in stage III ovarian carcinoma: role of diaphragm resection[END_REF][9][START_REF] Eisenhauer | Incidence and management of pleural effusions after diaphragm peritonectomy or resection for advanced mullerian cancer[END_REF][START_REF] Dowdy | Assessment of outcomes and morbidity following diaphragmatic peritonectomy for women with ovarian carcinoma[END_REF][START_REF] Devolder | Role of diaphragmatic surgery in 69 patients with ovarian carcinoma[END_REF][START_REF] Chéreau | Pulmonary morbidity of diaphragmatic surgery for stage III/IV ovarian cancer[END_REF][START_REF] Fanfani | Upper abdominal surgery in advanced and recurrent ovarian cancer: role of diaphragmatic surgery[END_REF][START_REF] Tsolakidis | Diaphragmatic surgery during primary debulking in 89 patients with stage IIIB-IV epithelial ovarian cancer[END_REF][START_REF] Gouy | Surgical procedures and morbidities of diaphragmatic surgery in patients M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT undergoing initial or interval debulking surgery for advanced-stage ovarian cancer[END_REF] . Pulmonary complications occurred in 43% of cases, with the main complication being pleural effusion (37%). Other complications were pneumothorax (4%), pulmonary infections (2%) and pulmonary embolism (5%). Several studies have reported rates of pulmonary complications after diaphragmatic surgery for ovarian cancer (Table 3). In these studies, the rates of diaphragmatic surgery ranged from 14 to 100%, and complete surgery was achieved in 43 to 93% of cases. Pneumothorax was found in 0 to 33% of cases. Pleural effusion occurred in 0 to 59% of cases, depending on the rate of chest drainage established during surgery (from 0 to 65%). In a previous study, we concluded on the relevance of chest drainage in cases of pleural opening [START_REF] Chéreau | Pulmonary morbidity of diaphragmatic surgery for stage III/IV ovarian cancer[END_REF] . Eisenhauer et al. [START_REF] Eisenhauer | Incidence and management of pleural effusions after diaphragm peritonectomy or resection for advanced mullerian cancer[END_REF] had previously claimed that systematic placement of chest tubes was not justified because, in their view, the occurrence of postoperative pleural effusion was not a major postoperative complication. However, in their study, only 40% of patients had lymphadenectomies, and 60% had only diaphragmatic surgery. In our experience, the need for secondary drainage or pleural puncture extended the length of hospitalisation and post-operative pain; therefore, placement of a chest tube in cases of pleural opening might be relevant [START_REF] Chéreau | Pulmonary morbidity of diaphragmatic surgery for stage III/IV ovarian cancer[END_REF] . Rates of secondary pleural puncture or chest tube placement in the literature ranged from 0 to 44%; this variability may be related to the number of chest drains inserted during surgery. The rates of secondary pleural puncture or chest tube placement in our study Risk factors for the occurrence of pulmonary complications were the addition of other upper abdominal procedures and the size of the diaphragmatic resection [START_REF] Tsolakidis | Diaphragmatic surgery during primary debulking in 89 patients with stage IIIB-IV epithelial ovarian cancer[END_REF] . Other studies found liver mobilisation [START_REF] Eisenhauer | Incidence and management of pleural effusions after diaphragm peritonectomy or resection for advanced mullerian cancer[END_REF] or pleural opening [START_REF] Dowdy | Assessment of outcomes and morbidity following diaphragmatic peritonectomy for women with ovarian carcinoma[END_REF] to be risk factors. Because we routinely divide the hepatic ligaments to mobilise the liver, we were unable to test this association in our cohort.

Non-pulmonary complications

The rates of non-pulmonary complications found in our study were similar to those reported in the literature [START_REF] Chéreau | Pulmonary morbidity of diaphragmatic surgery for stage III/IV ovarian cancer[END_REF][START_REF] Colombo | Aggressive surgical strategies in advanced ovarian cancer: a monocentric study of 203 stage IIIC and IV patients[END_REF][START_REF] Chi | Improved progression-free and overall survival in advanced ovarian cancer as a result of a change in surgical paradigm[END_REF][23][START_REF] Estes | Bowel resection at the time of primary debulking for epithelial ovarian carcinoma: outcomes in patients treated with platinum and taxane-based chemotherapy[END_REF][START_REF] Mourton | Morbidity of rectosigmoid resection and primary anastomosis in patients undergoing primary cytoreductive surgery for advanced epithelial ovarian cancer[END_REF][START_REF] Tamussino | Gastrointestinal surgery in patients with ovarian cancer[END_REF][START_REF] Houvenaeghel | Modified posterior pelvic exenteration for ovarian cancer[END_REF][START_REF] Gillette-Cloven | Bowel resection at the time of primary cytoreduction for epithelial ovarian cancer[END_REF][START_REF] Richardson | Risk factors for anastomotic leak after rectosigmoid resection for ovarian cancer[END_REF][START_REF] Gerestein | Causes of postoperative mortality after surgery for ovarian cancer[END_REF][31][32][33][34] : digestive fistula from 1.4 to 8.2%, lymphocyst from 0.6 to 32%, and septic complications from 3.7 to 41.4%. The revision surgery rate in our study was in accordance with data in the literature that report rates from 4.1 to 16.5%. Four patients died during the 30 postoperative days, all from septic complications. Rates in the literature ranged from 0.3 to 5.7%. In a recent meta-analysis, Gerestein et al. [START_REF] Gerestein | Causes of postoperative mortality after surgery for ovarian cancer[END_REF]37 found that the more frequent causes of postoperative mortality were adverse surgical events, pulmonary complications and cardiovascular complications.

The important rate of iterative surgery found among our population was in accordance with the rates reported in the literature for extensive surgery (from 4.1% to 16%) [START_REF] Chéreau | Pulmonary morbidity of diaphragmatic surgery for stage III/IV ovarian cancer[END_REF][START_REF] Estes | Bowel resection at the time of primary debulking for epithelial ovarian carcinoma: outcomes in patients treated with platinum and taxane-based chemotherapy[END_REF][START_REF] Mourton | Morbidity of rectosigmoid resection and primary anastomosis in patients undergoing primary cytoreductive surgery for advanced epithelial ovarian cancer[END_REF][START_REF] Tamussino | Gastrointestinal surgery in patients with ovarian cancer[END_REF][START_REF] Gillette-Cloven | Bowel resection at the time of primary cytoreduction for epithelial ovarian cancer[END_REF]31 .

Expert centres

Another major consideration when debating morbidity for AOC is the management of patients in expert centres. Indeed, publications increasingly highlight the importance of not only

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surgical skills and experience but also of high-quality surgical care delivered by a multidisciplinary team that includes oncology nurses, anaesthesiologists, pathologists, dieticians and physiotherapists for the management of advanced ovarian cancer patients [START_REF] Aletti | Surgical treatment of diaphragm disease correlates with improved survival in optimally debulked advanced stage ovarian cancer[END_REF] .

Many retrospectives studies have reported that debulking operations performed by gynaecologic oncologists result in the best outcomes (including survival) compared to surgery performed by general gynaecologists or general surgeons [START_REF] Kehoe | Upper abdominal surgical procedures: liver mobilization and diaphragm peritonectomy/resection, splenectomy, and distal pancreatectomy[END_REF][START_REF] Colombo | Aggressive surgical strategies in advanced ovarian cancer: a monocentric study of 203 stage IIIC and IV patients[END_REF][START_REF] Chi | Improved progression-free and overall survival in advanced ovarian cancer as a result of a change in surgical paradigm[END_REF] . Therefore, centralisation of these patients in expert centres is recommended.

In this study, no differences were found between the centres with under or over 20 patients. This outcome was expected because all surgeons were gynaecologic oncologists and all these centres were used to perform radical surgery not only for ovarian cancer but also for advanced cervical, endometrial or vulvar cancer.

Conclusion

One of the strengths of this study is the report of not only specific postoperative complications of diaphragmatic surgery but also other complications of extensive surgery for AOC.

In conclusion, diaphragmatic surgery is an essential step in cytoreductive surgery for AOC and improves survival. When this surgery is used, it causes pulmonary complications in addition to morbidity due to the need for radical surgery.

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  in agreement with these data. The rate of pleural effusion reported in our study could be explained by the importance of achieving 62% muscle resection and a median size of right hemi-diaphragm resection of 126 mm in diaphragmatic surgery. This rate emphasised the relevance of chest drainage in decreasing postoperative interventions.

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