Z K Klouch

F Caradec

M Plus

T Hernández-Fariñas

L Pineau Guillou

A Chapelle

S Schmitt

J Quéré

L Guillou

R Siano

Heterogeneous distribution in sediments and dispersal in waters of Alexandrium minutum in a semi-enclosed coastal ecosystem

Keywords: molecular ecology, dinoflagellate cyst, spatial distribution, real-time PCR, Lagrangian model, population dynamics

come

Introduction

The recovery of resting stages of harmful microalgae in sediment samples and the identification of accumulation sites indicate potential seeding sources for the initiation of blooms [START_REF] Anderson | The globally distributed genus Alexandrium: Multifaceted roles in marine ecosystems and impacts on human health[END_REF]. Cyst bank mapping is therefore particularly useful for the risk assessment of harmful microalgae, since it enables the prediction of blooming areas and the optimization of the management of coastal economic activities.

The distribution of Alexandrium species in coastal and shelf waters is relatively well known; however, comprehensive distributional data, especially for resting stage banks, are still needed [START_REF] Anderson | The globally distributed genus Alexandrium: Multifaceted roles in marine ecosystems and impacts on human health[END_REF]. On the basis of the available information, some common features in the distribution of Alexandrium cysts can be identified. Previous studies have reported that cyst accumulations are favored in fine-muddy rather than sandy sediments [START_REF] White | Resting cysts of the toxic red tide dinoflagellate Gonyaulax excavata in Bay of Fundy sediments[END_REF][START_REF] Kremp | Distribution, dynamics and in situ seeding potential of Scrippsiella hangoei (Dinophyceae) cyst populations from the Baltic Sea[END_REF][START_REF] Yamaguchi | Distribution and Abundance of Resting Cysts of the Toxic Dinoflagellates Alexandrium tamarense and A. catenella in sediments of the eastern Seto Inland Sea, Japan, Intergovernmental Oceanographic Commission of UNESCO[END_REF][START_REF] Joyce | Dinoflagellate cysts from surface sediments of Saldanha Bay, South Africa: an indication of the potential risk of harmful algal blooms[END_REF][START_REF] Gayoso | Observation on Alexandrium tamarense (Lebour) Balech and other dinoflagellate population in Golfo Nuevo, Patagonia (Argentina)[END_REF][START_REF] Matsuoka | Modern dinoflagellate cysts in hypertrophic coastal waters of Tokyo Bay, Japan[END_REF][START_REF] Wang | Seasonal distribution of dinoflagellate resting cyst in surface sediment from Changjang River Estuary[END_REF][START_REF] Anderson | Alexandrium fundyense cyst dynamics in the Gulf of Maine[END_REF][START_REF] Penna | Detection of microalgal resting cysts in European coastal sediments using a PCR-based assay[END_REF][START_REF] Horner | Spatial distribution of benthic cysts of Alexandrium catenella in surface sediments of Puget Sound, Washington, USA[END_REF][START_REF] Genovesi | Influences of sedimentation and hydrodynamics on the spatial distribution of Alexandrium catenella/tamarense resting cysts in a shellfish farming lagoon impacted by toxic blooms[END_REF][START_REF] Trikia | Distribution of resting cysts of the potentially toxic dinoflagellate Alexandrium pseudogonyaulax in recently-deposited sediment within Bizerte Lagoon (Mediterranean coast, Tunisia)[END_REF], Fertouna-Bellakhal et al., 2015), supporting the hypothesis that dinoflagellate resting stages behave physically like fine particles [START_REF] Dale | Dinoflagellate resting cysts: benthic plankton[END_REF]. In semi-enclosed, confined ecosystems discrete cyst banks may be found [START_REF] Anderson | The globally distributed genus Alexandrium: Multifaceted roles in marine ecosystems and impacts on human health[END_REF]. A close link between the local distribution of cyst banks and blooms has been documented for some Alexandrium species in estuaries [START_REF] Cembella | Spatial distribution of Protogonyaulax tamarensis resting cysts in nearshore sediments along the north coast of the lower St. Lawrence estuary[END_REF][START_REF] Crespo | Dynamics of Alexandrium fundyense blooms and shellfish toxicity in the Nauset Marsh System of Cape Cod (Massachusetts, USA)[END_REF][START_REF] Anderson | Alexandrium fundyense cysts in the Gulf of Maine: long-term time series of abundance and distribution, and linkages to past and future blooms[END_REF], lagoons [START_REF] Genovesi | Dormancy and germination features in resting cysts of Alexandrium tamarense species complex (Dinophyceae) can facilitate bloom formation in a shallow lagoon (Thau, southern France)[END_REF][START_REF] Genovesi | Influences of sedimentation and hydrodynamics on the spatial distribution of Alexandrium catenella/tamarense resting cysts in a shellfish farming lagoon impacted by toxic blooms[END_REF][START_REF] Trikia | Distribution of resting cysts of the potentially toxic dinoflagellate Alexandrium pseudogonyaulax in recently-deposited sediment within Bizerte Lagoon (Mediterranean coast, Tunisia)[END_REF], Fertouna-Bellakhal et al., 2015), and harbors [START_REF] Bravo | Alexandrium catenella and Alexandrium minutum blooms in the Mediterranean Sea: toward the identification of ecological niches[END_REF][START_REF] Penna | Detection of microalgal resting cysts in European coastal sediments using a PCR-based assay[END_REF]). This local distribution has been associated with the hydrodynamic features of the studied ecosystems. Despite occurring in adjacent waters, local blooms of A. fundyense Balech were temporally separated, probably due to water retention in the first site where the blooms occurred [START_REF] Crespo | Dynamics of Alexandrium fundyense blooms and shellfish toxicity in the Nauset Marsh System of Cape Cod (Massachusetts, USA)[END_REF]. Cyst densities of A. tamarense (Lebour) Balech were influenced by local hydrodynamics, with wind-induced currents causing cyst dispersal in the shallow ecosystem of the Thau lagoon [START_REF] Genovesi | Influences of sedimentation and hydrodynamics on the spatial distribution of Alexandrium catenella/tamarense resting cysts in a shellfish farming lagoon impacted by toxic blooms[END_REF]. These examples prove the interest of characterizing discrete, fine spatial scale cyst distributions to deduce local bloom dynamics in semienclosed ecosystems.

Traditionally, hot spots of harmful microalgae accumulation in sediments are identified by microscopy counting of their cysts [START_REF] Genovesi | Influences of sedimentation and hydrodynamics on the spatial distribution of Alexandrium catenella/tamarense resting cysts in a shellfish farming lagoon impacted by toxic blooms[END_REF], a method that is time-consuming and suffers from taxonomical limitations in identification due to the lack of distinctive morphological characteristics for the cysts of some species. In contrast, the analysis of specific genetic material in sediment has proved to be a valuable alternative to infer cyst distribution, enabling a large number of samples to be processed objectively in a relatively short time. The amplification of species-specific marker genes from DNA preserved in sediment samples has been used to infer the presence of dinoflagellate cysts [START_REF] Godhe | PCR detection of dinoflagellate cysts in field sediment samples from tropic and temperate environments[END_REF], Penna et al., 2010). Real-time PCR amplification to quantify DNA genes from sediments has been shown to be a good proxy for cyst abundances, including some Alexandrium species [START_REF] Kamikawa | Application of real-time PCR assay for detection and quantification of Alexandrium tamarense and Alexandrium catenella cysts from marine sediments[END_REF][START_REF] Erdner | A quantitative real-time PCR assay for the identification and enumeration of Alexandrium cysts in marine sediments[END_REF][START_REF] Park | Detection of Cochlodinium polykrikoides and Gymnodinium impudicum (Dinophyceae) in sediment samples from Korea using real -time PCR[END_REF]. Lastly, cyst species have been mapped using the fluorescence in situ hybridization (FISH) technique [START_REF] Hattenrath-Lehmann | Mapping the distribution of cysts from the toxic dinoflagellate Cochlodinium polykrikoides in bloom-prone estuaries by a novel fluorescence in situ hybridization assay[END_REF]. Genetic techniques can therefore be used to provide reliable information on accumulation spots of cysts and to infer ecological patterns. Given the close association between resting cyst abundance and sediment type, high specific DNA abundances should also b e found in the corresponding muddy sediments. The DNA extracted from sediments, however, can be of both intercellular (resting stages) [START_REF] Godhe | PCR detection of dinoflagellate cysts in field sediment samples from tropic and temperate environments[END_REF][START_REF] Erdner | A quantitative real-time PCR assay for the identification and enumeration of Alexandrium cysts in marine sediments[END_REF] and extracellular origin [START_REF] Pietramellara | Extracellular DNA in soil and sediment: fate and ecological relevance[END_REF], making the relationship between specific DNA traces and sediment type not completely predictable and still barely studied.

Although the analysis of genetic material in sediment cores showed that A. minutum Halim has been present in the Bay of Brest since at least the 19th century [START_REF] Klouch | Historical records from dated sediment cores reveal the multidecadal dynamic of the toxic dinoflagellate Alexandrium minutum in the Bay of Brest (France)[END_REF] [START_REF] Erard-Le Denn | Alexandrium minutum: resting cyst distribution in the sediments collected along the Brittany coast, France[END_REF][START_REF] Erard-Le Denn | Resting cysts of Alexandrium minutum in marine sediments: quantification by three methods[END_REF]. The species abundance increased over time in the bay, reaching the record concentration of ca. 42 x 10 6 cells l -1 in July 2012 [START_REF] Chapelle | The Bay of Brest (France), a new risky site for toxic Alexandrium minutum blooms and PSP shellfish contamination[END_REF][START_REF] Klouch | Historical records from dated sediment cores reveal the multidecadal dynamic of the toxic dinoflagellate Alexandrium minutum in the Bay of Brest (France)[END_REF] in the small, enclosed Daoulas estuary, where bloom occurrences were unsuspected and monitoring was not carried out. In parallel, other blooms of the species were observed in other estuaries on the bay (Elorn River, Aulne River), but these were of minor importance (< 2 x 10 6 cells l -1 ). After the 2012 event, monitoring of Daoulas Bay was initiated and seasonal blooms of A. minutum are observed in the Daoulas estuary along with blooms of lower cell abundance in other monitored estuaries. The development of different intensities in the Bay of Brest raises questions about the distribution of the major cyst banks of the species and the potential connectivity between its different adjacent estuarine ecosystems.

In this study, both genetic analyses of sediments and model simulations in the water column were used to try to explain the heterogeneity of A. minutum bloom occurrence in the Bay of Brest.

With a recently developed real-time PCR assay [START_REF] Klouch | Historical records from dated sediment cores reveal the multidecadal dynamic of the toxic dinoflagellate Alexandrium minutum in the Bay of Brest (France)[END_REF], the ITS1rDNA copy number of A.

minutum from total DNA extracts of superficial sediments was quantified and used to infer the distribution of cyst banks in the area. In parallel, the viability of these banks in the sampled stations was determined in order to verify whether DNA genetic data correspond to viable resting stages of the organisms and not only to the amplification of extracellular DNA. By means of a Lagrangian physical model, passive particle trajectories released from different estuarine zones were simulated in order to study the potential dispersal of A. minutum cells of different blooms and the connectivity between different estuaries of the bay. The information gathered on both the benthic and the pelagic habitat contributes to the understanding of A. minutum bloom dynamics in the Bay of Brest and provides an example of heterogeneity in the dispersal of toxic microalgae in a semi-enclosed coastal area.

Materials and Methods

Study area

The Bay of Brest (Brittany, France) is a semi-enclosed, marine ecosystem of 180 km 2 connected to the Iroise Sea (Atlantic Ocean) by an opening 1.8 km wide and ~50 m deep (Fig. 1). The bay is a shallow (about half of the total surface area is shallower than 5 m) macrotidal coastal system. The semidiurnal tidal amplitude ranges from 1.2 to 7.3 m (average of 4 m), leading to the presence of extended intertidal flats during low tides. Frequent storms can induce a resuspension of material and a very high turbidity (>100 mg l -1 of sediments) over a long period of time (Hily et al., 1992). The bay is characterized by fine and coarse sediments in shallow and deep waters, respectively, with a higher proportion of muddy sediments in the upstream part of the estuaries [START_REF] Hily | La megafaune benthique des fonds meubles de la rade de Brest: pré -échantillonage par vidéo sous-marine[END_REF]. The ecosystem hydrology is influenced by 5 different watersheds, with two main rivers, the Aulne (1842 km 2 catchment area, 30 m 3 s -1 interannual mean flow) flowing into the south basin and the Elorn (402 km 2 catchment area, 5.63 m 3 s -1 interannual mean flow) flowing into the north basin, contributing to about 80% of the total annual freshwater input. The total interannual mean flow has stabilized after a four-decade rise, while the anthropogenic loads of nitrogen and phosphorous have stabilized and decreased, respectively. The ban on washing powders containing orthophosphates in the last two decades has resulted in a decreased phosphorous supply and thus a significant imbalance in the N/P ratio (Chauvaud et al., 2000, Guillaud and[START_REF] Guillaud | Relation concentration-débit et évolution temporelle du nitrate dans 25 rivières de la région Bretagne (France)[END_REF] which has led to changes in the composition of planktonic and benthic communities [START_REF] Quéguiner | Studies on the Phytoplankton in the Bay of Brest (Western Europe). Seasonal variations in composition, biomass and production in relation to hydrological and chemical features (1981-1982)[END_REF][START_REF] Del Amo | Impacts of high-nitrate freshwater inputs on macrotidal ecosystems. II. Specific role of the silicic acid pump in the year-round dominance of diatoms in the Bay of Brest (France)[END_REF][START_REF] Chauvaud | Long-term variation of the Bay of Brest ecosystem: benthic-pelagic coupling revisited[END_REF].

Sampling strategy

Thirty sites were selected in the Bay of Brest on the basis of available cartographies of sediment typologies and benthic biotopes. Sampled stations correspond to ecosystems where : i) cyst accumulation may be favored by the site geomorphology (estuaries, small bays with low flushing, low bioturbation rates), ii) genetic material could be better preserved (muddy, anoxic sediments), iii) human activities are developed and/or the impact of Harmful Algal Blooms is higher (harbors, shellfish farming areas). Twenty-three stations were located in intertidal zones and seven in subtidal areas (Table 1). Altogether, the 30 sampled stations cover well the geography of the Bay of Brest (Fig. 1). Samples were collected at low tide ± 2 hours during two campaigns of 3-5 days, both carried out during the winter of two consecutive years (December 2013 and January 2015). Subtidal stations were sampled by scuba divers. The top 3 cm of sediments was collected in triplicate using plastic syringes at 1-2 m distance from each other. Sediment samples were carefully preserved in different tubes. Samples of DNA were immediately frozen in liquid nitrogen then stored at -80°C in the laboratory while samples for cyst germination experiments were preserved in the dark at 4°C.

Samples were preserved at 4°C for granulometry, at -80°C for chlorophyll a and pheopigments, and at -20° for organic carbon (OC).

Sediment analyses

Granulometry, chlorophyll a, pheopigment and organic carbon (OC) concentrations were determined from samples collected in triplicate at each station. Sediment grain size was analyzed using an LS 200

Beckman Coulter laser granulometer and sediment typologies were classified according to [START_REF] Larsonneur | La cartographie des dépôts meubles sur le plateau continental français: methode mise au point et utilisée en Manche[END_REF] on the basis of four size classes (0-63, 63-125; 125-500; 500-2000 µm). For chlorophyll and pheopigment concentration measurements, sediment samples were freeze -dried just before extraction and analysis [START_REF] Reuss | Effects of sediment storage conditions on pigment analyses[END_REF]. Before extraction, the sample was homogenized, and gravel and shell debris were removed. Chlorophyll a and pheopigments were extracted from 1 g of sediment with 10 ml of 90% acetone for at least 12 h at 4°C. Supernatants containing the extracted pigments were recovered after sample centrifugation. Chlorophyll a and pheopigment concentrations were determined spectrophotometrically at 750 and 665 nm before and after sample acidification with 0.3 N HCl [START_REF] Lorenzen | Determination of chlorophyll and pheopigments: spectroph otometric equations[END_REF][START_REF] Pusceddu | Enzymatically hydrolyzable protein and carbohydrate sedimentary pools as indicators of the trophic state of detritus sink systems: A case study in a Mediterranean coastal lagoon[END_REF]. Sediment samples for OC measurement were ground and homogenized. Organic C was measured using a vario EL-III CNS elementary analyzer after decalcification of a subsample of the freeze-dried and ground sediment with phosphoric acid [START_REF] Cauwet | Optimization of an analytical technique for evaluation of organic carbon in sediments[END_REF]. Concentrations were calculated by comparison with samples of known concentration of organic carbon (acetanilide, sulfanilamide) and analyses were verified with a certified reference sediment sample.

Molecular analyses

Copy numbers of A. minutum ITS1rDNA were measured directly on DNA extracts from sediments using a newly developed real-time qPCR assay [START_REF] Klouch | Historical records from dated sediment cores reveal the multidecadal dynamic of the toxic dinoflagellate Alexandrium minutum in the Bay of Brest (France)[END_REF]. Total DNA was extracted from 10 g of sediment material from each triplicate of all stations using the PowerMax soil isolation kit (Mobio Laboratories Inc., Carlsbad, California, USA), following the manufacturer's instructions.

Extracts of DNA were eluted in a final volume of 5 ml and immediately stored at -80°C. Samples of DNA were quantified by absorbance measurements using a Take3 trio microplate reader (BioTek, Winooski, Vermont, USA) on 3 µl of DNA extract, and sterile water was used as the blank. The quality of DNA was checked by 260/280 nm ratio to ensure that no contamination by proteins or other components had occurred during DNA extraction.

Real-time PCR reactions were carried using primers Am_48F (5'-TGAGCTGTGGTGGGGTTCC-3') and Am_148R (5'-GGTCATCAACACAGCAGCA-3') which target a fragment of 100 bp, the optimal amplicon length for real-time PCR efficiency [START_REF] Klouch | Historical records from dated sediment cores reveal the multidecadal dynamic of the toxic dinoflagellate Alexandrium minutum in the Bay of Brest (France)[END_REF]. Prior to real-time PCR reactions, a standard curve was constructed by cloning the ITS1rDNA gene from a local culture of A. minutum (A89) into a plasmid (pCR 4) using a TOPO TA cloning kit (Invitrogen, USA). The standard curve was prepared with 10-fold serial dilutions of the plasmid containing the ITS1rDNA sequence of A. minutum and ranged from 10 6 to 10 copies μl -1 . Real-time PCR (quantitative PCR or qPCR) reactions were performed using the iTaq Universal SYBR Green supermix kit (Bio-Rad) in a final volume of 20 µl. The reaction mixture was composed of 10 µl of SYBR Green supermix (1X) containing (dNTPs, iTaq DNA polymerase, MgCl2, SYBR Green I), 0.3 µM of the forward primer (Am_48F), 0.2 µM of the reverse primer (Am_148R), sterile water and 2 µl of DNA template. The experiments were conducted in 96-well plates containing the standard curve dilutions in duplicate, the target samples in triplicate and negative controls composed of water instead of DNA in duplicate. The plates were loaded onto a Stratagene Mxpro3000P (Agilent Technologies, Santa Clara, California, USA) thermal cycler with the following cycling conditions: 1 cycle at 95°C for 5 min followed by 40 cycles of 95°C for 5 sec and 62°C for 30 sec. A melting curve analysis was added at the end of each run to ensure specific A. minutum amplification. The optimal annealing temperature of 62°C was initially determined in conventional PCR. The primer combination that yielded the lowest threshold cycle value (Ct) and maximum realtime efficiency (Am_48F; 0.3 µM, Am_148R; 0.2 µM) was retained for further analysis. The reaction efficiency was estimated by the equation E= 10 (1/b)-1 , where b is the slope of the standard curve. To ensure specific amplifications, the melting temperature values (Tm) were systematically checked by analyzing the melting curves. For further details, see [START_REF] Klouch | Historical records from dated sediment cores reveal the multidecadal dynamic of the toxic dinoflagellate Alexandrium minutum in the Bay of Brest (France)[END_REF]. Abundances of A. minutum in each sample were expressed (assuming a 100% DNA extraction efficiency) in terms of copy number per g of wet sediment, using the following formula: Copy number x g -1 = copy number µl -1 x DNA extraction volume (µl)/sediment wet weight (g)

Cyst germination experiments

Germination experiments were carried out on samples from the 2013 series. An aliquot of ~5 cm 3 of sediment samples was added to filtered seawater and placed in an ultrasonic bath for 6 min to separate dinoflagellate cysts from inorganic particles. The 20-100 µm fraction of particles was retained for culturing experiments after sample sieving. Some drops of the 20-100 µm sediment fractions were distributed in 12-well plastic plates with K medium [START_REF] Keller | Media for the culture of oceanic ultraphytoplankton[END_REF]. The plates were placed in a culture room at 16°C, under an irradiance of 60 μmol photons m -2 s -1 and a light: dark cycle of 12 h:12 h. The plates were examined qualitatively once every day to check for A. minutum cell germination using an inverted microscope (Zeiss Axiovert 135). Germinated cells of A. minutum were identified using morphological characteristics (size, shape, plate arrangement).

Simulation of A. minutum cell trajectories: Lagrangian transport

The MARS3D hydrodynamic model (a detailed description is available in [START_REF] Lazure | An external-internal mode coupling for a 3D hydrodynamical model for applications at regional scale (MARS)[END_REF] was used to study planktonic cell trajectories after bloom development. This numerical code solves primitive physics equations (e.g. Navier-Stokes under hydrostaticity and Boussinesq assumptions)

and is based on a finite difference scheme coupling barotropic and baroclinic modes within a sigmacoordinate framework. For this study, the model was defined for the Bay of Brest with spatial limits (2015), i.e. when the water temperature was above 15°C and during a neap tide period. Four different starting points were tested: stations 3, 9, 13 and 16 (Fig. 1). At each station, 1,000 passive particles were released in the surface layer within a square stain of 100 m side length. Each particle position was recorded during 10 days of simulations, which is the approximate period before particles are flushed out of the bay. The level of dropping (surface or bottom) was tested but had no significant influence on the results (not shown here). For these simulations, it was also assumed that particles had no buoyancy, no mortality and no growth and that they could not wash up on the coast.

Connectivity between the four different release zones was assessed by defining reception areas as the geographical limits of the four different estuarine areas: the Elorn estuary (incorporating station

3), the Daoulas estuary (incorporating station 9), the Camfrout estuary (incorporating station 13), and the Aulne estuary (incorporating station 16). Total numbers of particles released at each station and reaching the other three areas were computed. The model also enabled the calculation of the mean total distance covered by particles starting from the different stations as well as the total number of particles remaining in each area by the end of the simulation as a proxy for confinement.

Statistical analyses

A Principal Component Analysis (PCA) was used to assess relationships between environmental and biological data along a reduced number of axes (ade4 package for R; [START_REF] Dray | The ade4 package: implementing the duality diagram for ecologists[END_REF]. Data used in the PCA included the four sediment size fractions (0-63 µm, 63-125 µm, 125-500 µm, 500-2000 µm) and the three biological variables (Chl a, A. minutum and total DNA concentration). To reduce the importance of observations with very high values, concentrations of A. minutum

ITS1rDNA copy number g -1 sediment were log10 (x+1)-transformed. The PCA result had the same dimension as the dataset, but the first principal components account as much as possible for the data variability. Thus, only the first two axes explaining most of the variance were retained for later interpretations. For graphical representation, PCA results were combined with a cluster analysis performed on environmental and biological variables (complete -linkage clustering, vegan package; [START_REF] Oksanen | Vegan: Community Ecology Package. R package version 2[END_REF] to highlight further differences between station groups. A single cutting level (Euclidean distance = 8.2) was selected to obtain major groups of samples. Prior to these analyses , all variables were centered and scaled in order to make them dimensionally homogenous. Finally, the Spearman rank correlation coefficients were calculated between all the environmental and biological variables. All statistical analyses were performed using the R software (R Core Team, 2015).

Results

Sediment analyses

The relative magnitude of the granulometric size classes analyzed enabled each sampling site to be classified on the basis of their sediment typology (Supp. Table 1) for the two sampling surveys. Of the 30 sampling stations, 13 were classified as sandy-mud, 6 as mud, 1 as muddy-sand, and 2 as fine sand, coherently for both sampling surveys. For the remaining 8 stations, the granulometric classification varied between the two years, more often due to variations in the percentage of either or both 0-63 µm and 125-500 µm sediment size fractions.

Quantification of A. minutum in DNA extracts of sediments

Total DNA concentrations extracted from the sediments ranged from 1.95 to 55.20 ng µL -1 for 2013 samples and from 1.57 to 36.08 ng µL -1 for 2015 samples. According to 260/280 nm ratios, the DNA extracts were of sufficient yield and purity to conduct amplification analyses. The reaction efficiencies of real-time PCR amplifications of about 100 bp of the ITS1rDNA of A. minutum ranged from 95 to 99% and the melting temperature values always corresponded to the expected value of 62°C, both results proving the high resolution of the PCR assay performed in this study. The ITS1rDNA copy number varied from 1.63 x 10 4 to 5.46 x 10 7 copies g -1 sediment in 2013 and from 2.89 x 10 4 to 5.47 x 10 7 copies g -1 sediment in 2015. Local A. minutum quantification was very variable between replicates of some stations (the ranges of the standard errors between the three replicates were 3.57

x 10 4 -2.63 x 10 7 and 8.06 x 10 4 -2.09 x 10 7 copies g -1 sediment in 2013 and 2015, respectively)

showing a significant spatial variability for some stations at a very fine spatial scale (1-2 m) (Figs 2A, B). At some stations, one replicate differed from the other two in one sampling year and not in another (stations 1-10, 30), while for other stations the data between replicates were coherent for the two years of analyses (stations 11-19). Stations 16-29 were characterized by higher copy numbers in 2015 (Fig. 2B). Despite this strong intrasite variability, a coherent pattern of copy numbers of ITS1rDNA of A. minutum was identified between the two years. On the whole, both the intertidal (6-19) and subtidal (26-29) stations of the south-eastern part of the Bay of Brest were characterized by higher copy numbers than the subtidal and intertidal stations of the western (20-22, 25, 30) and north-eastern part (1-5, 23-24) of the bay, in both 2013 and 2015. In particular, the intertidal stations within Daoulas Bay (6-12) and the subtidal station outside the bay (26-29) were characterized in both years by higher copy numbers of A. minutum ITS1rDNA (Fig. 2A).

Germination experiments

Germination of A. minutum occurred within the first 10 days of incubation of all (30/30) 2013 sediment samples. No differences (size, shape and swimming behavior) were observed in light microscopy between specimens of different localities. In the light of the 2013 successful germinations, cysts of the species were considered to have settled in all localities of the Bay of Brest and therefore germination experiments were not performed on 2015 sediment samples.

Genetic and environmental data correlations

The PCA performed with genetic, sediment granulometry and biological environmental parameters (Figs 3A, B) as well as Spearman correlations between variables (Fig. 3C) showed that A. minutum

ITS1rDNA copy numbers (labeled A. minutum DNA) and total DNA concentrations (labeled Total DNA)

were positively correlated with the fine sediment size fraction (labeled 0-63 µm),the Organic Carbon (labeled OC),and chlorophyll a (labeled CHL a) concentrations (Figs. 3A,C). In particular, A. minutum DNA was positively correlated with only fine sediment (0-63 µm) (0.54) and not with coarser sediment types. The 0-63 µm sediment fraction and A. minutum DNA were both positively correlated with OC concentration (0.60 and 0.83, respectively) (Fig. 3C). Cluster analysis identified two major groups of stations (differentiated in dark (cluster 1) and light gray (cluster 2) in Fig. 3B). Overall, the analysis separates the south-eastern intertidal and subtidal sampling stations of the Bay of Brest (cluster 2: 6-12, 14-19, 26, 28, 29) where the highest percentages of the fine sediment size fraction (0-63 µm) were associated with the highest concentrations of OC, CHL a and genetic material, from the western and north-eastern stations (cluster 1: 1, 3-5, 20-22, 25, 30) where measured values of these variables were lower. Yet, some exceptions to this geographical separation of sampling stations were highlighted. Eastern stations 13 and 27 were characterized by low correlations and were grouped within cluster 1. On the contrary, the north-eastern station 24 was grouped within cluster 2,

showing that the strong association between fine sediment granulometry, OC and CHL a and A. minutum copy number was not exclusive to a part of the Bay of Brest. Stations 2 and 23 had the same number of replicates in both clusters 1 and 2.

Simulation of particle trajectories in the water

Simulated trajectories and final particle positions after 10 days as a function of the initial release location and the year are shown in Figure 4 A-D as an example for 2015 (2014 simulated trajectories are not shown). Whichever year is considered, 56 to 81% of passive particles remain in the Bay of Brest after 10 days (Table 2). Particles released at Station 9 (Daoulas estuary) show the lowest percentage being flushed out of the Bay of Brest (Fig. 4B, Table 2), whilst particles released at station 3 (Elorn estuary) show the highest percentage (Fig. 4A, Table 2). The model simulations also show that particles released at stations 13 (Fig. 4C) and 16 (Fig. 4D) tend to be transported over greater distances than those released at stations 3 or 9. The Daoulas estuary appears to be the most confined area with 26.5-26.2% (depending on years) of the initial number of particles released at station 9 remaining in that area after 10 days (Table 2). The connectivity table between the four release areas (Table 3) shows similar patterns for 2014 and 2015 simulations. As expected, stations 13 and 16 show a high connectivity with the nearby Daoulas estuary ( from 29.7 to 30.7% of the initial released particles). Interestingly, this connectivity seems to be rather one-way (from stations 13 or 16 towards the Daoulas estuary) since very few particles starting from station 9 (Daoulas estuary) reach the Camfrout estuary (0-0.4%) or the Aulne estuary (7.8-8.5%). The Daoulas and Elorn estuaries seem particularly hydrodynamically disconnected with very few particles released at station 9 reaching the Elorn estuary (0.2-0.3%) and similarly from station 3 to the Daoulas estuary (1.2-1.4% of particles). Moreover, after 10 days of simulation, no particle released from station 3 reaches the Camfrout estuary. In the center of the Bay of Brest, particles are well-mixed and come from each releasing station. Overall, the simulations described here demonstrate that the south-east of the bay is quite disconnected from the Elorn estuary, which is the area exporting the highest proportion of particles outside the Bay of Brest, and that the Daoulas estuary is a confined area with little connectivity with the Aulne estuary and even less with the Elorn estuary. [START_REF] Dell'anno | Extracellular DNA plays a key role in deep-sea ecosystem functioning[END_REF] is an important issue to take into account when performing specific DNA quantification in sediments. This problem may lead to misinterpreting the presence of viable material (resting stages) in sediment and bias estimations of cyst abundances. Methods to separate extracellular from intracellular DNA have been developed (Corinaldesi et al., 2005[START_REF] Alawi | A procedure for separate recovery of extra-and intracellular DNA from a single marine sediment sample[END_REF][START_REF] Lever | A modular method for the extraction of DNA and RNA, and the separation of DNA pools from diverse environmental sample types[END_REF] but, even when this separation has not been directly applied, specific DNA amplifications by PCR methodologies in field sediment samples have been shown to be a good proxy of cyst abundances (Gohde et al., 2002[START_REF] Erdner | A quantitative real-time PCR assay for the identification and enumeration of Alexandrium cysts in marine sediments[END_REF], Penna et al., 2010[START_REF] Klouch | Historical records from dated sediment cores reveal the multidecadal dynamic of the toxic dinoflagellate Alexandrium minutum in the Bay of Brest (France)[END_REF], most probably due to the better preservation of DNA material in resting stages [START_REF] Boere | Sourcespecific variability in post-depositional DNA preservation with potential implications for DNA based paleoecological records[END_REF].

Discussion

The number of copies of genomic DNA markers and its variability among strains and growth phase stages in dinoflagellates, including Alexandrium spp. [START_REF] Galluzzi | Analysis of rRNA gene content in the Mediterranean dinoflagellate Alexandrium catenella and Alexandrium taylorii: implications for the quantitative realtime PCR-based monitoring methods[END_REF] and A. minutum in particular [START_REF] Galluzzi | Development of a realtime PCR assay for rapid detection and quantification of Alexandrium minutum (a dinoflagellate)[END_REF], may also cause a misinterpretation of the exact dinoflagellate cell numbers in field samples when applying real-time PCR analyses. This issue has been discussed in several studies focusing on the efficiency and limitations of the real -time PCR methodology (Gohde et al., 2002[START_REF] Gohde | Quantification of diatom and dinoflagellate biomasses in coastal marine seawater by real -time PCR[END_REF][START_REF] Erdner | A quantitative real-time PCR assay for the identification and enumeration of Alexandrium cysts in marine sediments[END_REF][START_REF] Galluzzi | Analysis of rRNA gene content in the Mediterranean dinoflagellate Alexandrium catenella and Alexandrium taylorii: implications for the quantitative realtime PCR-based monitoring methods[END_REF], Penna et al., 2010) underlining the importance of taking into account this variability when monitoring HAB species. The objective of this work was not to validate the real-time PCR amplifications to estimate exactly the cyst abundances of A. minutum, but to map potential accumulation zones in the study area in order to contribute to the understanding of the spatial heterogeneity of bloom dynamics and intensities of A. minutum in the estuaries of the Bay of Brest.

Genetic traces of A. minutum were found in 30 out of 30 sampled stations of the study area.

In parallel, successful germination experiments of A. minutum on 2013 sediment samples proved that living resting stages had settled in all stations and that the toxic species currently contaminates the whole Bay of Brest. The reduced interstitial space between fine particles decreases water circulation and can favor the establishment of anoxia in sediments, which are suitable conditions for slowing the digenetic process and preserving organic matter [START_REF] Genovesi | Influences of sedimentation and hydrodynamics on the spatial distribution of Alexandrium catenella/tamarense resting cysts in a shellfish farming lagoon impacted by toxic blooms[END_REF]. Therefore, as expected, the organic matter content, chl a and total DNA concentrations were higher in stations characterized by fine sand-muddy sediment typology, as proved for instance by the high correlation value (0.83) obtained between the finest sediment fraction (0-63 µm) and the organic carbon content (Fig. 3). It is acknowledged that Alexandrium cysts behave physically like fine particles and that accumulation spots mostly occur in fine sediment areas [START_REF] White | Resting cysts of the toxic red tide dinoflagellate Gonyaulax excavata in Bay of Fundy sediments[END_REF], Kremps, 2000[START_REF] Yamaguchi | Distribution and Abundance of Resting Cysts of the Toxic Dinoflagellates Alexandrium tamarense and A. catenella in sediments of the eastern Seto Inland Sea, Japan, Intergovernmental Oceanographic Commission of UNESCO[END_REF][START_REF] Joyce | Dinoflagellate cysts from surface sediments of Saldanha Bay, South Africa: an indication of the potential risk of harmful algal blooms[END_REF][START_REF] Gayoso | Observation on Alexandrium tamarense (Lebour) Balech and other dinoflagellate population in Golfo Nuevo, Patagonia (Argentina)[END_REF][START_REF] Matsuoka | Modern dinoflagellate cysts in hypertrophic coastal waters of Tokyo Bay, Japan[END_REF][START_REF] Wang | Seasonal distribution of dinoflagellate resting cyst in surface sediment from Changjang River Estuary[END_REF][START_REF] Anderson | Alexandrium fundyense cyst dynamics in the Gulf of Maine[END_REF][START_REF] Penna | Detection of microalgal resting cysts in European coastal sediments using a PCR-based assay[END_REF][START_REF] Horner | Spatial distribution of benthic cysts of Alexandrium catenella in surface sediments of Puget Sound, Washington, USA[END_REF][START_REF] Genovesi | Influences of sedimentation and hydrodynamics on the spatial distribution of Alexandrium catenella/tamarense resting cysts in a shellfish farming lagoon impacted by toxic blooms[END_REF]. Consequently, DNA traces of the species should mostly be found in sediments characterized by a large fraction of fine particles.

The good positive correlation found between the A. minutum ITS1rDNA amplifications and the 0-63 µm sediment fraction of the sampled stations confirms this hypothesis. Good correlations between

ITS1rDNA amplifications and the 0-63 µm sediment fraction were coherent for both 2013 and 2015 samples in stations of the south-eastern part of the Bay of Brest and particularly for stations of the Daoulas estuary, in areas that were confirmed to be of muddy-fine sediment facies in a recent comprehensive, morpho-sedimentological analysis of the Bay of Brest [START_REF] Gregoire | Modern morpho-sedimentological patterns in a tide-dominated estuary system: the Bay of Brest (west Brittany, France)[END_REF].

Seasonal blooms of A. minutum have been detected in the Daoulas estuary since July 2012, when a massive toxic bloom event (concentrations of 42 x 10 6 cells l -1 ) highlighted the Daoulas area as a new risky zone for toxic blooms of A. minutum in the Bay of Brest [START_REF] Chapelle | The Bay of Brest (France), a new risky site for toxic Alexandrium minutum blooms and PSP shellfish contamination[END_REF]. Before this event, the Daoulas area was not included in the monitored area of the REPHY observation network; in fact, the toxic species has only recently increased in the area as demonstrated by paleogenetic data from ancient sediment cores of the area [START_REF] Klouch | Historical records from dated sediment cores reveal the multidecadal dynamic of the toxic dinoflagellate Alexandrium minutum in the Bay of Brest (France)[END_REF]. As well as Daoulas Bay, blooms of the species occur in other zones of the Bay of Brest, but they have always been of minor intensity [START_REF] Chapelle | The Bay of Brest (France), a new risky site for toxic Alexandrium minutum blooms and PSP shellfish contamination[END_REF]. In conclusion, large numbers of copies of the marker gene of A. minutum were found in sediments or areas where blooms of higher intensity occur in the plankton. This leads to the suggestion that the Daoulas estuary is probably an accumulation zone of cysts of A. minutum in the Bay of Brest, an area which should be carefully monitored for toxic bloom occurrences.

Spatial heterogeneity in sediment and in water

The mapping of the potential accumulation spots of A. minutum obtained for December 2013 and January 2015 suggests a non-homogenous distribution of cyst banks within the Bay of Brest, with major accumulation areas in the south-eastern part of the bay. In parallel, the simulation of passive particle trajectories performed with real forcings in potential offspring periods of A. minutum (June 2014 and 2015, the summer periods after the wintertime cyst accumulation in 2013 and 2015)

suggests a differential dispersal of blooms in the bay. Blooms occurring in the south-eastern Daoulas estuary would be relatively disconnected from those in the north-eastern Elorn estuary, as the connectivity between the two areas is very low (<1.4%). The reasons for this heterogeneity in cyst banks and potential bloom dispersal must be found in the hydrology, geomorphology, and hydrodynamics of the bay.

Previous model simulations have shown that the estuaries of the Bay of Brest are preferential ecosystems for dinoflagellate bloom occurrence because of a sustained nitrogen supply from rivers [START_REF] Menesguen | A new numerical technique for tracking chemical species in a multisource, coastal ecosystem applied to nitrogen causing Ulva blooms in the Bay of Brest (France)[END_REF] and significant estuarine nutrient stocks in sediment [START_REF] Raimonet | Strong gradient of benthic biogeochemical processes along a macrotidal temperate estuary: focus on P and Si cycles[END_REF] that can be resuspended (Tallberg et al., 2006) and due to low flushing rates in estuaries that allow the development of the bloom (Sourisseau et al., accepted). Despite high nutrient loads, the Bay of Brest seems to be resistant to eutrophication problems due to strong semi-diurnal tidal currents that ensure the water exchange with the continental shelf (Le [START_REF] Pape | Hydrodynamic prevention of eutrophication in the Bay of Brest (France), a modelling approach[END_REF]Menesguen, 1997, Chavaud e t al., 2000). In the shallow estuarine ecosystems of the Bay of Brest, the tide and the wind intensity and direction could promote bottom currents that can influence cyst and sediment distributions as shown in other semi-enclosed ecosystems (e.g. [START_REF] Genovesi | Influences of sedimentation and hydrodynamics on the spatial distribution of Alexandrium catenella/tamarense resting cysts in a shellfish farming lagoon impacted by toxic blooms[END_REF][START_REF] Trikia | Distribution of resting cysts of the potentially toxic dinoflagellate Alexandrium pseudogonyaulax in recently-deposited sediment within Bizerte Lagoon (Mediterranean coast, Tunisia)[END_REF]. Weak bottom currents favor the settlement of fine-muddy (<0.63 µm) sediment and cysts of Alexandrium, which are acknowledged to behave like fine sediment particles [START_REF] Dale | Dinoflagellate resting cysts: benthic plankton[END_REF]. Therefore, bottom currents in the Bay of Brest may play a role in promoting the sediment movement and creating permanent superficial deposits of A. minutum in the shallow, peripheral embayments of the southeastern zone of the bay, such as the Daoulas estuary. The specificity of the distribution pattern of A.

minutum in sediments of the Bay of Brest remains to be demonstrated. The cysts of different species showed different abundance patterns in the same ecosystem [START_REF] Park | Detection of Cochlodinium polykrikoides and Gymnodinium impudicum (Dinophyceae) in sediment samples from Korea using real -time PCR[END_REF][START_REF] Satta | Studies on dinoflagellate cyst assemblages in two estuarine Mediterranean bays: a useful tool for the discovery and mapping of harmful algal species[END_REF], Fertouna-Bellakhal et al., 2014). Therefore, the cysts of other dinoflagellate species might be characterized by a different distribution in the Bay of Brest.

Sediment resuspension and transport in the water column of the Bay of Brest were analyzed by hydro-sedimentary model simulations. Tide currents would generate higher concentrations of resuspended muddy sediments in the south-eastern estuaries of the bay (the Daoulas and Aulne estuaries) than in the north-eastern estuary (Elorn estuary) [START_REF] Beudin | Suspended sediment modeling in the Bay of Brest impacted by the slipper limpet Crepidula fornicata[END_REF][START_REF] Beudin | Modelling dynamics and exchanges of fine sediments in the Bay of Brest[END_REF].

Tracked suspended mud of the south-eastern estuaries is predicted to be flushed out of the bay, without reaching the Elorn estuary, while the mud of the Elorn estuary is expected to remain and redeposit in the estuarine area without reaching the inner and south-eastern parts of the Bay of Brest [START_REF] Beudin | Suspended sediment modeling in the Bay of Brest impacted by the slipper limpet Crepidula fornicata[END_REF][START_REF] Beudin | Modelling dynamics and exchanges of fine sediments in the Bay of Brest[END_REF]. In parallel, the simulated particle dispersal trajectories suggest tidal currents coupled with river outflows would trigger current trajectories that cause low exchanges between the north-eastern Elorn estuary and the south-eastern Daoulas, Camfrout and Aulne estuaries. Potential blooms developing in the Elorn estuary would be mostly directly exported out of the bay, whereas blooms developing in each of the south-eastern estuaries would be connected to each other but not to the Elorn estuary. Simulations of both sediment and particle transport suggest that the hydrodynamics of the bay would create barriers for A. minutum dispersal.

Consequently, there could be low interbreeding between populations of the northern and southern zones of the Bay of Brest. The simulations carried out in this study are based on a physical model that does not include biological variables such as growth, asexual and sexual reproduction and mortality rates. These variables affect the retention time of a bloom and the connectivity between ecosystems and populations of the bay. New model simulations that integrate biological variables and a population genetic approach would complete the information provided by this study, probably supporting the heterogeneity of A. minutum dispersal in the Bay of Brest.

Conclusions

The successful germination of A. minutum from all sampled stations of the Bay of Brest demonstrates that A. minutum currently contaminates the whole Bay of Brest. Since in 1990 no cysts were found in estuarine samples of the bay, the information provided in this study contribute s to highlighting a relatively recent proliferation of this toxic species in the bay. Higher copy numbers of ITS1rDNA in sediment samples of the Daoulas estuary argue in favor of the possibility that this estuary could be a major accumulation spot of the cysts of A. minutum. This distribution pattern could explain the regular occurrence of blooms of higher intensity in this area of the bay. The simulations of particle trajectories demonstrate that the blooms occurring in the north-and south-eastern estuaries of the bay are disconnected and therefore rather independent of each other. This suggests the existence of potential physical barriers to A. minutum bloom dispersal and of populations interbreeding in the bay. Overall, a heterogeneous distribution of A. minutum in both sediment and the water column emerge from this study, proving that there may be discrete, localized accumulations of cysts even in a semi-enclosed coastal ecosystem. Supp. Table 1. Classification of sampling stations based on four sediment size classes (µm) following 908 [START_REF] Larsonneur | La cartographie des dépôts meubles sur le plateau continental français: methode mise au point et utilisée en Manche[END_REF]

  ranging between 48.203-48.447 °N and 4.093-4.730 °W, a spatial horizontal resolution of 50 meters and 20 vertical layers. Moreover, the model assumed a wetting and drying capability (intertidal areas), which is mass preserving. The model's bathymetry was provided by the SHOM (French Naval Hydrographic and Oceanographic Service). At its western and southern boundaries, the model was forced for water elevation (tides), water temperature and salinity by another model[START_REF] Lazure | Development of a hydrodynamic model of the Bay of Biscay. Validation of hydrology[END_REF], previously validated for tides and hydrology and simulating the Bay of Biscay and Channel hydrodynamics. Atmospheric forcing (wind and atmospheric pressure) came from the Météo-France AROME model[START_REF] Seity | The AROME-France convective scale operational model[END_REF] which has a temporal resolution of 1 hour and a spatial resolution of 0.025° (roughly 2.4 km). The three major rivers, the Aulne, the Elorn and the Mignonne, were taken into account, and water flows came from the HYDRO database (Governmental Environment Agency). Trajectories of A. minutum cells were computed by the ICHTYOP Lagrangian transport tool[START_REF] Lett | A Lagrangian tool for modelling ichthyoplankton dynamics[END_REF] coupled with the hydrodynamic model of the bay. This tool enables offline simulations of bloom dispersion by calculating fictive particle trajectories based on previously calculated currents. Two simulations were run for years 2014 and 2015. Particles were released at the beginning of June, when Alexandrium bloom conditions were fulfilled according toChapelle et al.

  Genetic mapping of A. minutum in sediments In this study, a geographically exhaustive survey of the presence of A.minutum in superficial sediment of the Bay of Brest (Brittany, France) during the winter of two consecutive years (December 2013 and January 2015) is provided. This is not the first screening of A. minutum traces in sediment of the study area. In 1990, no cyst of A. minutum was found in four estuarine stations of the Bay of Brest (Erard-Le Denn et al., 1993, Erard-Le Denn and Boulay, 1995) using cyst identification by light microscopy. Here, real-time PCR amplification of a fragment of the ITS1rDNA of A. minutum from DNA sediment extracts was proposed as an alternative method to cyst quantification. The high proportion of extracellular DNA in the total environmental DNA extracts from sediments (Dell'Anno

Figure 1 .

 1 Figure 1. Map of the Bay of Brest indicating intertidal (stars) and subtidal (circles) sampling stations .

Figure 2 :

 2 Figure 2: Log10 (x+1) transformed real-time PCR data of Alexandrium minutum copy number g -1 of

Figure 3 .

 3 Figure 3. Relationship between environmental parameters (chlorophyll a: CHL a; organic carbon: OC, sediment size class: 0-63, 63-125, 125-500 and 500-200 µm), ITS1rDNA copy number concentration g - 1 of sediment of Alexandrium minutum (A. minutum DNA) and total DNA concentration (ng/µl)

Figure 4 :

 4 Figure 4: Simulated trajectories of 1000 passive particles coming from 4 releasing estuarine stations

  , the vegetative form of the species was first identified within the framework of the REPHY (REseau de

	surveillance	et	d'observation	du	PHYtoplankton	et	des	PHYcotoxines:

http://envlit.ifremer.fr/surveillance/phytoplancton_phycotoxines/presentation) in 1990. The first cyst abundance survey was carried out in the same year and no cyst of A. minutum was found in four estuarine stations of the Bay of Brest (Erard

Table 1 .

 1 List and coordinates of sampling stations. Subtidal stations (23-27) are indicated by a circle.

	774
	775
	776 777	Station ID 1	Station locality Pol der	Coordinates (N/W) 48° 23' 3''/ 4° 26' 6''
	778	2	Moul i n Bl a nc	48° 23' 44''/ 4° 25' 55''
		3	Le pa s s a ge	48° 23' 25''/ 4° 23' 03''
	779	4	Kéra l i ou	48° 22' 35''/ 4° 24' 41''
		5	Ca ro	48° 20' 28''/ 4° 26' 26''
	780	6	Ti nduff	48° 20' 2''/ 4° 22' 03''
	781	7 8	Moul i n Neuf Penfoul	48° 21' 5''/ 4° 21' 04'' 48° 21' 25''/ 4° 19' 28''
	782	9	Kers a nton	48° 20' 45''/ 4° 18' 2''
		10	La nveur	48° 21' 19''/ 4° 17' 51''
	783	11	Ri vi ère de Daoulas 48° 21' 21''/ 4° 16' 2''
	784	12 13	Châ tea u Moul i n Mer	48° 20' 11''/ 4° 18' 46'' 48° 18' 56''/ 4° 17'11''
	785	14	Hôpi ta l Ca mfrout 48° 19' 37''/ 4° 14' 53''
		15	Ti bi dy	48° 18' 25''/ 4°14' 40''
	786	16	La nvoy	48° 17' 47''/ 4° 13' 29''
		17	Térénez	48° 16' 43''/ 4° 16' 49''
	787	18	La ndévennec	48° 17' 34''/ 4° 15' 29''
	788	19 20	Si l lon des Angl a i s 48° 17' 52''/ 4° 17' 22'' Fret 48° 16' 54''/ 4° 30' 13''
	789	21	Ros tel l ec	48° 17' 27''/ 4° 31' 30''
		22	Pers uel	48° 18' 1''/ 4° 33' 17''
	790	23 ○	Port de Commerce 48° 22' 7''/ 4° 29' 18''
	791	24 ○ 25 ○	Le Pa s s a ge Auberl a c'h	48° 23' 39''/ 4° 22' 54'' 48° 19' 9''/ 4° 25' 53''
	792	26 ○	Es tTi nduff	48° 19' 7''/ 4° 20' 7''
		27 ○	La nveoc-Ti nduff	48° 18' 2''/ 4° 23' 31''
	793	28 ○	Qui l l i en	48° 17' 36''/ 4° 20' 6''
	794	29 ○ 30	Ecol e Na va l e Sa i nte Anne	48° 17' 37''/ 4° 24' 6'' 48° 21' 41''/ 2° 33' 13''
	795
	796
	797
	798

Table 2 .

 2 Summary of simulated particle trajectories initiating from four different areas in the Bay of Brest: F stands for the percentage of particles flushed out of the Bay of Brest at the end of the simulation, D is the mean cumulative distance covered by particles until the end of the simulation and A represents the percentage of particles still located in the estuary of re lease at the end of the simulation (auto-connectivity). The two numbers stand for years 2014 and 2015, respectively.

	Release station	3	9	13	16
	F (%)	43.6 -37.7	9 -18.7	29.1 -30.8	23.5 -24.2
	D (km)	129.5 -127.9	114.0 -114.3	151.1 -149.7	152.9 -153.4
	A (%)	9.4 -8.3	26.5 -26.2	0 -0	12.8 -10.4

Table 3 .

 3 Connectivity table between releasing stations (3, 9, 13 and 16) and receiving areas (Elorn, Daoulas, Camfrout and Aulne estuaries). Percentage (%) of particles reaching the considered area at least once in 10 days for 2014 and 2015, respectively.

			Releasing stations
		St. 3	St. 9	St. 13	St. 16
	Elorn estuary area	-	0.3 -0.2	1.6 -2.0	2.0 -0
	Daoulas estuary area	1.4 -1.2	-	29.7 -28.4	30.7 -28.0
	Camfrout estuary area	0 -0	0.4 -0	-	6.6 -6.0
	Aulne estuary area	1.3 -1.5	7.8 -8.5	58.7 -57.4	-

mud 54.3 ± 8.5 70.0 ± 3.5 21.8 ± 1.6 15.6 ± 0.4 19.9 ± 6.9 12.9 ± 2.9 3.9 ± 3.2 1.5 ± 0.8 Sandy mud Sandy mud 77.7 ± 2.3 82.1 ± 2.3 12.9 ± 0.4 10.8 ± 0.9 8.4 ± 1.5 6.8 ± 1.1 1.0 ± 0.4 0.3 ± 0.3 Mud Mud 15.8 ± 7.8 67.4 ± 4.7 9.0 ± 2.0 17.5 ± 2.9 54.0 ± 11.1 14.1 ± 2.1 21.3 ±16.6 1.0 ± 0.3 Muddy sand Sandy mud 49.8 ± 10.7 10.9 ± 0.9 23.7 ± 2.8 10.1 ± 0.5 23.9 ± 6.8 72.2 ± 0.8 2.5 ±1.1 6.8 ± 2.2 Sandy mud Muddy sand

  for the two sampling surveys (January 2013 and December 2015).

	909
	910
	Id St.	0-63	63-125	125-500	500-2000	Classification
	2013	2015	2013	2015	2013	2015	2013	2015	2013	2015
	14.3 ± 7.7	53.8 ± 18.2	16.7 ± 0.9	11.9 ± 2.3	47.9 ± 9.4	20.4 ± 5.4	21.0 ± 2.7	13.9 ± 15.0	Muddy sand	Sandy mud
	63.4 ± 4.7	27.4 ± 4.3	14.8 ± 0.6	12.0 ± 1.2	18.0 ± 2.9	24.7 ± 1.3	3.9 ± 2.5	35.9 ± 5.9	Sandy mud	Sandy mud
	32.5 ± 0.6	40.8 ± 11.6	28.7 ± 0.3	18.1 ± 1.7	33.2 ± 0.9	33.6 ± 10.9	5.6 ± 0.5	7.5 ± 2.9	Sandy mud	Sandy mud
	4.1 ± 0.7	5.5 ± 2.8	2.7 ± 0.5	2.2 ± 0.8	61.5 ± 1.5	55.0 ± 3.9	31.6 ± 2.3	37.3 ± 5.6	Fine sand	Sandy mud
	3.6 ± 0.5	3.5 ± 0.6	17.3 ± 0.3	12.4 ± 4.6	75.6 ± 1.0	81.5 ± 5.3	3.4 ± 1.1	2.5 ± 0.7	Fine sand	Fine sand
	81.9 ± 2.9	77.7 ± 5.5	11.2 ± 1.0	11.2 ± 1.6	6.3 ± 1.5	10.0 ± 4.0	0.6 ± 0.3	1.1 ± 0.3	Mud	Mud
	69.6 ± 6.5	35.8 ± 6.6	16.0 ± 2.9	11.9 ± 0.2	12.4 ± 2.5	24.7 ± 4.2	2.0 ± 1.3	27.7 ± 9.9	Sandy mud	Sandy mud
	61.2 ± 5.4	45.2 ± 6.3	18.9 ± 2.3	15.5 ± 2.1	17.6 ± 3.1	31.0 ± 2.4	2.2 ± 0.8	8.3 ± 3.6	Sandy mud	Sandy mud
	62.6 ± 5.0	70.0 ± 6.4	11.9 ± 2.0	13.1 ± 1.0	18.9 ± 4.1	15.6 ± 4.7	6.5 ± 3.1	1.4 ± 1.3	Sandy mud	Sandy mud
	76.0 ± 2.1	70.6 ± 2.2	12.4 ± 0.2	13.5 ± 0	9.8 ± 1.2	14.4 ± 1.7	1.8 ± 0.8	1.5 ± 0.6	Mud	Sandy mud
	77.2 ± 1.1	76.5 ± 0.5	13.0 ± 0.4	12.8 ± 0.2	9.1 ± 0.6	9.9 ± 0.3	0.7 ± 0.2	0.8 ± 0	Mud	Mud
	44.2 ± 3.2	52.5 ± 7.7	25.1 ± 3.3	22.2 ± 2.1	24.4 ± 1.6	22.2 ± 5.6	6.3 ± 2.0	3.0 ± 2.5	Sandy mud	Sandy mud
	51.1 ± 11.1	36.7 ± 31.8	18.4 ± 1.8	12.7 ± 11.0	25.7 ± 9.5	15.1 ± 13.2	4.8 ± 3.2	2.2 ± 2.0	Sandy mud	Sandy mud
	80.1 ± 1.4	74.1 ± 1.8	13.0 ± 0.5	13.5 ± 0.2	6.5 ± 1.0	11.6 ± 1.7	0.5 ± 0.2	0.9 ± 0.7	Mud	Sandy mud
	69.6 ± 2.4	65.2 ± 3.5	16.5 ± 1.8	16.9 ± 1.2	12.2 ± 0.5	15.8 ± 2.0	1.6 ± 0.6	2.1 ± 0.8	Sandy mud	Sandy mud
	70.0 ± 12.7	76.6 ± 0.4	16.2 ± 4.0	12.0 ± 0.5	12.4 ± 7.8	10.4 ± 0.6	1.4 ± 0.9	1.0 ± 0.3	Sandy mud	Mud
	65.3 ± 6.1 Sandy 7.2 ± 1.1 64.2 ± 5.7 15.8 ± 1.0 13.5 ± 1.2 14.9 ± 2.9 18.6 ± 5.3 4.0 ± 2.7 3.6 ± 1.3 Sandy mud 10.4 ± 1.6 40.5 ± 1.8 31.9 ± 1.1 52.0 ± 2.7 56.5 ± 1.5 0.3 ± 0.1 1.2 ± 1.2 Muddy sand Muddy sand
	57.3 ± 6.8	27.5 ± 24.8	18.2 ± 1.1	12.4 ± 10.8	22.2 ± 3.8	23.3 ± 20.7	2.3 ±2.0	3.5 ± 4.5	Sandy mud	Sandy mud
	69.1 ± 4.8	81.6 ± 1.1	15.9 ± 0.6	10.7 ± 1.0	12.9 ± 3.0	7.3 ± 0.2	2.1 ±1.4	0.3 ± 0.6	Sandy mud	Mud
	63.3 ± 1.0	62.5 ± 1.5	24.9 ± 2.2	23.3 ± 1.6	10.4 ± 0.6	13.1 ± 0.6	1.4 ±1.1	1.1 ± 0.1	Sandy mud	Sandy mud
	77.4 ± 3.3	81.5 ± 2.6	12.6 ±0.7	11.0 ± 1.5	9.4 ± 2.7	7.5 ± 1.2	0.6 ±0.1	0	Mud	Mud
	35.1 ±2.8	32.1 ± 6.6	7.4 ±0.7	7.7 ± 1.4	19.4 ±2.1	25.9 ± 5.2	38.1 ±1.6	34.3 ± 10.5	Sandy mud	Sandy mud
	77.7 ± 1.1	81.7 ± 4.0	10.4 ± 0.2	9.8 ± 1.2	11.1 ± 0.7	8.2 ± 2.3	0.9 ± 0.9	0.3 ± 0.6	Mud	Mud
	79.4 ± 3.3	84.6 ± 0.7	10.9 ± 1.3	8.9 ± 0.4	8.9± 1.4	6.5 ± 0.6	0.8 ±0.7	0	Mud	Mud
		2.6 ± 1.3		4.1 ± 0.9		51.9 ± 6.2		41.4 ± 7.3	-	Fine sand
	911

Acknowledgements

This work was financed by the DAOULEX project supported by the Region Bretagne. This research was carried out within the framework of K. Klouch's PhD funded by Ifremer and Region Bretagne (Allocation de REcherche Doctorale (ARED) fellowship) and by the project of the ECosphere Continentale et CÔtière (EC2CO) initiative of the Institut National des Sciences de l'Univers/Centre National de la Recherche Scientifique (INSU/CNRS): PALMITO (2013-2015). The authors wish to thank all colleagues who helped with sample collection and Xavier Caisey for scuba diving sampling assistance. We wish to thank Dominique Hervio-Heath and members of the SG2M/LSEM laboratory of Ifremer for access to their laboratory facilities and all their technical suggestions. Pierre Bodenes is acknowledged for collaborating in the picture developments and Pascale Malestroit for helping with culture maintenance. This research falls within the scope of the French GDR (Groupement de Recherche) Phycotox (http://www.phycotox.fr) (2012-2018) on harmful microalgae and phycotoxins.


Luciana Kase Tanno
email: luciana.tanno@gmail.com

Nicolas Molinari

Sophie Bruel

Jean-Luc Bourrain

Moises A Calderon

Pierre Aubas

Pascal Demoly

MD Luciana Kase Tanno

Anaphylaxis FIELD-TESTING THE NEW ANAPHYLAXIS' CLASSIFICATION FOR THE WHO INTERNATIONAL CLASSIFICATION OF DISEASES (ICD)-11 REVISION

Keywords: anaphylaxis, classification, International Classification of Diseases, validation, World Health Organization

Background: In order to consolidate the new classification model addressed to the allergic and hypersensitivity conditions according to the International Classification of Diseases (ICD)-11 revision timeline, we here propose real-life application of quality assurance methodology to evaluate sensitivity and accuracy of the "Anaphylaxis" subsection.

Methods:

We applied field-testing methodology by analyzing all the consecutive inpatients' files documented as allergies from the University Hospital of Montpellier electronic database for the period of one year. The files clinically validated as being anaphylaxis were manually blind-coded under ICD-10 and current ICD-11 beta draft.

Background

ANAPHYLAXIS' CLASSIFICATION IN THE WHO INTERNATIONAL CLASSIFICATION OF DISEASES (ICD)

The spectrum of clinical presentations of allergic and hypersensitivity conditions is wide and, therefore, these disorders are managed not only by allergists but also by specialists from a range of different disciplines. A simple example is anaphylaxis, which could be faced by different health professionals. Up until recently, although the allergy community has made efforts to work on the classification of specific clinical allergic or hypersensitivity disorders, the document produced (1-3) have never reached consensual universal language for use by many different health settings.

A key role of the World Health Organization (WHO) is to produce, maintain and implement international health information standards, to provide a consensual, meaningful and useful common language for use by governments, health care providers and consumers. Internationally agreed classifications facilitate the storage, Accepted Article access, retrieval, analysis, interpretation and comparison of morbidity, mortality and health-related data. For these reasons, the WHO issued and has maintained the International Classification of Diseases (ICD) so that, in most countries, morbidity and mortality statistics are routinely compiled according to regulations and recommendations adopted by the World Health Assembly (WHA) (4). They ultimately help to distribute health expenditures at each nation level.

Anaphylaxis is known as a serious allergic reaction that involves more than one organ system (e.g. skin, respiratory tract, and/or gastrointestinal tract). It can begin very rapidly, and symptoms may be severe or life-threatening [START_REF] Sampson | Second symposium on the definition and management of anaphylaxis: summary report -Second National Institute of Allergy and Infectious Disease/Food Allergy and Anaphylaxis Network Symposium[END_REF]. Although anaphylaxis has been pointed as a high priority public health issue in the allergy community and food allergy world, it has never been considered a priority by the Orphanet (5) nor well addressed by a single section in the WHO ICD frame (Figure 1), resulting in its misclassification and undernotification regarding both morbidity [START_REF] Tanno | Categorization of Allergic Disorders in the New World Health Organization International Classification of Diseases[END_REF] and mortality data [START_REF] Tanno | Undernotification of anaphylaxis deaths in Brazil due to difficult coding under the ICD-10[END_REF]. From the ICD-10 perspective, anaphylaxis is classified under the "T78 Adverse effects, not elsewhere classified" chapter. Under this confusing chapter, only severe cases of anaphylaxis have been prioritized (T78.2 Anaphylactic shock). In fact, obstruction of the upper and/or lower respiratory tract leading to respiratory distress and potential fatality is more commonly observed in anaphylaxis than hypotension and shock per se. The misclassification implied in the ICD-10 is exemplified by scattering "T78.2 Anaphylactic shock" at he same level as the "T78.3 Angioneurotic oedema", "T78.4 Allergy, unspecified" and "T78.9 Adverse effect, unspecified" under the same heading (Figure 1).

Taking the window of opportunity presented by the ongoing ICD-11 revision, the documented anaphylaxis deaths under-notification data (7) triggered a cascade of strategic international actions supported by a Joint Allergy Academies' consortium and the ICD WHO governance [START_REF] Tanno | Categorization of Allergic Disorders in the New World Health Organization International Classification of Diseases[END_REF][START_REF] Tanno | Undernotification of anaphylaxis deaths in Brazil due to difficult coding under the ICD-10[END_REF][START_REF] Demoly | Global classification and coding of hypersensitivity diseases -An EAACI -WAO survey, strategic paper and review[END_REF][START_REF] Tanno | Constructing a classification of hypersensitivity/allergic diseases for icd-11 by crowdsourcing the allergist community[END_REF][START_REF] Tanno | EAACI/WAO Task force of a Global Classification of Hypersensitivity/Allergic diseases. Mapping hypersensitivity/allergic diseases in Accepted Article the International Classification of Diseases (ICD)-11: cross-linking terms and unmet needs[END_REF][START_REF] Tanno | on behalf the Joint Allergy Academies. Making allergic and hypersensitivity conditions visible in the International Classification of Diseases-11[END_REF][START_REF] Tanno | on behalf the Joint Allergy Academies. Optimization and simplification of the allergic and hypersensitivity conditions classification for the ICD-11[END_REF][START_REF] Tanno | on behalf the Joint Allergy Academies. New Allergic and Hypersensitivity Conditions Section in the International Classification of Diseases-11[END_REF][START_REF] Tanno | Revisiting Desensitization and Allergen Immunotherapy Concepts for the International Classification of Diseases (ICD)-11[END_REF][START_REF] Tanno | Updating Allergy/Hypersensitivity diagnostic procedures in the WHO ICD-11 revision[END_REF][START_REF] Tanno | Joint Allergy Academies. Surveying the new allergic and hypersensitivity conditions chapter of the International classification of diseases (ICD)-11[END_REF][START_REF] Tanno | Supporting the validation of the new allergic and hypersensitivity conditions section of the World Health Organization International Classification of Diseases-11[END_REF][START_REF] Tanno | Decreasing the undernotification of anaphylaxis deaths in Brazil through the International Classification of Diseases (ICD)-11 revision[END_REF][START_REF] Tanno | Smoothing the transition from International Classification of Diseases, Tenth Revision, Clinical Modification to International Classification of Diseases, Eleventh Revision[END_REF][START_REF] Tanno | Dissemination of definitions and concepts of allergic and hypersensitivity conditions[END_REF] in order to update the classifications of allergic and hypersensitivity conditions for the new ICD edition. These efforts have resulted in the construction of the pioneer "Allergic and hypersensitivity conditions" section under the "Disorders of the Immune system" chapter of the online ICD-11 Beta draft [START_REF] Tanno | on behalf the Joint Allergy Academies. Optimization and simplification of the allergic and hypersensitivity conditions classification for the ICD-11[END_REF][START_REF] Tanno | on behalf the Joint Allergy Academies. New Allergic and Hypersensitivity Conditions Section in the International Classification of Diseases-11[END_REF][START_REF]World Health Organization, ICD-11 Beta Draft website[END_REF], and "Anaphylaxis" is currently one of the six headings of the section recently compiled for the forthcoming 11 th Revision of ICD (Figure 2).

Accepted Article

The Allergic and hypersensitivity diseases section proposal was validated by crowdsourcing [START_REF] Tanno | Constructing a classification of hypersensitivity/allergic diseases for icd-11 by crowdsourcing the allergist community[END_REF] and simplified according to ICD Revision Steering Group (RSG) guidance [START_REF] Tanno | on behalf the Joint Allergy Academies. New Allergic and Hypersensitivity Conditions Section in the International Classification of Diseases-11[END_REF]; the "Anaphylaxis" subsection was the most well accepted modification. The development of the now visible "Anaphylaxis" subsection involved strong academic input and extensive consultation and agreement from the relevant Topic Advisory Groups (TAGs) and Expert Working Groups (EWGs). The building process of the section, undertaken with WHO RSG guidance, started in February 2014. As a result of all the previous actions, the new "Anaphylaxis" sub-section was constructed, with 11 entities classified under 7 main headings: Anaphylaxis due to allergic reaction to food, Drug-induced anaphylaxis, Anaphylaxis due to insect venom, Anaphylaxis provoked by physical factors, Anaphylaxis due to inhaled allergens, Anaphylaxis due to contact with allergens and Anaphylaxis secondary to mast cell disorders (Figure 1 and2). Timely, in order to consolidate the new classification model addressed to the allergic and hypersensitivity conditions according to the ICD-11 revision timeline, we here propose real-life application of quality assurance methodology to evaluate sensitivity and accuracy of the "Anaphylaxis" subsection.

Methods

APPLYING FIELD-TESTING METODOLOGY TO REACH QUALITY ASSURANCE

We first selected all the consecutive inpatients' files documented as allergies from the University Hospital of Montpellier (CHRUM) electronic database for the period of one year (2014). All patients' data are routinely collected in the French hospital information system and coded by professional non-physician coders using the ICD. The data accessed in the current study have been coded based on the ICD-10. Files have been selected based on pre-established ICD-10 allergy corresponding codes [START_REF]World Health Organization, ICD-10 version 2016 website[END_REF] registered by the Departments of specialties with whom overlapping allergy and hypersensitivity conditions co-exist (Pulmonology, ENT, Ophthalmology, Dermatology, Pediatric, Gastroenterology, Emergency and Intensive Unit Care). The data have been blindly extracted from the database by a professional from the Medical Information Department. All the data have been collected in an anonymous way. As the study is based on a database analysis and the data were anonymized

Accepted Article

before research coding, this study falls under the chapter X according to the French law and an informed consent is not needed (23). For this study, ICD-10 related to anaphylaxis have been identified as having any of the T78 Adverse effects, not elsewhere classified codes (T78.0 to T78.8), and T80.5.

In the second step of the process, two trained allergists clinically independently validated the retrospectively accessed cases. Discordances have been solved by opened discussions. Allergy specialists confirmed the allergy diagnosis, additionally considered all comorbidities related to allergy or hypersensitivity and blind the files after the selection. All cases in which the ICD-10 codes and/or clinical diagnosis were not related to allergic and hypersensitivity conditions have been excluded. In this evaluation, we asked for the coders to give their impressions regarding the sensitivity of each code added under the new ICD-11 frame and asked to justify if they thought it was not sensible enough. The here presented methodology (Figure 3) has been extensively discussed and acknowledged by the WHO RSG and the information, research and regulatory affairs' departments of the CHRUM.

Results

REACHING QUALITY ASSURANCE FOR THE NEW ICD-11 ANAPHYLAXIS SUBSECTION

From all 2,318 files accessed from the electronic database as having ICD-10 codes related to allergic or hypersensitivity conditions, 673 had some of the anaphylaxis ICD-10 codes (Figure 3).

After the clinical allergy validation, 309 files (46%) from 209 patients had anaphylaxis and allergic or hypersensitivity comorbidities description. Three situations resulted in the 364 eliminated files: (i) descriptions resembling allergic or hypersensitivity conditions, but not considered as real allergies or hypersensitivities (e.g.: food intolerance or Munchausen Syndrome); (ii) transversal analysis in which Accepted Article the description of allergic or hypersensitivity conditions were reported before or after the time of the evaluation, and (iii) unclear described diagnosis (e.g.: files containing initial hypothesis of anaphylaxis, but clinical evaluation and management of an episode of isolated bronchospasm). We have no discordances in the clinical evaluation. From overall 309 files, 89 (29%) have been validated as anaphylaxis and 220 (71%) as allergic or hypersensitivity comorbidities (Figure 3). Most of comorbidities (65%) were allergic or hypersensitivity conditions involving skin or mucous or non-anaphylactic food hypersensitivity conditions and allergic or hypersensitivity conditions involving the gastrointestinal tract (Figure 3). From the transversal file evaluation, 34 (38%) of the anaphylaxis cases had the etiology described, 91% associated to drugs and foodstuff. Most of the cases experienced anaphylaxis grade II (more than one system involved; not life-threatening) and grade III (more than one system involved; life-threatening) (Figure 4).

From all 309 entities, 20 (6.5%) had characteristics of anaphylaxis and combinations of ICD-10 codes were required to reach anaphylaxis ICD-11 codes (e.g. wheezing and hypotension or hives, tachycardia and wheezing but no ICD-10 corresponding anaphylaxis code).

Utilizing the ICD-10, the correspondence between the two coders was perfect for 162 codes from all 309 entities (52.4%) (Cohen-kappa value 0.63) and for 221 codes (71.5%) (Cohen-kappa value 0.77) with the ICD-11 beta draft. There was a high agreement regarding the question on sensibility of the ICD-11 usability (Cohenkappa value 0.75). The main reasons for which the coders indicated that the new ICD-11 frame was not sensible enough were related to the lack of additional severity classification or allergens description, which will eventually be corrected.

Discussion

LESSONS FROM THE FIELD-TESTING METHODOLOGY

We here propose the first attempt of real-life application to validate the new ICD-11 "Anaphylaxis" subsection. Clearer was the improvement of accuracy reaching 71.5% of agreement when ICD-11 was used. Field-testing is one of the quality assurance methodologies to reach accuracy and sensibility proposed by the WHO to validate the ICD-11 framework. The proposed method of validation intends to prove Accepted Article stability, accuracy and sensitivity of the new ICD-11 frame, taking clinically validated conditions as the reference for this procedure. By individual mapping allergic and hypersensitivity conditions in ICD-10 and 11, it was possible to ensure stability since most of the entities had corresponding codes in both editions of the ICD. The blinded-coding is a qualitative method, which permitted to demonstrate accuracy and sensitivity of the new model. This process allowed us to better understand the possible discrepancies and difficulties the end-users may face and correct before the official ICD-11 release.

Even with substantial structural changes to unify and accommodate the "Allergic and hypersensitivity conditions" section into the ICD-11, we have been able to show a high coding correspondence between ICD-10 allergic and hypersensitivity codes sample and the ICD-11 beta draft framework, reaching high sensibility and reassuring international coders and WHO that no previous codes (and patients) will be lost when longitudinal studies will be performed. The main reasons for which the coders indicated that the new ICD-11 frame was not sensible enough were related to the lack of additional severity classification or allergens description, although already in the working platform are still not implemented in the 2015 frozen version [START_REF]World Health Organization, ICD-11 Beta Draft website[END_REF].

The ICD-11 logic prioritizes the post-coordination, allowing the incorporation of more detailed classifications to the stem term. The additional classifications, such as topography, severity and chronological scale are now available in the "Extension codes" chapter (e.g.: L27.0 Generalized skin eruption due to drugs and medicaments of ICD10 = Drug eruption heading + XB13 Generalized of . Although this manuscript presents some technical aspects of classification and new ICD-11 concepts, its aim is also to serve as a step forward to reach quality assurance of the new model and as an introduction to ICD-11 for ICD end-users in the allergy community using anaphylaxis as an example.

The number of excluded files based on the clinical evaluation calls the attention of pitfalls in ability of documenting (medical records and registries) and coding, which hamper reliable epidemiological data. For this reason, the core ALLERGY in ICD-11 operational team (LKT, MC, PD) intends to implement educational tools to cover this gap, following the ICD-11 logic. Educational efforts will also help

Accepted Article

to address the decrease of under-recognition of anaphylaxis by patients, caregivers, and health professionals.

The CHRUM covers a population counted with 270,000 inhabitants for direct referrals and 2,700,266 inhabitants for tertiary referrals. Considering the mean number of total hospitalizations at the CHRUM (40,000 hospitalizations/year), 6% were related to allergic or hypersensitivity conditions based on the ICD-10 codes, 29% having anaphylaxis related codes. The clinical evaluation was able to confirm 89 cases/year. With the evaluation proposed, we are not able to estimate if these numbers can be reproduced over the years, but it provides the basis to estimate an average rate of 0.32 (95% CI: 0.8-0.95) anaphylaxis cases per thousand population per year. Although restricted to a French region, this data supports that anaphylaxis, as a severe life-threatening allergic condition, should be formally added into the list of rare diseases in order to support awareness and quality clinical management of patients by building up a network of reference and related competence centres spread in all regions as it already exists for every rare disease in France. Some limitations of the current study may have to be considered. There is a low risk of having the classification tuned up until the end of the revision process due to regular ICD-11 beta draft platform updates. Although limited to one institution only, we intend to extend the inclusion of new centres and the generated data follows the WHO ICD-11 revision agenda in order to reach global comparability with the presented results. The CHUM is known for performing drug hypersensitivity work-up and patients from this French region are advised for this reason. Although we are aware that it may have had influence in the quantitative data, it may not have influenced the qualitative field-testing methodology application and coding procedure. The inclusion of additional centres from the international network may allow us to objectively understand how the characteristics of patients' data can affect the quality assurance process.

Conclusion

The construction of the new section dealing with anaphylaxis means that the latter will now be recognized as a clinical condition requiring specific documentation Accepted Article and management. Besides increasing the accuracy and sensibility of clinical diagnosis data, unifying the allergic and hypersensitivity conditions into a single section of the ICD, endorsed by the WHO ICD governance bodies, can be considered a strong epidemiological, economical and political move that advocates in favour of the best diagnosis and management of allergic patients worldwide. By allowing all the relevant diagnostic terms for anaphylaxis to be included into the ICD-11 framework, WHO has recognized their importance not only to clinicians but also to epidemiologists, statisticians, health care planners and other stakeholders. This category is to be used as the primary code to identify the effects, not elsewhere classifiable, of unknown, undetermined or ill-defined causes. For multiple coding purposes this category may be used as an additional code to identify the effects of conditions classified elsewhere.

Accepted Article

LIST OF FIGURES

  The same sample with clinical diagnosis have been manually blind-coded by two trained coders based on the online ICD-10 2015 version[START_REF]World Health Organization, ICD-10 version 2016 website[END_REF] and current ICD-11 beta draft (May 2015 frozen version)[START_REF]World Health Organization, ICD-11 Beta Draft website[END_REF], both with online English versions. Data were anonymous from now onwards. The degree of inter-rater agreement was assessed using Cohen's kappa.

  ABBREVIATIONS: ICD: International Classification of Diseases CHRUM: University Hospital of Montpellier RSG: Revision Steering Group TAG: Topic Advisory Group WGs: Working Groups WHA: World Health Assembly WHO: World Health Organization

Figure 1 :Figure 2 :Figure 3 :Figure 4 :

 1234 Figure 1: Anaphylaxis corresponding ICD-10 and ICD-11 codes Figure 2: The "Anaphylaxis" subsection scattered into the pioneer ICD-11 "Allergic and hypersensitivity conditions" section Figure 3: General scheme and outcomes of the field-testing methodology applied for anaphylaxis Figure 4: Characterization of one-year evaluation of University Hospital of Montpelllier anaphylaxis cases

Figure 1 :

 1 Figure 1: Anaphylaxis corresponding ICD-10 and ICD-11 codes

Figure 2 :Figure 3 :Figure 4 :

 234 Figure 2: The "Anaphylaxis" subsection scattered into the pioneer ICD-11 "Allergic and hypersensitivity conditions" section

ACKNOWLEDGEMENT:

We are extremely grateful to all the representatives of the ICD-11 Revision Project with whom we have been carrying on fruitful discussions, helping us to refine the classification presented here: Robert Jakob, Linda Best, Nenad Kostanjsek, Robert J G Chalmers, Jeffrey Linzer, Linda Edwards, Ségolène Ayme, Bertrand Bellet, Rodney Franklin, Matthew Helbert, August Colenbrander, Satoshi Kashii, Paulo E. C. Dantas, Christine Graham, Ashley Behrens, Julie Rust, Megan Cumerlato, Tsutomu Suzuki, Mitsuko Kondo, Hajime Takizawa, Nobuoki Kohno, Soichiro Miura, Nan Tajima and Toshio Ogawa.

FUNDING

Pascal Demoly and Luciana Kase Tanno received an unrestricted AstraZeneca ERS-16-11927 grant through CHRUM administration.

Accepted Article

AVAILABILITY OF DATA AND MATERIAL Data sharing not applicable to this article as no datasets were generated or analyzed during the current study. The ICD-11 beta draft platform is open to the public.

COMPETING INTERESTS

The authors declare that they do not have any conflict of interests related to the contents of this article. AUTHOR CONTRIBUTIONS': Luciana Kase Tanno and Pascal Demoly contributed to the construction of the document (designed the study, analyzed and interpreted the data, and wrote the manuscript). Nicolas Molinari, Pierre Aubas and Sophie Bruel contributed to the methodology design and data evaluation. Nicolas Molinari, Sophie Bruel, Jean Luc Bourrain, Moises A Calderon and Pierre Aubas contributed to tuning the document and revision of the manuscript.


Y Ayed

G Germain

Anna Pubill Melsió

P Kowalewski

Effect of supply conditions of liquid nitrogen on the cryogenic assisted machining of the Ti64 Titanium alloy

Keywords: Tool wear, Titanium alloy, cryogenic assistance, residual stress

This study focuses on the optimization of the machining assisted by cryogenic cooling. The main objective is to analyze the effect of the pressure and the flow of liquid nitrogen on tool life when machining titanium alloy Ti-6Al-4V using the cryogenic assisted machining. A nozzle holder has been specially developed for this study to ensure positioning and the replacement of calibrated nozzles of different diameters. Several nozzle diameters have been therefore used in order to vary the pressure and the flow according to tests to be conducted. The flow rate has been varied between 1.2 l/min and 3.4 l/min for two pressure ranges 8-10 bar and 4-5 bar respectively.The machining tests have allowed to highlight the effect of the pressure and flow rate of liquid nitrogen jet on the tool life. Indeed, the results showed that increasing the flow rate increases the tool life. In addition, the increase in pressureslowed down the evolution of the wear and further improves the tool life.Indeed, in all tested cases, the cryogenic assistance improves the tool life but the best results have been obtained for the highest pressure and flow rate. Moreover, surface integrity has been greatly improved

INTRODUCTION

Titanium alloys present very interesting assets in the aerospace, marine and biomedical fields especially for their excellent mechanical characteristics, their corrosion resistance and their low density. However, machining these alloys is often challenging. Among the solutions that have been developed to overcome this problem is machining assistance. In the recent years, research about the cryogenic assistance is continually growing. Most of these studies were focused on the impact of this assistance on tool life. It has been shown that the phenomenon of wear is greatly reduced which leads subsequently to a considerable increase of tool life. [START_REF] Machai | Machining of βtitanium-alloy Ti-10V-2Fe-3Al under cryogenic conditions: Cooling with carbon dioxide snow[END_REF][START_REF] Biček | Cryogenic machining as an alternative turning process of normalized and hardened AISI 52100 bearing steel[END_REF][START_REF] Kaynak | Tool-wear analysis in cryogenic machining of NiTi shape memory alloys: A comparison of tool-wear performance with dry and MQL machining[END_REF].Other studies had as object to study the impact of the cryogenic lubrication on surface integrity (residual stress and surface roughness). Again, the results were very encouraging especially with the considerable improvement found compared to conventional machining [4,[START_REF] Shokrani | Investigation of the effects of cryogenic machining on surface integrity in CNC end milling of Ti-6Al-4V titanium alloy[END_REF]. According to [START_REF] Sun | Improved Surface Integrity from Cryogenic Machining of Ti-6Al-7Nb Alloy for Biomedical Applications[END_REF] surface integrity could be improved by 35% when machining Ti-6Al-4V titanium alloy. However, influence of the liquid nitrogen parameters such as its pressure and its flow rate is unknown. Thus, this study aims to assess the impact of these parameters on tool life and residual stresses. A new nozzle holder has been specially developed for this study (Figure 1).It allows the positioning and the supply of calibrated nozzles of different diameters.

TOOL WEAR

Tool wear has been controlled every minute using a stereo microscope and basing on the ANSI/ASME B94.55M-1985 standard. The tool is considered as worn if the flank wear (VB) exceeds 0.3 mm.

The first series of tests consists in varying the flow of liquid nitrogen while maintaining an elevated pressure (8-10 bar). Figure 2 shows the results of these trials.

First of all, it could be remarked that the cryogenic assistance permits to significantly increase the tool life. It allows, in the worst case, to increase the tool life of about 5 times compared to the dry machining. Moreover, these tests show that the flow rate has a great influence. Indeed, with a flow rate of 1.8 l/min tool life is about 12 min while when using a flow rate of 3.4 l/min the flank wear does not exceed 0.15 mm. The second series of tests consists in varying pressure of liquid nitrogen while maintaining the flow rate. Figure 3 shows the results of these tests. As well as the previous tests, the variation of the liquid nitrogen pressure impacts the tool life. In fact, when reducing the pressure from 8-10 bar to 4-5 bar the tool life drops. Finally, it should be noted that the tool life obtained for a high pressure (8-10 bar) and a low flow (1.8 l/min) corresponds almost to the tool life obtained at low pressure (4-5 bar) and a high flow rate (3 l/min)

RESISUAL STRESS

The last part of this study focuses on the influence of liquid nitrogen parameters on surface residual stress. Indeed, in dry machining the level of residual stress does not exceed -200 MPa. However, it reaches -330 MPa at low pressure (3 l/min) and-433 MPa at high pressure (3.4 l/min). Figure 4 shows these results. Basing on these results it could be noted that cryogenic assistance improves the work piece surface integrity. This improvement is more marked with the highest pressure and the most important flow rate.

CONCLUSION

From the experimental results it can be concluded that the pressure of the liquid nitrogen and its flow rate have a significant impact on the tool life and residual stress. Indeed, the best results have been obtained with the highest pressure and the highest flow rate. It can be noted also that whatever the parameters of liquid nitrogen, cryogenic assistance can significantly increase the tool life. In addition, it improves considerably the surface integrity.

  In order to determine the influence of the liquid nitrogen parameters (pressure and flow rate) on tool life, several wear tests have been carried out. These experimental trials were conducted on Leadwell LTC25iL (2 500 rev/min, 24kw) lathe. The liquid nitrogen is conditioned in a 180 liter tank. It is supplied to the tool through thermally insulated pipes.H13A uncoated carbide inserts have been used (CCMT 12-04-08KM). Different flow rates have been tested (1.4 l/min, 1.8 l/min and 3.4 l/min) for two different pressure levels. These tests have been accompanied by the measurement of surface roughness, cutting forces, tool wear and residual stresses. The study has been funded by Air Liquide and only a part of these results will be presented in the present article for reasons of confidentiality. The cutting conditions are listed below:  Cutting speed Vc: 80 m/min.  Depth of cut ap: 1 mm.  Feed rate: 0.2 mm/rev.

Figure 1 :

 1 Figure 1: New nozzle holder

Figure 2 :

 2 Figure 2: Liquid nitrogen flow rate influence

Figure 3 :

 3 Figure 3: Liquid nitrogen pressure influence

Figure 3 :

 3 Figure 3: Residual stress

Table 1

 1 summarizes the results of the preliminary tests.

	Liquid nitrogen pressure: 8-10 bar
	Nozzle diameter (mm)	Flow rate (l/min)
	1,6	1,8

Table 1 :

 1 Calibration of the flow rate and pressure