Marc Garel

Christos Panagiotopoulos

Mehdi Boutrif

Daniel Repeta

Richard Sempere

Chiara Santinelli

Bruno Charrière

David Nerini

Jean-Christophe Poggiale

Christian Tamburini
email: christian.tamburini@mio.osupytheas.fr

Richard Sempéré

Chiara Santinelli3

Christian Tamburini1

Contrasting degradation rates of natural dissolved organic carbon by deep-sea prokaryotes under stratified water masses and deep-water convection conditions in the NW Mediterranean Sea

Keywords: High-molecular weight dissolved organic carbon (HMW-DOC), Deep-sea prokaryotes, Deep-water convection, Marine microbes, Organic matter degradation, High-pressure, Deep Ocean

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

INTRODUCTION

The deep sea, below 1000 m, is one of the largest ecosystems and the largest biome on Earth, yet it is the least well studied and sampled. It is a microbially dominated environment, where prokaryotes drive the most important biological processes. It is characterized by highhydrostatic pressure, low temperature, high nutrient concentrations and low dissolved organic carbon content (around 33-45 µMC) [START_REF] Nagata | Emerging concepts on microbial processes in the bathypelagic ocean -ecology, biogeochemistry, and genomics[END_REF]. The main source of carbon and energy is organic matter produced in the euphotic layer and transferred to depth by different processes [START_REF] Boyd | Multi-faceted particle pumps drive carbon sequestration in the ocean[END_REF][START_REF] Dall'olmo | Substantial energy input to the mesopelagic ecosystem from the seasonal mixed-layer pump[END_REF][START_REF] Hansell | Dissolved Organic Matter in the Ocean: A Controversy Stimulates New Insights[END_REF][START_REF] Levy | Physical pathways for carbon transfers between the surface mixed layer and the ocean interior[END_REF][START_REF] Siegel | Prediction of the Export and Fate of Global Ocean Net Primary Production: The EXPORTS Science Plan[END_REF]. Hence, carbon dioxide and inorganic nutrients are converted by photosynthesis into particulate (POC) and dissolved organic carbon (DOC) in the euphotic zone, and transferred to the deeper ocean by various mechanisms including winter deep convection [START_REF] Copin-Montégut | Vertical distribution and temporal variation of dissolved organic carbon in the North-Western Mediterranean Sea[END_REF], subduction [START_REF] Aristegui | Microbial oceanography of the dark ocean's pelagic realm[END_REF][START_REF] Burd | Assessing the apparent imbalance between geochemical and biochemical indicators of meso-and bathypelagic biological activity: What the @$♯! is wrong with present calculations of carbon budgets?[END_REF][START_REF] Hansell | DIssolVeD oRgaNIc MatteR IN the oceaN[END_REF][START_REF] Sohrin | Seasonal variation in total organic carbon in the northeast Atlantic in 2000-2001[END_REF], fragmentation of large aggregates into small particles [START_REF] Briggs | Major role of particle fragmentation in regulating biological sequestration of CO 2 by the oceans[END_REF], dissolution of sinking particles [START_REF] Follett | Hidden cycle of dissolved organic carbon in the deep ocean[END_REF][START_REF] Smith | Intense hydrolytic enzyme activity on marine aggregates and implications for rapid particle dissolution[END_REF] and the vertical migration of zooplankton with release of POC/DOC by exudation and defecation [START_REF] Steinberg | Zooplankton vertical migration and the active transport of dissolved organic and inorganic carbon in the Sargasso Sea[END_REF][START_REF] Steinberg | Zooplankton and the Ocean Carbon Cycle[END_REF]. DOC concentration decreases with depth [START_REF] Hansell | Dissolved Organic Matter in the Ocean: A Controversy Stimulates New Insights[END_REF] and can be divided into two reservoirs of different biological lability: labile-DOC and recalcitrant DOC [START_REF] Carlson | DOM Sources, Sinks, Reactivity, and Budgets[END_REF][START_REF] Hansell | Dissolved Organic Matter in the Ocean: A Controversy Stimulates New Insights[END_REF]. The recalcitrant fraction can be further divided in semilabile, semi-refractory, refractory and ultra-refractory DOC [START_REF] Hansell | Recalcitrant Dissolved Organic Carbon Fractions[END_REF]. Semi-labile DOC accumulates in the surface ocean where DOC production exceeds DOC consumption and is transferred in the dark ocean where consumption exceeds production [START_REF] Carlson | Annual flux of dissolved organic carbon from the euphotic zone in the northwestern Sargasso Sea[END_REF][START_REF] Carlson | DOM Sources, Sinks, Reactivity, and Budgets[END_REF]. However, turnover times for semi-labile DOC are largely unconstrained, and the contribution of semi-labile DOC to global prokaryotic heterotrophic production is hard to quantify [START_REF] Carlson | Production and Removal Processes[END_REF][START_REF] Carlson | DOM Sources, Sinks, Reactivity, and Budgets[END_REF]. From a chemical point of view, a major portion of surface high-molecular-weight-DOC (HMW-DOC) is composed of carbohydrates (acyl-polysaccharides) that have remarkably conservative spectrometric and chemical properties throughout the global ocean (Aluwihare et al., 1997a;[START_REF] Benner | Bulk chemical characteristics of dissolved organic matter in the ocean[END_REF][START_REF] Repeta | Chemical Characterization and Cycling of Dissolved Organic Matter[END_REF].

Heterotrophic prokaryotes are one of the main actors of the carbon cycle in marine ecosystems.

They i) consume 10 to 50% organic matter produced by primary production in the surface waters [START_REF] Azam | The Ecological Role of Water-Column Microbes in the Sea[END_REF], ii) facilitate particle solubilization [START_REF] Aristegui | Microbial oceanography of the dark ocean's pelagic realm[END_REF][START_REF] Cho | Major role of bacteria in biogeochemical fluxes in the ocean's interior[END_REF][START_REF] Panagiotopoulos | Bacterial degradation of large particles in the southern Indian Ocean using in vitro incubation experiments[END_REF][START_REF] Sempéré | Microbial decomposition of large organic particles in the northwestern Mediterranean Sea: An experimental approach[END_REF]Tamburini et al., 2009b), iii) produce semi-labile DOC from labile DOC (ranged 0.1 to 0.2 Gt C yr -1) [START_REF] Fang | The POM-DOM piezophilic microorganism continuum (PDPMC)-The role of piezophilic microorganisms in the global ocean carbon cycle[END_REF][START_REF] Jiao | Microbial production of recalcitrant dissolved organic matter: long-term carbon storage in the global ocean[END_REF][START_REF] Tamburini | Role of deep-sea bacteria in organic matter mineralization and adaptation to hydrostatic pressure conditions in the NW Mediterranean Sea[END_REF] and finally, iv) account for a large part of heterotrophic respiration in open ocean (20-33.3 Gt C yr -1) [START_REF] Arístegui | Respiration in the dark ocean[END_REF][START_REF] Del Giorgio | Respiration rates in bacteria exceed phytoplankton production in un prroductive aquatic systems[END_REF].

However, there are still significant gaps in our knowledge of prokaryotic processes that control transformation, and degradation of the organic matter in the deep sea.

Most studies of DOC degradation have targeted the labile fraction and used simple compounds coupled with radioelements or fluoregenic substrate analogs to measure uptake and turnover time [START_REF] Hoppe | Profiles of ectoenzymes in the Indian Ocean: Phenomena of phosphatase activity in the mesopelagic zone[END_REF][START_REF] Koike | High potential activity of extracellular alkaline phosphatase in deep waters of the central Pacific[END_REF]Tamburini et al., 2009a[START_REF] Tamburini | Biopolymer hydrolysis and bacterial production under ambient hydrostatic pressure through a 2000 m water column in the NW Mediterranean[END_REF]Teira et al., 2006aTeira et al., , 2006b)). As such very little is known about the degradation of semi-labile or semirefractory DOC fractions. In addition, most studies have not taken into account the effect of hydrostatic pressure, which is a major parameter acting on prokaryotic metabolisms (Tamburini et al., 2013a). One of the few studies of semi-labile DOC degradation under pressure was made by [START_REF] Boutrif | Assimilation of marine extracellular polymeric substances by deep-sea prokaryotes in the NW Mediterranean Sea[END_REF] who used radiolabeled exopolysaccharides (3H-EPS) as a proxy semi-labile DOC and incubated their samples under in situ high-pressure conditions.

Using this approach, Boutrif and colleagues were able to show (i) an increase with depth of specific-cell activity assimilating 3H-EPS and (ii) a high contribution of Euryarchaeota in driving the degradation of 3H-EPS in the deep-sea waters of the Mediterranean Sea.

The phylogenetic composition and metabolic capabilities of marine microbial communities change with depth [START_REF] Delong | Community Genomics Among Stratified Microbial Assemblages in the Ocean's Interior[END_REF][START_REF] Nagata | Emerging concepts on microbial processes in the bathypelagic ocean -ecology, biogeochemistry, and genomics[END_REF] as does metabolic capabilities of the microbial communities that regulate carbon export [START_REF] Giovannoni | Molecular diversity and ecology of microbial plankton[END_REF][START_REF] Mccarren | Microbial community transcriptomes reveal microbes and metabolic pathways associated with dissolved organic matter turnover in the sea[END_REF]. [START_REF] Delong | Community Genomics Among Stratified Microbial Assemblages in the Ocean's Interior[END_REF] identified a great number of genes, putatively involved in polysaccharide degradation, in deep microbial populations compared to those found in the surface. More recently, using comparative metaproteomics, [START_REF] Bergauer | Organic matter processing by microbial communities throughout the Atlantic water column as revealed by metaproteomics[END_REF] found that deep-sea microorganisms produce transporters not only for substrate such as amino acids and carbohydrates, but also for osmolytes. These osmolyte transporters increase with depth, reaching 39% of protein sequences identified in the bathypelagic zone. Recently, [START_REF] Saw | Pangenomics Analysis Reveals Diversification of Enzyme Families and Niche Specialization in Globally Abundant SAR202 Bacteria[END_REF] describe the enzymatic repertoire of resident mesopelagic and bathypelagic SAR202 that appear to favor remineralization of recalcitrant DOC. Moreover, under high hydrostatic pressure, piezophile deep-sea microorganisms display unique metabolisms [START_REF] Campanaro | Laterally transferred elements and high pressure adaptation in Photobacterium profundum strains[END_REF][START_REF] Lauro | Prokaryotic lifestyles in deep sea habitats[END_REF]. As an example, piezophilic Photobacterium profondum SS9 have shown its ability to degrade complex organic matter. The regulation of metabolic pathways for the degradation of different polymers such as chitin, pullulan, and cellulose is controlled by pressure, being activated at 28 MPa and turned off at 0.1 MPa [START_REF] Campanaro | Laterally transferred elements and high pressure adaptation in Photobacterium profundum strains[END_REF].

Fieldwork investigation using 3H-labeled extracellular polymeric substance labeled (3H-EPS), done at in situ high pressure conditions, showed that prokaryotes increased their ability to use 3H-EPS with depth [START_REF] Boutrif | Assimilation of marine extracellular polymeric substances by deep-sea prokaryotes in the NW Mediterranean Sea[END_REF].

The Mediterranean Sea is a semi-enclosed sea, with a deep warm temperature (~13°C), and very short ventilation and residence times for deep waters of ~70-126 years [START_REF] Schlitzer | Chlorofluoromethane and oxygen in the Eastern Mediterranean[END_REF]. The NW Mediterranean Sea is one of the few regions in the world's ocean where both dense shelf water cascading and open-sea convection take place [START_REF] Canals | Flushing submarine canyons[END_REF][START_REF] Durrieu De Madron | Deep sediment resuspension and thick nepheloid layer generation by open-ocean convection[END_REF], 2011;[START_REF] Mertens | Interannual Variability of Deep-Water Formation in the Northwestern Mediterranean[END_REF][START_REF] Santinelli | DOC dynamics in the meso and bathypelagic layers of the Mediterranean Sea[END_REF]Tamburini et al., 2013b). These sinking water masses carry POC and DOC, as well as significant numbers of organisms from the surface layer into the deep sea [START_REF] Avril | DOC dynamics in the northwestern Mediterranean Sea (DYFAMED site)[END_REF][START_REF] Marshall | Open-ocean convection: Observations, theory, and models[END_REF][START_REF] Martín | Impact of open sea deep convection on sediment remobilization in the western Mediterranean[END_REF][START_REF] Santinelli | DOC in the Mediterranean Sea[END_REF][START_REF] Santinelli | DOC dynamics in the meso and bathypelagic layers of the Mediterranean Sea[END_REF][START_REF] Testor | Post-convection spreading phase in the Northwestern Mediterranean Sea[END_REF][START_REF] Vidal | Across margin export of organic matter by cascading events traced by stable isotopes, northwestern Mediterranean Sea[END_REF]. Depending on the preconditioning phase different volumes of surface water are exported (in a more cold and dry winter, more water will sink; Durrieu de [START_REF] Durrieu De Madron | Deep sediment resuspension and thick nepheloid layer generation by open-ocean convection[END_REF], driving a larger amount of dissolved oxygen, semi-labile DOC [START_REF] Canals | Flushing submarine canyons[END_REF][START_REF] Lefèvre | Is DOC the main source of organic matter remineralization in the ocean water column?[END_REF][START_REF] Powley | Nutrient Cycling in the Mediterranean Sea: The Key to Understanding How the Unique Marine Ecosystem Functions and Responds to Anthropogenic Pressures[END_REF][START_REF] Santinelli | DOC in the Mediterranean Sea[END_REF][START_REF] Santinelli | DOC dynamics in the meso and bathypelagic layers of the Mediterranean Sea[END_REF] and surface-prokaryotic communities [START_REF] Luna | Dense water plumes modulate richness and productivity of deep sea microbes[END_REF][START_REF] Severin | Impact of an intense water column mixing (0-1500 m) on prokaryotic diversity and activities during an open-ocean convection event in the NW Mediterranean Sea[END_REF]Tamburini et al., 2013a) from surface to deep-sea layers.

This paper investigates the utilization of HMW-DOC on the short temporal scale (10-15 days) by deep-sea prokaryotes maintained at in situ high-pressure conditions. Deep-sea prokaryotic natural assemblages were collected in the Mediterranean Sea in two contrasting hydrological conditions including water column stratification and deep-water formation period conditions.

Here, the experimental results were coupled with a cell-quota model [START_REF] Droop | Vitamin B 12 and Marine Ecology. IV. The Kinetics of Uptake, Growth and Inhibition in Monochrysis Lutheri[END_REF], in order to quantify the kinetics of HMW-DOC degradation and its impact on the prokaryotic assemblages under these two contrasting hydrological conditions.

MATERIALS AND METHODS

RECOVERING AND PREPARATION OF HMW-DOC

HMW-DOC was obtained from seawater that was drawn from the 600 m depth at the Natural Energy laboratory of Hawaii Authority NEHLA (19° 43' 42.7"N; 156° 03' 33.2" W) in December 2003. Samples were filtered in-line, and the <0.2 µm fraction concentrated using a custom crossflow ultrafiltration system fitted with a GE-osmonics "GE series" membrane. The membrane has a pore size of ~1 nm and nominally retains organic matter of molecular weight >1 kDa (>99% rejection of vitamin B12 in laboratory tests). Seawater (~1800 L) was concentrated daily to 20 L, frozen and returned to the laboratory for further processing. In the laboratory, HMW-DOC concentrates were thawed and filtered through an Ultracel 30kD membrane (Millipore Corp.) to remove viruses and other small particles, reduced in volume to 2 L by ultrafiltration, and desalted by serial (~10x; 2L each) dilution/concentration with ultrahigh purity water until addition of a 0.1N AgNO3 solution remained clear. Samples from different concentrates were pooled and freeze-dried to a fluffy white powder that was ~36% carbon. Between 18-21% of the total dissolved organic carbon in seawater was recovered (modified protocole from [START_REF] Repeta | Radiocarbon analysis of neutral sugars in highmolecular-weight dissolved organic carbon: Implications for organic carbon cycling[END_REF].

STUDY SITE AND HYDROLOGICAL CONDITIONS

Water samples were collected at 2000 m depth in August 2008 and April 2010 at the ANTARES study site (42°48'N; 6°10'E) about 40 km offshore the French Mediterranean coast (NW Mediterranean Sea; Tamburini et al., 2013b). The hydrological conditions at this site were monitored over the time period of two and a half years prior to sample collection as part of the cabled ANTARES neutrino telescope and EMSO (European Multidisciplinary Subsea Observatory) observation program (ANTARES -EMSO-LO site), in addition measurements of NW Mediterranean deep convection zone located in the Gulf of Lions (LION Site; Tamburini et al. 2013b). In August 2008, the water column was characterized by a strong summertime stratification, which isolates the Western Mediterranean Deep Water from the upper water masses. In contrast, deep-sea waters sampled in April 2010, were recorded as modified due to a strong deep-water convection (see for details Tamburini et al., 2013b and[START_REF] Durrieu De Madron | Deep sediment resuspension and thick nepheloid layer generation by open-ocean convection[END_REF] causing surface water cooling, vertical mixing and finally homogenization of the water column to the deep that occurred in the Gulf of Lion. These two experiments will be called hereafter stratified (Strat.) and deep-water convection period (Conv.), respectively.

SAMPLING

Deep-sea water (2000 m) was sampled and kept in high pressure bottles (HPBs) to maintain constantly the ambient high hydrostatic pressure (20 MPa) during all manipulations (sampling and retrieval, incubation, transfer and sub-sampling) corresponding to the in-situ depth conditions [START_REF] Garel | Pressure-Retaining Sampler and High-Pressure Systems to Study Deep-Sea Microbes Under in situ Conditions[END_REF]. Before collecting samples, 500µL of the HMW-DOC solution was added in the top-part of HPBs (Figure 1). To assess the effect of pressure on deep-sea prokaryotes, two HPBs were maintained at in situ high-pressure condition (thereafter HP). To determine the effect of HP on our results, two replicates were decompressed and incubated at atmospheric pressure (thereafter DEC). Before use, HPBs (volume capacity 500 ± 20 mL) were thoroughly cleaned as described in [START_REF] Garel | Pressure-Retaining Sampler and High-Pressure Systems to Study Deep-Sea Microbes Under in situ Conditions[END_REF]. Using this protocol, the organic carbon background (DOC) in the HPBs bottles was ≤ 2 µMC.

INCUBATION EXPERIMENTS

HMW-DOC solution was amended into the HPBs, just before the CTD cast, to a theoretical final concentration of 120 µMC, and the incubation experiments started once the HPBs came on board (t=0 point). As such, HMW-DOC was incubated with Strat. and Conv. seawater under in situ and atmospheric pressure conditions, in the dark at 13 °C along with the prokaryotic assemblages sampled at 2000 m-depth for 10 and 15 days, respectively. Subsamples were collected using a piloted pressure generator that maintains the hydrostatic pressure within the HPBs [START_REF] Garel | Pressure-Retaining Sampler and High-Pressure Systems to Study Deep-Sea Microbes Under in situ Conditions[END_REF]. Aliquots (in duplicates or triplicates) of 10 -40 mL were sampled for DOC, sugars, and bacterial abundance measurements.

All glassware including glass pipettes and ampoules used for DOC and carbohydrates sampling were combusted at 450 °C for at least 6 h to remove traces of organic compounds. For DOC measurements, 8 mL of sample were collected directly into glass ampoules with 10 µL of H3PO4 85%, flame-sealed, stored in the dark at 4 °C and analyzed within 3 months of subsampling. Carbohydrates were collected into cleaned (10% HCl and Milli-Q water) plastic tubes and stored at -20 °C until analyses. Subsamples for microbial abundance were collected into sterile plastic tubes, fixed with formaldehyde (2 -4% final concentration) and stored at 4 °C for 24 h. Samples were then filtered through 0.22µm-pore-sized polycarbonate filter, dried and stored at -20 °C.

DOC MEASUREMENTS

DOC was measured by high temperature combustion on a Shimadzu TOC 5000 analyzer [START_REF] Sohrin | Seasonal variation in total organic carbon in the northeast Atlantic in 2000-2001[END_REF]. A four point-calibration curve was performed daily with standards prepared by diluting a stock solution of potassium hydrogen phthalate in Milli-Q water. To avoid the small error associated with day-to-day instrument variability, all samples from a given experiment were analyzed in a single day's run. Procedural blanks were run with acidified sparged Milli-Q water and ranged from 1 to 2 µM C. Blanks were subtracted from the measured values. Deep seawater reference samples (provided by D. Hansell; Univ. Miami) were run daily (43.5 ± 1 µM C, n = 4) to check the accuracy of the TOC analysis. Finally, it is important to note that in our study sub-samples were not filtered, in order to reduce contamination, we therefore consider DOC≈TOC since seawater samples were collected at 2000 m, where POC may be considered as negligible. Experimental errors based on triplicates analyses were estimated to be about 5-8% for DOC.

DISSOLVED COMBINED NEUTRAL SUGARS (DCNS)

DETERMINATION

Aliquots of 8 mL were desalted using dialysis tubes with a molecular weight cut-off of 100-500 Da (Spectra/Por® Biotech cellulose ester) [START_REF] Engel | A novel protocol for determining the concentration and composition of sugars in particulate and in high molecular weight dissolved organic matter (HMW-DOM) in seawater[END_REF]. Before use, dialysis tubes were rinsed with Milli-Q water to remove sodium azide. Before applying the sample, dialysis tubes were rinsed with 1-2 mL of the sample volume. Then, the dialysis tube was filled with 8 mL of the sample and the dialysis was conducted in a 1 L beaker filled with Milli-Q water at 4 °C. Dialysis was achieved after 4-5 h (salinity dropped from 35 to 1-2 g L -1 ). Prior to sample removal, the tubes were placed into an ultrasonic bath for 5 min. Samples were transferred into pre-combusted glass vials (500 °C, 4 h) and freeze dried. The obtained powder was hydrolyzed with 1M HCl for 20 h at 100 °C [START_REF] Engel | A novel protocol for determining the concentration and composition of sugars in particulate and in high molecular weight dissolved organic matter (HMW-DOM) in seawater[END_REF][START_REF] Murrell | Distribution and composition of dissolved and particulate organic carbon in northern San Francisco Bay during low flow conditions[END_REF]. As a precaution, we ensured the complete removal of HCl by adding 2-3 mL of Milli-Q water and repeating the freeze-drying. The dried sample was then re-dissolved in 4 mL of Milli-Q water, filtered through quartz wool, and pipetted into scintillation vials and kept at 4 °C until the time of analysis (this never exceeded 24 h). Finally, it is important to note that the current desalination procedure does not allow for the determination of the dissolved free neutral sugars (i.e., sugar monomers present in samples with MW~180 Da) because these compounds are lost and/or poorly recovered during the dialysis step [START_REF] Panagiotopoulos | Composition and distribution of dissolved carbohydrates in the Beaufort Sea Mackenzie margin (Arctic Ocean)[END_REF].

Carbohydrate concentrations in samples were measured by HPAEC-PAD according to [START_REF] Mopper | Determination of Sugars in Unconcentrated Seawater and Other Natural Waters by Liquid Chromatography and Pulsed Amperometric Detection[END_REF] and were modified by [START_REF] Panagiotopoulos | The composition and flux of particulate and dissolved carbohydrates from the Rhone River into the Mediterranean Sea[END_REF][START_REF] Panagiotopoulos | Sub-ambient temperature effects on the separation of monosaccharides by high-performance anion-exchange chromatography with pulse amperometric detection -Application to marine chemistry[END_REF]. Briefly, monosaccharides were separated on an-anion exchange column (CarbopacPA-1, Dionex) by isocratic elution (mobile phase 19 mM NaOH) and were detected by an electrochemical detector set in the pulsed amperometric mode [START_REF] Panagiotopoulos | Composition and distribution of dissolved carbohydrates in the Beaufort Sea Mackenzie margin (Arctic Ocean)[END_REF]. The flow rate and the column temperature were set at 0.7 mL min -1 and 17°C, respectively. Data acquisition and processing were performed using the Dionex software Chromeleon. The recovery yields of the whole procedure (dialysis and hydrolysis) were estimated using standard polysaccharides (laminarin, and chondroitin sulfate) and ranged from 82 to 86% (n = 3). Repeated injections (n = 6) of a dissolved sample previously submitted to dialysis and hydrolysis resulted in a CV of 12 -15% for the peak area, for all sugars.

PROKARYOTIC ABUNDANCE

Prokaryotic cells were stained by 4, 6-di-amidino-2-phenylindole (DAPI, final concentration 25 µg mL -1 ). Total cells marked by DAPI were counted using semi-automatic epifluorescence microscope (Olympus B61) and image analyses with biovolume calculation were done as described by [START_REF] Cottrell | Contribution of major bacterial groups to bacterial biomass production (thymidine and leucine incorporation) in the Delaware estuary[END_REF]. Biovolume (V, Table 1) was converted in carbon content (CC) (µM C) according to the methods described in [START_REF] Posch | Precision of bacterioplankton biomass determination: a comparison of two fluorescent dyes, and of allometric and linear volume-to-carbon conversion factors[END_REF] using the following equation: CC = 218 × V-0.86 [START_REF] Loferer-Krössbacher | Determination of bacterial cell dry mass by transmission electron microscopy and densitometric image analysis[END_REF]. Prokaryotes biomass (µg C L - 1 ) is calculated as the product of abundance (DAPI-cells count, Table 1) and mean cellular carbon content (CC). Experimental errors based on duplicates analyses were estimated to be about 3-5%.

DYNAMICS OF DOC AND PROKARYOTES ADJUSTED TO A DROOP MODEL

A cell-quota model [START_REF] Droop | Vitamin B 12 and Marine Ecology. IV. The Kinetics of Uptake, Growth and Inhibition in Monochrysis Lutheri[END_REF]) was built to represent both the kinetics of HMW-DOC and growth of microbial community. Such model, which has been already reported as much relevant for prokaryote dynamics as well [START_REF] Eichinger | Increased bacterial growth efficiency with environmental variability: Results from DOC degradation by bacteria in pure culture experiments[END_REF][START_REF] Eichinger | Consumption and release of dissolved organic carbon by marine bacteria in a pulsed-substrate environment: from experiments to modelling[END_REF](Eichinger et al., , 2011) ) describes here the ability of the deep-sea microbial community to degrade HMW-DOC, store carbon with cellquota and coupling HMW-DOC, uptake and biomass synthesis. Equations of the model are the following:

⎩ ⎪ ⎪ ⎨ ⎪ ⎪ ⎧ &' &( = * !"# ' +1 - . ! . / &012 &( = -3(012 -012 $%& )' &. &( = 3(012 -012 $%& ) -* !"# (. -. ! )
The model involves three state variables: the biomass of microorganisms denoted as ' (µM C), the concentration of the substrate, here HMW-DOC, denoted as 012 (µM C) and the intracellular quota of nutrient, here the carbon, denoted as .

>>?(µ !"# , 3, . ! , 012 $%& ) = @ A '(( ' ) -7 ' B # C ( ) '*+ + @ A 012(( ' ) -&9: ' B ,-& C ( ) '*+ .
This cost function has been constructed to give the same weight between cell biomass ' and concentration of the substrate 012 by dividing each distance with its respective standard deviation, B # for the cell biomass data and B ./0 for the substrate concentration data. At each step of the minimization process, the trajectories '(() and 012(() were estimated from the model by numerical integration (Euler method) until convergence to the minimum of >>?.

Once the parameters were estimated and under some classical statistical hypotheses, bootstrapped data were drawn from the distribution of the model errors (Seber and Wild, 2003, chap. 2). The minimization process has been reconducted 500 times. By this way, a 95% confidence interval for each parameter as well as some interval of variability of the trajectories '(() and 012(() have been evaluated in each experimental condition. By this way, it is easy to compare the dynamical evolution of each state variable between different experimental conditions and to assess how variability bands are superimposed i.e. how experience are similar (see Figure 2).

STATISTICAL METHODS

Non-parametric statistical methods were used to test the parameters (growth rates -µ !"# , degradation rates -k, minimum quota -. ! and the remaining DOC at the end of the incubation named recalcitrant carbon -012 $%& ) obtained using the Droop model after 500 simulations (see above) and to compare incubation (HP versus DEC) and hydrological (Strat. versus Conv.) conditions. Specifically, Kruskal-Wallis and Pairwise Wilcoxon Rank Sum tests (R Core Team, 2017) were used to compare medians between incubation and hydrological conditions. These tests performed on the box-and-whisker plots attests that each parameter estimated is significantly different (p < 0.05) between each incubation and each condition (except for DOCrec between Strat_HP and Conv_HP). with literature data showing that sugars represent about <10% of DOC (Table 1; [START_REF] Panagiotopoulos | Analytical methods for the determination of sugars in marinesamples: A historical perspective and future directions[END_REF].

RESULTS

BULK AND MOLECULAR COMPOSITION CHARACTERISTICS OF HMW-DOC

time(d) µM C • • • • • • • • • • • • • • • • 0 5 10 15 0.0 0.5 1.0 1.5 2.0 [Cell Biomass] time(d) µM C • • • • • • • • • • • • • • • • 0 2 4 6 8 10 0 50 100 150 [DOC] time(d) µM C • • • • • • • • • • • • • • • • 0 2 4 6 8 10 0.0 0.5 1.0 1.5 2.0 [Cell Biomass] time(d) µM C • • • • • • • • • • • • • • • • 14
Before the addition to the HPBs, the analysis of hydrolyzed HMW-DOC indicated the presence of six neutral monosaccarides namely fucose, rhamnose, galactose, glucose, mannose and xylose occurring at approximately equimolar abundance (11-17% of DCNS) as well as arabinose (5% of DCNS) and glucosamine (19% of DCNS). With the exception of glucosamine, which was unusually high in this sample, all the above values agree well with previous investigations and support the idea that these sugars are an important component of acyl-polysaccharides or semilabile DOM (Aluwihare et al., 1997b;[START_REF] Mccarthy | Major biochemical composition of dissolved high molecular weight organic matter in seawater[END_REF][START_REF] Repeta | Chemical Characterization and Cycling of Dissolved Organic Matter[END_REF][START_REF] Skoog | Aldoses in various size fractions of marine organic matter: Implications for carbon cycling[END_REF]). Although we have not measured in situ background DCNS concentrations at the ANTARES site, data obtained during Conv. conditions (CASCADE cruise 1-23 March 2011)

suggested that DCNS represented 1.7% of DOC whereas glucose (49% DCNS), galactose (9% DCNS) and rhamnose (9% DCNS) were among the most abundant monosaccharides.

Immediately after HMWDOM addition in HPBs bottles, glucose accounted for 59 to 48% of the DCNS at the beginning of the experiments while at the end it represented 53 -46% of the DCNS, in HP and DEC incubations respectively, suggesting a selective degradation of this compound during the incubation (Table 1). Galactose was second in abundance accounting for 12 -32% of the DCNS at the beginning of the experiment and did not show variation throughout the experiment (13-27%), in HP and DEC incubations respectively. With the exception of mannose, the remaining sugars accounted less than 10% of the DCNS pool and again they vary little during the incubation experiment.

DOC DEGRADATION AND PROKARYOTIC BIOMASS

Key degradation kinetic parameters including DOC degradation rate (k), estimated recalcitrant DOC concentration (DOCrec) as well as maximum growth rate (µmax) and metabolic state of microbial community were estimated in non-steady state and closed conditions by using the Droop model (Figure 2 -Figure 3 and Table 2). Figure 2A Results from the Conv. period conditions are given in Figure 2 B and D. Hence, it is possible to directly compare HP and DEC incubations on the same graph and between water masses period conditions, Strat_HP versus Conv_HP, comparing all panels in Figure 2).

During Strat. conditions, DOC degradation was significantly higher in HP than in DEC incubations (Figure 2A). On the timescales of the incubations, 56.0 µM (i-e. 46.6% of the initial concentration) of DOC were degraded in HP incubation whereas only 11.2 µM (i-e. 9.3% of the initial concentration) of DOC were degraded in DEC incubation. Degradation rates (k) averaged 0.45 ± 0.12 d -1 and 0.11 ± 0.10 d -1 in HP and DEC conditions, respectively (Table 2). Growth rate was also higher in HP conditions averaging 0.51 ± 0.07 d -1 compared to 0.41 ± 0.03 d -1 for DEC incubations (Figure 2B), being closed to growth rates median (Table 2).

By contrast, during Conv. period, DOC degradation rates (k) were higher (k = 0.51 ± 0.11 d -1 ) in DEC than in HP incubations (k = 0.01 ± 0.03 d -1 ) (Figure 2C). Due to this very low DOC Table 2. Parameters estimated by cell-quota model and bootstrapped variance and median during stratified period (Strat.) and deep-water mass convection period (Conv.) conditions. µmax is the growth rate in d-1; k is the degradation rate in d-1; Qm is the minimum cell-quota (a ratio between intracellular concentration of organic carbon and cellular biomass, dimensionless); DOCrec is the quantity of residual HMW-DOC in µMC. HP: samples maintained under in situ high pressure conditions without decompression; DEC: samples decompressed and incubated at atmospheric pressure conditions (DEC). degradation rates in HP incubations, the DOCrec is highly variable (65.04 ± 29.11 µMC, Table 2). This does not allow us to calculate with confidence a percentage of degradation in this case.

µ max k Q m DOC rec µ max k Q m DOC rec µ max k Q m DOC rec µ max k Q m DOC rec mean 0.
Prokaryotic growth rates averaged 0.76 ± 0.02 and 0.56 ± 0.08 d -1 , for DEC and HP incubations (Figure 2D and Table 2), respectively. In addition, for HP incubation, the community of prokaryotes does not seem to reach a stationary phase in contrast to DEC incubation.

DISCUSSION

HMW-DOC COMPOSITIONAL CHANGES DURING DEGRADATION

The monosaccharide composition of the samples after addition of HMW-DOC (samples retrieved at 2000 m at DEC and HP conditions) resembled that generally reported for deep waters (Table 1) [START_REF] Kaiser | Major bacterial contribution to the ocean reservoir of detrital organic carbon and nitrogen[END_REF][START_REF] Panagiotopoulos | Composition and distribution of dissolved carbohydrates in the Beaufort Sea Mackenzie margin (Arctic Ocean)[END_REF][START_REF] Skoog | Aldoses in various size fractions of marine organic matter: Implications for carbon cycling[END_REF]. Our results showed distinct differences in the initial and final sugar composition during the biodegradation experiments for both Strat. and Conv. conditions (Table 1). This finding was more pronounced for glucose (45% decrease of its initial concentration) mannose (27%) and galactose (20%) during Stat. water period under HP incubations than Conv. period also under HP conditions (glucose 14%; mannose and galactose <1%). These results suggest deepsea prokaryotes under high HP preferentially remove hexoses (e.g. glucose, mannose and galactose) from HMW-DOC similar to results of previous studies carried out in Atlantic and Pacific Oceans [START_REF] Goldberg | Systematic removal of neutral sugars within dissolved organic matter across ocean basins[END_REF][START_REF] Kaiser | Biochemical composition and size distribution of organic matter at the Pacific and Atlantic time-series stations[END_REF].

Overall, these results further indicate that neutral sugars can be used as tracers of deep-sea semilabile DOC and that changes in DOC composition are related to the bioavailability of DOC.

PROKARYOTIC DEGRADATION OF DOC IN STRATIFIED PERIOD

CONDITION

In the NW Mediterranean Sea, summertime stratification isolates the upper mixed layer from deeper water masses preventing down-mixing of DOC [START_REF] Copin-Montégut | Vertical distribution and temporal variation of dissolved organic carbon in the North-Western Mediterranean Sea[END_REF][START_REF] Santinelli | Influence of stratification on marine dissolved organic carbon (DOC) dynamics: The Mediterranean Sea case[END_REF][START_REF] Santinelli | DOC dynamics in the meso and bathypelagic layers of the Mediterranean Sea[END_REF]. Thus, the prokaryotic communities sampled at 2000 m-depth in summertime are well adapted to the deep-sea conditions, due to the stratification (Tamburini et al., 2013a) while surrounded with old and recalcitrant DOC [START_REF] Santinelli | DOC dynamics in the meso and bathypelagic layers of the Mediterranean Sea[END_REF][START_REF] Santinelli | DOC in the Mediterranean Sea[END_REF]. Gravitational sinking of particles carrying HMW-DOC in its plume can locally enhance and provide HMW-DOC to free-living deep-sea prokaryotes [START_REF] Fang | The POM-DOM piezophilic microorganism continuum (PDPMC)-The role of piezophilic microorganisms in the global ocean carbon cycle[END_REF][START_REF] Follett | Hidden cycle of dissolved organic carbon in the deep ocean[END_REF][START_REF] Kiørboe | Marine snow, organic solute plumes, and optimal chemosensory behavior of bacteria[END_REF][START_REF] Long | Antagonistic Interactions among Marine Pelagic Bacteria[END_REF][START_REF] Tamburini | Role of deep-sea bacteria in organic matter mineralization and adaptation to hydrostatic pressure conditions in the NW Mediterranean Sea[END_REF].

Then, results presented in [START_REF] Carlson | Annual flux of dissolved organic carbon from the euphotic zone in the northwestern Sargasso Sea[END_REF], show that stratification sequesters DOC in deep water, leading to an increase of remineralization by deep prokaryotes, that is consistent with our results in Strat_HP. HMW-DOC issue from surface water is more bioreactive than HMW-DOC already present in deep ocean [START_REF] Carlson | Interactions among dissolved organic carbon, microbial processes, and community structure in the mesopelagic zone of the northwestern Sargasso Sea[END_REF]. Our results showed that autochthonous deep-sea prokaryotes, during stratified period conditions, are able to use HMW-DOC, at a higher rate (1.7-fold) under in situ high pressure conditions than if decompressed and incubated at atmospheric pressure conditions. These results agree with previous investigations of [START_REF] Boutrif | Assimilation of marine extracellular polymeric substances by deep-sea prokaryotes in the NW Mediterranean Sea[END_REF] showing higher degradation rates of radiolabeled marine extracellular polymeric substances by deep-sea prokaryotes under HP compared to DEC incubations during stratified period conditions. Overall, the above results are in agreement with other investigations that demonstrated that deep-sea adapted prokaryotes have specific enzymes able to degrade complex organic matter substrates [START_REF] Delong | Genomic perspectives in microbial oceanography[END_REF][START_REF] Campanaro | Laterally transferred elements and high pressure adaptation in Photobacterium profundum strains[END_REF] and with those of [START_REF] Bergauer | Organic matter processing by microbial communities throughout the Atlantic water column as revealed by metaproteomics[END_REF] reporting an increase of protein transporter of the microbial community with depth to adapt to the change of OM quality. del [START_REF] Giorgio | Bacterial growth efficiency in natural aquatic systems[END_REF] , if the supply of organic carbon is scarce, then most of the substrate will be catabolized and used primarily for maintenance energy requirements rather than for growth. On the other hand, the DEC community also sampled at 2000m depth but decompressed may need less organic carbon to grow. Recent results by [START_REF] Arrieta | Ocean chemistry: Dilution limits dissolved organic carbon utilization in the deep ocean[END_REF], have incubated at atmospheric pressure conditions, deep seawater with natural community from the Pacific and Atlantic Ocean, have shown that even a low concentration of labile DOC (even of only 2-fold of the natural DOC) could sustain growth after a 10-day incubation. Closed incubation approaches as well as changes in pressure lead to changes in prokaryotic community composition [START_REF] Edgcomb | Comparison of Niskin vs. in situ approaches for analysis of gene expression in deep Mediterranean Sea water samples[END_REF][START_REF] Garel | Pressure-Retaining Sampler and High-Pressure Systems to Study Deep-Sea Microbes Under in situ Conditions[END_REF][START_REF] Ionescu | A new tool for long-term studies of POM-bacteria interactions: overcoming the century-old Bottle Effect[END_REF]. The prokaryotic community, able to withstand changes in pressure, showed greater catabolism requirements in growing with the available DOC (Qm DEC = 8.94 versus Qm HP = 11.32). However, the HMW-DOC degradation is more efficient under HP than DEC incubations since the DOCrec is significantly higher in DEC incubations (median DOCrec = 109.34 µM) than in HP incubations (median DOCrec = 63.94 µM) on the timescales of the incubations (Figure 3 and Table 2). (Tamburini et al., 2013b), surface seawater includes a larger proportion of surface prokaryotic cells, which are not adapted to in situ HP conditions [START_REF] Egan | An investigation of the physiology and potential role of components of the deep ocean bacterial community (of the NE Atlantic) by enrichments carried out under minimal environmental change[END_REF]Tamburini et al., 2013a). Another study of [START_REF] Turley | The effect of pressure on leucine and thymidine incorporation by freeliving bacteria and by bacteria attached to sinking oceanic particles[END_REF] has shown that prokaryotes from surface water are affected by increasing hydrostatic pressure, i.e decrease of protein synthesis, during sinking of particles, thus preserving particles to reach the seabed. A study of [START_REF] Grossart | Hydrostatic pressure affects physiology and community structure of marine bacteria during settling to 4000 m: an experimental approach[END_REF], using shallow-water bacterial strains submitted to increasing pressure, indicates that strains from the surface respond individually to pressure exposure and appear to rapidly reduce cell division. In the same vein, our series of experiments increasing hydrostatic pressure of surface prokaryotic communities lead in generally to a decrease in the activities of surface prokaryotic communities with increasing pressure [START_REF] Tamburini | Pressure effects on surface Mediterranean prokaryotes and biogenic silica dissolution during a diatom sinking experiment[END_REF](Tamburini et al., , 2009b;;[START_REF] Riou | Biodegradation of Emiliania huxleyi aggregates by a natural Mediterranean prokaryotic community under increasing hydrostatic pressure[END_REF]. As a consequence, on the timescales of the incubations, DOC degradation rates in the HP incubations (median k = 0.006 d -1 ) are significantly lower than in the DEC incubations (median k = 0.49 d -1 ) during the deep-water convection event (Kruskal-20 Wallis and Wilcoxon Signed Rank tests, p <0 .05) (Figure 3 and Table 2). Due to low degradation rate during the deep-water convection under HP incubation (Figure 2C and Figure 3B, Conv_HP), the highest variability is found, by the Droop model, on the estimation of DOCrec (Figure 3D, Conv_HP).

PROKARYOTIC

Similarly, growth rates are lower when incubated at HP conditions (median µmax = 0.55 d -1 ) than when decompressed and incubated at atmospheric pressure conditions (median µmax = 0.76 d -1 ) (Figure 3 and Table 2, Kruskal-Wallis and Wilcoxon Signed Rank tests, p < 0.05).

Moreover, in the HP incubations, the minimum cell-quota estimation is relatively high with the highest variability (Qm HP = 9.05 ± 1.34, mean ± s.d., see Table 2), slightly lower that DEC conditions (Qm DEC = 10.42 ± 0.18). In the HP incubations of our experiments during deepsea convection event, degradation rates appear to be inhibited or not visible. The production and removal of recalcitrant DOC can be hypothesized to occur, as shown in [START_REF] Romera-Castillo | Net Additions of Recalcitrant Dissolved Organic Carbon in the Deep Atlantic Ocean[END_REF], sustaining the growth rates estimated in the HP incubations. In contrast, after decompression (DEC incubations), surface prokaryotes carried out in the deep-sea water and incubated at atmospheric conditions are able to partially degrade the DOC available. However, the DOCrec at the end of incubation during the deep-water convection event remained relatively high in DEC incubations. In their experiments conducted with surface and mesopelagic prokaryotic consortium, [START_REF] Carlson | Interactions among dissolved organic carbon, microbial processes, and community structure in the mesopelagic zone of the northwestern Sargasso Sea[END_REF] found high DOC degradation and biomass yields in surface waters inoculated with upper mesopelagic consortium than with surface ones. They suggested that mesopelagic prokaryotes adapted to use recalcitrant DOC are in competition for inorganic nutrients with surface prokaryotes that are adapted to use labile DOM, they may grow at slower rates thereby limiting semi-labile DOC remineralization.

DOC DEGRADATION IN STRATIFIED VERSUS DEEP-WATER CONVECTION PERIOD CONDITIONS

Changes of the in situ hydrostatic pressure conditions during sample retrieval and incubation impact the degradation of HMW-DOC due to the change of prokaryotic community [START_REF] Egan | An investigation of the physiology and potential role of components of the deep ocean bacterial community (of the NE Atlantic) by enrichments carried out under minimal environmental change[END_REF]Tamburini et al., 2013a). Recent studies have demonstrated that decompression of deep seawater samples very likely involves a shift of the prokaryotic community [START_REF] Edgcomb | Comparison of Niskin vs. in situ approaches for analysis of gene expression in deep Mediterranean Sea water samples[END_REF][START_REF] Garel | Pressure-Retaining Sampler and High-Pressure Systems to Study Deep-Sea Microbes Under in situ Conditions[END_REF]. Even if the shift of the prokaryotic community is true for the both incubations (HP and DEC) due to the 2-weeks incubation time [START_REF] Lee | Species composition shift of confined bacterioplankton studies at the level of community DNA[END_REF][START_REF] Zobell | Observations on the multiplication of bacteria in different volumes of stored sea water and the influence of oxygen tension and solid surfaces[END_REF], to make statements about DOC degradation in the deep ocean, HP incubation conditions are more realistic. [START_REF] Follett | Hidden cycle of dissolved organic carbon in the deep ocean[END_REF] have shown that in the deep ocean, 10 -30% of the deep DOC reservoir is semi-labile and supported by a flux of ~1 Gt C year -1 carbon introduced by sinking particles.

During stratified period conditions, the deep seawaters are sequestered for up to century, and carbon is introduced principally by gravitational sinking of particles [START_REF] Le Moigne | Pathways of Organic Carbon Downward Transport by the Oceanic Biological Carbon Pump[END_REF][START_REF] Siegel | Prediction of the Export and Fate of Global Ocean Net Primary Production: The EXPORTS Science Plan[END_REF]. Moreover, autochtonous prokaryotes adapted to in situ high pressure conditions [START_REF] Boutrif | Assimilation of marine extracellular polymeric substances by deep-sea prokaryotes in the NW Mediterranean Sea[END_REF][START_REF] Delong | Genomic perspectives in microbial oceanography[END_REF]Tamburini et al., 2013a;[START_REF] Campanaro | Laterally transferred elements and high pressure adaptation in Photobacterium profundum strains[END_REF] seem able to degrade up to 46.6% of the added DOC (according to Figure 2A; Table 2). Finally, it is more and more obvious that some deep prokaryotes exploit environments where the most abundant energy resources are sinking organic particles or recalcitrant dissolved organic matter (DOM). As an example, SAR202 group III dominate bathypelagic waters presumably indicating that molecules, such as recalcitrant organic compounds, susceptible to oxidation by FMNOs (flavin-dependent monooxygenases) become one of the few remaining harvestable DOM resources at these depths [START_REF] Saw | Pangenomics Analysis Reveals Diversification of Enzyme Families and Niche Specialization in Globally Abundant SAR202 Bacteria[END_REF]. However, during the deep convection event periods, surface prokaryotes are carried deeper into the water column, mixing with the pressure adapted community. The result is a lower degradation observed under in situ HP incubations, (Figure 2C; Table 2). In this experiment, we hypothesize that adapted deep-sea bacteria grew by using mainly the surface semi-labile DOC transported by deep water formation. Semi-labile DOC can stay in deep waters for several weeks in agreement with [START_REF] Santinelli | DOC dynamics in the meso and bathypelagic layers of the Mediterranean Sea[END_REF]. These authors estimated DOC removal rates to be 14.4 µM C year -1 , or 0.04 µM C d -1 in deep waters recently ventilated (and thus characterized by high DOC concentrations). This removal rate is in agreement with our results, the estimate of the degradation rate in the HP incubations during

Conv. experiments, being apparently very low (0.01 ± 0.03 d -1 ), the production and removal of recalcitrant DOC can be hypothesized to occur as discussed previously.

CONCLUSION AND PERSPECTIVES

Our results demonstrate that the degradation of DOC under stratified and deep convective mixing conditions depends on the origin and the history of the prokaryotic communities, which were controlled by the origin of the water masses in the NW Mediterranean Sea. Depending on the hydrological conditions, the proportion of allochthonous and autochthonous prokaryotes in deep-sea microflora can vary, with surface bacteria increasing in deep-sea waters during deep-sea convection [START_REF] Luna | Dense water plumes modulate richness and productivity of deep sea microbes[END_REF][START_REF] Severin | Impact of an intense water column mixing (0-1500 m) on prokaryotic diversity and activities during an open-ocean convection event in the NW Mediterranean Sea[END_REF].

Degradation of HMW-DOC is less effective during deep-sea convection than during stratified period conditions, where adapted deep-sea prokaryotes probably have a specific metabolism to degrade HMW-DOM. This study must be considered in the context of climate change, as the stratification of the surface layers of the Mediterranean Sea is expected to intensify and thus limit the vertical transfer of both dissolved oxygen and DOC by winter convection of surface waters [START_REF] Adloff | Mediterranean Sea response to climate change in an ensemble of twenty first century scenarios[END_REF][START_REF] Powley | Circulation and oxygen cycling in the Mediterranean Sea: Sensitivity to future climate change[END_REF].

The interactions between the DOC and the deep-sea prokaryotic communities are still Genomic and transcriptomic analysis will be required in further studies to highlight the succession of different prokaryotic communities and metabolic pathways involved in degradation of the different pool of dissolved organic matter.

Figure 1 .

 1 Figure 1. Timeline of the HMW-DOC incubation experiment. Before use, high-pressure bottles (HPBs) were thoroughly cleaned as described in Garel et al. (2019). Two experiments were done during stratified (Strat.) and deep-water convection period (Conv.), see text for details. [DOC]initial (μM) is the DOC concentration in the deep-sea water sampled at 2000 m-depth before adding HMW-DOM.

  (µM C. µmol cells -1 ). The growth rate of prokaryotes, µ is the product of the maximum growth rate * !"# by an increasing function of the intracellular quota .. The parameter . ! is defined as a threshold of intracellular quota, under which growth of prokaryotes is inhibited. The dynamics of concentration of substrate DOC depends on the cell biomass X that degrades substrate with degradation rate k. Only a fraction of DOM is labile and can be degraded by the microbial community present in the closed system, thus we denote by DOCrec the concentration of the recalcitrant fraction of carbon substrate. Using the sampled data (7 ' , &9: ' ), ; = 1, ⋯ , = in each experimental condition, parameters * !"# , k, Qm and DOCrec were estimated by non-linear regression (Nelder-Mead simplex method, Seber and Wild, 2003) when minimizing the sum of squared error (SSE) which measures a distance from the data to the model as follows:

  THROUGHOUT THE EXPERIMENT At 2000m-depth, DOC concentration significantly increased from 42 µM in December 2009, prior to a deep-water convection period, to 63 µM in March and 72 µM in May 2010 when the new deep water mass occupied the ANTARES site, concurrently with higher oxygen concentration in the bottom waters between March and mid-June 2010 (see for details Tamburini et al. 2013b and Durrieu de Madron et al. 2017). The in situ DOC concentrations for Strat. and Conv. experiments were 42 and 72 µM, respectively; after HMW-DOC addition, DOC initial concentrations in HPBs reached 96 ± 16 and 182 ± 46 µM for Strat. and Conv.experiments, respectively. In order to apply the Droop model to compare the kinetics of DOC degradation between each condition, we normalized the raw data of DOC concentrations (Table1) to a fixed value of 120 µM, corresponding to the expected theoretical final concentration of DOC (Figure2). Dissolved combined neutral sugars (DCNS) concentrations after HMW-DOC addition were 9 -11 µMC for Strat. and Conv. experiments under HP conditions, respectively whereas the corresponding values for the DEC experiment were 5 -12 µMC. These results indicate that sugars account about 5 -9% of DOC which is in agreement

Figure 2 .

 2 Figure 2. Changes in DOC concentrations (A, C), cell biomass concentrations (B, D) in µMC over time (in days) during stratified period (Strat.) and deep-water mass convection period (Conv.). Blue and black dots are observations respectively for HP and DEC incubations. Blue and black lines are predicted data by model and blue and grey variability bands are 95% confident intervals, respectively for HP and DEC incubations.

  Figure 2

  compares the kinetics of DOC degradation between observed data (black and blue circles for DEC and HP conditions, respectively) and theorical data (black and blue curves for DEC and HP conditions, respectively) during the stratified period condition. The variability bands around the curves represent 95% confidence intervals showing the statistical difference over time (or not if the variability bands intersect) between incubations. The same method has been used for the cell biomass concentration (Figure2B).

Figure 3 .

 3 Figure 3. Bootstrapped (with 500 simulations) distribution of parameters estimated by Droop Model during stratified period (Strat.) and deep-water mass convection period (Conv.) conditions maintained under in situ high pressure conditions without decompression of the sample (HP) and decompressed plus incubated at atmospheric pressure conditions (DEC). A) Growth rate (µmax) for both conditions in d-1; B) Degradation constant (k) in d-1; C) Minimum cell-quota (Qm) (a ratio between intracellular concentration of organic carbon and cellular biomass, dimensionless); and D) Concentration of recalcitrant (DOCrec) in µMC on the timescales of the incubations. The horizontal lines are respectively, third quartiles, median and first quartiles. The whiskers correspond to the 95% of the confidence interval.

  Figure3

Figure 3

 3 Figure 3 summarizes the distribution of parameters estimated by the cell-quota model after 500 simulations (see Materials and Methods section) and to compare incubation (HP versus DEC) and hydrological conditions (Strat. versus Conv.). The Kruskal-Wallis and Pairwise Wilcoxon Rank Sum tests (R Core Team, 2017) performed on the box-and-whisker plots attests that each parameter estimated is significantly different (p < 0.05) between each incubation (HP versus DEC) in stratified period condition. Under HP conditions Qm (median Qm HP = 11.32) was significantly higher than DEC conditions (median Qm DEC = 8.94). These results indicate that under HP conditions, deep-sea prokaryotes have elevated carbon requirements to grow, or in other words expends more energy for their growth. According to

  unclear, and future experiments should include measurements of oxygen consumption throughout the incubation and the dissolved inorganic matter (DIC) concentration, key indicators of the microbial remineralization. Furthermore, a better understanding of the metabolic abilities of deep-sea prokaryotes, at a cellular scale, and under in situ conditions of pressure and temperature, are needed. Since dense water formation occurs in other regions worldwide, a steering of deep pelagic ecosystem activity similar to that observed in the NW Mediterranean Sea should occur there too.

Table 1 .

 1 Raw data of DOC concentrations before normalization, DAPI-counts, biovolume and sugars relative abundance during incubation experiments during stratified period (Strat.) and deep-water mass convection period (Conv.) conditions. The contribution of the dissolved combined neutral sugars (DCNS) to the dissolved organic carbon (DCNS/DOC) pool is also given. Abbreviations: Fuc.: Fucose, Rha.: Rhamnose.: Ara.: Arabinose.: GlcN.: Glucosamine, Gal.: Galactose, Glc.: Glucose, Man.: Mannose, Xyl.: Xylose. HP: samples maintained under in situ high pressure condition without decompression; DEC: sampled decompressed and incubated at atmospheric pressure (DEC).

	Fuc.

DEGRADATION OF DOC IN DEEP-WATER CONVECTION PERIOD CONDITION During

  deep-water convection event, the story is completely different. Under that condition, bioavailable surface DOC can be carried to the deep microbial community with the mixing of surface and deep Mediterranean seawaters. Tamburini et al. (2013b) reported that the concentration of DOC at 2000m increases from ~42 µM under stratified conditions, to ~72 µM under deep-water period condition. These values are in agreement with those reported by Santinelli et al. (2010) in the Gulf of Lions in May 2005, that show a marked increase in DOC

	by deep convection event. During deep-water convection events, deep seawater is amended
	with ~30 µM labile or semi-labile DOC originating from the surface. Moreover, in this specific
	case, the prokaryotic communities were composed of both prokaryotes from surface water
	mixed with prokaryotes from deep waters

Acknowledgments

This research is endorsed by the national French program MERMEX and funded by the National Research Agency under the grant POTES [grant number ANR ANR-05-BLAN-0161-01, 2007] and the French LEFE-Cyber program [DORADE project]. Part of the equipment used in this work was funded by European Regional Development Fund (ERDF). The project associated to this publication has received funding from European ERDF Fund under project 1166-39417. This work is a contribution to the Mediterranean Institute of Oceanography "Pompe Biologique" (BioPump Group). Authors have benefited of the support of the SOERE-MOOSE and the SAM-MIO platform with special thanks for Nagib Bhairy for organizing cruise logistics. Authors thank the captain and the crew of Tethys II ship for excellent service at sea, M. Patrisi for help on board during April 2010 sampling; F. Van Wambeke, D. Kirchman and H.-P. Grossart for valuable discussions; C. Carlson and the two anonymous reviewers for their comments.


Nader Zirak

Mohammadali Shirinbayan

Smaine Kouidri

Erfan Salahinejad

Abbas Tcharkhtchi

Farid Bakir

Navideh Abbasnezhad
email: navideh.abbasnezhad@ensam.eu

| Nader Zirak

| Erfan Salahinejad

| Farid Bakir

Controlled release from polyurethane films: Drug release mechanisms

come

as for low aqueous soluble drugs. In this regard, chemical and physical properties of the polymer such as glass transition temperature, permeability, viscosity, degradability, and concentration of polymers are the influential criteria that control the drug release from the polymer carrier. 3 Thus, all the characteristics referring to the polymer and drug, take account in the drug release profile. 4 Drug release refers to the definition where the drug solutes/ nonsolutes migrate from the initial position of the carrier to the outer side of the carrier to contact with the medium and consequently release in the medium. 4 Studies focused on achieving the systems with reducing toxicity, side effects, and enhancing the effectiveness of treatment-controlled release. Controlled drug release is affected by some parameters to improve the therapy's efficacy. These include, for example, the released time rate, global time, and position accuracy. [START_REF] Nezami | Biomechanics of Coronary Atherosclerotic Plaque[END_REF] DDS in the form of the polymeric matrix have drawn interest in the area of therapeutic. Hydrophilic polymers are in this choice because they are generated with pore spaces which facilitate the release of the drug, especially as regards for low water soluble drugs. The time that the polymer is contacted with the aqueous medium diverse phenomena can occur like, degradation, dissolution, swelling, etc.. [START_REF] Bode | [END_REF] This can result in different drug release profiles by the mechanisms of diffusion, convection, burst, ion exchange, osmotic pressure, etc. Depending on the necessities of the therapy, each of these mechanisms can take importance to the others. 7 The effects of the presence of each mechanism can differ depending on the polymer properties. As an example, the water swollen and nonswollen polymers have been compared. 8,9 It was revealed that the diffusion of the drug in the water swollen polymer was increased compared with the nonswollen polymer due to the creation of the free volume fraction. However, it is not always the same, as another study indicated that swelling of the nondegradable polymer decreases the release rate. This is for the reason that, it increases the path of the drug in the matrix for attaining to the release medium. 8,9 Polyurethane has always been used in biomedical applications due to the good biocompatibility and mechanical properties. 4,[10][11][START_REF] Basu | 8-Polyurethanes for controlled drug delivery[END_REF][START_REF] Lowinger | [END_REF][14][15] Polyurethane due to show the favorable ability to drug release profiles in various modes such as microparticles, films, and also as a coating on implants and stents has been the focus of many studies. In some studies, it is noted that the release from the nondegradable polymeric system is controlled by diffusion. In this case, the parameters which are taken importance are the thickness and hydrophilicity of the polymeric matrix; on the other hand, the solubility of the drug charged in the polymer also takes value. However, in a study by Huynh et al. 16 they have studied the release behavior of the chlorhexidine diacetate from the nondegradable PU and found that the release was followed by zero order mechanism. In the case of diffusion-controlled mechanisms, the reservoir and matrix type of the DDS is in the main categories. Indeed, matrix type is more favorable as it accepts not the risk of depleting the drug by the tearing of the cover layer. Furthermore, it utilizes a straightforward process of fabrication. [17][18][19] The other parameters which are important in the release are related to the properties of the drug. One of the types of the drugs used in the case of cardiovascular stenting is the antiinflammatory drugs. Diclofenac is one of the most prescribed nonsteroidal antiinflammatory drugs which inhibits the pain and reduces the inflammation. [20][21][22] Where different indicators such as the solubility, particle size, hydrophilicity of drug, etc., will affect the release profile. [23][24][25] The drug particles in the matrix can have two kinds: they can dissolve in the polymer solvent therefore covalent bonds with the polymer are made or they can be dispersed in the matrix in the particle shape. The first type of degradation of the polymer affects the drug release data. However, for the second case degradation rate of the polymer, drug loading, solute size, swelling, and solubility influence the release rate. 9 Consequently, according to the polymer and the drug is chosen, various mechanisms of release can contribute to the release of the drug from the DDS. These mechanisms can continue the dissolution of the drug and DDS, diffusion of the liquid into the DDS and diffusion of the drug from DDS to the release medium, swelling, degradation, erosion of the DDS, osmotic pressure, etc.. 26 Depending on the portion of participation, each of these mechanisms can represent the dominated mechanism of release or can be negligible. Also, depending on the rate of each mechanism occurring during the time of the release, it can be rate controlling on the whole period of the release. 27 In this study, the results related to the experiments conducted with charged polyurethane (PU) have been demonstrated. The experiments have been performed with varying two parameters: (a) flow rates of 0, 7.5, and 23.5 ml/s where there is a lack of study on it and, (b) drug percentages of 10, 20, and 30 wt%. Then the steps related to the whole release were identified and the mechanisms have been analyzed. Subsequently, the contribution of the identified mechanisms has been calculated. The flow rate and drug ratio caused a significant effect on the mechanism of drug release from the carrier.

| EXPERIMENTAL PROCEDURE

| Materials

| Polyurethane

In this analysis the substance used is nondegradable polyurethane (PU) which is the result of the synthesis of the hardener (isocyanate type 4,4-diphenylmethylene diisocyanate [MDI]) with resin Gyrothane 639 which is composed of polyol with I OH value of 336 (mg KOH/g), dye, and catalyst. The substance prepared from the hardener-resin combination in a proportion of 2:5 according to the datasheet, casted in a mold, and heated at 50 C for about 30 min. The related items were supplied from the RAIGI Company.

| Diclofenac

Diclofenac as a nonsteroidal antiinflammatory drug is the agent loaded in PU samples for drug release tests. 14 It was purchased from Genevrier Laboratory in granular shape with a density of approximately 450.7 mg/ml. The solubility of the drug at a temperature of 37 C in water is about 5.554 g/L. The particle size was determined by SEM images: around 40 μm ≤ particle size ≤ 160 μm.

| Preparation of carriers and drug loading

For drug release experiments, polymer films with the dimensions of 30 × 5 × 2 mm 3 were prepared. This dimension is considered an enlarged dimension of the strut of a stent. A process of molding and heating in an oven at the temperature of the 50 C for about 30 min was performed. For the samples with the active substance in the initial preparation of the mixture, a certain dosage of the drug [the mass ratio of drug/(drug + polymer): 10, 20, and 30 wt%] was added to the resin. After homogeneously dispersing the drug in the polyol the hardener was added to the mix. Finally, the prepared mix was poured in the mold and then it was put in the oven. Drug particles were maintained in the form of the granules after mixing. Figure 1 shows the schematic of this procedure. Scanning electronic microscope "HITACHI 4800 SEM" has been used to analyze the morphology of the microstructure of the specimen throughout the study.

| Test bench components

The test facility used in this experiment is represented in Figure 2. This equipment was designed to perform the test from static flow to the different flow rates by the aid of a pump and inverter. Valves are for adjusting the flow rate. A tank with the capacity of 10 L is employed, although to avoid the risk of saturation of liquid, each 2 days of test it was refreshed with new one.

| EXPERIMENTAL RESULTS AND DISCUSSIONS

| Drug release procedure and associated measurements

Measurement methods were performed according to the following method. In the first step, the samples were dried in the oven at 50 C for 1 hr to remove any moisture. The samples were weighed immediately after cooling in the desiccator (m 0 ). The second step is to put the samples in the in-vitro test. Further, the samples are collected from the test after a specified period for each test, to begin the following stage. The third step comprises cleaning the surface of the taken samples with a dry cloth to remove any water present. These samples then weighed (m 1 ). After that, to remove all the water in the film, the samples were transferred to an oven at 50 C, after ensuring that all the water absorbed by the film was removed (after the sample weight was stabilized), and the film was weighed (m 2 ). The equations for measuring the water absorption and drug release are listed below:

Water absorption % ð Þ= m 1 -m 2 m 0 × 100 ð1Þ
Drug release % ð Þ= m 0 -m 2 initial mass of drug × 100 ð2Þ
where, m 0 represents the sample mass at the initial state; m 1 is the mass after wiping; and m 2 is the mass after drying in the oven.

| Water absorption at diverse flow rates and drug percentages

Figure 3(a) shows the water absorption of the PU loaded with diverse drug percentages of 0, 10, 20, and 30% at the static state. It is noted that the water penetrates to the PU.0.Q:0 (PU with zero percentage of the drug at the flow rate of zero ml/s) up to 5%, where it is augmented to the 70% for the samples with 30% of the drug after 10 days of immersion.

Therefore, the presence of the hydrophilic drug carries out a significant role in water absorption. It is remarkable that the values of the percentage of water absorption are affected as well by the variation of the density of water and diclofenac which are 997 and 450.7 mg/L, respectively.

Figure 3(b) shows the results of the water absorption for three various percentages of the drug at the flow rate of 7.5 ml/s; the concept is repeating once more for the effect of the drug percentage on water absorption in the flow condition. This figure indicates that the water absorption is increased by increasing the drug percentage.

By comparing the three curves of the Figure 3(a)-(c), one can note that the equilibrium water absorption for the samples with the same percentage of drug (e.g., 10%) at different flow rates gives rather the same value (30%). Therefore, the equilibration value of water absorption is independent of the flow rate, and it firmly depends on the composition of the sample (the percentage of the drug loaded). Further, it will affect the release behavior, whereas all the mechanisms mentioned attributing to the release are highly related to the water/liquid absorption. In the case of the more drug percentage due to the more quantity and larger diameter of the pores, F I G U R E 2 Equipment elements for tests at different flow rates water absorption increases where the free volume in the matrix can handle more solvent molecules. This process goes on until reaching an equilibrium value. Applying the equation of Korsemeyer-Peppas for the water absorption results gives the n value lower than 0.5. Therefore, it indicates that water absorption and hence swelling in all the experimental tests are controlled by the diffusion mechanism (Fickian diffusion). [28][29][30] Results are given in Figure 4(a),(b), depict the drug release at 10, 20, and 30% of initial dosage under static and dynamic conditions, respectively. It is clear that the release time for the samples with the higher drug dosage has decreased. On the other hand, by comparing Figure 4(a)-(c) one can note that with increasing flow rate, drug release is occurring at a higher rate. However, these results need more analysis, which is discussed in Section 5.

| Cumulative drug release at diverse flow rates and drug percentages

| Understanding of drug release mechanisms: Strategy to investigate

Mathematical models have always been one of the most effective ways to improve the design of different carriers for the DDS. In addition, it has always been important to determine the mechanisms of drug release and release kinetics for various systems. [31][32][33][34] For this purpose, in this section, we will investigate the steps of drug release from the carrier as well as the precise mechanisms of drug release from the carrier using fitting experimental data with different physical models. 7,10,14,35,[START_REF] Moradmand | 2017 5th Int. Conf. Control Instrum. Autom. (ICCIA)[END_REF] Additionally, all the regressions were performed with 95% confidence intervals. In order to investigate the mechanisms, first finding the steps of the release profile is considered. The experimental data was investigated using Higuchi model, which has been used extensively in several studies to evaluate the stages of drug release from carries. 27,[START_REF] Unagolla | [END_REF][38][39] The Higuchi equation is as follows 40 :

Q = ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi D 2C -C s ð Þ C s t p ð3Þ
where, Q is the amount of drug released at time t per unit area, C is the amount of primary drug in the matrix per unit volume, C s is the drug solubility in the matrix media, and D is the diffusion coefficient of the drug molecules in the carrier. In general, the simplified Higuchi model is defined as below 40 :

M t M ∞ = K H ffiffi t p ð4Þ
where, M t and M ∞ , are drug released at t and infinitive time, respectively, and K H is a kinetic constant.

After identifying the steps, Korsmeyer-Peppas was applied to each curve in order to detect the mechanisms whether it is diffusion or degradation and swelling controlled. For this purpose, the Peppas model was first evaluated 41 :

M t M ∞ = kt n ð5Þ
where, k is a constant and the exponent n determines the mechanism of drug release from the carrier.

As per to the coefficient of categorization for a thin film, when n < 0.5, the semi-Fickian mechanism is presented while the n = 0.5 the drug release mechanism can be controlled by Fickian diffusion. Whereas 0.5 < n < 1 the mechanism can be followed by anomalous transport (diffusion and degradation: non-Fickian). Once n = 1 the release can be controlled by degradation. To further investigate the mechanism of drug release from carriers; Zero-order, First-order, and Peppas-Sahlin models were examined. Zero-order model is utilized where drug release is controlled by matrix degradation 42 :

M t M ∞ = kt ð6Þ
Here, model order is the order of release rate and not the order of cumulative release.

The first-order release in the case where drug release experiences an exponential behavior, also, the dissolution and geometry of the matrix are considered in this model 42 :

M t M ∞ = 1-exp -kt ð Þ ð7Þ
In Peppas-Sahlin equation, drug release is controlled by the diffusion and relaxation mechanism 43 :

M t M ∞ = k 1 t m + k 2 t 2m ð8Þ
where, k 1 and k 2 are kinetic constants and m is the diffusion exponent.

Moreover, Peppas-Sahlin model is used to calculate the percentage of the contribution of the mechanism of the diffusion during the release. In Peppas-Sahlin equation, by considering the following relation 43 :

F = 1 1 + k 2 k 1 t m ð9Þ
where, k 1 and k 2 are constants obtained from Equation (6), the contribution of the diffusion mechanism at different times can be investigated.

Figure 5 shows the algorithm for following this strategy.

| Identification of drug release steps: Higuchi equation

The experimental results have been analyzed by Higuchi equation (Figure 6 and Table 1). Fitting the experimental data at the static and dynamic conditions with different dosages by Higuchi model, presented two-step drug release from the PU films.

The regression results of the Higuchi model for each step are presented in Table 1. The correlation coefficients for all the samples were high and near to 0.99. In general, comparing the values of the K H from Table 1, show that the kinetic constants in the first and second steps are increased by flow rate.

From these curves, the below conclusion can be drawn:

• The number of steps seems to be independent of the considered parameters. • Second step gives another kinetic of the release more than the first step. Therefore, it notes the presence of the other mechanism(s) or it can be the same mechanism as first step but with different kinetics due to some reasons. • The release kinetics of the first step is independent of different drug percentages for different flow rates. • One can define that the threshold time, which is the time where the kinetic changes, are different for dynamic flow rates; however, it is the same for the static state shown in Figure 7(a). • In static state, the rate of drug release in the second step increases by increasing the drug dosage. However, it is constant for dynamic flow rates (Figure 7(b)). On the other hand, the rate of release is more influenced by the drug dosage in the static state. • For dynamic flow rates, it is notable that by increasing the drug percentage the threshold time is increased (Figure 7(a)). The later confirms that when the drug content is increased at dynamic state more particles can participate in the release at first step. This means there is a delay time in kinetic reduction by increasing the drug dosage perhaps due to the presence of flow or agitation.

| Investigation of the drug release mechanism

In the previous section, dual-stage drug release from films was observed. In this section, the mechanisms of drug release under static and dynamic conditions were investigated.

| Static state

In this section, the mechanism of drug release at the different dosages of Diclofenac from PU.10.Q:0, PU.20.Q:0, and PU.30.Q:0 is studied. To investigate and intuition the mechanisms of drug release from carriers, Equations ( 5)- (7) were fitted. The fittings were applied to each step; the results of these models are presented in Table 2. Figure 8 shows the curves related to the fitting of the Korsemeyer-Peppas model.

The constants related to the fitting of Equations ( 5)-( 7) related to Korsemeyer-Peppas, Zero-order, and First-order models, respectively, are presented in Table 2. The unfavorable fit of Equations ( 6) and (7) indicates the ignorable of polymer degradation and nonintegration of the dissolution, respectively. The regression results of the Korsemeyer-Peppas model presented in Table 2 show the correlation coefficients for all three samples were higher than 0.98. The n values are less than 0.5. It is noteworthy that, the amount of n value less than 0.5 indicates the pseudo-Fickian mechanism 44,45 for drug release from the loaded PU. Therefore, in the case of the static state at two steps for three different percentages diffusion is the involved mechanism but it is not the only mechanism intervene.

| Dynamic state

For identifying the mechanisms in dynamic state, the flow rate of 7.5 ml/s was chosen. The results of regression by Equations ( 5)- (7) on the data are presented in Table 3, and as per the obtained value, it can be stated that the mechanism of drug release represents pseudo-diffusion. Like as the static one here also the curves do not show good fit to the Equations ( 6) and ( 7); therefore, it indicates that the release is unintegrated into the dissolution or degradation of the matrix. The semi-Fickian mechanism is controlling the drug release at all two steps. However, for considering the degradation in the test situation degradation test were conducted in the continuous flow state where, the three pure polyurethane samples were immersed in the aquatic environment for 28 days. The results demonstrated no mass loss during this test. As the mass loss is an indicator of the degradation, the material is facing the first type of degradation where it experiences a decrease in mechanical properties but no weight loss during the test period. 40,41 Therefore, referring to the experimental degradation test of polyurethane samples, no degradation was observed. Figure 9 shows the curves related to the fitting of Korsemeyer-Peppas model applied on these results.

| Contribution of the diffusion mechanism

| Effect of flow rates

After confirming the diffusion transport of the drug from the carriers, the contribution of diffusion mechanisms for F I G U R E 5 Algorithm for defining the mechanisms contributed during the release from a drug loaded carrier the samples with 10% of drug at the flow rates of 0, 7.5, and 23.5 ml/s by Equations ( 8) and ( 9) was calculated. Figure 10 shows the contribution of the diffusion mechanism against drug release times for PU.10.Q:0, PU.10. Q:7.5, and PU.10.Q:23.5. It shows that the portion of the diffusion mechanism decreased along with increasing the time for all three samples and also it is clear that an increase of flow rate from 0, 7.5 to 23.5 ml/s, causes a decrease in the portion of the diffusion mechanism in drug release.

The decrease in the contribution of the diffusion mechanism over time will be justified by the decrease in the concentration gradient by the time because the diffusion mechanism is controlled by the potential chemical gradient. As mentioned, drug release can involve a variety of mechanisms, common mechanism for drug delivery based on polyurethanes can be diffusion. [START_REF] Unagolla | [END_REF] In the previous section, the contribution of the diffusion mechanism was obtained by Equation ( 9) and it was shown that the diffusion mechanism was the dominant mechanism throughout the drug release period, but according to Figure 10, all the drugs were not released just by this mechanism. It is also noteworthy that if the mechanism of drug release was uniquely based on diffusion, the n

Test condition

k H R 2
Step 1

Step 2

Step 5) should be equal to the m value obtained from Equation ( 8) 43 which in accordance with the calculations these values were not equal.

Therefore, the contribution of the other mechanisms takes attention. The contribution of the other mechanisms can be calculated by the following relation:

Total drug release = (diffusion mechanism + other mechanisms) contributions to release.

The results of the degradation of polyurethane at different times showed no degradation. Therefore, drug release cannot be attributed to the carrier's degradation or dissolution.

In the first step for the matrix carrier especially with the undissolved drug particles, the first moments of the release are probably related to the phenomena of burst release. As the studies of the burst-release have shown this mechanism inevitably occurs in the first liberation period and will continue until the release of the drug is stable. 46,47 Referring to the initial values of the burst release obtained from the Figure 10 indicate that the burst release is increased by changing the state of the flow from static to continuous, whereas it shows fewer differences for two cases of flow rates.

For the second step, another mechanism in which the drug can be released is based on osmotic pump, this mechanism can be created by osmotic pressure and it is Zero-order First-order

K n R 2 K R 2 K R 2
Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2 not based on diffusion. One of the reasons for this mechanism is the absorption of water into the polymer. Also, the polymer degradation must be negligible and the channels of the polymer should be larger than 60 microns. [START_REF] Cussler | Diffusion: Mass Transfer in Fluid Systems[END_REF][START_REF] Hjärtstam | Ethyl Cellulose Membranes Used in Modified Release Formulations[END_REF][START_REF] Fredenberg | [END_REF] This value is justified by the microscopic images (Figure 11). In this figure the dark round holes refer to the cavities, where the lighter holes refer to the bubbles created during the preparation which may contain the drug inside of them.

The results of water absorption showed the amount of water absorbed by PU.10.Q:0, PU.10.Q:7.5 and PU.10. Q:23.5 increased with time. Moreover, increasing the flow rate increases water penetration into the polymer channels and pores. On the other hand, the osmotic pumping is based on the osmotic pressure resulting from water absorption and the solutes dissolved in it. 47,[START_REF] Fredenberg | [END_REF] Depending on the type of the matrix as it is semipermeable or nonpermeable with the solutes inside, the osmotic pressure can result in the swelling or shrinkage of the samples, respectively. According to the semipermeable samples used in this study swelling is the probable case. However, as it is mentioned in the Section 3.2 the swelling in this case is also Fickian-controlled. Thus, it can be said that increasing the rate of water uptake over time and increasing the flow rate causes the release of the drug through osmotic pressure. [START_REF] Cussler | Diffusion: Mass Transfer in Fluid Systems[END_REF][START_REF] Fredenberg | [END_REF] Consequently, the contribution of the diffusion mechanism to the drug release is decreased by increasing the flow rate and the time of the incubation.

| Different drug percentages

Figure 12 shows the contribution of diffusion mechanisms for the samples with different drug percentages at the flow rate of 7.5 ml/s by Equations ( 8) and (9). As shown in Figure 12, the contribution of the diffusion mechanism decreases over time for all three cases. Furthermore, the nonequilibrium coefficients n and m T A B L E 3 Regression constants for different mathematical models for PU.10, 20, and 30.Q:7.5

Polymeric films

Korsemeyer-Peppas

Zero-order First-order

K n R 2 K R 2 K R 2
Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2

Step 1

Step 2 obtained from equations Korsemeyer-Peppas and Peppas-Sahlin showed that drug release was not affected only by diffusion. In the previous section, it was shown that the amount of water absorbed by the carrier increased over time. On the other hand, with increasing drug content in polymer films, water absorption increased which reduced the influence of the diffusion mechanism on drug release and increased the contribution of the other mechanisms. Referring to the Figure 12 at the first step as the contribution of the diffusion is decreased at the starting point of release for the samples with 10, 20, and 30% of drug. Therefore, release related to the contribution of other phenomena at the first period of the release, respectively, for 10, 20, and 30% of drug increases. As mentioned above for the matrix sample at the first moments of the release the probable phenomenon is the burst release which is less related to the water absorption. As the percentage of the drug increases the probability of the drug particles to stay on the surface of the polymer matrix increases. It is, therefore, by increasing the drug percentage the value related to the burst release increases.

In the second step, the other mechanism which is contributed is the osmotic pressure [START_REF] Hjärtstam | Ethyl Cellulose Membranes Used in Modified Release Formulations[END_REF][START_REF] Fredenberg | [END_REF] which is increased by the water absorption and increasing the free space by releasing the more drugs. It is notable more the drug percentage, more the contribution of the osmotic pressure. The system is more nonequilibrium where the drug percentage increases, therefore activation energy for contributing osmotic pump increases. Moreover, hydrophilicity of the sample due to the more hydrophilic drug increases, hence water absorption increases, and vapor pressure would be another reason for commencing the osmotic pressure. Additionally, another parameter affecting the osmotic pressure is the permeability of the matrix, where increasing the drug content increases the permeability in the matrix. Therefore, the release of the drug through osmotic pressure will depend on the amount of drug loaded and consequently water absorbed into the polymer.

| CONCLUSION

In this work, the release of diclofenac from a polyurethane film loaded with various drug percentages was studied under static and dynamic flow conditions. Water absorption and cumulative drug release values were identified for all flow rates and drug dosages.

The experimental data was investigated using Higuchi model and proposed calculation algorithm to evaluate the stages of drug release from carries and contributed mechanisms. Drug release took place in two stages for static and dynamic states which were independent of the considered parameters. The second step gives another kinetic of the release more than the first step. Therefore, it notes the presence of the other mechanism(s), or it can be the same mechanism as the first step but with different kinetics due to some reasons. One can notice that the release kinetics of the first step was independent of different drug percentages for different flow rates. Threshold time, which is the time where the kinetic changes, are different for dynamic flow rates; however, it is the same for the static. In addition, the rate of release is more influenced by the drug dosage in the static state. There was a delay time in kinetic reduction by increasing the drug dosage perhaps due to presence of flow or agitation.

The results allowed the identification of three drug delivery of mechanisms; burst-release, diffusion, and osmotic pressure mechanisms. The diffusion represents the dominant mechanism in all periods of delivery. However, the contribution of the burst-release throughout the initial time and the osmotic pressure during the second step is accompanied by the diffusion. The proportion of drugs delivered in accordance with time for each of these mechanisms changes during the release period. In addition, the contribution of the other mechanisms apart from diffusion increases with the flow rate and as the percentage of drugs.

F

  I G U R E 1 Process of casting for preparing PU films with the diclofenac dispersed inside [Color figure can be viewed at wileyonlinelibrary.com]

Figure 4 (

 4 Figure 4(a),(b) shows the drug release percentage for the three loaded PU cases in the case of static and dynamic with the flow rate of 7.5 ml/s.Results are given in Figure4(a),(b), depict the drug release at 10, 20, and 30% of initial dosage under static and dynamic conditions, respectively. It is clear that the release time for the samples with the higher drug dosage has

F

  I G U R E 3 Water absorption percentage in accordance to the time of the incubation for different percentages of the drug at (a) static state, (b) the flow rate of 7.5 ml/s, and (c) 23.5 ml/s [in PU.X.Q:Y:X is indicator of drug percentage and y is indicator of flow rate (ml/s)] [Color figure can be viewed at wileyonlinelibrary.com]

F I G U R E 4

 4 Cumulative drug release in accordance with the time of the incubation for different percentages of the drug and at (a) static state, (b) the flow rates of 7.5 ml/s, and (c) 23.5 ml/s [Color figure can be viewed at wileyonlinelibrary.com]

F I G U R E 6

 6 Step analyzing by Higuchi model for the experimental tests of drug release with different drug loads (10, 20, and 30%) at flow rates of (a) 0, (b) 7.5 ml/s, and (c) 23.5 ml/s [Color figure can be viewed at wileyonlinelibrary.com] T A B L E 1 Values related to the Higuchi model by fitting the experimental results

F

  I G U R E 7 Comparing (a) the threshold times and (b) K H (release kinetic) for the second step of drug release; at different drug percentage for two flow rates of zero and 7.5 ml/s [Color figure can be viewed at wileyonlinelibrary.com] T A B L E 2 Regression constants for different mathematical models for PU.10, 20, and 30.Q:0 Polymeric films Korsemeyer-Peppas

F I G U R E 8

 8 Regression results of PU.10.Q:0, PU.20.Q:0, and PU.30.Q:0 in two steps with Korsemeyer-Peppas model [Color figure can be viewed at wileyonlinelibrary.com]

F I G U R E 9

 9 Regression results of PU.10, 20, 30.Q:7.5 with Korsemeyer-Peppas model [Color figure can be viewed at wileyonlinelibrary.com] F I G U R E 1 0 Contribution of diffusion in accordance with the time of the release at different flow rates for PU + 10% drug [Color figure can be viewed at wileyonlinelibrary.com]

F I G U R E 1 1

 1 Microscopic images representing the size of the holes (PU.10.Q:7.5, 1 hr after the test) [Color figure can be viewed at wileyonlinelibrary.com] F I G U R E 1 2 Contribution of diffusion in accordance with the time of the release at different initial drug percentages at the Q = 7.5 ml/s [Color figure can be viewed at wileyonlinelibrary.com]

CONFLICT OF INTEREST

The authors declare no conflicts of interest.