Bonastre Oliete
email: bonastre.oliete@u-bourgogne.fr

Cases, E., Saurel, R Salim A Yassine
email: salimyassine007@yahoo.fr

Drying method determines the structure and the solubility of microfluidized pea globulin aggregates

Keywords: Pea globulin, Aggregate, Microfluidization, High dynamic pressure, Spraydrying, Freeze-drying, Microscopy, Structure, Solubility, Suspension stability

The effects of microfluidization and drying method on the characteristics and technofunctional properties of pea (Pisum sativum L.) globulin aggregates were investigated. Pea globulin aggregates were microfluidized at 130 MPa and spray-dried or freeze-dried thereafter. Microfluidization decreased aggregate size and surface hydrophobicity due to protein re-arrangements. Microfluidized pea globulin aggregates showed higher solubility but less suspension stability than non-microfluidized aggregates. Drying favored the reaggregation of pea globulins with modifications in secondary structure of proteins more marked for spray-drying, decreased surface hydrophobicity and solubility, but increased suspension stability. Spray-dried aggregates were smaller than freeze-dried, with improved suspension stability. These results indicated that microfluidization and drying determine the structure of pea globulin aggregates and their associated techno-functional properties. These findings are crucial for the preparation of plant protein powders in the food industry.

Introduction

The use of vegetal proteins is increasing rapidly in food applications due to their nutritional, environmental and economic benefits. However, their inclusion in food formulation implies adequate techno-functional properties, which mainly depends on the protein structure.

Structure and technological properties of vegetal proteins are modified by the technological process applied during extraction (Stone et al., 2015, Fuhrmeister and[START_REF] Fuhrmeister | Impact of processing on functional properties of protein products from wrinkled peas[END_REF], and conditioning [START_REF] Sun | Gelation properties of salt-extracted pea protein isolate induced by heat treatment: Effect of heating and cooling rate[END_REF][START_REF] Ghribi | Effect of drying methods on physico-chemical and functional properties of chickpea protein concentrates[END_REF][START_REF] Shen | Microfluidization as a potential technique to modify surface properties of soy protein isolate[END_REF]. These processes may result in protein denaturation and/or aggregation [START_REF] Shen | Microfluidization as a potential technique to modify surface properties of soy protein isolate[END_REF].

Generally, globular proteins like whey proteins spontaneously and irreversibly aggregate when heated above 60 °C. The structure of globular protein aggregates formed after heating has been studied in detail [START_REF] Nicolai | Controlled food protein aggregation for new functionality[END_REF]. Earlier studies showed that in a first step, globular protein participates in a first aggregation or pre-aggregation leading to different structure depending on pH, ionic strength and concentration. Three distinctly morphologies of thermal aggregates have been observed: spherical particles (50 nm-few microns) next to the isoelectric point; strands (< 10 nm width, 10 nm -10 µm length) far from the isoelectric point or with high net charge; and long semi-flexible fibrils (micron length) during heating at very low pH values (< 2.5) and low ionic strength [START_REF] Nicolai | Controlled food protein aggregation for new functionality[END_REF]. At higher protein concentration, these aggregates will re-aggregate in a secondary aggregation resulting in larger fractal clusters [START_REF] Baussay | Influence of the ionic strength on the heat-induced aggregation of the globular protein β-lactoglobulin at pH7[END_REF][START_REF] Mehalebi | Light scattering study of heat-denatured globular protein aggregates[END_REF]. Although the general features are common to most globular proteins, pea protein aggregates are widely unknown and need to be characterized for optimal functionality. Structure and properties of protein aggregates are modified by technological process such as microfluidization. Microfluidization or dynamic high pressure modifies protein structure due to a combination of turbulence, shear and impact in a liquid by going through a fixed and small geometry. A previous study [START_REF] Oliete | Modulation of the emulsifying properties of pea globulin soluble aggregates by dynamic high-pressure fluidization[END_REF] showed that microfluidization at 70 MPa and 130 MPa led to re-arrangements in the structure of pea globulin aggregates resulting in decreased protein particle size and hydrophobicity. Microfluidization at 120 MPa also resulted in modifications in physicochemical and conformational properties of soy protein aggregates that improved protein solubility and emulsifying ability [START_REF] Shen | Microfluidization as a potential technique to modify surface properties of soy protein isolate[END_REF]. [START_REF] Dissanayake | Functional properties of whey proteins affected by heat treatment and hydrodynamic high-pressure shearing[END_REF] indicated that microfluidization at 140 MPa improved solubility and emulsifying activity index of whey protein aggregates at pH 7 as a result of the disintegration of insoluble big aggregates into small soluble particles. In these studies, characterization and evaluation of the techno-functional properties of aggregated proteins were performed immediately after microfluidization. However, for industrial use, protein aggregates should follow at least a drying step to facilitate their conservation, transport and utilization.

Spray-drying and freeze-drying are the two most commonly used methods for drying proteins [START_REF] Gong | Emulsifying properties and structure changes of spray and freeze-dried peanut protein isolate[END_REF]. Most of researchers in protein characterization use freeze-drying as a low temperature drying method to preserve the native structure of protein molecules, but the industrial production of food protein involves spray-drying because of the high cost and low productivity of freeze-drying. Differences in temperature and water evaporation process may affect differently protein structure and thus techno-functional properties of proteins [START_REF] Tang | Physicochemical, functional and structural properties of vicilin-rich protein isolates from three Phaseolus legumes: Effect of heat treatment[END_REF][START_REF] Mehalebi | Light scattering study of heat-denatured globular protein aggregates[END_REF]. The effect of drying method has been studied on the structure and technological properties of legume proteins such as soy protein [START_REF] Hu | Effects of drying methods on physicochemical and functional properties of soy protein isolates[END_REF], lentil [START_REF] Joshi | Physicochemical and functional properties of lentil protein isolates prepared by different drying methods[END_REF], rice dreg [START_REF] Zhao | Effects of spray drying and freeze drying on the properties of protein isolate from rice dreg protein[END_REF], chickpea [START_REF] Ghribi | Effect of drying methods on physico-chemical and functional properties of chickpea protein concentrates[END_REF], peanut [START_REF] Gong | Emulsifying properties and structure changes of spray and freeze-dried peanut protein isolate[END_REF], and grass pea [START_REF] Feyzi | Grass pea (Lathyrus sativus L.) protein isolate: the effect of extraction optimization and drying methods on the structure and functional properties[END_REF] proteins. Freeze-drying legume proteins showed more compact and ordered conformations [START_REF] Zhao | Effects of spray drying and freeze drying on the properties of protein isolate from rice dreg protein[END_REF] with higher water/oil holding capacity and lower emulsifying and foaming properties than spray-dried proteins [START_REF] Joshi | Physicochemical and functional properties of lentil protein isolates prepared by different drying methods[END_REF][START_REF] Hu | Effects of drying methods on physicochemical and functional properties of soy protein isolates[END_REF][START_REF] Ghribi | Effect of drying methods on physico-chemical and functional properties of chickpea protein concentrates[END_REF][START_REF] Gong | Emulsifying properties and structure changes of spray and freeze-dried peanut protein isolate[END_REF][START_REF] Zhao | Effects of spray drying and freeze drying on the properties of protein isolate from rice dreg protein[END_REF]. Authors attributed differences between drying methods to lower protein denaturation during freeze-drying than during spray-drying. However, to our knowledge the effect of the drying method on the characteristics and functionality of plant protein aggregates has not been studied.

The aim of this work was to determine the effect of microfluidization and drying method (spray-drying vs freeze-drying) on some physicochemical characteristics of pea globulin aggregates accountable for their techno-functional properties. Globulin aggregates were characterized in terms of particle size, microstructure, charge, surface hydrophobicity and secondary structure of proteins. Protein solubility at different pH and suspension stability were also determined.

Material and Methods

2.1.Globulin extraction and proximate analysis

Pea flour, provided by Cosucra (Warcoing, Belgium), was a mixture of different cultivars.

Flour was defatted by vigorous stirring in 5 volumes of petroleum ether for 1 h at room temperature (twice), and in 5 volumes of ethanol for 1 h at 4 °C (twice). The slurry was vacuum-filtered on a No. 2 porosity glass filter, and dried at room temperature for 48 h. Alkali extraction-isoelectric precipitation was used for globulin extraction as indicated by [START_REF] Mession | Effect of pea proteins extraction and vicilin/legumin fractionation on the phase behaviour in admixture with alginate[END_REF]. The dry flour was poured in a 0.1 M tris-HCl, pH 8 buffer and soluble proteins were extracted for 8 h at 4 °C (ratio flour-to buffer of 1:10). Insoluble materials were removed by centrifugation (10,000 g, 50 min, 20 °C). HCl 0.1 M was added to the supernatant up to pH 4.8 for globulin precipitation. Mixture was stirred for 1 h at 4 °C. Proteins were collected by centrifugation (10,000 g, 25 min, 4 °C), the pellets were washed with distilled water (pellet to water ratio of 1:25). The proteins were collected by centrifugation (10,000 g, 15 min, 4 °C), re-suspended at a concentration of 4 (w/w) and neutralized (pH 7.2) by adding slowly NaOH 0.25 M. The mixture was stirred at room temperature for 1 h, and again centrifuged to remove remaining insoluble material (10,000 g, 15 min, 4 °C). Globulins were frozen for 24 h at -18 °C and then freeze-dried in a Labconco Freeze dryer (Labconco, Kansas city, MO, USA). The process consisted in four steps of 24 h, at -50, -30, 0 and 25 °C. The resulting powder was stored at -18 °C until further use. The dry matter (95.38 ± 0.2% (w/w)) was determined according to AOAC International method 923.03 (AOAC, 1990). The protein content was 97.05% ± 0.2 (w/w) on a dry basis as determined by using the Kjeldahl method as AOAC International method 920.87 (AOAC, 1990) with a nitrogen conversion factor of 6.25 [START_REF] Mession | Thermal denaturation of pea globulins (Pisum sativum L.)-molecular interactions leading to heat-induced protein aggregation[END_REF][START_REF] Shand | Physicochemical and textural properties of heat-induced pea protein isolate gels[END_REF]. The mineral content (2.36% ± 0.02 (w/w)) on a dry basis was determined as AOAC International method 945.39 (AOAC, 1990).

2.2.Preparation of aggregates

Pea protein aggregates were obtained using the protocol described by [START_REF] Chihi | Heat-induced soluble protein aggregates from mixed pea globulins and β-lactoglobulin[END_REF]. 4% (w/w) globulin dispersions were prepared in 10 mM sodium phosphate buffer, pH 7.2, and stirred overnight at 4 °C to complete hydration. Sodium azide (0.05% w/w) was added as a preservative. The pH was adjusted to 7.2 with 0.1 M NaOH.

The dispersion was centrifuged at 10,000g for 20 min at 20 °C to remove insoluble proteins.

The supernatant, with a protein concentration of 3.41% ± 0.04, was poured into tubes (0.5 cm in diameter) and placed in a temperature-controlled water bath previously equilibrated at 40 °C, then heated at 1 °C/min from 40 to 90 °C, incubated at 90 °C for 60 min, and rapidly cooled on ice for 10 min. Aggregated pea globulins showed no endothermic peak in the DSC thermogram (data not shown), indicative of complete protein denaturation due to thermal treatment.

Aggregated protein dispersions were subjected to microfluidization at 130 MPa (denoted as A130) in a LM10 Microfluidizer (Microfluidics, Newton, MA, USA) fitted with a Z-type chamber (G10Z). Samples were passed 3 times through the system. Aggregated protein samples without microfluidization treatment were denoted as A0. A0 and A130 samples were analyzed directly after preparation without drying.

2.3.Drying

Spray-drying or freeze-drying method was applied to microfluidized pea globulin aggregates (A130). For spray-drying (A130S) an atomizer Büchi Mini Spray Dryer B-290 (Büchi Sarl, Rungis, France) was used. The outlet temperature was fixed at 65 °C and the inlet temperature to 160 °C during drying. For freeze-drying (A130F) globulin solutions were first frozen for 24 h at -18 °C and then freeze-dried in a Labconco Freeze dryer (Labconco, Kansas city, MO, USA). Freeze-drying consisted in four steps of 24 h, at -50, -30, 0 and 25 °C.

After drying, aggregate samples were equilibrated at constant water activity of 0.293 ± 0.008% by storing for at least 7 days before analysis in a saturate ambient with potassium acetate. Water activity of aggregates was measured at least in triplicate with an Aqual Lab Dew Point Water Activity Meter 4TE (Aqua Lab, Pullman, WA, USA). Protein content of dried aggregates was 95.70% ± 0.44 for A130S and 95.42% ± 1.82 determined by the Kjeldahl method as indicated before.

2.4.Particle size

Size and distribution of pea globulin aggregates were measured using a laser diffraction particle size analyzer MasterSizer 3000 analyser (Malvern Instruments), with 10 mM phosphate buffer, pH 7.2, 0.05% (w/w) sodium azide as a dispersant. The relative refractive index of the dispersion was taken as 1.09, that is, the ratio of the refractive index of wheat gliadin considered as reference (1.45) to that of the continuous phase (1.33). All determinations were conducted at least in triplicate. Volume-average diameter, d4,3 was reported as an indicative measure of particle size [Eq. 1]:

d4,3 = Σnidi4/Σnidi3 [Eq. 1]
The particle size heterogeneity Span was calculated as [Eq. 2] :

Span = [(d90 -d10) / d50] [Eq. 2]

2.5.Microscopy

Aggregated pea globulin suspensions were prepared in 10 mM phosphate buffer pH 7.2 for Transmission Electron Microscopy (TEM) by negative staining according to the procedure previously described by [START_REF] Munialo | Fibril Formation from Pea Protein and Subsequent Gel Formation[END_REF]. A 10 μL aliquot of 125mg/mL aggregated pea globulin dispersions was deposited onto a carbon support film on a copper grid. The excess was removed after 30 min using a filter paper (Whatman no. 1, 512-1002, VWR International Europe BVBA, Leuven, Belgium). A droplet of 3% uranyl acetate at pH 3.8 was added for 30 s to improve the contrast. Excess uranyl acetate was removed by use of a filter paper. Electron micrographs were obtained using a Hitachi H-7500 transmission electron microscope (Hitachi High-Technologies Europe GmbH) equipped with an AMT camera driven by AMT software (Hitachi) operating at 80 kV.

2.6.Fourier transform infrared (FTIR) spectroscopy

The secondary structure of aggregated pea proteins was characterized using FTIR spectroscopy. Aggregated pea protein suspensions (A0 and A130) were poured in a crystallizer forming a thin layer, dehydrated at 40 °C until water elimination and manually ground. A130S and A130F were analyzed as they were. FTIR spectra were collected in the wave number range from 600 to 4000 cm -1 with a resolution of 4 cm -1 using a Spectrum 65 FT-IR spectrometer (Perkin-Elmer, Courtaboeuf, France). The spectra were the average of 32 scans.

2.7.Zeta potential

The electrical charge (ζ-potential) of aggregates was measured using a ZetaCompact Z8000 zetaphoremeter (CAD Instruments, Les Essarts, Le Roi, France). The samples were diluted with 10 mM phosphate buffer, pH 7.2, to about 25 µg/g to obtain a tracking value of at least 100. The temperature of the cell was maintained at ambient temperature. The data was the average value of at least 5 measurements.

2.8.Surface hydrophobicity

Protein surface hydrophobicity (Ho) was determined with the fluorescence probe 1anilinonaphthalene-8-sulfonic acid (ANS; Sigma, St. Louis, MO, USA), according to the method of [START_REF] Kato | Hydrophobicity determined by a fluorescence probe method and its correlation with surface properties of proteins[END_REF] modified by [START_REF] Karaca | Emulsifying properties of chickpea, faba bean, lentil and pea proteins produced by isoelectric precipitation and salt extraction[END_REF]. Aggregates were diluted in a range of concentrations from 0.004% to 0.02% (w/w) in 10 mM phosphate buffer pH 7.2. 20 µL of the 8 mM ANS solution prepared in the same buffer were added to 4 mL of each protein sample, and the mixture was kept in the dark for 15 min. To ensure sufficient ANS to link the free surface hydrophobic groups of the protein, a calibration curve was constructed with the most concentrated protein solution (0.02%). The fluorescence intensity was measured using an LS-50B luminescence spectrometer (PerkinElmer, Waltham, MA, USA) at 380 nm (excitation) and 460 nm (emission). Blanks were protein samples without ANS and buffer with ANS. The initial slope of the fluorescence intensity versus protein concentration (mg/mL) plot, calculated by linear regression analysis, was used as an index of protein surface hydrophobicity.

2.9.Solubility

1% (w/w) aggregated pea globulin suspensions were hydrated overnight in 10 mM phosphate buffer at pH 3 to 8 at 4 °C. Subsequently, the suspensions were centrifuged at 10000 g for 20 min at 4 °C. The protein content in the supernatant was determined by Kjeldhal method.

Protein solubility was determined as Nitrogen Solubility Index (NSI) by dividing the nitrogen content of the supernatant by the total nitrogen in the sample (x100%). Analyses were performed in triplicate.

Suspension Stability

The stability of 5% (w/w) aggregated globulin suspensions in 10 mM phosphate buffer pH 7.2 was measured by Turbiscan® Lab Expert (Formulaction, Toulouse, France). Turbiscan®

Statistical analysis

Differences between samples (A0, A130, A130S, A130F) were studied by analysis of variance (one-way ANOVA). Significance was set at p < 0.05. Tukey's post-hoc leastsignificant-differences method was used to describe means with 95% confidence intervals.

The statistical analyses were performed using Statistica software, version 12 (Tulsa, OK, USA).

Results

Particle size

The particle size distribution of pea globulin aggregates obtained by laser granulometry at pH 7.2 was displayed in Figure 1. Particle size distribution of pea aggregate samples before microfluidization and drying (A0) showed a high peak around 600 nm that corresponded to the highest volume fraction of aggregates. Another heterogenic population with particle size ranging from ~4 to ~200 μm was observed and corresponded to highly aggregated pea globulins. When microfluidization at 130 MPa was applied (A130) particle size distribution shifted to smaller values compared to A0 (Figure 1), decreasing the volume-average diameter and the distribution heterogeneity (Table 1). Drying microfluidized pea globulin aggregates (A130S, A130F) caused the drastic reduction of the smallest-sized population and formed bigsized aggregates (1 -100 µm) (Figure 1). Freeze-drying (A130F) showed higher d4,3 values compared to A130S (Table 1).

Figure 1.

Table 1.

Microscopy

Figure 2 presented transmission electron micrographs (TEM) of pea globulin aggregates at pH 7.2. Pea globulin aggregates before microfluidisation and drying (A0) appeared as small curved strands, which agglomerated and formed secondary aggregates (Figure 2a). After microfluidization at 130 MPa (A130), secondary aggregates disappeared and primary aggregates showed smaller and more angular-shaped than in A0 (Figure 2b). Drying after microfluidization (A130S, A130F) favored the formation of voluminous secondary aggregates compared to A130, especially when freeze-drying (A130F) was used compared to spraydrying (A130S) (Figure 2 c and d respectively).

Figure 2.

3.3.FTIR spectra analysis

Figure 3 showed the amide I region (1700 -1600 cm -1 ) of pea protein aggregates, permitting to identify the characteristic bands of the protein secondary structure. Amide I region mainly comprises the stretching vibration of C=O [START_REF] Ellepola | Conformational study of globulin from rice (Oryza sativa) seeds by Fourier-transform infrared spectroscopy[END_REF]. The obtained bands were assigned to different conformations according to existing data [START_REF] Yang | Effects of high pressure homogenization on faba bean protein aggregation in relation to solubility and interfacial properties[END_REF]Chen, 2018, Gharsallaoui et al., 2012) as indicated in Table 2. Microfluidization at 130 MPa (A130) decreased the intensity of peaks 1602 cm -1 (corresponding to vibration of amino acid residues), 1614 cm -1 (corresponding to antiparallel β-sheet), 1634 cm -1 , 1641 cm -1 (corresponding to β-sheet) and 1694 cm -1 (corresponding to aggregated strands), compared to A0, whereas it increased the intensity of peaks 1668 cm -1 and 1681 cm -1 (corresponding to βturn). Drying microfluidized pea aggregates by spray-drying (A130S) markedly increased the intensity of peak 1652 cm -1 (corresponding to random coil), 1683 cm -1 (corresponding to βturn), and 1695 cm -1 (corresponding to aggregated strands) compared to A130. In parallel, freeze-drying slightly increased the intensity of peaks 1630 cm -1 and 1638 cm -1 (corresponding to β-sheet), and reduced the intensity of peaks 1646 cm -1 (corresponding to random coil), and 1662 cm -1 and 1684 cm -1 (corresponding to β-turn).

Surface hydrophobicity and ζ-potential

The surface hydrophobicity (Ho) of aggregates at pH 7.2 was evaluated using an ANS fluorescence probe (Table 1). Pea globulin aggregates before microfluidization and drying (A0) showed the highest Ho values. Microfluidization at 130 MPa (A130) significantly decreased surface hydrophobicity of pea globulin aggregates (~6% reduction). Drying after microfluidization (A130S, A130F) notably decreased Ho (~30% reduction), but no significant differences were observed between freeze-(A130F) and spray-drying (A130S) methods.

No significant differences were observed in the charge (ζ-potential) of pea globulin aggregates due to the technological process i.e. microfluidization and drying (Table 1).

3.5.Protein Solubility

The solubility profile of pea globulin aggregates as a function of pH (Figure 4) showed an inverted bell shape with the minimum around pH 5 which is near the isoelectric point (pI) of globulins. Microfluidization at 130 MPa did not significantly improved solubility of pea globulin aggregates compared to A0. Drying microfluidized aggregates (A130S, A130F) notably reduced solubility of microfluidized pea globulin aggregates except at pH 5.

Comparing drying methods, no significant differences were observed between freeze-dried samples (A130F) and spray-dried samples (A130S).

Figure 4.

3.6.Suspension stability

Figure 5 showed the transmission profiles of pea aggregates obtained by Turbiscan® in delta mode, i.e. the first scan was subtracted from all other scans during time, which allowed easier visualization of the transmission flux variations [START_REF] Cvek | A systematical study of the overall influence of carbon allotrope additives on performance, stability and redispeersibility of magnetorheological fluids[END_REF].

A0 samples showed a stable transmission profile (Figure 5a). The decrease of transmission in the bottom of the sample indicating modest sedimentation of particles in suspension would be negligible since transmission variation did not reach 2%. In A130 samples, T noticeably increased in the top of A130 sample (Figure 5b) indicating the formation of a clarification layer. The increase in the middle of the sample indicated that particles increased in size (flocculation) allowing photons to go through the sample without being diffused.

Drying of microfluidized pea globulin aggregates (A130S, A130F) induced less transmission flux variation than A130 samples (Figure 5c and d respectively). A130S formed a limited clarification layer at the top of the sample (Figure 5c). A130F formed a clarification layer similar to A130 but the increase in particle size (transmission increase in the middle of the sample) was smaller (Figure 5d).

Discussion

Microfluidization effect on pea globulin aggregates characteristics

Pea globulin aggregates before microfluidization and drying (A0) appeared as small curved strands in the micrographs obtained by TEM, as already indicated by [START_REF] Nicolai | beta-lactoglobulin and WPI aggregates: formation, structure and applications[END_REF] and [START_REF] Jung | Structure of heatinduced β-lactoglobulin aggregates and their complexes with sodium-dodecyl sulfate[END_REF] for β-lactoglobulin aggregates at neutral pH. Primary aggregates agglomerated into secondary aggregates as fractal clusters in which a self-similar structure was repeated [START_REF] Baussay | Influence of the ionic strength on the heat-induced aggregation of the globular protein β-lactoglobulin at pH7[END_REF][START_REF] Mehalebi | Light scattering study of heat-denatured globular protein aggregates[END_REF]. β-sheet were the dominant secondary structure in A0 as revealed the strong absorption at 1640 cm -1 in the amine I region, confirming previous results concerning legume globulins: soy protein thermal aggregates [START_REF] Zhang | Preparation and in vitro evaluation of calcium-induced soy protein isolate nanoparticles and their formation mechanism study[END_REF], faba bean protein isolate [START_REF] Yang | Effects of high pressure homogenization on faba bean protein aggregation in relation to solubility and interfacial properties[END_REF], and field pea and kidney bean globulins [START_REF] Shevkani | Structural and functional characterization of kidney bean and field pea protein isolates: A comparative study[END_REF]. The negative charge obtained in all pea aggregate samples was related to the working pH value (pH 7.2) which is higher than pI of vicilins (pI 4.5, Ezpeleta et al., 1996) and pI of legumin acid subunit (pI 4.7, [START_REF] Krishina | Heterogeneity in subunit composition of the legumin of Pisum sativum[END_REF]. At pH 7.2, amine and carboxylic free groups of proteins are deprotonated. Charge values were included in the range between -10 and -15mV defined by [START_REF] Riddick | Control of colloid stability through zeta potential[END_REF] as aggregation threshold, which is in agreement with the observation of protein aggregation.

Microfluidization at 130 MPa modified the structure of pea globulin aggregates as clearly observed by TEM, FTIR, and particle size distribution. The combination of turbulence, shear and collisions caused by microfluidization at 130 MPa broke secondary aggregates and modified the conformation of primary aggregates which appeared smaller, more homogeneous in size and more angular in shape than in A0. Small sized aggregates obtained by microfluidization (compared to initially present aggregates) underwent structural rearrangement. Microfluidization seemed to induce the unfolding of β-sheet structures producing a self-reassembly to less ordered structures as β-turns, while most of the other secondary structures of pea protein aggregates were almost maintained. [START_REF] Yang | Effects of high pressure homogenization on faba bean protein aggregation in relation to solubility and interfacial properties[END_REF] also indicated that high pressure homogenization at 207 MPa had a certain impact on faba bean protein, but most of the secondary structures were intact. These authors however observed a decrease of α-helix and β-turn after homogenization. Wang, Li, Jiang, Qi and Zhou, (2014) signaled that the processing conditions such as temperature and time determine the protein secondary structures of soybean proteins. New re-arrangements hided hydrophobic groups, made them less accessible to the binding of ANS fluorescence probe, and resulted in decrease of surface hydrophobicity [START_REF] Oliete | Modulation of the emulsifying properties of pea globulin soluble aggregates by dynamic high-pressure fluidization[END_REF]. However, [START_REF] Shen | Microfluidization as a potential technique to modify surface properties of soy protein isolate[END_REF] observed an increase in hydrophobicity after 120 MPa microfluidization of soy aggregates applied after a 30 min thermal treatment. Hydrophobicity behavior of aggregates was clearly dependent on the temperature and time used in the thermal aggregation [START_REF] Shen | Microfluidization as a potential technique to modify surface properties of soy protein isolate[END_REF]Tang, 2012, Wang et al., 2014). The charge of pea globulin aggregates was not significantly modified by microfluidization as already indicated in previous works [START_REF] Oliete | Modulation of the emulsifying properties of pea globulin soluble aggregates by dynamic high-pressure fluidization[END_REF]. The absence of significant differences in the ζ-potential within samples could be related to the presence of salts coming from the extraction method (~2.4% mineral content in the dried protein isolate).

Salt could surround the protein, reducing the ζpotential absolute value by screening effect and thus the amount of electrostatic repulsive forces [START_REF] Lam | Pea protein isolates: structure, extraction and functionality[END_REF].

Structural changes induced by microfluidization at 130 MPa did not reach to significantly improve solubility of pea globulin aggregates. Solubility is an important prerequisite for proteins to be used in food applications, since it affects all other techno-functional properties. [START_REF] Dissanayake | Functional properties of whey proteins affected by heat treatment and hydrodynamic high-pressure shearing[END_REF] and [START_REF] Shen | Microfluidization as a potential technique to modify surface properties of soy protein isolate[END_REF] indicated that microfluidization of whey and soy aggregates increased solubility, as a result of several complementary factors.

First of all, high shearing due to microfluidization will disrupt large insoluble aggregates into small soluble ones [START_REF] Shen | Microfluidization as a potential technique to modify surface properties of soy protein isolate[END_REF], and size reduction would decrease sedimentability of particles [START_REF] Meerdink | Modeling segregation of solute material during drying of liquid foods[END_REF]. In the case of pea globulin aggregates, microfluidization at 130 MPa decreased the volume-average diameter of particles. However, the non-negligible residual big sized particles in A130 would hinder the increase of solubility caused by the increased in submicron sized particles. These big sized particles (>10 µm) could come from the non-microfluidized sample or could be formed after microfluidization.

New arrangements resulting in less ordered secondary structure could favour interactions between particles. Secondly, protein solubility depends on the protein-water interactions which are driven mainly by the protein surface charge and the presence of free hydrophobic groups, at pH values far from the pI. Since no difference in particle charge was observed between A0 and A130, we rather suggest that hydrophobic attractive interactions play a predominant role regarding hydration properties of protein aggregates. In fact, [START_REF] Karaca | Emulsifying properties of chickpea, faba bean, lentil and pea proteins produced by isoelectric precipitation and salt extraction[END_REF] observed a negative correlation between protein solubility and surface hydrophobicity.

Lower surface hydrophobicity made microfluidized aggregates less compact and more flexible [START_REF] Tang | Physicochemical, functional and structural properties of vicilin-rich protein isolates from three Phaseolus legumes: Effect of heat treatment[END_REF] than non-microfluidized aggregates. Lower aggregate compactness would facilitate the interactions between proteins and water molecules [START_REF] Feyzi | Grass pea (Lathyrus sativus L.) protein isolate: the effect of extraction optimization and drying methods on the structure and functional properties[END_REF]. In the present case, similar solubility values between microfluidized and non-microfluidized pea globulin aggregates indicated that, despite significant difference in hydrophobicity, the presence of big sized particles would define the solubility behavior of pea globulin aggregates. Microfluidization at 130 MPa was in detrimental to suspension stability as revealed by enhanced flocculation and clarification phenomena during Turbiscan® test . New re-arrangements induced by microfluidization would favour protein-protein interactions, resulting in increasing particle size along time, which was not measurable by laser diffraction due to highly diluted sample conditions. These interactions were probably driven by hydrogen bonds. Electrostatic interactions are managed by particle charge which did not significantly vary between samples in the present work. Hydrophobic interactions decreased between A0 and A130 as was indicated by the significant reduction of surface hydrophobicity measured by fluorescence probing.

Drying effects on microfluidized pea globulin aggregates characteristics

Drying after microfluidization (A130F, A130S) caused the re-aggregation of pea globulin proteins, as indicated by the particle size data and the TEM observations. Drying increased connection points between primary aggregates leading to branched fractal objects. These effects were more noticeable when freeze-drying (A130F) was used compared to spray-drying (A130S). Other authors [START_REF] Cepeda | Functional properties of faba bean (Vicia faba) protein flour dried by spray drying and freeze drying[END_REF][START_REF] Ghribi | Effect of drying methods on physico-chemical and functional properties of chickpea protein concentrates[END_REF][START_REF] Joshi | Physicochemical and functional properties of lentil protein isolates prepared by different drying methods[END_REF][START_REF] Zhao | Effects of spray drying and freeze drying on the properties of protein isolate from rice dreg protein[END_REF] already indicated that freeze-dried protein showed higher particle size than other more intense drying methods such as spray-drying or hot air convection. In the case of freezedrying, local cryo-concentration during freezing would increase opportunities of aggregated proteins to come into close contact with one another. In consequence freeze-drying would favour molecular interactions such as electrostatic interactions, hydrophobic interactions and even disulfide bridges [START_REF] Gong | Emulsifying properties and structure changes of spray and freeze-dried peanut protein isolate[END_REF] resulting in compact protein conformations [START_REF] Zhao | Effects of spray drying and freeze drying on the properties of protein isolate from rice dreg protein[END_REF]. On the other hand, spray-drying process forces the sample through a nozzle forming small droplets that encounter dry and hot air. The drastic kinetics conditions of spraydrying process compared to freeze-drying may limit interactions between molecules and make aggregation more difficult. Differences between drying methods have been observed even in the secondary structure of pea proteins as other authors [START_REF] Feyzi | Grass pea (Lathyrus sativus L.) protein isolate: the effect of extraction optimization and drying methods on the structure and functional properties[END_REF][START_REF] Lan | Solid dispersion-based spray-drying improves solubility and mitigates beany flavor of pea protein isolae[END_REF]. Peaks in the amide I region from dried samples shifted compared to peaks of non-dried samples, suggesting that the protein structures were affected by the drying methods [START_REF] Zhao | Effects of spray drying and freeze drying on the properties of protein isolate from rice dreg protein[END_REF]. Freeze-drying (A130F) seemed to increase the β-sheet structure and decreased the random coils and β-turns. Spray-drying (A130S) markedly increased random coils which became the predominant structure, β-turns and aggregated strandsindicating significant conformation changes to less ordered secondary structure.

Simultaneously, the drying method did not show a clear effect on Ho. Changes in the structure of microfluidized pea globulin aggregates caused by drying decreased protein solubility but improved suspension stability, compared to their non-dried counterpart. The decrease in solubility of dried microfluidized pea globulin aggregates was related to higher particle size and thus higher sedimentability of rehydrated aggregates (A130S, A130F) compared to non-dried microfluidized aggregates (A130). The negative effect of increasing particle size due to drying on protein solubility seemed to prevail over the positive effect caused by the decrease of the surface hydrophobicity resulting from reaggregation. This statement was already suggested above to explain the effect of microfluidization on pea globulin aggregate solubility. The effect of particle size on pea globulin solubility behavior overcomes the effect caused by re-arrangement in aggregate structure modification. Comparing drying methods, freeze-drying (A130F) and spray-drying (A130S) did not show significant differences in solubility. Contradictory results have been published about the effect of the drying method on protein solubility. [START_REF] Hu | Effects of drying methods on physicochemical and functional properties of soy protein isolates[END_REF] and [START_REF] Sumner | Production and evaluation of pea protein isolate[END_REF] reported that spray-dried soy and pea proteins had lower solubility compared to the freeze-dried counterparts. However, [START_REF] Cepeda | Functional properties of faba bean (Vicia faba) protein flour dried by spray drying and freeze drying[END_REF]), Johsi et al. (2011[START_REF] Zhao | Effects of spray drying and freeze drying on the properties of protein isolate from rice dreg protein[END_REF] reported that the solubility of spray-dried faba bean, soy and rice dreg proteins respectively was higher than that of freeze-dried samples. In the case of microfluidized pea globulin aggregates, the presence of big sized particles in both spray-and freeze-dried aggregates would determine their solubility behavior. Drying A130S and A130F improved suspension stability compared to A130. Protein re-aggregation caused by drying would create a stable structure with limited particle size evolution, probably due to enhanced steric repulsion. Increase in protein particle interactions in A130S and A130F was hindered compared to A130, and led to a reduction of the clarification effect. Freeze-dried microfluidized pea globulin aggregates (A130F) showed lower suspension stability than A130S which was in accordance with higher initial particle size.

Conclusion

In the current study, the effect of microfluidization and drying method on the structure, solubility and suspension stability of pea globulin aggregates were investigated.

Microfluidization at 130 MPa broke pea globulin aggregates and formed smaller, more angular-shaped, and lower surface-hydrophobicity particles with less ordered protein structure compared to pea globulin aggregates before microfluidization. Solubility of pea globulin aggregates seemed to be defined by particle size more than protein structure. However, the new re-arrangements produced by microfluidization led to less suspension stability due to time-evolving flocculation. Drying microfluidized aggregates favored re-aggregation of particles with modifications in structural conformation of proteins, and significantly decreased surface hydrophobicity. The new structures created in dried microfluidized pea globulin aggregates decreased solubility but increased suspension stability. Comparing drying methods spray-dried aggregates showed lower re-aggregation than freeze-dried aggregates, resulting in smaller particle size what improved suspension stability. This study showed that drying methods determine the structure of microfluidized pea globulin aggregates and will impact their techno-functional properties. These findings are decisive for using pea globulin aggregates as dry powders in the preparation of suspensions, emulsions and gels for the food industry.

Figure captions

  measurements are based in multiple light scattering. The equipment possesses two optical sensors that measure the transmitted and the backscattered near-infrared monochromatic light (λ = 800nm).[START_REF] Mengual | Characterisation of instability of concentrated dispersions by a new optical analyser: The TURBISCAN MA 1000[END_REF] indicated the ability of this technique to characterize particle or aggregate size variation and particle/aggregate migration.In diluted systems (transmission variation > 0.2%), these phenomena are measured by the transmission light intensity of the sample as a function of sample height and time. The measurement of the backscattering light in non-opaque systems can give erroneous information since the backscattering profiles can be affected by the partial reflection of the light crossing the sample. Suspensions were maintained under agitation until analysis. Samples were placed in flat-bottomed cylindrical borosilicate glass tubes and introduced into Turbiscan® measurement cell. Turbiscan detection head scanned the sample by moving vertically along the analysis cell and acquiring data every 40 µm. The light scattering profiles were recorded every 10 minutes for 12 hours. Differences in the transmission profiles along time indicate sample instability. Light transmitted intensity (T) is affected by the average diameter of particles and the mean free-path of photon. T may change over time and height. Light transmitted intensity (T) Based on Turbiscan® graphs three different regions were distinguished along the tube axis: the bottom, the middle and the top. Variations of T in the top and in the bottom of the sample are related to migration phenomena, such as clarification (top) and sedimentation (bottom). The variations of T in the middle part of the sample indicate the interaction phenomena between particles, and thus particle size variation. Based on the obtained spectra, suspension stability can be calculated by Turbiscan stability index (TSI) according to equation Eq.3 = ∑ ∑ | | [Eq.3] Where H: sample height from bottom of the cell to the meniscus Scani(h): intensity of scanning light (time is i, height is h) Scani-1(h): intensity of scanning light (time is i-1, height is h) The lowest TSI values indicated the most stable suspensions. Turbiscan® spectra were analyzed with the software Turbisoft-Lab version 2.2.0.82-5 (Formulaction, Toulouse, France).

Figure

  Figure 3 and Table 2

  Figure 5.

Figure 6

 6 Figure 6 permitted the analysis of the global stability by means of TSI variation. A0 showed the smallest TSI variation in accordance with the most stable transmission profile. A130 showed the highest TSI values as a result of the clarification and flocculation phenomena that took place during measurements. Instability in A130 was especially intense during the first five hours as indicated the notable TSI variation. Drying decreased the instability of samples compared to A130, especially in A130S.

Figure 6 .

 6 Figure 6.

Figure 1 .

 1 Figure 1. Particle size distribution profiles of pea globulin aggregates before microfluidization and drying (A0), after microfluidization at 130 MPa (A130), and after microfluidization and spray-drying (A130S) or freeze-drying (A130F) in 10 mM phosphate buffer at pH 7.2.

Figure 2 .

 2 Figure 2. Transmission electron micrographs (TEM) of pea globulin aggregates pea globulin aggregates before microfluidization and drying (A0) (a), after microfluidization at 130 MPa (A130) (b), and after microfluidization and spray-drying (A130S) (c) or freeze-drying (A130F) (d) in 10 mM phosphate buffer at pH 7.2.

Figure 3 .

 3 Figure 3. Deconvoluted FTIR spectra in the amine I region of pea globulin aggregates before microfluidization and drying (A0), after microfluidization at 130 MPa (A130), and after microfluidization and spray-drying (A130S) or freeze-drying (A130F).

Figure 4 .

 4 Figure 4. Nitrogen Solubility Index (%) of pea globulin aggregates before microfluidization and drying (A0), after microfluidization at 130 MPa (A130), and after microfluidization and spray-drying (A130S) or freeze-drying (A130F).

Figure 5 .

 5 Figure5. Turbiscan® spectra of pea globulin aggregates before microfluidization and drying (A0), after microfluidization at 130 MPa (A130), and after microfluidization and spray-drying (A130S) or freeze-drying (A130F) in 10 mM phosphate buffer at pH 7.2.

Figure 6 .

 6 Figure 6. Turbiscan Stability Index (TSI) variation of pea globulin aggregates before microfluidization and drying (A0), after microfluidization at 130 MPa (A130), and after microfluidization and spray-drying (A130S) or freeze-drying (A130F) in 10 mM phosphate buffer at pH 7.2.

  Figure 1.

  Figure 5.

  in spray-drying rice dreg protein isolate compared to freeze-dried,[START_REF] Gong | Emulsifying properties and structure changes of spray and freeze-dried peanut protein isolate[END_REF] observed higher Ho values in freeze-dried peanut isolate than in spray-dried one.[START_REF] Feyzi | Grass pea (Lathyrus sativus L.) protein isolate: the effect of extraction optimization and drying methods on the structure and functional properties[END_REF] signaled different effect of drying method on Ho depending on the protein extraction method used.

	Similar values of Ho for
	A130S and 130F samples were indeed observed despite different effects of the drying method
	on secondary structure of proteins. Thus, new arrangements between molecules in protein
	aggregates induced by dehydration (A130S, A130F), tended to bury polypeptides with

hydrophobic groups which were initially exposed in non-dried microfluidized pea globulin aggregates, decreasing surface hydrophobicity. Whilst

[START_REF] Zhao | Effects of spray drying and freeze drying on the properties of protein isolate from rice dreg protein[END_REF]

signaled higher surface hydrophobicity

Acknowledges: Authors would thank the Centre de Microscopie INRA/uB (Dijon) of the Plateforme DImaCell Platform (INRA, Univ. Bourgogne Franche-Comté, F-21000 Dijon, France. Authors would also thank Formulaction company.

Funding: This work was supported financially by European Funds for Regional Development (FEDER-FSE Bourgogne 2014/2020), French Inter-Ministerial Unique Funds (FUI), and the Region of Burgundy (France) as part of project LEGUP Lot 3 2015 03 03.

Tables

 Table 1.Particle size distribution in terms of volume-average diameter (d4,3) and heterogeneity (Span) , surface hydrophobicity (Ho), and charge (ζ-potential) of pea globulin aggregates before microfluidization and drying (A0), after microfluidization at 130 MPa (A130), and after microfluidization and spray-drying (A130S) or freeze-drying (A130F) in 10 mM phosphate buffer at pH 7.2.


Bouzat

MD Edouard Girard
email: egirard1@chu-grenoble.fr

MD Quentin Jegousso

MD Bastien Boussat

MD Patrice François

MD François-Xavier Ageron

MD, PhD Christian Letoublon

MD Pierre Bouzat

For

Trenau Group

Preventable deaths in a French regional trauma system: A six-year analysis of severe trauma mortality

Keywords: trauma system, preventable deaths, avoidable errors, quality, safety

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

2

Background

Over the past decades, the management of severe trauma patients has been improved by the implementation of trauma systems across the world allowing standardization of trauma care [START_REF] Mackenzie | A national evaluation of the effect of trauma-center care on mortality[END_REF]. Trauma systems are based upon early recognition of severe trauma, adequate allocation of resources for each patient and the standardization of procedures for trauma care.

Indicators for a trauma system's effectiveness rely on the rate of under/over-triage [START_REF]Hospital and prehospital resources for optimal care of the injured patient. Committee on Trauma of the American College of Surgeons[END_REF] but also on the analysis of mortality within the trauma network [START_REF] Shafi | Moving beyond personnel and process: a case for incorporating outcome measures in the trauma center designation process[END_REF]. Classically, deaths after severe trauma can be categorized as followed: preventable deaths, potentially preventable deaths and non-preventable deaths [START_REF] Davis | The significance of critical care errors in causing preventable death in trauma patients in a trauma system[END_REF][START_REF] Teixeira | Preventable or potentially preventable mortality at a mature trauma center[END_REF][START_REF] Vioque | Classifying errors in preventable and potentially preventable trauma deaths: a 9-year review using the Joint Commission's standardized methodology[END_REF]. This categorization can be performed by benchmarking care to accepted guidelines (For instance, advanced trauma life support [START_REF] Subcommittee | American College of Surgeons' Committee on T, International Awg. Advanced trauma life support (ATLS(R)): the ninth edition[END_REF] or National Institute for health and Care Excellence, guidelines for major trauma) or by determining the risk of death according to trauma scores (Trauma Revised Injury Severity Score, TRISS or mechanism, age, Glasgow coma scale, arterial pressure, MGAP, score) [START_REF] Schluter | Trauma and Injury Severity Score (TRISS) coefficients 2009 revision[END_REF][START_REF] Sartorius | Mechanism, glasgow coma scale, age, and arterial pressure (MGAP): a new simple prehospital triage score to predict mortality in trauma patients[END_REF]. Regardless of methodology, the concept of preventable deaths has been reported for decades in severe trauma patients and reducing their number is one of the main objectives of trauma system [START_REF] Teixeira | Preventable morbidity at a mature trauma center[END_REF]. Hence, the analysis of errors related to preventable/potentially preventable deaths is necessary for quality improvement of trauma care within a specific region. Ultimately, comparisons of errors between trauma systems would be useful to analyze their efficiency and thereby defining the best standard of care. For that purpose, analyzing preventable and potentially preventable deaths is of interest to classify reported errors that may induce corrective actions to avoid these events. A major limitation for work in this area is the lack of standardization of error classification, which undermines the reproducibility of such analysis. To overcome this limit, the Joint Commission on the accreditation of Healthcare Organizations (JCAHO) has proposed a taxonomy to facilitate a common approach for patient safety information systems [START_REF] Chang | The JCAHO patient safety event taxonomy: a standardized terminology and classification schema for near misses and adverse events[END_REF]. This classification allocates errors in five interacting nodes: impact, type, domain, cause and prevention. The JCAHO taxonomy has been successfully used for the analysis of preventable deaths in diverse trauma systems and has become the benchmark of error reporting after severe trauma [START_REF] Vioque | Classifying errors in preventable and potentially preventable trauma deaths: a 9-year review using the Joint Commission's standardized methodology[END_REF][START_REF] Montmany | Preventable deaths and potentially preventable deaths. What are our errors?[END_REF][START_REF] Ivatury | Patient safety in trauma: maximal impact management errors at a level I trauma center[END_REF]. Since 2007, a French regional trauma system, named TRENAU, has been implemented in the French Alps to optimize the management of trauma patients in this region [START_REF] Bouzat | Trauma network for severely injured patients[END_REF]. Our organization has demonstrated efficiency in terms of under and over-triage but an analysis of mortality has not been performed [START_REF] Bouzat | A regional trauma system to optimize the pre-hospital triage of trauma patients[END_REF]. The main objective of our study was to describe preventable/potentially preventable deaths in our trauma system and to classify our errors using the JCAHO taxonomy.

Methods

Study design and data collection

We conducted a retrospective study using the registry of the Trauma System of the Northern French Alps (TRENAU). Briefly, this trauma system gathers data from thirteen hospitals located in the Northern French Alps and consists of one level-I trauma center, two level-II trauma centers and ten level-III trauma centers [START_REF] Bouzat | Trauma network for severely injured patients[END_REF]. A registry has been implemented since 2009 and has been collected data prospectively using the Utstein-style template [START_REF] Soreide | New recommendations for uniform reporting of data following major trauma: "the Utstein style[END_REF]. The Regional Institutional Ethics Committee approved the implementation of the TRENAU registry (Comité d'Ethique des Centres d'Investigation Clinique de l'inter-région Rhône-Alpes-Auvergne, IRB number 5891) and, given its observational nature, waived the requirements for written informed consent from each patient.

Consecutive adult patients recorded in the TRENAU registry from January 2009 to December 2014 were included if they died following a severe traumatic injury in the prehospital setting or within their stay at hospital. Patients who died before the arrival of prehospital emergency physicians were not included in the TRENAU registry and, thus, were not considered for this study. The following data were collected for each patient: age, sex, mechanism, first recorded vital signs, the mechanism, Glasgow coma scale (GCS), age and arterial pressure (MGAP) score [START_REF] Sartorius | Mechanism, glasgow coma scale, age, and arterial pressure (MGAP): a new simple prehospital triage score to predict mortality in trauma patients[END_REF] in the pre-hospital setting, vital signs on admission, the need for emergency surgery or embolization, the injury severity score (ISS) and the Trauma revised injury severity score (TRISS) [START_REF] Schluter | Trauma and Injury Severity Score (TRISS) coefficients 2009 revision[END_REF]. The Injury Severity Score (ISS) is an anatomical scoring system that provides an overall score for patients with multiple injuries. Each injury is assigned an Abbreviated Injury Scale (AIS) score and is allocated to one of six body regions (Head, Face, Chest, Abdomen, Extremities (including Pelvis), External). Only the highest AIS score in each body region is used. The three most severely injured body regions have their score squared and added together to produce the ISS score. The ISS score correlates linearly with mortality, morbidity, hospital stay and other measures of severity. The TRISS determines the probability of survival. It is calculated from the ISS, the Revised Trauma Score (calculated with respiratory rate, GCS and systolic arterial blood pressure) and patient's age.

Cause, date and location (prehospital phase, trauma bay or intensive care unit, ICU) of death were also reported.

Primary endpoint

The primary endpoint was the preventability of death from the pre-hospital field to the end of hospital's stay. Each patient's file was reviewed by a multidisciplinary independent committee (adjudication committee) composed by two anesthesiologists (PB, QJ) and two trauma surgeons (EG, CL) to classify mortality according to the analysis of errors. A preventable death was defined by a death caused directly by an avoidable error. A potentially preventable death was defined by a death that might have been caused by a preventable error, and non-preventable deaths were those that occurred regardless of any errors in the patient's management. Errors were also classified according to the Joint Commission on the accreditation of Healthcare Organizations (JCAHO) taxonomy [START_REF] Chang | The JCAHO patient safety event taxonomy: a standardized terminology and classification schema for near misses and adverse events[END_REF].

Secondary endpoints

Secondary endpoints were 1) the comparison between patients with preventable/potentially preventable deaths and patients with non-preventable deaths and 2) the time course of preventable/potentially preventable deaths from 2009 to 2014.

Statistical analysis

Continuous variables were presented as median and 25th-75th interquartile ranges (IQRs). Categorical variables were presented as numbers and percentages. We compared patient characteristics according to the preventability of death using a Mann-Whitney test for continuous variables and a Chi square test, or a Fisher exact test where appropriate, for categorical variables. The trend in mortality over time was tested with a Chi-squared test for linear trend. Subgroup trends according to deaths' category were also analyzed. Two-sided p values <0.05 were considered as statistically significant. All analyses were performed using Stata version 14.0 (Stata Corporation, College Station, TX, USA).

Results

Within the study period, 7,484 consecutive trauma patients were included in the TRENAU registry. Among them, 503 consecutive patients died (overall mortality equal to 6.7%) and were included in the study. Twenty-nine patients (6%) died in the prehospital phase, 47 (9%) patients died in the trauma bay before their transfer to ICU, and 427 (85%) patients died in the ICU. One hundred and sixty-eight patients (33%) died within the first 24 hours after the insult and median time between accident and death was 1 [0-5] day. Seventytwo (14%) deaths were judged as potentially preventable and 36 (7%) deaths as preventable.

Patients characteristics are shown in Table 1 and causes of deaths are presented in Supplemental File N°2. Patients with preventable/potentially preventable deaths had different location of lethal injuries as compared to patients with non-preventable deaths. Nonpreventable deaths were most often attributed to CNS injuries, whereas preventable deaths were related to torso or pelvic injuries with acute hemorrhage. Accordingly, pre-hospital GCS were also lower in patients with non-preventable deaths. At hospital admission, GCS were similar between the two groups due to shock or on-going sedation. MGAP score and TRISS scores were also most severe in these patients. Regarding the time course of preventable/potentially preventable deaths, the proportion of patients with preventable deaths remained stable from 2009 to 2014. Indeed, the rate of preventable/potentially preventable deaths was 28% in 2009 and 25% in 2014 (p=0.43; see Supplemental File N°2).

We reported 170 errors in 108 patients (92 errors in preventable deaths and 78 errors in potentially preventable deaths, Table 2). Errors were both described in the pre-hospital setting and in the in-hospital phases. Excessive pre-hospital time was the prominent error found for preventable deaths whereas triage errors and omission of essential procedures were the most frequent types of error for potentially preventable deaths. Using the classification of errors in the JCAHO taxonomy, errors in clinical performance were prominent. They mainly occurred during the diagnostic process or within the therapeutic procedure (Table 3) and consisted of incorrect procedures or delayed correct procedures. Regarding the setting of errors, most of them were found in the pre-hospital phase (Table 4). Main errors consisted of inadequate triage (failure in diagnosis) or excessive pre-hospital time. Errors could also occur in the trauma bay or in the operating room and were related to inappropriate diagnostic procedures. For instance, we reported 24 errors in the operating room for 23 patients. Three types of errors were found: excessive delay for surgery, technical difficulties, wrong procedures or failure to perform damage control procedures. Regarding timing of surgery, these errors concerned a delayed evacuation of a subdural hematoma, or delayed laparotomies. Regarding technical difficulties, we found an injury of the mesenteric artery and an iliac venous wound. Regarding therapeutic mistakes, some laparotomies were unjustified because of negative FAST. In other cases, some procedures were carried out not respecting damage control rules: operating time too long, complete abdominal parietal closure, no pelvic packing, no peri-hepatic packing, or no vascular damage control on lower limbs. Wrong procedures in this context were incorrect surgical incisions like sternotomy for a thoracic damage control surgery. The main cause of error was human failure, specifically knowledgebased and rule-based errors. These mistakes were related to an inadequate observance or an ignorance to established instructions or protocols (Table 5), for instance, performing CT scan in hemodynamically unstable patients.

Prevention or mitigation of errors required an improvement of communication among caregivers (Supplemental File N°3). This prevention measure lies upon regular meetings between anesthesiologists, emergency physicians, radiologists and trauma surgeons to discuss morbidity and mortality. Prevention or mitigation of errors is also based upon the diffusion of procedures within the trauma network. Selective measures, like eliminating wrong procedures, were less frequently necessary to avoid errors in prehospital triage or to establish the appropriate surgical technique in the operating room.

Discussion

The analysis of mortality is mandatory to evaluate the efficiency of a trauma system and the rate of preventable or potentially preventable deaths is increasingly used as a benchmark of patient safety reporting in trauma systems across the world. Over a 6-year period including 7,484 trauma patients, we found 170 errors in 108 preventable/potentially preventable deaths among 503 deaths in our regional trauma system. Using a common classification, the prominent type of error was a failure in clinical performance of physicians in the prehospital setting or in the trauma bay. These mistakes were mainly made during diagnostic or therapeutic procedures and the majority of errors were related to rule-based or knowledge-based failures.

Improving the quality of care in mature trauma systems is the ultimate goal of these organizations. The first step to perform such improvement is undoubtedly linked to the recognition of errors, which prompts corrective actions to limit future potential failures [START_REF] Vioque | Classifying errors in preventable and potentially preventable trauma deaths: a 9-year review using the Joint Commission's standardized methodology[END_REF].

Despite this well-known concept, few studies addressed appropriately the challenge of errors' classification. In the United States, the Pennsylvania trauma system and the Virginia Commonwealth University Medical Centre used the JACHO classification for errors reporting [START_REF] Vioque | Classifying errors in preventable and potentially preventable trauma deaths: a 9-year review using the Joint Commission's standardized methodology[END_REF][START_REF] Ivatury | Patient safety in trauma: maximal impact management errors at a level I trauma center[END_REF], while others used their own classification [START_REF] Teixeira | Preventable morbidity at a mature trauma center[END_REF][START_REF] Esposito | Analysis of preventable trauma deaths and inappropriate trauma care in a rural state[END_REF]. The disparity of error reporting does not facilitate comparisons between trauma systems whereas trauma procedures may be optimized by such analysis. In Europe, the JACHO taxonomy was also used in the United Kingdom and Spain to categorize errors during the management of severe trauma patients [START_REF] Montmany | Preventable deaths and potentially preventable deaths. What are our errors?[END_REF][START_REF] Pucher | Identifying and addressing preventable process errors in trauma care[END_REF]. Our study adds to a small body of literature regarding classification of avoidable errors in preventable trauma deaths. Preventable or potentially preventable deaths account from 6% to 27% of deaths in trauma systems [START_REF] Teixeira | Preventable or potentially preventable mortality at a mature trauma center[END_REF][START_REF] Vioque | Classifying errors in preventable and potentially preventable trauma deaths: a 9-year review using the Joint Commission's standardized methodology[END_REF][START_REF] Ivatury | Patient safety in trauma: maximal impact management errors at a level I trauma center[END_REF]. With 21% of preventable/potentially preventable deaths, our study displayed poor performance of our trauma system according to the existing literature. The variability of these preventable deaths relies upon the efficiency of trauma system but also upon the methodology used by the adjudication committee. Similarly, the vast majority of previously published reports reviewed patients' files with an expert panel to decide whether trauma death was categorized as preventable, potentially preventable or non-preventable [START_REF] Teixeira | Preventable morbidity at a mature trauma center[END_REF][START_REF] Ivatury | Patient safety in trauma: maximal impact management errors at a level I trauma center[END_REF]. This methodology did not account for uncertainty in the classification of potentially preventable death, and using a 100point scale, Kobewka et al showed that only 5 of 31 deaths classified as a "possibly preventable" were judged to likely be alive in 3 months with perfect care [START_REF] Kobewka | The prevalence of potentially preventable deaths in an acute care hospital: A retrospective cohort[END_REF]. In our study, we had only 7% of preventable deaths whereas 14% of deaths were judged as potentially preventable by the expert committee. The high proportion of preventable/potentially preventable deaths in our study was probably related to the high proportion of potentially preventable deaths that was subjected to uncertainty. Alternatively, the proportion of preventable deaths was similar to other studies and overall mortality (6.7%) in the TRENAU was also comparable.

In our study, we found 170 errors occurring in 108 preventable/potentially preventable trauma deaths. Interestingly, the setting of these errors was mainly in the prehospital field.

On-scene treatment and diagnosis were performed by emergency physicians in our trauma system [START_REF] Bouzat | Trauma network for severely injured patients[END_REF] and such findings challenged the performance of pre-hospital medical teams. The main error was excessive pre-hospital time, based on a one-hour time-lapse. It should be noted that the French prehospital organization is different from the US prehospital system. In France, emergency physicians are in charge of the prehospital management of severe trauma whereas paramedics lead this management in the US. Such difference may explain longer stay in the prehospital field where on-site damage control resuscitation can be provided. Another frequent mistake was an inadequate triage due to ignorance of existing guidelines in our network [START_REF] Bouzat | A regional trauma system to optimize the pre-hospital triage of trauma patients[END_REF]. These findings highlight the need for continuous education of pre-hospital physicians but also do not reflect actual knowledge of prehospital doctors as intense education regarding damage control resuscitation has only been done since recent French terrorist attacks [20]. Moreover, the TRENAU network is located in a mountainous area where conditions for pre-hospital teams may be hazardous [START_REF] Bouzat | Trauma network for severely injured patients[END_REF]. These geographical considerations may account for inherent excessive pre-hospital time due to extreme conditions or complex extraction. In the trauma bay or in the operating room, we also found errors mainly related to omissions of essential procedure. For instance, unstable patients have been transferred for CT scanning or damage control protocols have not been applied. These errors were surprising since intra-hospital management might be seen as a more controlled scenario. They occurred within the trauma bay or within the operating room and most common errors were clinical and mainly therapeutic. These failures were observed in trauma leaders who did not comply or ignored established protocols. Although meetings were frequently organized between emergency physicians, anesthesiologists, trauma surgeons and radiologists from 2009 to 2014, these findings proved that the diffusion of procedures remained challenging in trauma centers.

Accordingly, prevention of errors was mainly based upon improving communication between caregivers to ensure adequate compliance to procedures and protocols. These universal measures were more frequent than selective measures directed to different subgroup of trauma patients. Of note, the human factor was highly involved in these mistakes. This finding highlighted the critical importance of effective teamwork and communication in delivering a high-quality patient care. Our findings also highlight the importance of initial and continuous training in trauma care for anesthesiologists, surgeons, and emergency physicians. Several university diplomas for severe trauma management exist in France and the compliance to procedures may be enhanced by such initiatives.

We acknowledge several limitations of our study. First, the number of deaths was relatively small and only 170 errors were described. Nevertheless, the study size was similar to previously published works and a 6-year analysis allowed us to cover a large period of time within our trauma system. Second, our methodology to categorize deaths was based upon an adjudication committee composed by two anesthesiologists and two trauma surgeons. This method does not account for uncertainty in categorization and may have contributed to excessive number of potentially preventable deaths. However, the JACHO taxonomy was applied and the classification of errors was reliable enough to allow comparisons between trauma systems.

Conclusions

With our 6-year retrospective study, we demonstrated that preventable or potentially preventable deaths were related to avoidable errors in the prehospital field or in the trauma bay. These errors were attributed to physicians who ignored essential procedures regarding diagnosis or therapy. These results confirm that preventable deaths are an indicator of quality of care in an organized trauma system. Efforts should be made to reduce their prevalence and the first step is probably to improve communication among caregivers. Apart from selfevaluation, describing errors is also helpful for determining the best management of severe trauma patients in developed countries. Note: One preventable/potentially preventable death may be related to more than one error, so that sum totals of errors exceed the number of deaths. *Failures that are beyond the control and responsibility of the organization †Failures related to patient characteristics or actions that are beyond the control of the practitioner ‡Failure to perform at the level of competence consistent with professional norms of practice and operation §Intentional deviation from professional norms of good practice and operation without cause Note: Cause parameters can overlap so that errors can be categorized in more than one category

Table 1 .

 1 Population characteristics

	Variable	Deaths	Non-preventable	Preventable or
		(n=503 patients)	deaths (n=395 patients)	potentially preventable deaths (n=108 patients)

Table 2 .

 2 Analysis of errors by the adjudication committee

	Preventable deaths	Potentially	Total
	n=72 patients	preventable deaths	n=108 patients
		n=36 patients

Table 3 .

 3 Types of error according to JCAHO taxonomyNote: Errors may involve multiple categories, sum totals do not equal 170.

	Types of errors	Number
	Communication
	Inaccurate & incomplete information	19
	Questionable advice or interpretation	7
	Questionable documentation	5
	Patient Management
	Questionable tracking or follow-up	16
	Questionable referral or consultation	20
	Questionable use of resources	64
	Clinical performance
	Diagnostic (pre-intervention)
	Correct diagnosis, questionable intervention	2
	Inaccurate diagnosis	4
	Incomplete diagnosis	29
	Intervention
	Correct procedure, with complication	2
	Correct procedure, incorrectly performed	5
	Correct procedure, but untimely	36
	Omission if essential procedure	17
	Procedure contraindicated	9
	Procedure not indicated	2
	Post-intervention
	Questionable prognosis	5

Table 4 .

 4 Domain of error according to JCAHO taxonomy Domain parameters can overlap so that errors can be classified in more than one category

	Domain of errors	Number
	Setting
	Emergency department	10
	Diagnostic procedures (Crash room)	40
	Operating room	24
	Interventional radiology	5
	Pre-Hospital care	82
	Intensive care unit	8
	Staff
	Physician	165
	Nurse/paramedics	5
	Target
	Therapeutic	105
	Diagnostic	41
	Other	24
	Note:

Table 5 .

 5 Cause of error according to JCAHO taxonomy

	Cause of error

Acknowledgements

The authors thank the investigators of the TRENAU network for implementing the registry.

Availability of data and supporting materials section: the authors can share their data if requested by any reader of the present study.

Fundings: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors

Competing interest

The authors declare that they have no competing interest.

Declarations

The Regional Institutional Ethics Committee approved the implementation of the TRENAU registry (Comité d'Ethique des Centres d'Investigation Clinique de l'inter-région Rhône-Alpes-Auvergne, IRB number 5891) and, given its observational nature, waived the requirements for written informed consent from each patient Consent for publication: not applicable.