Elisabetta Filomena Buonaguro

Sara Morley-Fletcher

Camilla Avagliano

Licia Vellucci

Felice Iasevoli

Hammou Bouwalerh

Gilles Van Camp

Ferdinando Nicoletti

Stefania Maccari

Andrea De Bartolomeis

Prof Stefania Maccari

Glutamatergic postsynaptic density in early life stress programming: Topographic gene expression of mGlu5 receptors and Homer proteins

Keywords: Synapse, Stress, Early life programming, Animal model, Gene expression

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Introduction

Stress-related disorders are a major public health issue [START_REF] Alonso | Overview of key data from the European Study of the Epidemiology of Mental Disorders (ESEMeD)[END_REF][START_REF] Lepine | The epidemiology of anxiety disorders: prevalence and societal costs[END_REF]. Stress causes profound changes in excitatory and inhibitory synaptic transmission; these have been investigated in various animal models (de [START_REF] De Bartolomeis | Immediate-Early Genes Modulation by Antipsychotics: Translational Implications for a Putative Gateway to Drug-Induced Long-Term Brain Changes[END_REF] but only rarely in humans [START_REF] Shcheglovitov | SHANK3 and IGF1 restore synaptic deficits in neurons from 22q13 deletion syndrome patients[END_REF]. However, animal studies oversimplify pathologies that are uniquely human, such as psychiatric disorders.

Proteins of the postsynaptic density (PSD) play a major role in the synaptic response to stress. PSD is a thickening of the glutamatergic synapse that comprises a complex of receptors, scaffolding, and adaptor proteins; it acts as a multimodal hub for multiple cellular signaling [START_REF] Lum | Neurodevelopmental Expression Profile of Dimeric and Monomeric Group 1 mGluRs: Relevance to Schizophrenia Pathogenesis and Treatment[END_REF][START_REF] Soler | Genetic variability in scaffolding proteins and risk for schizophrenia and autism-spectrum disorders: a systematic review[END_REF]. The PSD protein network fine-tunes signal transduction, integrating synaptic signals from presynaptic neurons and different neurotransmitter systems [START_REF] Collins | Molecular characterization and comparison of the components and multiprotein complexes in the postsynaptic proteome[END_REF][START_REF] De Bartolomeis | Dopamine-glutamate interaction and antipsychotics mechanism of action: implication for new pharmacological strategies in psychosis[END_REF][START_REF] Gold | A frontier in the understanding of synaptic plasticity: solving the structure of the postsynaptic density[END_REF][START_REF] Sheng | The postsynaptic architecture of excitatory synapses: a more quantitative view[END_REF]. N-Methyl-D-Aspartate (NMDA) receptors, type-I metabotropic glutamate receptors (mGlu1 and mGlu5), and their interacting proteins (Homers) are integral components of the PSD. They have been implicated in stress-induced alterations [START_REF] Palmfeldt | Protein biomarkers of susceptibility and resilience to stress in a rat model of depression[END_REF]. The induction of Homer1a, an immediate earlygene member of the Homer1 family that is involved in glutamate-mediated synaptic plasticity, is part of the mechanism of action of several antidepressant and antipsychotic treatments (Buonaguro et al., 2017a, Buonaguro et al., 2017b[START_REF] De Bartolomeis | Switching antipsychotics: Imaging the differential effect on the topography of postsynaptic density transcripts in antipsychotic-naive vs. antipsychotic-exposed rats[END_REF][START_REF] De Bartolomeis | Imaging brain gene expression profiles by antipsychotics: region-specific action of amisulpride on postsynaptic density transcripts compared to haloperidol[END_REF][START_REF] Iasevoli | Regulation of postsynaptic plasticity genes' expression and topography by sustained dopamine perturbation and modulation by acute memantine: relevance to schizophrenia[END_REF][START_REF] Serchov | Signaling pathways regulating Homer1a expression: implications for antidepressant therapy[END_REF]. The constitutively expressed splice variants of Homer proteins (e.g., Homer1b and Homer1c) link mGlu5 to the intracellular signaling machinery and mediate the ligand-dependent activity of mGlu5 [START_REF] Brakeman | Homer: a protein that selectively binds metabotropic glutamate receptors[END_REF]. Homer1b and other long isoforms of Homer link mGlu5 to NMDA receptors and various signaling molecules, such as inositol-1,4,5-trisphosphate receptors and transient receptor potential ion channels [START_REF] Bertaso | Homer1a-dependent crosstalk between NMDA and metabotropic glutamate receptors in mouse neurons[END_REF][START_REF] De Bartolomeis | Calcium-dependent networks in dopamine-glutamate interaction: the role of postsynaptic scaffolding proteins[END_REF][START_REF] Tu | Homer binds a novel proline-rich motif and links group 1 metabotropic glutamate receptors with IP3 receptors[END_REF][START_REF] Yuan | Homer binds TRPC family channels and is required for gating of TRPC1 by IP3 receptors[END_REF]. In contrast, the short Homer isoform, Homer1a, which is produced by an immediate early gene, acts as a negative dominant signaling molecule, disrupting mGlu5/Homer1b coupling and modulating ligandindependent mGlu5 signaling [START_REF] Ango | Agonist-independent activation of metabotropic glutamate receptors by the intracellular protein Homer[END_REF]. Therefore, Homer1 moderates the NMDA/mGlu5 complex [START_REF] Bertaso | Homer1a-dependent crosstalk between NMDA and metabotropic glutamate receptors in mouse neurons[END_REF], Tu et al., 1999), which is involved in the activity of the glutamate synapse.

A growing body of evidence suggests that abnormalities of glutamatergic transmission are involved in the regulation of emotions and stress response [START_REF] Chen | Bi-directional effect of cholecystokinin receptor-2 overexpression on stress-triggered fear memory and anxiety in the mouse[END_REF][START_REF] Luoni | Delayed BDNF alterations in the prefrontal cortex of rats exposed to prenatal stress: preventive effect of lurasidone treatment during adolescence[END_REF][START_REF] Musazzi | The action of antidepressants on the glutamate system: regulation of glutamate release and glutamate receptors[END_REF][START_REF] Popoli | The stressed synapse: the impact of stress and glucocorticoids on glutamate transmission[END_REF][START_REF] Vyas | Chronic stress induces contrasting patterns of dendritic remodeling in hippocampal and amygdaloid neurons[END_REF]. Acute stress-induced release of glucocorticoids enhances extracellular glutamate levels in the hippocampus and prefrontal cortex [START_REF] Bagley | Temporal dynamics of glutamate efflux in the prefrontal cortex and in the hippocampus following repeated stress: effects of pretreatment with saline or diazepam[END_REF]Moghaddam 1997, Yuen et al., 2009), thereby influencing some aspects of cognitive processing in rodents (Danysz et al., 1995, Robbins and[START_REF] Robbins | Behavioural pharmacology: 40+ years of progress, with a focus on glutamate receptors and cognition[END_REF]. The effects of chronic stress on glutamate release are still mostly unknown, although the few available studies have suggested that chronic stress can reduce glutamate release [START_REF] Moghaddam | Stress activation of glutamate neurotransmission in the prefrontal cortex: implications for dopamine-associated psychiatric disorders[END_REF][START_REF] Popoli | The stressed synapse: the impact of stress and glucocorticoids on glutamate transmission[END_REF]. Furthermore, abnormalities of the glutamatergic system may persist in adult animals exposed to stressful manipulation during the perinatal period [START_REF] Jia | Alterations of Group I mGluRs and BDNF Associated with Behavioral Abnormity in Prenatally Stressed Offspring Rats[END_REF][START_REF] Sun | Phospholipase Dmediated hypersensitivity at central synapses is associated with abnormal behaviours and pain sensitivity in rats exposed to prenatal stress[END_REF], Zhang et al., 2013), suggesting that adult vulnerability to stress-related diseases may be programmed during perinatal life [START_REF] Barker | Mechanisms of disease: in utero programming in the pathogenesis of hypertension[END_REF][START_REF] Maccari | The consequences of early-life adversity: neurobiological, behavioural and epigenetic adaptations[END_REF]. The rat model of perinatal stress (PRS) has been widely used to investigate stress-related alterations. Recently, we showed profound and persistent impairment of glutamatergic neurotransmission in PRS rats [START_REF] Laloux | Anxiety-like behaviour and associated neurochemical and endocrinological alterations in male pups exposed to prenatal stress[END_REF], Marrocco et al., 2012[START_REF] Marrocco | The effects of antidepressant treatment in prenatally stressed rats support the glutamatergic hypothesis of stressrelated disorders[END_REF], Zuena et al., 2008), characterized by impaired synaptic activity and reduced depolarization-evoked glutamate release in the ventral hippocampus. Defective glutamate transmission has been causally related to reduced risk-taking behavior [START_REF] Morley-Fletcher | The reduction in glutamate release is predictive of cognitive and emotional alterations that are corrected by the positive modulator of AMPA receptors S 47445 in perinatal stressed rats[END_REF], and it is associated with severe reduction in synaptic vesicle-associated proteins [START_REF] Marrocco | Anxiety-like behavior of prenatally stressed rats is associated with a selective reduction of glutamate release in the ventral hippocampus[END_REF]. This deficit at the presynaptic level can be corrected by long-term treatment with antidepressants or carbetocin agonists [START_REF] Mairesse | Activation of presynaptic oxytocin receptors enhances glutamate release in the ventral hippocampus of prenatally restraint stressed rats[END_REF][START_REF] Marrocco | The effects of antidepressant treatment in prenatally stressed rats support the glutamatergic hypothesis of stressrelated disorders[END_REF][START_REF] Morley-Fletcher | The reduction in glutamate release is predictive of cognitive and emotional alterations that are corrected by the positive modulator of AMPA receptors S 47445 in perinatal stressed rats[END_REF]. However, to date, no investigations have focused on how PRS can shape synapse architecture at the postsynaptic level or in different brain regions.

Therefore, the present study aimed to investigate the long-term molecular characteristics of PRS rats, focusing on the expression of genes linked to glutamatergic signaling and synaptic plasticity at the level of the PSD, such as Homer1a, Homer1b, and Grm5. We performed a topographic study to explore expression of the above-mentioned transcripts, using in situ hybridization in different brain regions related to the stress response to obtain quantitative and qualitative data on gene expression.

Finally, we evaluated the relationship between risk-taking behavior and transcript expression within discrete brain subdivisions.

Materials and Methods

Animals

Nulliparous female Sprague-Dawley rats weighing approximately 250 g were housed in the presence of a sexually experienced male rat. A sperm-positive vaginal smear was used to determine embryonic day 0 (E0). Pregnant females were then individually housed under controlled temperature (22°) and humidity (60%) conditions, with ad libitum access to food and water. They were kept under a regular 12-hour light/dark cycle (on at 07:00, off at 19:00). At E11, pregnant rats were randomly assigned to gestational stress and control groups. All animal experiments were carried out in accordance with EU Directive 2010/63/EU for animal experiments.

Gestational stress procedure (perinatal stress in offspring)

Restraint stress was induced according to a previously described protocol [START_REF] Maccari | Adoption reverses the long-term impairment in glucocorticoid feedback induced by prenatal stress[END_REF][START_REF] Morley-Fletcher | Environmental enrichment during adolescence reverses the effects of prenatal stress on play behaviour and HPA axis reactivity in rats[END_REF]. The local ethical committee CEEA-75 (Comité d'Ethique en Expérimentation Animale Nord-Pas de Calais, 75) approved the gestational restraint procedure.

Female pregnant rats at E11 were subjected to three 45-minute stress sessions daily until delivery.

The sessions started at 09.00, 12.00, and 17.00. Specifically, they were placed in transparent plastic cylinders and exposed to bright light. Control dams were left undisturbed in their home cages.

In both groups, the litters used contained between 8 and 14 pups. Offspring were weaned 21 days after birth and left undisturbed until adulthood (4 months). The study was conducted on male offspring rats only.

Behavioral analysis

Risk-taking behavior was assessed in the light/dark test (n=5 rats/group). The light/dark box apparatus consisted of two asymmetrical compartments: one dark compartment (5 lx; 30 × 32 × 32 cm;) and one light compartment (50 lx; 45 × 32 × 32 cm). A small opening (10 × 15 cm) connected the two compartments, thus enabling transition between the two boxes. The adult (4-month old) male PRS and control rats (n = 5 per group) were tested. Animals were housed in the testing room for 2 hours before the beginning of the test to enable adaptation to the new environment. The 5minute test started when the animal was placed in the light compartment. A video camera located above the box recorded (1) the latency to the first spontaneous entry into the light compartment once the animal had entered the dark compartment, (2) the time spent in each compartment, and (3) the number of transitions to each compartment (data not shown). Scoring was performed by a trained observer using The Observer® (Noldus, The Netherlands). Of note, we used the term "risktaking" behavior instead of "anxiety-like behavior" because, in our opinion, this term reflects the nature of the behavioral test. "Anxiety" refers to a complex pathology in which a reduced risktaking is only one aspect. Thus, we prefer to avoid the term "anxiety-like behavior" for a reduced risk-taking behavior in the light-dark test although we are aware that the test has pharmacological validity for the study of anxiolytic agents.

In situ hybridization

For gene imaging topography, radioactive in situ hybridization was performed according to previously published protocols [START_REF] Ambesi-Impiombato | Method for quantitative in situ hybridization histochemistry and image analysis applied for Homer1a gene expression in rat brain[END_REF]. Animals (n=5 rats/group) were sacrificed by decapitation and their brains were immediately removed, frozen on powdered dry ice, and stored at -70°C to await sectioning. On a cryostat set at -18°C, serial coronal sections with a thickness of 12 µm were cut through the forebrain at the level of the medial prefrontal cortex (mPFC), the cortex and caudate putamen, the amygdala, and the hippocampus, with reference to the rat brain atlas by [START_REF] Paxinos | The Rat Brain in Stereotaxic Coordinates[END_REF] (Figure 1). The sections were then thaw-mounted on to gelatin-coated slides and stored at -70°C for subsequent analysis.

Radioactive in situ hybridization was carried out using oligodeoxyribonucleotide probes that were complementary with the mRNA sequences of the target genes (MWG Biotech, Italy) (Table 1); these were designed based on Gene-Bank sequences and checked using BLAST to avoid crosshybridization. For each probe, a 50-µL labeling reaction mix was prepared on ice using DEPCtreated water, 1x tailing buffer, 7.5 pmol/µL of oligodeoxyribonucleotide, 125 units of terminal deoxynucleotidyl transferase (TdT), and 100 mCi 35 S -dATP. Unincorporated nucleotides were separated from radiolabeled DNA using ProbeQuant G-50 Micro Columns (Amersham-GE Healthcare Biosciences, Italy). Sections were fixed in 4% formaldehyde in 0.12-M PBS (pH 7.4), quickly rinsed three times with PBS, placed in 0.25% acetic anhydride in 0.1 M triethanolamine in 0.9% NaCl (pH 8.0) for 10 minutes, and then dehydrated in 70%, 80%, 95%, and 100% ethanol.

The sections were then delipidated in chloroform for 5 minutes, rinsed again in 100% and 95% ethanol, and finally air-dried. Sections were hybridized using 0.4-0.6 x 106 of 2-cpm radiolabeled oligonucleotides in a buffer containing 50% formamide, 600 mM NaCl, 80 mM Tris-HCl (pH 4-7.5), 4 mM EDTA, 0.1% pyrophosphate, 0.2 mg/mL heparin sulfate, and 10% dextran-5 sulfate.

The slides were incubated at 37°C in a humidified chamber for 22-24 hours and subsequently washed twice in SSC/50% formamide at 43ºC-44°C, and then once in SSC at room temperature.

Finally, the sections were dried and exposed to a Kodak-10 Biomax MR autoradiographic film (Sigma, Italy); a slide containing a scale with 16 known amounts of 14 C (ARC-146C; American Radiolabeled Chemical) was co-exposed. The optimal exposure time was chosen to maximize signal-to-noise ratio, but to prevent the optical density from approaching the limits of saturation.

Quantitation of the autoradiographic signal was performed using a computerized image analysis system (ImageJ v. 1.46v; http://rsb.info.nih.gov/ij/). All hybridized sections used for comparative statistical analysis were exposed on the same sheet of X-ray film. Signal intensity analyses were carried out on digitized autoradiograms, and mean optical density was measured within outlined regions of interest (ROIs) in one or the other hemisphere for each section (Figure 1). Measurements of optical density within the ROIs were converted into relative dpm using a calibration curve based on the co-exposed standard scale; 14 C standard values from 4 through 12 were previously crosscalibrated to 35 S brain paste standards. To obtain a calibration curve for each X-ray film, a best fit 3 rd degree polynomial was used. For each animal, measurements from four adjacent sections were averaged, and the final data were reported in relative dpm as mean ± SEM. The whole in situ hybridization procedure was performed blinded with coded frozen brains.

Statistical Analysis

Statistical analyses were performed using JMP9.0.1, SPSS 24.0, and Statistica software. One-way ANOVA (Group: control vs. PRS) was used to analyze behavior, while one-way ANOVA with repeated measures was used to analyze differences in gene expression, with region subdivisions used as within variables. Intergroup comparisons for one-way ANOVA and post-hoc analysis for two-way ANOVA (Group and Brain Region) were performed using the Newman-Keuls test. An independent-sample Student's t-test was performed to analyze differences in relative ratio gene expression levels between PRS and control rats. Correlation between behavioral data and gene expression levels was analyzed using Pearson's correlation analysis. Significance was set at p < 0.05.

Results

Gene expression topography

Homer1a

Statistically significant differences in Homer1a expression were found in different regions between the PRS and control animals. In particular, PRS up-regulated the transcript of Homer1a in both the basolateral amygdala (BLA) and the medial amygdala (MeA; Figure 2

Homer1b

No differences in Homer1b expression were found between PRS and control animals in any of the brain regions, with the exception of the BLA and MeA subdivisions of the amygdala (Figure 2

Relative ratio of gene expression

The biological activity of the mGlu5-Homer1 system critically depends on the relative abundance of the two molecules [START_REF] Kammermeier | Endogenous homer proteins regulate metabotropic glutamate receptor signaling in neurons[END_REF]. For this reason, we determined the ratio of normalized gene expression in PRS and control rats. As shown in Figure 6, Homer1a gene expression in PRS rats was normalized to expression in control rats and compared with either Homer1b or Grm5 transcript expression. In the amygdala, Homer1a expression was higher in PRS rats than in control rats, while the opposite was true for Homer1b and Grm5 transcripts. The relative expression of Homer1a was significantly higher than that of both Homer1b (Student's t-test: t = 3.83, df = 1,8; p = 0.004) and Grm5 (Student's t-test: t = 2.23, df = 1,8; p = 0.05). In the dorsal hippocampus, expression of both Homer1a and Homer1b was higher in controls than in PRS rats, while expression of Grm5 was predominant in PRS rats. A significant difference in relative expression between Homer1a and Grm5 was found in the dorsal hippocampus (Student's t-test: t = 2.43, df = 1,8, p = 0.04). No differences were found between Homer1a and Homer1b in this regard. In all the other regions, expression of Homer1a was higher in controls than in PRS rats, and it was significantly lower than the relative expression of Homer1b and Grm5 (Figure 6).

Risk-taking behavior

As shown in Figure 7, PRS rats showed reduced risk-taking behavior in the light/dark test, as indicated by the reduced time spent in the light box compared with the controls (Group effect: F[1,8] = 28.383, p < 0.01). The latency before the first spontaneous entry into the light box was higher in the controls than in the PRS rats (Group effect: F[1,8] = 6.449; p < 0.05; 54.5 ± 3.9 seconds vs 34.6 ± 6.8 seconds). No significant difference was found between the groups in terms of the number of light/dark transitions (data not shown).

Correlations between gene expression and risk-taking behavior

All PRS and control rats used in the topographical analysis of gene expression (n = 5 rats per group) had been previously tested for risk-taking behavior in the light/dark test. In each animal in each group, we examined the correlation between time spent in the light box and relative gene expression in each brain region and subdivision (Figures 8910). Homer1a expression was correlated with risktaking behavior in all brain regions other than the cortex. In the amygdala, the correlation was negative (Pearson's correlation analysis, r = -0.66; p < 0.05), while in all other brain regions, we observed positive correlations (Figures 9 and10 Pearson's correlation analysis: r = 0.65; p < 0.05).

Discussion

The goal of this study was to evaluate whether exposure to perinatal stress can shape synapse architecture at the postsynaptic level and in different brain regions linked to stress and stress-prone behavioral disorders; in this way, we aimed to expand and complete our previous data of impaired presynaptic architecture [START_REF] Mairesse | Activation of presynaptic oxytocin receptors enhances glutamate release in the ventral hippocampus of prenatally restraint stressed rats[END_REF], Mairesse et al., 2012, Marrocco et al., 2012[START_REF] Marrocco | The effects of antidepressant treatment in prenatally stressed rats support the glutamatergic hypothesis of stressrelated disorders[END_REF]. To this end, we specifically focused on the genes encoding the mGlu5 and Homer proteins because the mGlu5 play a role in resilience to stress [START_REF] Shin | mGlu5 in the nucleus accumbens is critical for promoting resilience to chronic stress[END_REF][START_REF] Wagner | Homer1/mGlu5 activity moderates vulnerability to chronic social stress[END_REF][START_REF] Sun | Hippocampal GR-and CB1-mediated mGlu5 differentially produces susceptibility and resilience to acute and chronic mild stress in rats[END_REF][START_REF] Schwendt | A novel rat model of comorbid PTSD and addiction reveals intersections between stress susceptibility and enhanced cocaine seeking with a role for mGlu5 receptors[END_REF][START_REF] Yim | Differential mGlu5 expression in response to the same stress causes individually adapted hippocampal network activity[END_REF].

We found that PRS affected the expression patterns of Homer1a, Homer1b, and Grm5 in the central nervous system. A major finding was that the expression pattern of the three genes differed between the amygdala and all other regions examined, with PRS enhancing Homer1a expression exclusively in the amygdala. In contrast, Grm5 and Homer1b expression were higher than Homer1a expression in all other brain regions. Homer1a is the product of an immediate early gene and acts as a master regulator of mGlu5 function. Up-regulation of Homer1a disrupts mGlu5-Homer1b, interactions, thereby restraining all signaling mechanisms that rely on long Homer-mediated protein-to-protein interaction, such as intracellular Ca 2+ mobilization [START_REF] Mao | The scaffold protein Homer1b/c links metabotropic glutamate receptor 5 to extracellular signal-regulated protein kinase cascades in neurons[END_REF][START_REF] Roche | Homer 1b regulates the trafficking of group I metabotropic glutamate receptors[END_REF].

These findings may have important implications for our understanding of the role played by different brain regions in the overall response to stress. The positive ratio between Homer1a and mGlu5/Homer1b in the amygdala suggests that PRS causes long-lasting impairment of canonical mGlu5 signaling-i.e., coupling between mGlu5 activation and intracellular Ca 2+ mobilization resulting from local activation of InsP3 receptors. This might favor mGlu5 signaling via Homerindependent mechanisms, such as the opening of voltage-sensitive Ca 2+ channels, or arrestindependent activation of MAP kinase or phosphatidylinositol-3-kinase pathway during receptor desensitization and internalization. The opposite scenario may take place in the other brain regions, where expression of the genes encoding Homer1b and mGlu5 was greater than that of the genes encoding Homer1a in PRS rats.

Another interesting finding was the correlation between changes in Grm5/Homer expression and behavioral abnormalities in PRS rats. Specifically, PRS rats spent less time in the light box than unstressed controls, confirming the characteristic phenotype of reduced risk-taking behavior previously observed in the PRS rat model [START_REF] Marrocco | Anxiety-like behavior of prenatally stressed rats is associated with a selective reduction of glutamate release in the ventral hippocampus[END_REF][START_REF] Morley-Fletcher | Chronic agomelatine treatment corrects behavioral, cellular, and biochemical abnormalities induced by prenatal stress in rats[END_REF], Zuena et al., 2008). Interestingly, we found that Homer1a expression in the amygdala was inversely correlated with time spent in the light compartment of the light/dark box, and that expression of Homer1b and Grm5 was positively correlated. In contrast, in most subregions of the dorsal hippocampus, mPFC, and neostriatum, Homer1a gene expression was positively correlated with time spent in the light compartment.

The amygdala is one of the brain regions most involved in stress-related disorders, and its overactivation [START_REF] Shin | The neurocircuitry of fear, stress, and anxiety disorders[END_REF] combined with Homer1a overexpression [START_REF] Mahan | Epigenetic modulation of Homer1a transcription regulation in amygdala and hippocampus with pavlovian fear conditioning[END_REF], play a central role in fear conditioning. Accordingly, Homer1a knockout mice showed impaired long-term fear memory formation [START_REF] Inoue | Requirement of the immediate early gene vesl-1S/homer-1a for fear memory formation[END_REF]. With regards to the present study, the increased Homer1a expression found in the amygdala of PRS rats suggests that these rats are more prone to developing fear memory in response to stress, which is consistent with the reduced risktaking behavior. Moreover, because Homer1a expression is a marker for neuronal depolarization [START_REF] Hu | Homeostatic scaling requires group I mGluR activation mediated by Homer1a[END_REF], persistent overexpression of Homer1a in the amygdala of PRS rats may reflect sustained neuronal activation in this region, which is associated with stress-related behaviors [START_REF] Ressler | Amygdala activity, fear, and anxiety: modulation by stress[END_REF]. Indeed, we have previously shown increased neuronal reactivity in the amygdala in PRS rats [START_REF] Mairesse | Prenatal stress alters the negative correlation between neuronal activation in limbic regions and behavioral responses in rats exposed to high and low anxiogenic environments[END_REF]. In addition, the present data indicate that PRS modulates the mGlu5-Homer1 interaction, corroborating previous data on Homer1a and Homer1b at the transcript and protein levels in different animal models of stress [START_REF] Ary | Prenatal stress alters limbo-corticostriatal Homer protein expression[END_REF][START_REF] Wagner | Homer1/mGlu5 activity moderates vulnerability to chronic social stress[END_REF].

We were surprised to find that PRS significantly reduced Homer1a mRNA levels in the dorsal hippocampus, because hippocampal Homer1a expression is markedly increased in all hippocampus regions in response to acute stress [START_REF] Clifton | Hippocampal Regulation of Postsynaptic Density Homer1 by Associative Learning[END_REF][START_REF] Qi | Anxiety-related behavioral inhibition in rats: a model to examine mechanisms underlying the risk to develop stress-related psychopathology[END_REF]. In contrast, overexpression of Homer1b/c in the dorsal hippocampus reduces the impairment of spatial object recognition in mice exposed to social defeat stress [START_REF] Wagner | Homer1 mediates acute stress-induced cognitive deficits in the dorsal hippocampus[END_REF]. One possible explanation for our findings is that reduced Homer1a expression in the dorsal hippocampus and other brain regions of PRS rats represents a defensive mechanism that supports canonical mGlu5/Homer1b/c signaling, thereby avoiding robust abnormalities in activity-dependent synaptic plasticity, spatial memory, and cognitive function in animals exposed to early life stress. Therefore, region-specific Homer1a expression and its impact on mGlu5-Homer1b/c vs. mGlu5-Homer1a signaling may shape the vulnerability of stress-related brain regions to early life events. This influences the developmental trajectory of the hypothalamic-pituitary-adrenal axis and the brain response to stress in the adult life.

In conclusion, the results of gene expression mapping in the present study, as well as the correlation between gene expression and behavior in PRS rats, show that early life events critically influence PSD molecules, which control excitatory synaptic responses and the induction and expression of long-term mechanisms of synaptic plasticity. Overall, the PRS integrated model might be of great value in deciphering the mechanisms of resilience to stress and unraveling the intricate mechanisms that lie at the border between the physiological and pathological responses to stress.

;

  Group effect: F[1, 8] = 5.802; p < 0.05), whereas it significantly reduced Homer1a mRNA levels in other brain regions, with differential effects in various subregions, including the dorsal hippocampus (Figure3; Group effect: F[3,24] = 45.071; p < 0.001 and Group x region subdivisions effect: F[3,24] = 4.020; p < 0.05 for PRS vs. control, with the exception of the CA2 subdivision), the mPFC (Figure4; Group effect: F[1,8] = 9.668; p < 0.05 and Group x region subdivisions effect: F[5,40] = 2.5391; p < 0.05 for PRS vs. control, with the exception of the lateral orbital cortex and secondary motor cortex subregions), the cortex (Figure5; Group effect: F[1,8] = 40.384; p < 0.001 and Group x region subdivisions effect: F[4,32] = 4.023; p < 0.001 for PRS vs. control in all region subdivisions) and the caudate putamen-striatum (Figure5; Group effect: F[1,8] = 63.246; p < 0.001).

  ),where PRS downregulated Homer1b expression (Group effect: F[1,8] = 13.165; p < 0.001).mGlu5Similar to Homer1b, mGlu5 mRNA levels were downregulated by PRS in the amygdala only, as shown in Figure2(Group effect: F[1,8] = 4.843; p < 0.05). No differences were observed in the other brain regions.

  ). Behavior was positively correlated with Homer1b expression in the amygdala (Figure 8; Pearson's correlation analysis: r = 0.81; p < 0.01), cortex (Figure 9B; Pearson's correlation analysis: r = 0.84; p < 0.01), and caudate putamenstriatum (Figure 10). Behavior was positively correlated with Grm5 expression in the amygdala (Figure 8; Pearson's correlation analysis: r = 0.65; p < 0.05) and in the cortex (Figure 9C;

Figure 1 .

 1 Figure 1. Regions of interest for topographical evaluation of gene expression. Medial prefrontal cortex (MO: medial orbital cortex, VO: ventral orbital cortex, LO: lateral orbital cortex, AI: agranular insular cortex, M2: secondary motor cortex, Prl: prelimbic cortex). Amygdala (BLA: basolateral amygdala, MeA: medial amygdala). Cortex and caudate putamen (ACC: anterior cingulate cortex, MAC: medial agranular cortex (premotor cortex), MC: motor cortex, SS: somatosensory cortex, IC: insular cortex, DM: dorsomedial putamen, DL: dorsolateral putamen, VM: ventromedial putamen, VL: ventrolateral putamen, Cab: core of the nucleus accumbens, Sab: shell of the nucleus accumbens). Dorsal hippocampus (DG: dentate gyrus, CA1, CA2, CA3 Ammon's Corn).

Figure 2 .

 2 Figure 2. Autoradiographic film images of Homer1a, Homer1b, and mGlu5 mRNAs detected using in situ hybridization histochemistry in coronal brain sections at the level of amygdala in PRS and control (CONT) rats n=5/group. Levels of mRNA expression are in relative dpm. Values are expressed as means ± SEM *p < 0.05 compared with control.

Figure 3 .

 3 Figure 3. Autoradiographic film images of Homer1a, Homer1b, and mGlu5 mRNA detected using in situ hybridization histochemistry in coronal brain sections at the level of the dorsal hippocampus in PRS and control (CONT) rats (n=5 per group). Levels of mRNA expression are in relative dpm. Values are expressed as means ± SEM. **p < 0.001 compared with control.

Figure 4 .

 4 Figure 4. Autoradiographic film images of Homer1a, Homer1b and mGlu5 mRNAs detected by means of in situ hybridization histochemistry in coronal brain sections at the level of medial Prefrontal Cortex in PRS and control (CONT) unstressed rats (n=5 per group). Levels of mRNA expression are in relative dpm. Values are expressed as means ± SEM. ** p < 0.001 compared with control.

Figure 5 .

 5 Figure 5. Autoradiographic film images of Homer1a, Homer1b, and mGlu5 mRNAs detected using in situ hybridization histochemistry in coronal brain sections at the level of the cortex and caudate putamen in PRS and control (CONT) rats (n=5 per group). Levels of mRNA expression are in relative dpm. Values are expressed as means ± SEM. **p < 0.001 compared with control.

Figure 6 .

 6 Figure 6. Relative ratio of Homer1a vs. Homer1b (upper panel) and of Homer1a vs. mGlu5 (lower panel) mRNA expression in outlined regions of interest (Amy: amygdala, dHPC: dorsal hippocampus, CP: caudate putamen). For each brain region, Homer1a gene expression in PRS rats was normalized to expression in the control group and compared with either Homer1b or mGlu5

Figure 7 .

 7 Figure 7. Risk-taking behavior in the light/dark test in PRS and control (CONT) unstressed rats (n=5 per group). Both time spent in the light box (left) and latency to enter the light box (right) were reduced by PRS. Values are expressed as means ± SEM. * p < 0.05 compared with control.

Figures 8 .

 8 Figures 8. Correlations between risk-taking behavior and gene expression in the amygdalaPearson's correlation analyses between time spent in the light box of the light/dark test and relative dpm for Homer1a, Homer1b, and mGlu5 in PRS and control (CONT) rats.

Figures 9 .

 9 Figures 9. Correlations between risk-taking behavior and gene expression in each region of interest Pearson's correlation analyses between time spent in the light box of the light/dark test and relative dpm for Homer1a in medial prefrontal cortex (A) and dorsal hippocampus (D-F) in PRS and control (CONT) rats. B and C: Pearson's correlation analyses between time spent in the light box of the light/dark test and relative dpm for Homer1b, and mGlu5 in PRS and control (CONT) rats.

Figures 10 .

 10 Figures 10. Correlations between risk-taking behavior and gene expression in striatumPearson's correlation analyses between time spent in the light box of the light/dark test and relative dpm for Homer1a, Homer1b, and mGlu5 in PRS and control (CONT) rats.

Table 1 .

 1 Probes for in situ hybridization histochemistry.

	Probe	cDNA length (bp)	cDNA position	mRNA	Gen-Bank#
	Homer1a	48	2527-2574	Homer1a	U92079
	Homer1b	48	1306-1353	Homer1b/c	AF093268
	mGluR5	48	3005-3053	mGluR5	NM_017012.1

Role of the funding sources

This work was partially supported by the Department of Neuroscience, Reproductive and Odontostomatological Sciences, University Federico II of Naples, Italy, through its own researchdevoted funding to the Laboratory of Molecular Psychiatry (Andrea de Bartolomeis). This study was also supported by the University of Lille, Sapienza University of Rome (Framework Agreement signed on February 15 th , 2007), and the CNRS within the framework of the Prenatal Stress and Neurodegenerative Diseases International Associated Laboratory (LIA-PSND), codirected by Professors S. Maccari (France) and F. Nicoletti (Italy). Behavioral assessments were carried out using the platform PHExMAR of the University of Lille. We are indebted to the Research Federation FRABio (Univ. Lille, CNRS, FR 3688, FRABio, Biochimie Structurale et Fonctionnelle des Assemblages Biomoléculaires) for providing the scientific and technical environment conducive to completing this body of work. English editing was provided by Editing Elsevier services.

Abbreviations

Declaration of interest

None. The funding source had no role in the study design, in the collection, analysis, and interpretation of data, in the writing of the report, and in the decision to submit the article for publication.


A Santandrea

S Pacault

L Perrin

A Vignes

& O Dufaud

Nanopowders explosion: influence of the dispersion characteristics

Keywords: dust explosion, nanopowders, agglomeration, 20L sphere

This work aims to study the influence of the dispersion conditions in a standard 20L sphere on the explosibility of a nanopowder. Even more than for micropowders, the dispersion conditions have a strong impact on the dust cloud homogeneity and its particle size distribution (PSD). Due to their high surface energy, nanoparticles are prone to agglomeration, but such structures can be broken during the dispersion process. Varying the dispersion procedure, the ignition delay time and even the nozzle type (rebound or symmetric) leads to modifications of the dust specific surface area, and thus of its reactivity. Tests were performed on aluminum and carbon black nanopowders. They were characterized before and during their dispersion in the sphere, notably using in situ laser PSD measurement. The initial turbulence level of the dust cloud was determined by particle image velocimetry. A lower shear stress is exerted on the agglomerates by using the symmetric nozzle, which causes less fragmentation and decreases the explosion severity. However, the results obtained with this nozzle are more reproducible than with the rebound nozzle.

Because pre-ignition phenomenon was observed for aluminum nanopowders during their injection through the electrovalve, the dust dispersion by dust lifting was experimented. With regard to the standard procedure, the maximum rate of pressure rise decreased by approximately 30% whereas the maximum overpressure remains nearly unchanged. It means

Introduction

Feedback on accidents involving nanopowders explosions is still rare. However, some accidents involving nanometric powders have already been identified for aluminum in attrition millers (Wu et al., 2010b) or in a Taiwanese laboratory when handling 75 nm titanium particles [START_REF] Wu | Flame phenomena in nanogrinding process for titanium and iron[END_REF]. As for micron-sized particles, a quantitative risk analysis must be conducted in order to propose appropriate prevention and protection means.

However, transposing directly knowledge and practices acquired with microparticles to nanopowders may be questionable. An accurate risk assessment requires consideration of industrial conditions, whereas standardization implies the use of normalized test conditions, which are often different from the former ones. The determination of dust explosibility characteristics is no exception of the rule and it is especially true for nanopowders. Indeed, these powders exhibit specific properties that can challenge the application of the standards and the use of conventional scaling law such as the 'cubic law'.

Previous results show that the ignitability and explosivity of nanopowders vary as a function of the particles physico-chemical properties. Nevertheless, it generally appears that an increase in specific surface area leads to an increase in the ignition sensitivity but does not affect significantly the explosion severity [START_REF] Bouillard | Ignition and explosion risks of nanopowders[END_REF][START_REF] Holbrow | Fire and Explosion Properties of Nanopowders[END_REF]. In the case of metal nanopowders, minimum ignition energies lower than 1 mJ were determined for nano-iron, aluminum and titanium [START_REF] Dufaud | Ignition and explosion of nanopowders: something new under the dust[END_REF][START_REF] Wu | Research of minimum ignition energy for nano Titanium powder and nano Iron powder[END_REF][START_REF] Wu | Fire and explosion risk analysis for nanomaterials[END_REF].

Pyrophoric behaviours can even be observed for iron or aluminum nanopowders, notably as a function of the testing procedures [START_REF] Krietsch | Burning and explosion properties of metallic nano powders[END_REF][START_REF] Krietsch | Explosion behaviour of metallic nano powders[END_REF][START_REF] Mohan | Pyrophoricity of nano-sized aluminum particles[END_REF][START_REF] Sundaram | Pyrophoricity of nascent and passivated aluminum particles at nano-scales[END_REF]. Moreover, several studies demonstrated that a significant increase in explosion severity occurs as the particle size decreases in micron size, but showed a plateau for smaller particle sizes [START_REF] Boilard | Explosibility of micron-and nano-size titanium powders[END_REF][START_REF] Bouillard | Ignition and explosion risks of nanopowders[END_REF][START_REF] Mittal | Explosion characteristics of micron-and nano-size magnesium powders[END_REF][START_REF] Vignes | Risk assessment of the ignitability and explosivity of aluminum nanopowders[END_REF], Dastidar et al., 2013). For carbonaceous compounds of nanosize, their explosibility were found to be rather close to that of micropowders [START_REF] Holbrow | Fire and Explosion Properties of Nanopowders[END_REF][START_REF] Turkevich | Potential explosion hazard of carbonaceous nanoparticles: screening of allotropes[END_REF]. Similarly, when determining the minimum ignition energy (MIE), the minimum explosive concentration (MEC) and minimum ignition temperature (MIT) of carbonaceous nanoparticles, [START_REF] Turkevich | Potential explosion hazard of carbonaceous nanoparticles: Explosion parameters of selected materials[END_REF] found that their explosion parameters were similar to those of coals and usual carbon blacks. More precisely, [START_REF] Bouillard | Ignition and explosion risks of nanopowders[END_REF]showed that the MIT of carbon blacks decreases when the particle size drops but increases when the primary diameter (diameter of an individual particle) of the powder reaches the nano-size range, which is related to very strong inter-particle cohesion forces [START_REF] Eckhoff | Does the dust explosion risk increase when moving from μm-particle powders to powders of nm-particles[END_REF].

Several hypotheses have been put forward to explain these observations: i) as the specific surface area increases, nanoparticles tend to agglomerate which reduces the reactive active surface with oxygen and decreases the explosivity [START_REF] Eckhoff | Are enhanced dust explosion hazards to be foreseen in production, processing and handling of powders consisting of nano-size particles[END_REF]Wu et al., 2010b); ii) the evolution of the particle size distribution (PSD) of the nanoparticles impacts the heat transfer phenomena, especially radiative, taking place upstream of the flame front [START_REF] Dufaud | Ignition and explosion of nanopowders: something new under the dust[END_REF][START_REF] Kosinski | Explosions of carbon black and propane hybrid mixtures[END_REF][START_REF] Sundaram | Pyrophoricity of nascent and passivated aluminum particles at nano-scales[END_REF]; iii) in the case of metal nanopowders, the passivation of the surface can be enhanced with regard to the microparticles [START_REF] Eckhoff | Does the dust explosion risk increase when moving from μm-particle powders to powders of nm-particles[END_REF][START_REF] Sundaram | Pyrophoricity of nascent and passivated aluminum particles at nano-scales[END_REF]; iv) the rate-determining step of the combustion reaction differs from micro to nanopowders [START_REF] Bouillard | Ignition and explosion risks of nanopowders[END_REF]; v) flame stretching effects, which can be observed for large non-volatile particles, are unlikely to be observed for pure nanos [START_REF] Cuervo | Determination of the burning velocity of gas/dust hybrid mixtures[END_REF].

The unique characteristics of nanopowders were also underlined by studying the explosivity of gas/nanoparticles hybrid mixtures. For instance, (Torrado et al., 2017a) demonstrated that the addition of carbonaceous nanopowders to methane does not only impact the oxidation kinetics, but also the heat transfer and, to a lesser extent, the flame stretching. As a consequence, for fuel lean mixtures, the insertion of carbon black nanoparticles to pure gas can increase the explosion pressure [START_REF] Kosinski | Explosions of carbon black and propane hybrid mixtures[END_REF] as well as the maximum rate of pressure rise, especially at high initial turbulence levels (Torrado et al., 2017b).

Recent investigations have also highlighted the specific hazard inherent in handling nanoparticles, in terms of chemical reactivity. For instance, [START_REF] Martin | Aluminum nanopowder: A substance to be handled with care[END_REF] showed that the reaction between sulfuric acid and aluminum powder, which is not considered as highly explosive when performed with microparticles, leads to a violent explosion when a mixture of H2S04 and of Al-nanopowders is ignited by an open flame.

Thus, as it clearly appears that the specificities of the nanopowders can impact their safety parameters, the need to characterize these powders before ignition and to choose wisely the operating conditions of the tests is more and more imperative. Two peculiar cases can be distinguished: that of ignition sensitive metals which are prone to pyrophoricity and that of carbonaceous compounds which are likely to strongly agglomerate. In the first case, alternative testing modes have notably been proposed by [START_REF] Krietsch | Modified setup of 20-l-sphere for the determination of safety characteristics of nano powders[END_REF] for nano aluminum and iron, by placing directly the dust into the explosion chamber and by avoiding the contact between powder and oxygen before injection. In this paper, the method of dust lifting has been used as well as dust injection through a pressurised container. The efficiencies of the standard rebound nozzle and a symmetric one, developed in a previous study [START_REF] Murillo | Proposal of a new injection nozzle to improve the experimental reproducibility of dust explosion tests[END_REF], have also been compared in order to break the agglomerates and approach an 'ideal homogenous dust cloud', or at least, ensure a better homogeneity. As the dispersion conditions have an impact both on the initial turbulence of the dust cloud and on its particle size distribution, it can be interesting to determine the 'best ignition delay time' for each (nanoparticles / operating conditions) couple. The influences of such dispersion conditions on the dust explosivity will be presented for some selected examples based on aluminum and carbon black nanopowders.

Nanomaterials and characterization of their dispersion

Nanomaterials

Two kinds of nanomaterials have been chosen for this study: a carbonaceous powder, Corax N550, and a nano-aluminum with a primary particle diameter of 100 nm. Before dispersing them in the 20L sphere, their particle size distributions were characterized by various means: by wet dispersion in ethanol (Mastersizer, Malvern), by sedimentation in air through in situ granulometric analyses (HelosVario -Sympatec GmbH) or by determining the specific surface area by BET measurements and estimating the 'BET equivalent' diameter.

Results presented in Table 1 show that measurements carried out in wet dispersion lead to agglomerates diameters much larger than those observed by dry dispersion. Obviously, it is irrelevant to use the PSD of a wet sample to characterize the PSD of a dust cloud. Moreover, without using a dispersion system (by gravity fall), the nanopowders remain agglomerated and their size is far from that of their primary diameter, which is close to BET diameter. Scanning Electron Microscopy observations confirm these results, but also reveal that the size of the agglomerates can also vary as a function of time. Indeed, Figure 1a and 1d show the primary particles of respectively carbon black and aluminum, but both tend to agglomerate as shown notably in Figure 1b for Corax N550. It should be stressed that the agglomeration effect is less visible for aluminum. The comparison between Figures 1b (Corax N550, 2017) and 1c (Corax N550, 2006) is also rich in lessons: this is the same powder that has been stored under air for more than ten years. It is clear that, over this period, the size of the agglomerates has been greatly increased (from 100 µm to 1 mm), which is also visually perceptible. Such phenomenon will lead to a modification of the surface area-to-volume ratio of the nanoparticles and then change their properties [START_REF] Yeap | Permanent agglomerates in powdered nanoparticles: Formation and future prospects[END_REF]. Vacuum drying of the powder at 90°C leads to the breaking of the agglomerates, which confirms that the aging is mainly due to the presence of humidity and underlines the role of capillary forces in such agglomerated structures. If a similar aging occurs with Al-nanoparticles, it is less perceptible by SEM observations. It is consistent with [START_REF] Kyrmakova | Influence of long-term storage on fire hazard properties of metal nanopowders[END_REF] results, who found that aging of metal nanoparticles (iron, zinc, copper) lead to changes in their phase composition but also in their flame propagation velocity; no significant changes in terms of reactivity were observed for Al-nanopowders.

Characterization of the dispersed powders

This work aims at determining the influence of the dispersion conditions of the nanopowders on their explosivity. However, two main issues arise. One is related to the metrology of nanoparticles: determining the PSD of nanoparticles over a range from 10 nm (primary particles) to 500 µm (agglomerates), at high concentrations (above the minimum explosive concentration) and with an acquisition frequency of the order of 1 ms is currently technically impossible. Tests have been performed by combining two different techniques: a laser diffraction sensor (Sympatec) for particle size analysis from 0.5 to 175 µm (up to 2 analyses/ms) and a tandem DMA-UCPC for diameters lower than 500 nm (2 min/analysis), Differential Mobility Analyzer (Electrostatic Classifier -TSI 3080) and Ultrafine

Condensation Particle Counter (UCPC -TSI 3776) in series (Torrado et al., 2017b). The other issue is due to the interdependence of the dispersion parameters. By modifying the dispersion nozzle/procedure in the 20L sphere, both the PSD and the initial turbulence is modified, the

a) b) c) d)
two latter parameters being also linked. Therefore, in order to decouple the influences of turbulence and initial particle size, it is necessary to choose the ignition delay adequately.

As previously said in introduction, metallic nanopowders which are very sensitive to ignition, cannot be injected through a pressurized reservoir as they can ignite spontaneously due to high shear forces through the injection ducts and outlet valve [START_REF] Bouillard | Nanoengineering, Global Approaches to Health and Safety Issues[END_REF]. Using such operating procedure may lead to unreliable safety parameters. Consequently, explosion tests have been performed on nanopowders by placing them within the 20L sphere before the gas injection and lifting them through an air pulse. Concurrently, a new nozzle has been proposed in order to improve the homogeneity of the dust cloud and increase the reproducibility of the explosion tests. It is based on the geometry of the standard rebound nozzle for which an axial symmetry has been applied [START_REF] Murillo | Proposal of a new injection nozzle to improve the experimental reproducibility of dust explosion tests[END_REF].

Particle image velocimetry (PIV) -turbulence

The PIV set-up which was used to determine the turbulence level of the dust clouds in the 20L sphere is described by [START_REF] Vizcaya | CFD as an approach to understand flammable dust 20 L standard test: Effect of the ignition time on the fluid flow[END_REF]. The dispersion of dust particles may generate changes in the turbulence of the fluid depending on the diameter of the dust. This influence is determined by the ratio of the turbulence length scale to the particle diameter; hence nanometric dusts do not represent significant variations in macroscopic turbulent flows.

However, they cannot be used as tracers and wheat starch particles (10 µm) were used instead. With regard to the time evolution of the flow turbulence, three stages can be identified: from 0 to 40 ms, the bulk of the dust cloud is characterized by a high turbulence;

from 40 to 120 ms: a 'transition' stage characterized by a decrease of the fluctuations; 120 ms or more: a 'stability [START_REF] Murillo | Proposal of a new injection nozzle to improve the experimental reproducibility of dust explosion tests[END_REF]. Then, it appears that the mean horizontal velocity is not affected by a nozzle change. On the contrary, vertical root-mean-square velocity (vrms) is significantly modified and the initial turbulence level of the dust cloud dispersed through a rebound nozzle is twice that obtained with a symmetric one. Nevertheless, between 60 and 80 ms, there is little difference between the two devices. For comparison, the data obtained by [START_REF] Dahoe | On the Decay of Turbulence in the 20-Liter Explosion Sphere[END_REF] for a rebound nozzle have been plotted in the figure 2.

In situ particle size distribution measurements

In view of the PSD obtained by dispersing the particles in a liquid, it is legitimate to ask whether 'true' nanoparticles are present in the flow during ignition. Tests performed with DMA-UCPC demonstrates that 6 minutes after the dispersion of Corax N550, the mean mobility diameter reaches 370 nm and the total concentration is 1.1×10 5 particles/cm 3 , which confirms that stable nanometric dust cloud is generated during the dispersion phase and is still present a few minutes after the dispersion (Torrado et al., 2017b). The time evolution of the PSD of the dust cloud was observed at the center of the 20 L sphere.

For Corax N550 as well as for aluminum, the mean diameters observed are of the order of 5 µm. Figure 3 shows a very sharp decrease of the d90 -diameter below which 90% of the powder lies -during the first moments of the dust injection. As expected, this evolution is much more marked for the carbonaceous. Moreover, the particle characteristics are more rapidly stable with a symmetrical nozzle and this stability is improved by using dust lifting instead of injection through a reservoir. It should also be underlined that no re-agglomeration phenomenon is visible during the dispersion, neither for aluminum nor for carbon black, which is not the case with powders such as starch [START_REF] Vizcaya | CFD as an approach to understand flammable dust 20 L standard test: Effect of the ignition time on the fluid flow[END_REF].

Figure 4 shows the impact of the injection procedure on the particle size distribution of Corax N550. Firstly, it should be stressed that, when using a nozzle, very few agglomerates are observable over the 10-175 µm diameter range. Therefore, it seems that the dispersion procedure is effective since the average diameter measured by sedimentation is 24 µm. This assertion is confirmed by comparing the PSD obtained with or without any nozzle. In the latter case, agglomerates ranging from 40 to 90 µm are clearly visible, which is not the case when a nozzle is used (rebound or symmetric). However, agglomerates greater than 100 µm are scarce, notably when the dust is injected through the reservoir, which suggests that fragmentation also occurs through the injection duct, due to high shear forces. Apart from a slight shift towards the very small diameters, only few significant modifications are observable when the various injection procedures are used for the carbonaceous powder.

Figure 5 confirms that the aluminum particles are less prone to agglomeration than the carbon blacks, which is visible by the absence of agglomerates greater than 10 µm and the presence of ultrafine particles smaller than 1 µm. When aluminum dust is dispersed through the reservoir, the PSDs are rather similar. Nevertheless, a larger dispersion is visible at 8 ms with the rebound nozzle, which results in the presence of fine particles, with diameters lower than 1 µm, as well as particles greater than 10 µm. On the contrary, the presence of fine particles is more pronounced at 60 ms when a symmetric nozzle is used. When the dust is put within the sphere (dust lifting), two peaks are clearly visible around 2 and 5 µm, which suggest that less fragmentation occurs with this procedure. corresponds to the choice of a couple (PSD, turbulence level). The standards (ASTM E1226-12a, EN 14034 or ISO 6184/1) set a tv and a dispersion procedure. However, it has been proven, and recalled in the introduction, that such procedures must be reconsidered for the nanoparticles due to their specificities, e.g. strong agglomeration for the carbon blacks and pre-ignition (spontaneous ignition during their injection) for aluminum. Experiences have proven that such phenomena can occurs (Figure 6), which makes the standard 20 L protocol questionable, especially for testing highly sensitive nanopowders [START_REF] Bouillard | Nanoengineering, Global Approaches to Health and Safety Issues[END_REF].

Figure 6: Injection reservoir covered with alumina after the pre-ignition of nano-aluminum

The Minimum Ignition Energies (MIE) of Corax N550 and aluminum nanopowders were determined in previous studies [START_REF] Bouillard | Ignition and explosion risks of nanopowders[END_REF] and are respectively greater than 100 J and lower than 1 mJ. With regard to these results, explosion tests have been performed in the 20L sphere with 10 kJ chemical igniters for Corax N550 and 100 J chemical igniters for aluminum, in order to limit the overdriving phenomenon. In addition to the classical safety parameters (Pmax, dP/dtmax, Kst), the combustion gases were analysed by micro-gas chromatography and solid combustion residues were characterized.

Nanopowders explosion: beyond the standards

Explosion of carbon nanoparticles

Aging effect

As shown by Figure 1, the particle size distribution of the Corax N550 was apparently modified when stored under air for more than 10 years. A first set of explosion tests was realized under the same standard conditions at 11 years apart (Figure 7). The maximum explosion overpressure of carbon nanoparticles is not significantly modified by aging.

However, the maximum rate of pressure rise is greatly decreased by the aging of the particles: dP/dtmax drops from 503 bar.s -1 [START_REF] Bouillard | Ignition and explosion risks of nanopowders[END_REF] to 242 bar.s -1 , which is probably due to a change in the PSD. Unfortunately, no in situ measurements were performed in 2006 and it is not possible to compare directly the PSD of the dust cloud at 60 ms, before and after aging.

Nevertheless, it can be argued that, as the agglomerates do not fragment completely during their injection (section 2.2.2) [START_REF] Yeap | Permanent agglomerates in powdered nanoparticles: Formation and future prospects[END_REF], the presence of bigger agglomerates still impacts the final PSD of the carbon nanoparticles in the sphere and thus, reduces the overall surface/volume ratio of the powder and its reactivity. It is consistent with the results presented in Figure 7 as the evolution of the Pm shows that the same amount of powder reacts, but with slower kinetics (dP/dtm). The explosion severity of nanopowders is then governed by their primary particle size and tendency to agglomerate, which is a noticeable difference from micropowders [START_REF] Bouillard | Nanoengineering, Global Approaches to Health and Safety Issues[END_REF].

Influence of the dispersion characteristics

Four different configurations, described in 2.2.3. have been tested. Note that dust lifting with the rebound nozzle will not be shown here for the sake of conciseness. At first, it should be noticed that the explosion overpressures are not significantly modified by a change in the injection procedure (Figure 8). The maximum Pmax is obtained for the standard injection procedure (rebound nozzle, reservoir) and the most notable variations are visible for concentrations greater than stoichiometry. When the carbonaceous powder is injected through the reservoir (standard injection), the maximum rate of pressure rise decreases significantly, from 242 to 173 bar.s -1 , using the symmetric nozzle rather than the rebound nozzle. In addition, a shift of the maximum is observable from 250 to 500 g.m -3 . In parallel, as shown by [START_REF] Murillo | Proposal of a new injection nozzle to improve the experimental reproducibility of dust explosion tests[END_REF], the reproducibility of the explosion tests is greatly increased by the symmetric nozzle. These changes can be correlated to both an increase of the turbulence level and to a slight decrease of the particle size when a rebound nozzle is used. Indeed, Figure 4 shows that finer particles are present at 60 ms when a standard injection procedure is followed. However, it should be stressed that the PSD shown in this figure correspond to a specific location (at the centre of the sphere) and a specific time, and that the PSD as well as the local dust concentration vary greatly as a function of time in the case of the rebound nozzle [START_REF] Murillo | Proposal of a new injection nozzle to improve the experimental reproducibility of dust explosion tests[END_REF]. As the maximum explosion pressure does not vary much, the shift of the (dP/dt)max cannot be due to a decrease of the fuel conversion rate but may be attributed to both PSD and turbulence alterations (Figure 2). Figure 8 also demonstrates that significant changes are noticeable when using different injection procedures with the same nozzle, e.g. the symmetric one. As the turbulence level is not affected by the injection of the powder through the reservoir or the dust lifting (nanoparticles and their agglomerates can be considered as tracers) and as the maximum explosion pressures are not significantly modified, it seems that the PSD evolution is one of the main cause of the explosivity changes. This is partially shown in Figure 4 at the sphere centre, and it is particularly visible by integrating the data over the entire duration of the dispersion. A slight shift in the PSD of the dust cloud can affect both the reaction kinetics (modification of the specific surface area and oxygen accessibility) and the radiative transfer through a dust cloud [START_REF] Cassel | Radiative transfer in dust flames[END_REF], especially when considering the nanoparticles agglomerates.

Explosion of aluminum nanoparticles

The same tests performed on the carbonaceous compounds were performed on aluminum nanoparticles, using the four different configurations of powder injection. In Figure 9, it is clearly visible that, whatever the configuration tested and the concentration, the standard procedure (rebound nozzle and standard injection) always leads to the most important explosion characteristics. However, it should be highlighted that, when the concentration exceeds 750 g.m -3 , this procedure systematically leads to powder ignition within the reservoir, which obviously modifies the reactivity of the dust during its ignition within the sphere.

Contrary to the Corax N550, the maximum overpressure of the Al nanoparticles varies as a function of the injection mode, which raises the question of the full conversion of the powder.

Especially in the case of dust lifting with the symmetric nozzle, Pm decreases at 5.4 bars whereas it reaches 6.5 bars at 750 g.m -3 when the standard procedure is applied. This assertion is confirmed by collecting the dust after combustion at the bottom of the 20 L sphere, where grey crusts composed of both alumina and aluminum can be observed. It is worth noting that the Minimum Explosive Concentration is not significantly modified by the various procedures.

Concerning the maximum rate of pressure rise, the difference between the standard procedures and the other injection modes seems to be increased as the dust concentration increases. It should be underlined that the (dP/dt)max was not identified over the chosen concentration range, whereas the stoichiometry (by considering only the oxidation of aluminum in alumina) is reached at 315 g.m -3 . Other reactions should then be considered such as the nitridation of aluminum at high temperature, which is confirmed by measuring the pressure drop in the 20L sphere after explosion and cooling. Thus, at high dust concentrations, the final pressure is lower than the one obtained by only removing the oxygen, which is due to nitrogen consumption and the generation of aluminum nitride [START_REF] Loryan | Aluminum Combustion in Nitrogen[END_REF]. SEM observations combined with EDX (energy dispersive X-ray spectrometry) performed on the oxidation residues confirm these results. Moreover, dust lifting leads to lower explosivity than with the standard injection procedure. Finally, even if only slight PSD changes occur by using various nozzles and injection procedures with the aluminum powders (Figure 5), significant variations of the dust explosivity are observed. It is consistent with the results obtained by Wu et al. (2010a), who found that if the particle sizes of 35 nm and 100 nm of aluminum powders were comparable after agglomeration, yet their explosive parameters were different. The following assumptions can be proposed: i) the slight PSD modifications and notably the presence of fine particles with diameters lower than 1 µm have a noticeable impact on the evolution of the specific surface area (note that no precise PSD can be given for particle diameter lower than 0.5 µm at such concentrations), ii) the same modification have also an effect on the particles emissivity, which diminishes as the PSD decreases to nanosizes [START_REF] Sundaram | Pyrophoricity of nascent and passivated aluminum particles at nano-scales[END_REF][START_REF] Sundaram | A general theory of ignition and combustion of nano-and micron-sized aluminum particles[END_REF], iii) the injection procedure changes the dust repartition within the sphere, which can influence the flame propagation and the radiative transfer [START_REF] Cassel | Radiative transfer in dust flames[END_REF], iv) the use of different nozzles implies changes in the initial turbulence level (Figure 2), parameter impacting the flame kernel growth and flame front propagation [START_REF] Proust | Flame propagation and combustion in some dust-air mixtures[END_REF]. This last hypothesis was tested by modifying the ignition delay time. should not be forgotten that, during the injection procedure, the 20L is initially vacuumed at 0.4 bar absolute. Hence, for a relative humidity of 0.4, the initial molar percentage of water in the sphere is 0.36%. By considering that water reacts with carbon monoxide at high temperature to generate carbon dioxide and hydrogen, and by using the adequate equilibrium constants [START_REF] Wagman | Heats, free energies, and equilibrium constants of some reactions involving O2, H2, H2O, C, CO, CO2, and CH4[END_REF], the hydrogen concentration can be calculated as a function of the reaction temperature. Conversely, using the hydrogen content and the CO/CO2 ratio determined by chromatography and the calculated H2O content, it is possible to evaluate the equilibrium constant and estimate the corresponding reaction temperature. The results of these calculations are presented in Table 2, as well as the carbon monoxide content. It appears that the greater the turbulence level (low ignition delay time), the greater the carbon monoxide concentration. This might be explained by the heterogeneous repartition of the fuel within the sphere at low tv, which leads to zones at high local fuel equivalent ratio and quenching due to intense turbulence, both phenomena tending to increase the CO content. It should also be kept in mind that the CO/CO2 equilibrium will be shifted to the direction of CO formation when the temperature increases (Table 2). The maximum rate of pressure rise strongly decreases as the ignition delay time increases, e.g. from 704 bar.s -1 at 20 ms to approximately 50 bar.s -1 at 120 ms (low turbulence levels), which confirms that the reactivity of the dust cloud is still enhanced for tv as low as 20 ms.

However, the reproducibility greatly decreases at low tv and flame kernel quenching can also occur at very low ignition delay times. Moreover, it should be stressed that the injection of the dust is still in progress at 20 ms. This augmentation of explosivity is probably related to the turbulence increase 2), which improve the heat and mass transfers, rather than to a PSD variation (Figure 4). The heterogeneity of the dust cloud should also be considered, even if this parameter has not been studied experimentally, its influence was demonstrated by CFD simulations [START_REF] Vizcaya | CFD as an approach to understand flammable dust 20 L standard test: Effect of the ignition time on the fluid flow[END_REF]. Finally, due to their low sedimentation rate and high stability, tests performed at higher tv could lead to the estimation of explosion characteristics of a 'quasi-initially quiescent' dust cloud. By using correlations such as those developed by [START_REF] Silvestrini | Correlations for flame speed and explosion overpressure of dust clouds inside industrial enclosures[END_REF], 'unstretched flame velocities' might then be appraised.

Conclusions

Nanopowders have specific characteristics, such as the propensity to agglomeration or to selfignition or even pyrophoricity for metals compounds, that can have a significant impact on the determination of their explosivity. Standards exist with established procedures, but there are currently no recommendations on how to interpret their results correctly: i) what about the extrapolation of results on an industrial scale (i.e. of the validity of the cubic law)?, ii) how to analyze explosion parameters in the case of pre-ignition phenomenon or how to avoid this phenomenon?, iii) are these results representative of the industrial operating conditions, in terms of turbulence and particle size distribution? As the operating conditions appear to have much greater influence in the case of nanoparticles than for micropowders, one of the key elements is to know precisely the characteristics of the dust cloud during its dispersion. This knowledge is difficult to achieve because the changes in dispersion conditions have not only an influence on the PSD, but also on initial turbulence level.

From this study, it appears that the particle size distribution of the nanoparticles before and after injection within the 20L sphere are greatly different and that modifications in the dispersion procedure can impact the fragmentation of the nanoparticles agglomerates. Even slight changes in the PSD of a nanoparticles cloud lead to significant modifications of its explosivity. It should also be noticed that changing the dispersion nozzle can improve the reproducibility of the tests and limit the pre-ignition phenomenon. However, the use of a symmetric nozzle instead of a standard rebound nozzle lead to much lower explosivities. A similar finding can be drawn from the replacement of the dust injection through a reservoir by dust lifting. Finally, a peculiar attention should be paid to aging phenomenon of nanoparticles with regard to their safety parameters.

By thoroughly characterizing the dust cloud before ignition, it is then possible to choose a suitable injection procedure and ignition delay time which will correspond to the worst-case scenario or, in a more relevant way, to conditions consistent with the actual industrial processes.

Figure 1 :

 1 Figure 1: a) Focus on Corax N550 primary particles, b) Carbon black agglomerates -2017, c) Carbon black agglomerates -2006, d) Focus on Al-100 primary particles

Figure 2 :

 2 Figure 2: Time evolution of the vertical root-mean-square velocity within the 20L sphere during a standard injection phase -with a rebound nozzle or a symmetric nozzle.

  Figure 3: Influence of the injection procedure on the time evolution of the d90 during the dispersion of aluminum or carbon black nanoparticles

Figure 4 :

 4 Figure 4: Effect of the injection procedure on the particle size distribution of Corax N550 nanoparticles

Figure 7 :Figure 8 :

 78 Figure 7: Maximum overpressure (left) and maximum rate of pressure rise (right) for Corax N550 powder in 2006 and 2017 -tv = 60 ms

Figure 9 :

 9 Figure 9: Maximum overpressure (left) and maximum rate of pressure rise (right) for aluminum powder-various injection procedures -tv = 60 ms

Figure 10 :

 10 Figure 10:Influence of the ignition delay time on the maximumrate of pressure rise of Corax N550 at 250 g.m -3 (left) and on theCO/CO2 ratio and H2 content (right)

Table 1 :

 1 Properties of the nanopowders used in this study.

	Powders

Mean volume diameter d50 dry sedimentation (µm) Mean diameter d50 wet dispersion (µm) BET diameter (nm)

	Corax N550	24	333	75
	Al-100	2	286	96

Table 2 :

 2 Estimation of the reaction temperature from the composition of the combustion gases and carbon monoxide content from chromatography measurements for Corax N550 explosion

Ignition delay tv 20 ms 30 ms 40 ms 60 ms 80 ms 100 ms 120 ms

	CO (% mol)	25.0	21.3	18.8	17.0	14.0	12.1	8.5
	Treaction (°C)	1072	963	902	853	837	809	751