Pauline Bardin

Emmeline Marchal-Duval

Florence Sonneville

Sabine Blouquit-Laye

Nathalie Rousselet

Philippe Le Rouzic

Harriet Corvol

Sabine Blouquit- Laye

Olivier Tabary

-3p in inflammatory processes in cystic fibrosis airways

Keywords: cystic fibrosis, lung, miRNome, transcriptome, miR-199a-3p, NF-κB

Introduction

Cystic fibrosis (CF) is the most common lethal genetic disease in the Caucasian population [START_REF] O'sullivan | Cystic fibrosis[END_REF], caused by mutations in the CFTR (Cystic Fibrosis transmembrane Conductance Regulator) gene [START_REF] Riordan | Identification of the cystic fibrosis gene: cloning and characterization of complementary DNA[END_REF]. CFTR encodes a chloride channel [START_REF] Anderson | Demonstration that CFTR is a chloride channel by alteration of its anion selectivity[END_REF] essential for the osmotic balance of airway surface liquids. The most common mutation is F508del [START_REF] Cutting | Cystic fibrosis genetics: from molecular understanding to clinical application[END_REF], resulting in the lack of the channel at the apical membranes of epithelial cells and leading to an ionic imbalance and thickened mucus [START_REF] Boucher | An overview of the pathogenesis of cystic fibrosis lung disease[END_REF]. The resulting hyperviscosity impairs mucociliary clearance, promoting bacterial colonization and the establishment of infection/inflammation cycles which, in the long term, degrade the pulmonary epithelium. Chronic inflammation is the hallmark of CF lung disease with the presence of polynuclear neutrophil invasion and interleukin-8 (IL-8) in the airway of CF patients [START_REF] Tabary | Selective up-regulation of chemokine IL-8 expression in cystic fibrosis bronchial gland cells in vivo and in vitro[END_REF][START_REF] Cohen | Cystic fibrosis: a mucosal immunodeficiency syndrome[END_REF] mainly caused by changes in the NF-κB pathway [START_REF] Jacquot | Airway epithelial cell inflammatory signalling in cystic fibrosis[END_REF][START_REF] Tirouvanziam | Inflammation and infection in naive human cystic fibrosis airway grafts[END_REF]. NF-κB is a nuclear transcription factor involved in many cellular processes; it plays a fundamental role in the immune response, especially in the secretion of cytokines, such as IL-8, in the lungs. NF-κB is a dimeric transcription factor present in a latent form in cells and can be induced to bind to DNA at κB sites. The canonical pathway is usually induced by microbial or viral infections and/or pro-inflammatory cytokines, all of which activate the β-subunit of the IκB kinase (IKKβ) complex. IκB kinases (IKK) phosphorylate IκB (inhibitors of κB) bound to NF-κB, resulting in the ubiquitindependent degradation of IκB and translocation of NF-κB dimers into the nucleus [START_REF]The beginning of the end: IkappaB kinase (IKK) and NF-kappaB activation[END_REF]. In CF, the origin of the deregulation of NF-κB remains unclear, despite extensive publications in the field [START_REF] Tabary | Calcium-dependent regulation of NF-(kappa)B activation in cystic fibrosis airway epithelial cells[END_REF][START_REF] Jacquot | Hyperinflammation in airways of cystic fibrosis patients: what's new?[END_REF].

Here therefore we focused on microRNA (miRNA), as an alternative mechanism that has been suggested to regulate the NF-κB [START_REF] Arora | miR-9 and let-7g enhance the sensitivity to ionizing radiation by suppression of NFkappaB1[END_REF][START_REF] Poos | How microRNA and transcription factor co-regulatory networks affect osteosarcoma cell proliferation[END_REF][START_REF] Yang | The functional analysis of microRNAs involved in NF-κB signaling[END_REF]. MicroRNA are small endogenous non-coding single-stranded RNA (19-23 nucleotides) that negatively regulate gene expression. The control exerted by a miRNA on its target gene most commonly occurs through the 3′-untranslated region (UTR) of the mRNA, leading to the inhibition of its translation [START_REF] Filipowicz | Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight?[END_REF]. miRNA regulate more than 60% of human proteincoding genes; hence, they are implicated in normal physiological function [START_REF] Friedman | Most mammalian mRNAs are conserved targets of microRNAs[END_REF].

Moreover, miRNA play a critical role in many diseases, in which their expression is deregulated [START_REF] Dai | MiR-199a attenuates endometrial stromal cell invasiveness through suppression of the IKKbeta/NF-kappaB pathway and reduced interleukin-8 expression[END_REF][START_REF] Byrnes | Overexpression of miR-199a-5p decreases esophageal cancer cell proliferation through repression of mitogen-activated protein kinase kinase kinase-11 (MAP3K11)[END_REF][START_REF] Foster | The emerging role of microRNAs in regulating immune and inflammatory responses in the lung[END_REF][START_REF] Ramachandran | Post-transcriptional regulation of cystic fibrosis transmembrane conductance regulator expression and function by microRNAs[END_REF]. Many studies on CF have focused on the role of miRNA in regulating CFTR gene expression [START_REF] Sonneville | New insights about miRNAs in cystic fibrosis[END_REF], but few studies have compared miRNA expression levels between CF patients and non-CF controls. We aimed to understand the role of miRNA in pulmonary physiopathology in CF patients in basal conditions. We assessed miRNA and mRNA expression in bronchial cell specimens from CF patients and non-CF controls, and we also performed an experimental in vitro modulation of miRNA expression to elucidate miRNA/mRNA regulation in the context of CF by bioinformatics followed by functional analyses.

Methods

Human bronchial epithelial cell culture

Human bronchial epithelial cells obtained from lung tissues removed during surgery and cultured at an air-liquid interface (ALI) were purchased from Epithelix (Plan-les-Ouates, Switzerland) [START_REF] Wiszniewski | Long-term cultures of polarized airway epithelial cells from patients with cystic fibrosis[END_REF]. Cells were cultured with MucilAir™ culture medium (Epithelix) for at least 8 wk. The permeability of tight junctions and the differentiation were validated by transepithelial electrical resistance measurement (>400 .cm²) and cilia beating frequency (>7 Hz). Data were generated from human bronchial epithelial cells from five CF patients homozygous for the F508del mutation and five healthy donors (non-CF). The human bronchial epithelial cell lines CFBE41o - (CF) and 16HBE14o -(non-CF) were a gift from Prof. D.C. Gruenert (UCSF, San Francisco, USA). They were cultured in minimum essential medium (MEM) in the presence of Earle's salts and L-glutamine (Thermo Fisher, Villebon-sur-Yvette, France) containing 10% bovine growth serum (Eurobio, les Ulis, France) and 1% penicillin/streptomycin (Thermo Fisher). Cell cultures were grown and maintained at 37 °C in a 5% CO 2 humidified incubator.

Human lung explants and plasma

Human lung explants were collected and processed in compliance with the current mRNA and miRNA isolation, purification, library construction, and sequencing

Small RNA (<200 nt) and large RNA (>200 nt) were isolated using the NucleoSpin miRNA kit (Macherey-Nagel, Düren, Germany). RNA purification and library construction were performed as previously described by the transcriptome and epigenome facilities [START_REF] Balloy | Normal and cystic fibrosis human bronchial epithelial cells infected with Pseudomonas aeruginosa exhibit distinct gene activation patterns[END_REF]. RNA sequencing (RNA-seq) was performed at the Institut Pasteur (Paris, France). We used against the reference genome (hg19). Genes were counted using HTseq-count.

For miRNome analysis, miRNA-seq was performed at the Institute of Molecular and Cellular Pharmacology (IPMC, Valbonne, France) as described previously [START_REF] Pandit | Inhibition and role of let-7d in idiopathic pulmonary fibrosis[END_REF].

Briefly, small RNA libraries were constructed using a TruSeq small RNA sample preparation kit (Illumina). Small RNA-seq libraries were generated using 200 ng of small RNA as input from each sample. Using multiplexing, the platform combined up to four samples into a single lane to obtain sufficient coverage and ran two technical replicates for each library. T Cluster generation was performed on a Flow Cell v3 (TruSeq SR Cluster Kit v3; Illumina) using cBOT. Sequencing was conducted on the HiSeq1000 platform [START_REF] Balloy | Normal and cystic fibrosis human bronchial epithelial cells infected with Pseudomonas aeruginosa exhibit distinct gene activation patterns[END_REF]. The PANTHER (Protein ANalysis THrough Evolutionary Relationships; http://www.pantherdb.org/) classification system was used to classify genes identified in our transcriptomics data according to their molecular functions annotated using ontology terms.

Predicted miRNA target

Several online algorithms (Pictar, TargetScan, miRBase, and miRWalk) were used to identify putative binding sites between the seed regions of miRNA and the mRNA of potential target genes.

miRNA and RNA extraction

For miRNA and RNA extraction from human lung explants, 100 mg of pulmonary sample was crushed with a POLYTRON® sonde (PT 3 100, Kinematica, Luzern, Switzerland) in 1 mL of TRIzol® (Life Technologies, Saint-Aubin, France) [START_REF] Chomczynski | Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction[END_REF].

For cells, miRNA and RNA were extracted using a Nucleospin miRNA kit (Macherey-Nagel). For plasma samples, miRNA was extracted using a Nucleospin miRNA Plasma kit (Macherey-Nagel). RNA and miRNA were eluted with sterile water. The concentration and quality of the RNA and miRNA were evaluated using a NanoDrop spectrophotometer by Absorbance at 260 nm.

Reverse transcription and quantitative polymerase chain reaction (RT-qPCR) analysis

The genes of interest, human miR-199a-3p, IKBKB, and IL8, as well as the endogenous controls RNU6B, miR-103, and GAPDH, were reverse transcribed with the TaqMan microRNA and RNA reverse transcription kit using 20 ng miRNA and 100 ng RNA sample. qPCR was performed using a StepOnePlus™ thermocycler (Thermo Fisher) and TaqMan technology. For relative quantification, miRNA and RNA levels were calculated using the 2-ΔC T method and normalized to the expression levels of RNU6B, miR-103, and GAPDH. Each sample was assessed in triplicate.

Protein extraction and western blot analysis

Proteins were extracted using a lysing solution (anti-protease cocktail, Na 3 VO 4 , NaPPi). Total protein concentration was evaluated with a Qubit fluorometer (Thermo Fisher). Next, 20 μg of total protein extract was reduced and size-separated on 10% SDS-polyacrylamide gels; transferred to nitrocellulose membranes (Bio-Rad, Marnes-la-Coquette, France); blocked in TBS-T milk; and incubated with specific primary antibodies against IKKβ (#2884), phospho-IκBα (#9246), NF-κB (#6956), and β-actin (#3700) (Cell Signaling Technology, Boston, MA, USA). The proteins of interest were detected, imaged, and quantified (Chemidoc, Bio-Rad, France).

Luciferase assay

An IKBKB-3′-UTR wild-type plasmid,

CGCCTTGTCTGCACACTGGAGGTCCTCCATT, (supplementary material,

Figure S1) and a mutated plasmid, CGCCTTGTCTGCTGTGACCAGGTCCTCCATT were used for the luciferase assay (Tebu-Bio, Le Perray en Yvelines, France). CF cells were seeded in six-well plates and were transfected the next day with 1 µg/ml of the IKBKB 3′-UTR using ExGen 500 (Euromedex, Souffelweyersheim, France). Cells were co-transfected with 30 nM miR-199a-3p mimic or scramble mimic as the control.

Supernatants were collected 48 h after co-transfection. For these experiments, we used a Secrete-Pair™ Dual Luminescence Assay kit (Genecopoeia, Tebu-bio), designed to analyse the activities of Gaussia luciferase (GLuc) and secreted embryonic alkaline phosphatase (seAP), an endogenous reporter using the same samples from the cell culture medium.

NF-κB activity

Nuclear proteins were extracted from cells transfected with miR-199a-3p mimic or scramble mimic as the control using a Nuclear Extract kit (Active Motif, Rixensart, Belgium). Total protein concentration was evaluated with a Qubit fluorometer (Thermo Fisher). The transcriptional activity of p65 NF-κB in 20 µg of nuclear protein extract from CFBE41o -cells was assayed using the TransAM TM Transcription Factor Assay kit (Active Motif).

IL-8 assay (ELISA)

The supernatants of cells transfected with miR-199a-3p mimic or scramble mimic as the control were recovered 48 h after transfection. The IL-8 concentration of each sample was determined with the human IL-8 Duo-Set kit (R&D Systems, Lille, France).

Statistical analysis

RNA-seq data counts were analysed using R version 3.0.2 and the Bioconductor package DESeq2 version 1.2.9 (www.bioconductor.org). The generalized linear model included time and condition (CF vs. non-CF). Extracted contrasts included comparisons between the CF and control groups and pairwise comparisons of time points in each condition. Raw p-values were adjusted for multiple testing using the Benjamini and Hochberg procedure, and genes with an adjusted p-value < 0.001 were considered differentially expressed [START_REF] Balloy | Normal and cystic fibrosis human bronchial epithelial cells infected with Pseudomonas aeruginosa exhibit distinct gene activation patterns[END_REF].

For functional analysis, all data are described as mean ± SD. Between-group differences were assessed using the Mann-Whitney U-test, Student's t-test, and Pearson correlations. Values of p ≤ 0.05 were considered significant; in the figures, statistically significant differences are indicated for p ≤ 0.05 (*), p ≤ 0.01 (**), and p ≤ 0.001 (***).

Results

miRNome and transcriptome analyses

Differential expression of miRNA and mRNA between CF patients and non-CF controls was assessed by biostatistical analysis. Among the differentially expressed genes, we selected those whose fold change (FC) was ≥2 in upregulation and ≤0.5 in downregulation. Eleven significantly differentially expressed miRNA were observed when comparing miRNA expression levels between CF and non-CF cells, including 9 upregulated miRNA and 2 downregulated miRNA CF cells. In the same sample, 18 significantly differentially expressed mRNA were observed, including 7 upregulated mRNA and 11 downregulated mRNA in CF cells (Table 1).

We speculated that the integration of both levels of transcript information should considerably enhance the conclusiveness of pathway analysis. Thus, by integrating both the miRNA and mRNA profiles, we aimed to identify specific signalling pathways that account for these regulatory phenotypes; this experimental concept is graphically outlined in Figure 1. To detect miRNA-mRNA networks affecting CF cells, we combined experimentally validated mRNA and miRNA targets, as well as significantly deregulated genes, for pathway analysis using DAVID bioinformatics resources, including BioCarta and the KEGG database (Figure 1). Based on these analyses, we decided to focus our study on miR-199a-3p, a miRNA predicted and validated in other models to control the NF-κB pathway. As many as 50% of the RNA found to be dysregulated in CF by the transcriptomic analysis are associated with this pathway.

Expression of miR-199a-3p, IKBKB, and IL8 in CF and non-CF bronchial tissues

To characterize and confirm the relevance of the chosen pathway in an ex vivo model, we first quantified the expression of miR-199a-3p, IKBKB, and IL8 in human lung explants from CF patients and non-CF controls biopsies using RT-qPCR. In the non-CF bronchial tissues, we observed that miR-199a-3p was expressed heterogeneously due to inter-individual phenotypic variability (Figure 2A). In CF patients, miR-199a-3p expression was significantly lower, and IKBKB and IL8 mRNA levels were elevated compared to those in non-CF controls (Figure 2A-C). According to Pearson's correlation analysis, there was a significant correlation between miR-199a-3p and IKBKB/IL8 expression in non-CF patients, whereas miR-199a-3p expression was only correlated with IKBKB expression in CF patients (p ≤ 0.005;

Table 2). We analysed one miRNA that was unchanged between non-CF and CF cells. We randomly selected miR-23a from the list of the unchanged miRNA. RT-qPCR revealed no significant difference in miR-23a expression between non-CF and CF cells (supplementary material, Figure S2), confirming the small RNA-seq results.

miR-199a-3p directly regulates IKBKB

In CF patients, we hypothesized that the expression of miR-199a-3p can modify IL8 expression through the NF-κB pathway. To confirm this, CFBE cells were transfected with miR-199a-3p mimic at different concentrations (2.5, 10, 30, 50, or 100 nM; supplementary material, Figure S3) or with scramble mimic as the control for different durations (24, 48, or 72 h; supplementary material, Figure S4). miR-199a-3p expression was analysed by RT-qPCR. The level of miR-199a-3p in the presence of 30 nM of the mimic for 48 h increased by a factor of 300 compared to that in the control. As this represented the optimal conditions, subsequent experiments were performed under these conditions. Next, to test whether miR-199a-3p inhibits IKBKB expression by binding to its 3′-UTR, CFBE cells were co-transfected with a luciferase reporter vector containing the 3′-UTR region of wild-type IKBKB (WT-IKBKB-3′UTR)

or with the 3′-UTR region of mutated IKBKB (M-IKBKB-3ʹUTR) and with miR-199a-3p mimic or scramble mimic as the control. At 48 h, transfection with the mimic induced stronger miR-199a-3p expression than that in the control (Figure 3A). We observed a significant decrease in luciferase activity after the co-transfection of miR-199a-3p mimic/WT-IKBKB-3ʹUTR compared to miR-199a-3p mimic/M-IKBKB-3ʹUTR, and this decrease is more important compared to that of mimic control/WT-IKBKB-3ʹUTR

(Figure 3B). This indicates a direct miR-199a-3p/IKBKB interaction at the 3′-UTR region of IKBKB.

miR-199a-3p regulates the NF-κB pathway through IKBKB

Under the same conditions as described above, we assayed various proteins implicated in the NF-κB pathway (IKKβ, phospho-IκBα, NF-κB, and IL-8). In the presence of miR-199a-3p mimic in CFBE cells, we observed that IKKβ protein expression was lower by 40% than in CFBE transfected with scramble mimic (Figure 4A). Similar results were obtained with other validated miR-199a-3p targets at the transcript level (supplementary material, Figure S5). There appeared also to be a trend for reduced expression (by 14%) of phospho-IκBα in the presence of miR-199a-3p mimic (Figure 4B). Moreover, we observed a 36% decrease of NF-κB protein expression in CFBE cells transfected with miR-199a-3p mimic compared to the control (Figure 4C).

Next, we evaluated the effect of miR-199a-3p on NF-κB activation in the nucleus using the TransAM method. From CFBE cells transfected with miR-199a-3p mimic or control, we extracted nuclear proteins 48 h after transfection. NF-κB activity was measured from these protein extracts through a colorimetric reaction, with the absorbance being proportional to NF-κB activity. We observed that NF-κB activity was significantly lower in CFBE cells transfected with miR-199a-3p mimic (0.2 arbitrary unit (AU)) than that in the control condition (0.6 AU; Figure 4D). Finally, we assayed IL-8 secretion in CFBE supernatants 48 h after transfection with miR-199a-3p mimic or the control by ELISA. We observed significantly lower IL-8 secretion by cells transfected with miR-199a-3p mimic (2,446 pg/ml) than that in the control condition (3,367 pg/ml; Figure 4E). In contrast, no significant difference in IL8 mRNA was observed (data not shown).

Expression of miR-199a-3p in CF and non-CF plasma

To verify the association between inflammation and miR-199a-3p expression in the plasma of CF patients, we used RT-qPCR to measure the levels of this miRNA in non-CF and CF patient plasma extracts. We found no significant difference in the expression of miR-199a-3p between the plasma of CF and non-CF controls (Figure 5).

Discussion

For the first time, all dysregulated miRNA and mRNA were analysed in the same sample of primary CF bronchial epithelial cells cultured at an air-liquid interface as compared to levels in non-CF cultures, providing a non-biased approach. In this model, we found few dysregulated miRNA and RNA between the primary cells of CF patients and non-CF controls. Interestingly, half of the dysregulated genes were predicted to be associated with the NF-κB pathway, and one miRNA was significantly downregulated in CF patients: miR-199a-3p. Bioinformatics approaches predicted that this miRNA regulates the NF-κB pathway via an interaction with IKKβ. We thus focused our study on miR-199a-3p, and through functional analysis, we confirmed that miR-199a-3p specifically binds directly to the 3′-UTR of IKBKB in the CF pulmonary context. Furthermore, we demonstrated that the upregulated expression of miR-199a-3p leads to decreases in the activation of NF-κB and the secretion of IL-8, the main pro-inflammatory parameter dysregulated in CF airways. In the absence of inducible inflammation, our results indicate that the NF-κB pathway is constitutively activated in CF cells, leading to the production of pro-inflammatory cytokines such as IL-8, by contrast to the results obtained by Becker et al. [START_REF] Becker | Cytokine secretion by cystic fibrosis airway epithelial cells[END_REF].

Moreover, we demonstrated that different miRNA are dysregulated, and miR-199a-3p can control the NF-κB pathway through IKKβ. Other groups have performed miRNA expression profiling studies and have identified other altered miRNA expression patterns [START_REF] Oglesby | miR-126 is downregulated in cystic fibrosis airway epithelial cells and regulates TOM1 expression[END_REF][START_REF] Ramachandran | A microRNA network regulates expression and biosynthesis of wild-type and DeltaF508 mutant cystic fibrosis transmembrane conductance regulator[END_REF]. The differences might be explained by the model and/or the method used. For example, Oglesby et al. observed an increase in miR-199a-3p, but CF bronchial brush sampling might be prone to bacterial infection, confirming the evidence for important roles for miRNA in regulating innate immunity. For the first time, in the context of CF, we demonstrated a new mechanism of inflammation regulation.

To our knowledge, this is the first observation of a possible link between miR-199a-3p expression and IL-8 secretion in bronchial epithelial resting cells. This result provides novel clues among IL-8 expression, and NF-κB activation in the context of CF and highlighting the role of miRNA in this regulation.

The deregulation of inflammatory processes has been shown to pass through the NF-κB and MAPK signalling pathways, notably via p38 and ERK1/2, which are constitutively active in the CF context [START_REF] Muselet-Charlier | Enhanced IL-1beta-induced IL-8 production in cystic fibrosis lung epithelial cells is dependent of both mitogen-activated protein kinases and NF-kappaB signaling[END_REF]. However, the causes of the infection/inflammation cycles that degrade the pulmonary epithelium remain unknown. Previous studies in our laboratory showed that mutations in the CFTR gene led to chloride dysfunction, resulting in the deregulation of cellular homeostasis and an increase in the intracellular calcium concentration at the beginning of NF-κB hyperactivation [START_REF] Tabary | Calcium-dependent regulation of NF-(kappa)B activation in cystic fibrosis airway epithelial cells[END_REF][START_REF] Ribeiro | The role of intracellular calcium signals in inflammatory responses of polarised cystic fibrosis human airway epithelia[END_REF][START_REF] Antigny | CFTR and Ca signaling in cystic fibrosis[END_REF]. Nevertheless, there is no direct link between calcium flow variation and NF-κB pathway activation in the literature. According to our results, miR-199a-3p regulates the activation of the NF-κB pathway by targeting the 3′-UTR of IKBKB, but the origin of the miR-199a-3p deregulation in CF remains to be identified. Therefore, we analysed the level of pre-miR-199a-1 and pre-miR-199a-2 as a precursor of miR-199a (data not shown) and the level of miR-199a-5p, the other form of miR-199a. We did not observe any significant difference in the pre-miRNA, but we found a significant increase in miR-199a-5p in CF cells (data not shown), as previously demonstrated [START_REF] Zhang | Pharmacological modulation of the AKT/microRNA-199a-5p/CAV1 pathway ameliorates cystic fibrosis lung hyper-inflammation[END_REF]. We can hypothesise that a post-maturation mechanism could regulate the expression of miR-199a-3p. Even if we cannot prove and establish this, for the time being, miR-199a-3p could be an intermediary actor between calcium and the NF-κB pathway. Sun et al. demonstrated that miR-199a-3p expression is dependent on calcium [START_REF] Sun | Regulation of miR-101/miR-199a-3p by the epithelial sodium channel during embryo implantation: involvement of CREB phosphorylation[END_REF]. Interactions between miRNA and calcium are prevalent in the literature and play fundamental roles in many pathologies [START_REF] Magenta | Oxidative stress, microRNAs and cytosolic calcium homeostasis[END_REF][START_REF] Finger | MicroRNAs meet calcium: joint venture in ER proteostasis[END_REF][START_REF] Harada | MicroRNA regulation and cardiac calcium signaling: role in cardiac disease and therapeutic potential[END_REF], notably in the cellular processes of proliferation, adhesion, differentiation, and inflammation. For example, miRNA are known to act on genes such as SERCA, IP3R, and RYR, genes that encode calcium carriers located on the endoplasmic reticulum [START_REF] Finger | MicroRNAs meet calcium: joint venture in ER proteostasis[END_REF]. Thus, one hypothesis is that miR-199a-3p is regulated by calcium in CF. The second hypothesis is that miR-199a-3p is regulated by a pre-existing proinflammatory context. The level of miR-199a-3p is decreased in CF cells, leading to increases in the activation of the NF-κB pathway and secretion of IL-8, and this cytokine may act to regulate the expression of miR-199a-3p through a feedback cycle. Further investigations are needed to understand the origin of miR-199a-3p dysregulation in the context of CF.

Based on the IKKβ luminescence assay, the significant decrease (70%) in IKKβ observed in the presence of miR-199a-3p mimic explains the reduction in IL-8

secretion. These relatively low decreases in IL-8 secretion can be explained by the fact that protein translation is under the regulation of other miRNA and not only miR-199a-3p. Sonneville et al. [START_REF] Sonneville | New insights about miRNAs in cystic fibrosis[END_REF] reported that more than 49,000 proteins (representing half of all proteins expressed in human cells) are predicted to be regulated by the miRNA that regulate CFTR, and one miRNA can target multiple mRNA, highlighting the complexity of this regulatory system [START_REF] Teta | Inducible deletion of epidermal Dicer and Drosha reveals multiple functions for miRNAs in postnatal skin[END_REF]. Thus, other miRNA are likely to act on numerous targets in the NF-κB signalling pathway [START_REF] Ma | MicroRNAs in NF-kappaB signaling[END_REF][START_REF] Lu | Macrolide antibiotics inhibit mucus secretion and calcium entry in Swine airway submucosal mucous gland cells[END_REF], such as miR-9 [START_REF] Wang | Epigenetic inactivation of miR-9 family microRNAs in chronic lymphocytic leukemia--implications on constitutive activation of NFkappaB pathway[END_REF], which has been shown to directly target the 3′-UTR of RELA encoding the NF-κB p65 subunit [START_REF] Guo | MicroRNA-9 inhibits ovarian cancer cell growth through regulation of NF-kappaB1[END_REF] and whose expression increases when NF-κB/MyD88 is activated [START_REF] Liu | Molecular hydrogen regulates the expression of miR-9, miR-21 and miR-199 in LPS-activated retinal microglia cells[END_REF].

Moreover, compensatory phenomena targeting other proteins in this pathway could modulate the regulation of inflammation. Downstream of the NF-κB pathway, miR-93 is controlled by the minichromosome maintenance complex component 7 (MCM7) gene, can bind the 3′-UTR of IL8, thereby decreasing IL8 mRNA levels and IL-8 secretion [START_REF] Fabbri | Expression of miR-93 and Interleukin-8 during Pseudomonas aeruginosa-mediated induction of pro-inflammatory responses[END_REF]. During Pseudomonas aeruginosa infection, miR-93 downregulation has been shown to directly lead to the stabilization of IL8 mRNA. In CF, NF-κB has been indicated to not be the only transcription factor involved in the regulation of IL-8 secretion; in fact, one study has shown that the MAPK pathway is also implicated in the deregulation of this process, and this activation could compensate the observed decrease in NF-κB activation [START_REF] Muselet-Charlier | Enhanced IL-1beta-induced IL-8 production in cystic fibrosis lung epithelial cells is dependent of both mitogen-activated protein kinases and NF-kappaB signaling[END_REF][START_REF] Dosunmu | The anti-microbial peptide TP359 attenuates inflammation in human lung cells infected with Pseudomonas aeruginosa via TLR5 and MAPK pathways[END_REF][START_REF] Dong | CFTR-regulated MAPK/NF-kappaB signaling in pulmonary inflammation in thermal inhalation injury[END_REF].

In the future, the role of miR-199a-3p in processes such as apoptosis, proliferation, and differentiation should be determined in the context of CF, as well as its involvement in muscular dystrophy and oesophageal cancer [START_REF] Byrnes | Overexpression of miR-199a-5p decreases esophageal cancer cell proliferation through repression of mitogen-activated protein kinase kinase kinase-11 (MAP3K11)[END_REF][START_REF] Alexander | MicroRNA-199a is induced in dystrophic muscle and affects WNT signaling, cell proliferation, and myogenic differentiation[END_REF]. This will allow for the further elucidation of its function in the regulation of cellular processes that involve the MAPK and Wnt pathways. Moreover, the therapeutic use of miR-199a-3p might prevent the chemo-attraction of neutrophils and thus limit the tissue degradation induced by these cells at the pulmonary level. We have demonstrated that miR-199a-3p as a plasma biomarker in the monitoring of pulmonary inflammation in CF patients is not sufficient to improve patient management of inflammatory processes; therefore, more studies are needed to propose specific serum miRNA expression profiles in CF. Nevertheless, this study represents a new breakthrough in our understanding of the regulation of chronic inflammation occurring in CF and highlights the importance of dysregulated miRNA in this regulation. Student's t-test was used to determine significance.

  /www.legifrance.gouv.fr). Each participating institution informed the patients and ensured that they were not opposed to the use of surgical samples, removed during a medical act, for research purposes. Lung fragments were obtained from nine non-CF controls undergoing surgery (45 ± 21 years old) and from eight CF patients (homozygous for the F508del mutation; 35 ± 9 years old) undergoing lung transplantation. For non-CF controls, samples were obtained from a non-pathologic area without inflammatory cells from patients with bronchial carcinoma. After tissue dissection, samples were directly frozen in liquid nitrogen before miRNA/RNA extraction.Plasma samples were collected during annual blood tests from 26 non-CF controls (30 ± 13 years old) and 25 CF patients (homozygous for the F508del mutation; 15 ± 3 years old). The blood samples were centrifuged for 15 min at 3,000 x g. The plasma (supernatant) was harvested, aliquoted, and stored at -80 °C until miRNA extraction.

Figure 1 .

 1 Figure 1. Flowchart of bioinformatics analyses. Differentially expressed genes/miRNA

Figure 2 .

 2 Figure 2. Expression of (A) miR-199a-3p, (B) IKBKB, and (C) IL8 in CF (n = 8) and

Figure 3 .

 3 Figure 3. miR-199a-3p directly regulates IKKβ. (A) Expression of miR-199a-3p

Figure 4 .

 4 Figure 4. miR-199a-3p regulates the NF-κB pathway through IKKβ. Representative

Figure 5 .

 5 Figure 5. Expression of miR-199a-3p in CF patient and non-CF control plasma.

FC

  = fold-change of absolute values; Raw p = raw p-value after miRNome or transcriptome analysis; Padj = p-value adjusted for multiple testing; n = 5 each group.

  Chen et al.[START_REF] Chen | Regulation of IKKbeta by miR-199a affects NF-kappaB activity in ovarian cancer cells[END_REF] demonstrated a functional role for miR-199a-3p in epithelial ovarian cancer cells as a direct inhibitor of IKKβ (IKBKB) expression, leading to the modulation of the NF-κB pathway. Dai et al.[START_REF] Dai | MiR-199a attenuates endometrial stromal cell invasiveness through suppression of the IKKbeta/NF-kappaB pathway and reduced interleukin-8 expression[END_REF] found similar results in endometrial stromal cells, showing through in vitro and in vivo experiments that NF-κB inhibition through miR-199a-3p transfection could abrogate the development and maintenance of endometriosis, partly by reducing pro-inflammatory and invasion mediators. Our results validate the presence of this regulatory system in lung tissue and provide new insights into the origin of the constitutive inflammation observed in CF patients. If the

targets of certain miRNA are tissue-specific, miR-199a-3p can regulate different types of cells by downregulating different target genes

[START_REF] Dahiya | MicroRNA expression and identification of putative miRNA targets in ovarian cancer[END_REF][START_REF] Inomata | MicroRNA-17-92 down-regulates expression of distinct targets in different B-cell lymphoma subtypes[END_REF]

. However, the regulation of the NF-κB signalling pathway by miR-199a-3p via direct interaction with IKBKB appears to be applicable to different cell types (epithelial ovarian cancer cells, endometrial stromal cells, and CF cells) in different pathological contexts, including those involving tissue repair, chemoresistance, tumour progression, and proinflammatory environments.

Table 1 .

 1 MiRNome and transcriptome results, including significantly differentially expressed (A) miRNA and (B) mRNA in primary air-liquid interface-cultured cells from CF patients and non-CF controls.

	A
		microRNA	Log FC	Raw p	padj
	Downregulated	hsa-miR-199a-3p hsa-miR-199b-3p	-2.565 -2.555	5.23E-05 5.54E-05	0.026 0.026
		hsa-miR-449a	1.586	1.87E-04	0.043
		hsa-miR-449b-5p	1.628	1.51E-04	0.040
		hsa-miR-4516	1.733	3.49E-05	0.026
	Upregulated	hsa-miR-449b hsa-miR-449c-5p hsa-miR-2682-3p	1.734 1.771 2.124	2.19E-04 1.21E-04 2.36E-04	0.043 0.036 0.043
		hsa-miR-449c-3p	2.345	1.82E-05	0.022
		hsa-miR-636	2.533	7.99E-05	0.027
		hsa-miR-639	2.643	2.52E-06	0.006

Table 2 .

 2 Pearson correlation matrix for miR-199a-3p, IKBKB, and IL8 expression levels in (A) non-CF controls (n = 9) and (B) CF patients (n = 8).

	The values in bold are significantly different from 0 at an alpha of 0.05.
	A
	p-values/non-CF pathology group
	Variables	IL8	IKBKB
	miR-199a-3p	0.001	0.002
	IKBKB	<0.0001
	B
	p-values/CF pathology group
	Variables	IL8	IKBKB
	miR-199a-3p	0.115	0.005
	IKBKB	0.151

Acknowledgments

We thank Dr. D.C. Gruenert, who provided the 16HBE14o -and CFBE41o -cells. This research was funded in part by grants from Inserm, UPMC Univ Paris 06, the nonprofit organization Vaincre la and the Legs Poix-Chancellerie des Universités, Paris. PB received a PhD grant from Sorbonne Université, UPMC Univ Paris 06. FS received a Ph.D. grant from Vaincre la Mucoviscidose and a postdoctoral grant from SATT Lutech.

Data Availability Statement

RNAseq raw datafiles are available in the European Nucleotide Archive (ENA) (primary accession number PRJEB25563). http://www.ebi.ac.uk/ena/data/view/ PRJEB25563.

Author contribution statement

PB performed and designed the experiments, interpreted results, and wrote the manuscript. MDE and FS performed and designed some experiments and interpreted some results. NR and PLR performed some experiments. SBL provided human explants from patients. HC interpreted some results. OT performed and designed experiments, interpreted results, obtained funding, and wrote the manuscript.


Jalal Joseph
email: jalal.possik@u-bordeaux.fr

Possik Aicha

Anne Amrani
email: aicha.amrani@ims-bordeaux.fr

Gregory Zacharewicz
email: gregory.zacharewicz@ims-bordeaux.fr

DEVELOPMENT OF A CO-SIMULATION SYSTEM AS A DECISION-AID IN LEAN TOOLS IMPLEMENTATION

Keywords: Lean Manufacturing, Lean tools and techniques, Discrete Event Simulation, Co-Simulation, Key Performance Indicator

Aside from the human and managerial skills necessary to propel any business, the right Lean deployment can play a big role in reducing waste and maximizing efficiency. Capturing these benefits is highly dependent on adequate Lean techniques integration. Companies shifting towards Lean conversion have tried one of many Lean Manufacturing optimization tools at their disposal today (JIT, Pull System, U cells, CrossTraining, Visual Management, SMED, Poka Yoke, etc.) hoping to capture the benefits of such conversion. One of the major hurdles these companies face is the difficulty to choose the Lean tools that best fit their economic contexts and that are best tailored towards reaching their productivity or quality milestones. The Discrete Event Simulation becomes an interesting approach, to imitate the evolution of a manufacturing system and to represent the transformation induced by the Lean tools integration in the manufacturing line. The system developed in this paper is a Co-Simulation system. It is built based on a two-level structure. The first level is a basic framework for modeling the manufacturing assembly line with its various components (using JaamSim), while the second is a hierarchical framework for executing parallel Lean Tools simulations (using MECSYCO). To demonstrate the usefulness of this Co-Simulation system, an example of an Aeronautic Assembly Line is used. Three Lean Configuration Scenarios are investigated under market fluctuation context (Batch Policy, Setup times reduction with SMED, Pull System), compared with an Actual model simulated as a Lean Free scenario.

INTRODUCTION

Scientific publications pointed out the effectiveness of Lean implementation in different companies, services, departments, supply chain, production workshops and assembly lines. Research strongly supports the benefits of Lean manufacturing approach in optimizing a company's performance [START_REF] Bhasin | An appropriate change strategy for lean success[END_REF][START_REF] Laureani | Critical success factors for the effective implementation of Lean Sigma[END_REF]. However, Lean implementation has experienced many failures [START_REF] Nordin | A survey on lean manufacturing implementation in Malaysian automotive industry[END_REF][START_REF] Jadhav | Exploring barriers in lean implementation[END_REF]. The recent research lead by Mirdad et al. [START_REF] Mirdad | A Conceptual Map of the Lean Nomenclature: Comparing Expert Classification to the Lean Literature[END_REF] suggested a conceptual Lean map that could assist with a better Lean implementation in minimization of Lean misuse. The actual challenge is to understand and appropriately implement Lean concepts well-tailored to the company's current economic contexts and future projections [START_REF] Sarhan | Barriers to Implementing Lean Construction in the UK Construction Industry[END_REF]. Managers and engineers are in continuous search for supported methodology and cross analysis for effective Lean use [START_REF] Mirdad | A Conceptual Map of the Lean Nomenclature: Comparing Expert Classification to the Lean Literature[END_REF]. Moreover, the literature is abundant with cases where Lean is successfully or unsuccessfully implemented. Some authors tried to catalog these success stories and failures in order to use them in similar environments.

These cases and empirical findings cannot be reliably scalable to be applied ubiquitously in similar scenarios. Consequently, simulation related researches help tackle and solve this actual problem. In [START_REF] Olhager | Simulating production and inventory control systems: a learning approach to operational excellence[END_REF], the author outlined the necessity for thoroughly understanding the nature of manufacturing operations to achieve the Lean and operational excellence target. Thus, simulation is by nature an added value analysis approach because it allows testing many possible scenarios without real implementation which saves time and money. In our paper, we built a Co-Simulation system that monitors the behavior of a production line based on multiple models simulated simultaneously to check and compare the respective system output in an interesting graphical way. Furthermore, for each iteration we vary the economic context and based on the results, we choose the best Lean tool behavior to be subsequently applied in similar cases. This paper is structured as follows: in section 2 the literature review is used to position our work. Section 3 introduces the built simulation system, its constraints and targets, its manufacturing context, as well as its initial data inputs. Section 4 shows the experimental protocols, analysis and the issued results. A comprehensive graph illustrates the chosen key performance indicators for this study: WIP (Work In Progress), SKU (Stock Keeping Unit), Material Buffers and Lead-times. Subsequently, results will be analyzed and discussed. Finally, further research experimentations are highlighted to define the framework of coming future simulations.

LITERATURE REVIEW

Simulation Field encompasses broad methods that are able to imitate the behavior of real systems [START_REF] Detty | Quantifying benefits of conversion to lean manufacturing with discrete event simulation: A case study[END_REF]. The simulation development process starts by defining the problem and the system, formulating the conceptual model, designing the initial experiment, collecting and preparing the data and by translating, verifying and validating the model [START_REF] Kelton | Simulation with Arena[END_REF]. The next phases will be to design and run the experiments, analyze and interpret the results, and finally, document the output results. The simulation in Manufacturing and Supply Chain fields became a very widespread scientific approach since early 2000's [START_REF] Jain | Manufacturing supply chain applications: modeling computer assembly operations for supply chain integration[END_REF] because of the ability to reproduce a virtual system that simulates the real production system [START_REF] Long | Distributed supply chain network modelling and simulation: integration of agent-based distributed simulation and improved SCOR model[END_REF], in addition to a "What If" analysis of different scenarios that observes and understands the Supply Operations [START_REF] Chatfield | SISCO: An object-oriented supply chain simulation system[END_REF][START_REF] Zhao | Genetic production line-balancing for the hard disk drive industry[END_REF] and forecasts the impact of alternative configurations [START_REF] Tan | A message-driving formalism for modeling and simulation of multiagent supply chain systems[END_REF].

The Discrete-Event Simulation (DES), in particular, is one of the preferred research topics nowadays [START_REF] Yoo | Hybrid algorithm for discrete event simulation based supply chain optimization[END_REF] for its ability to simulate production system and supply chain behaviors [START_REF] Zengin | Modeling discrete event scalable network systems[END_REF][START_REF] Zengin | Discrete event modeling of swarm intelligence based routing in network systems[END_REF]. DES was often considered as a dynamic tool that allows the visualization and quantification of technological and operational changes in processes (Julie [START_REF] Yazici | Influence of flexibilities on manufacturing cells for faster delivery using simulation[END_REF]. DES is suitable for leading analysis of the dynamics of discrete processes such as manufacturing systems [START_REF] Ingemansson | Improved efficiency with production disturbance reduction in manufacturing systems based on discrete-event simulation[END_REF] and the possibility to run different scenarios in a short period of time [START_REF] Banks | Handbook of simulation: principles, methodology, advances, applications, and practice[END_REF]. [START_REF] Jeon | A survey of simulation modeling techniques in production planning and control (PPC)[END_REF] remind that DES for Production Planning and Control problems is a frequently used tool that represents more than 45% of the simulation models in the studied sample. Further studies have made the attempt of combined methods as DES and Agent technology for studying complex supply network [START_REF] Alavi-Moghaddam | Application of queuing analytic theory to decrease waiting times in emergency department: does it make sense?[END_REF] to be able to integrate micro-behaviors of individuals and macro system to guide the managers in their decision-making process. In a complex production environment with a complex demand evolution, many authors use DES to quantify the effect of VSM implementation on Lean performance measures, such as work in process and lead time [START_REF] Abdulmalek | Analyzing the benefits of lean manufacturing and value stream mapping via simulation: A process sector case study[END_REF][START_REF] Detty | Quantifying benefits of conversion to lean manufacturing with discrete event simulation: A case study[END_REF]. Along the same line, our choice is to focus on WIP, Lead-times, material buffers and the SKU. Indeed, the SKU represents the level of end-products that the company has to plan and control in each Lean tools configuration scenario. It provides a quick appreciation of the global storage in the facilities and Plants.

Early studies confirmed the benefit of Lean tool use in the right context. The relationship between Cellular Manufacturing (CM) and flexibility of products was investigated and remains unclear [START_REF] Hulya | Influence of flexibilities on manufacturing cells for faster delivery using simulation[END_REF]. Cells were found to be flexible to volume fluctuations and withstand changes over time [START_REF] Hulya | Influence of flexibilities on manufacturing cells for faster delivery using simulation[END_REF][START_REF] Wemmerlov | Empirical findings on manufacturing cell design[END_REF]. Since, the performance advantage of CM and manufacturing flexibilities has not been clearly demonstrated, and several questions remain unanswered. One question is, how is the delivery lead time affected by volume, mix, routing, and labor flexibilities? In [START_REF] Kück | A Data-driven Simulation-Based Optimisation Approach for Adaptive Scheduling and Control of Dynamic Manufacturing Systems[END_REF], the demand variation going beyond 20% is investigated, and the level of storage is explored and found to be significantly reduced after a period of time. This finding is corroborated with the previous study of [START_REF] Agarwal | Modeling the metrics of lean, agile and leagile supply chain: An ANP-based approach[END_REF] which confirms that Lean SCM practices are preferably adopted within contexts where the variability tends to be lower, and where there are frequent changes in customer demand. To reiterate, the notion of context influence in the choice of the Lean practices reinforces our approach combining both context and simulations. We subscribe to the idea of checking the relevance of tools regarding the economic environment. Still, new insights and analysis are required to better perceive the interest of Lean practices implementation.

Simulation models discussed in this paper are designed in JaamSim. This software is used in this research instead of other simulation software, because of its transparency, reliability, capability and most importantly because it is an open-source software and can be configured to interact with third-party applications. In order to implement our Co-Simulation system, MECSYCO (Multi-agent Environment for Complex SYstem CO-simulation) was used. It is an open-source framework which supports Java and C++ programming languages to manage complex simulation models. It also has the MECSYCO-visu package that helps visualize simulation events in real time and shows output data in 2D graphs, pie charts or other visualization forms.

MANUFACTURING CONTEXT

As per Figure 1, The developed Co-simulation system has the objective to simulate the manufacturing assembly line undergoing different economic contexts so that we can choose the best Lean tool that reacts better to such context variation. In this paper, Demand Fluctuation context is tested.

As outlined in [START_REF] Detty | Quantifying benefits of conversion to lean manufacturing with discrete event simulation: A case study[END_REF] and as analyzed in our work, some Lean practices are Engineering related and can be configured and parametrized, while, others are not. Kanban, SMED, Cross Training, Poka Yoke, Cellular Manufacturing, 5S can be modeled and simulated. However, human-related Lean tools are inimitable technically in simulation models. Those include kaizen, employee commitment, leadership, direction management, empowerment, continuous improvement. The aim of this paper is to focus on Pull System (Kanban), Setup time reduction (SMED) and Batch strategy. The assessment of Lean tools configuration consistency regarding the economic context is achieved through four KPI: Key Performance Indicators. The global lead-times, WIP, SKU and Material Buffers are used to evaluate the performance of the manufacturing assembly line.

SYSTEM ARCHITECTURE

Co-Simulation Configuration

MECSYCO is an agent-based system that simulates, in parallel and simultaneously, interactions and operations of multiple agents. In our case, it is used as an orchestrator for all the models and simulations developed using JaamSim. It launches the simulations, captures respective simulations times and outputs data, synchronizes time between simulations, simultaneously sketches the output data to graphs, and finishes all the simulations when the maximum simulation time, defined by the variable maxSimulationTime, is reached. As per Figure 2, each model is linked to a specific agent and Model Artifact responsible for sending and receiving data from the simulators. Jaamsim configuration file and output of each model, are sent respectively to Model Artifacts. Each model represents a specific configuration of the assembly line where models represent the Lean tools to be tested: SMED, Batch Policy, Pull System, and the Actual model representing the Lean Free scenario.

Interface Configuration

In this proposed Co-Simulation system's architecture, as per Figure 3, the user inserts the input data used by the four existing models and launches the system through a web interface developed using Node.js which will initiate all the models simultaneously, get the data and time from each model, and draw graphs representing real-time outputs. This Co-Simulation system will be a decision-aided system to select the best model that suits the organization production and financial targets. Furthermore, these models and results will be cataloged and used as references for companies facing similar future situations. The simulated manufacturing assembly line issued from Aeronautic Industry represents a 2 nd Tier supplier providing aeronautic fasteners. Ten Final Product references are items assembled in-house. Demand is assumed to be stochastic. Ten raw materials types are used to start the assembly of aeronautic fasteners. The manufacturing facility is an assembly Line (items are manufactured by subcontractors) and the ten references are assembled undergoing a flow shop consisting of five workshops with limited human capacity. As initial data, the input parameters identify the Demand distributions, workshops production times and setup times. The simulation will be executed on a one year order book. Initial Data settings are filled into a web interface as per Figure 4, the user enters the Setup Time and Processing Time for each Machine (WS1, WS2…, WS6). Then, the user can choose the yearly demand for each product type by, selecting the type (Type 1, Type 2…, Type 10), randomizing the demand for each month, and if needed, changing the demand for each day in the month. By clicking on Submit, the system launches the Co-Simulation of the four developed models. Currently, the web interface is only used to provide the Input data (Setup Times, Processing Times and yearly order book) to the simulators. For future improvements, we are planning to add the output graph and results, provided by the Co-Simulation system, to the web interface. In this paper, we considered that simulations run without machine downtime.

Models Configuration

Ten Entity Generators are created to generate ten different types of Raw Materials, See Figure 5. The Raw Material generation is based on the yearly order demand filled in the Web Interface. Raw Materials are then sent to the Machine (WS1) in the Cutting Shop. WS1 machine has a Setup Time and a Processing Time defined also in the Web Interface. After being processed, goods are sent to WS2, and so on until the delivery process. Entity Conveyors are used to specify the travel time between machines. WIP1 is the Work In Progress of the First Machine, WIP2 is the Work In Progress for the second Machine, and so on. The same model structure is used for the remaining three models. For Batch Strategy scenario configuration, Raw Materials are set in batches before being processed. For SMED scenario, each machine setup time is reduced by a certain percentage. As for Pull scenario configuration, each machine sends a signal to the upstream one when its WIP exceeds three units to stop sending products in process. Simulations outputs are communicated simultaneously, during the simulation process, to the respective Model Artifacts and agents created using MECSYCO, then generated simultaneously into real-time graphs. Four outputs, global lead-times, WIP, SKU and Material Buffers are configured for four configuration scenarios. Table 1 summarizes the input and output parameters used for this Co-Simulation.

EXPERIMENTATION RESULTS AND DISCUSSIONS

We started by simulating the four discussed models in parallel for the initial situation of the organization's assembly line, without any economic context variations. As per Figure 6, we can see that the actual model has an excess WIP considered as a waste, this waste is caused by bottlenecks in the production process.

After a simulation time equivalent to one year of production, WIP of the actual model exceeded 2000 units in the production facilities. SMED and Batch implementations minimized the WIP but the Pull scenario yielded the best results. Pull Model also yielded the best global Lead-time average. Concerning Material Buffers which are raw materials waiting for production, the batch strategy showed the best result in terms of production speed and setup time reduction. On the other hand, the SKU issue was solved in the three developed Lean scenarios as shown in Figure 6. In this paper, we tested the Demand Fluctuation economic context, by increasing the market demand by 50% during February, March and April in the first simulation iteration then decreasing the demand by 50% for the same months in the second one. After a simulation time equivalent to one year of production, we got the results shown in Table 2. We conclude that, by decreasing the market demand, Batch strategy, which is not a Lean technique, and SMED scenario gave almost the same good results. In fact, as market demand drops, less production is required. This alleviates the constraints on the assembly line which justified the results discussed above. However, by increasing the market demand, batch strategy gave bad results with an almost doubling in the lead-time average when compared to the actual model. This in return will delay customers' orders delivery. In Figure 7, we see that Batch Strategy started to increase at time 1000 h, equivalent to the second half of February, and gets to 820 h of lead-time average after one year, which is 320 h of lead-time average more than the actual model. This analysis strengthens the relevance of both Lean tools, Pull and SMED, in coping with unpredictable ramp in production.

CONCLUSION AND PERSPECTIVES

The use of MECSYCO broadens our horizons and opens the door for multiple models developed in different and heterogeneous simulators, to be added to our system. As shown in this paper, our study was limited to four simultaneous simulation scenarios due to process power limitation. As future work and improvement, Distributed Simulations will be developed to solve this problem; it allows for different simulations to be run simultaneously on different processors available on a network, opening the door for unlimited testing capabilities. The use of Distributed Simulations will enable us to create and run multiple Lean scenarios over a broad processors' network. The hypothesis test of the relevance of Lean techniques in different market contexts will be investigated in depth. The goal is to expand the built Co-Simulation System to gradually integrate other Lean techniques. Using our system, we can introduce modifications and disruptions in many variables from conception to commercialization (quality defect, machine downtime, mix flexibility of market, etc.). Running our system will allow us to track the behavior of different Lean tools and techniques and determine the most suited Lean Tools accordingly.

Figure 1 :

 1 Figure 1: Manufacturing Simulated Context.

Figure 2 :

 2 Figure 2: Multi-Agent configuration.

Figure 3 :

 3 Figure 3: Co-System Architecture.

Figure 4 :

 4 Figure 4: Web Interface, Input Parameters.

Figure 5 :

 5 Figure 5: Simulation Model Interface.

Figure 6 :

 6 Figure 6: Parallel Output Graphs.

Table 1 :

 1 Input and Output Parameters.

		Input Parameters			Output Parameters
		§ Stochastic Yearly Demand		§ WIP average
	Initial Data	§ Randomly Generated Demand § Production time per shop	§ Overall Lead-times § SKU
		§ Setup time per Machine		§ Material Buffers
		§ Deterministic Raw Materials Supply
				Uptime	Setup Time [min]	Processing Time [min]
		Cutting shop	WS1	100%	0.05	3.7
			WS2	100%	0.7	3.1
	Assembly		WS3	100%	0.4	3.22
	Line Data	Assembly shop	WS4	100%	0.25	3.42
		Treatment shop	WS5	100%	0.1	3.72
		Machining shop	WS6	100%	0.8	3.15

Table 2 :

 2 Market Fluctuation Context and Lean tools configurations relevancy.Figure 7: Lead-time of the Batch Strategy with 50% increase in Market Demand on FEB, MAR, APR.

	Initial Situation	1 Year Simulation	10 References
		WIP (u)	Lead Time (hours)	Material Buffers (u)	SKU (u)
	Actual Model	2110	210	2300	725
	Batch Strategy	360	62	550	1
	Pull Model	13	17	2300	2
	SMED	600	70	800	1
	Economic Context	Market Fluctuation | +50% of demand increase FEB MAR APR
		WIP (u)	Lead Time (hours)	Material Buffers (u)	SKU (u)
	Actual Model	2110	500	2300	725
	Batch Strategy	360	820	550	1
	Pull Model	13	320	2300	2
	SMED	600	370	800	1
	Economic Context	Market Fluctuation | -50% of demand decrease FEB MAR APR
		WIP (u)	Lead Time (hours)	Material Buffers (u)	SKU (u)
	Actual Model	1800	180	2200	750
	Batch Strategy	200	30	500	1
	Pull Model	13	17	2200	2
	SMED	380	32	650	1

AUTHOR BIOGRAPHIES

JALAL JOSEPH POSSIK is a Ph.D. candidate at the University of Bordeaux, IMS Lab, Department of Production. His thesis focuses on the "Development of a configurable simulation model to evaluate the impact of Lean scenarios in a highly variable context", under the supervision of Mr. ZACHAREWICZ and Mrs. AMRANI. He received his Diploma in Computer and Communication Engineering from the Holy Spirit University, Kaslik (USEK) in 2010. He was the first to develop and lunch an automated music arranger (Java Application). In 2011, he got the MCITP Enterprise Administrator and Microsoft Exchange certifications and worked as a System Engineer at Teletrade, Lebanon. In 2012, he joined WorldNet, Lebanon where he worked as a Senior System Engineer and Virtualization Expert. He implemented VDI (Virtual Desktop Infrastructure) and Server Virtualization projects in multiple banks and big companies in Lebanon and abroad. In 2013, Jalal joined the Lebanese American University (LAU), Byblos as a System Engineer, Windows and Linux Administrator of the School of Arts and Sciences servers and machines. His email address is jalal.possik@u-bordeaux.fr. GREGORY ZACHAREWICZ is an Associate Professor HDR at the University of Bordeaux (France). His research interests include discrete event M&S, distributed simulation (HLA), model driven approaches, semantics aspects (short-lived ontology), and enterprise modeling (workflow, BPM, and ERP). He focused recently on Social-Organizational M&S and Interoperability. He is involved in several M&S conferences and journals. He has been participating in a number of French, European and transatlantic M&S projects. His email address is gregory.zacharewicz@ims-bordeaux.fr.

AICHA ANNE AMRANI is an


H Hounsa

F Bankolé

E Loko

J Chabriere

Rolain

H Koudokpon

N Armstrong

T V Dougnon

L Fah

E Hounsa

H S Bankolé

F Loko

E Chabrière

J M Rolain

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

Erratum

(iv) e sentence "Antimicrobial activity of dihydrochalcones form Populus balsamifera tree buds was also reported before [35]" should be corrected to "Antimicrobial activity of dihydrochalcones from Populus balsamifera tree buds was also reported before [35]."

(v) In the Conclusion, the last sentence should be updated from "Finally, further chemical description and antimicrobial activity measurements of each individual detected compounds are important perspectives that should be addressed in the future" to "Finally, further chemical description and antimicrobial activity measurements of each individual detected compound are important perspectives that should be addressed in the future."

  Erratum to (Antibacterial Activity of Chalcone and Dihydrochalcone Compounds from Uvaria chamae Roots against Multidrug-Resistant Bacteria) (ii) In the description of Table , p< , should be corrected into p< . . (iii) In Figure , BIP on the vertical axis should be corrected to BPI.

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