dataesr/scientific-paragraphs-categorization huggingface dataset:
The column eluent was directly sprayed into the ESI source of the mass spectrometer. Mass spectra were acquired in continuum mode; fragmentation of the peptides was performed in data-dependent mode. Peak lists were automatically created from raw data files using the Protein Lynx Global Server software (version 2. 0). The background subtraction threshold for noise reduction was set to 35% (background polynomial 5). Smoothing (Savitzky-Golay) was performed (number of interactions: 1, smoothing window: 2 channels). Deisotoping and centroiding settings were: minimum peak width: 4 channels, centroid top: 80%, TOF resolution: 5000, NP multiplier: 1. Mascot search algorithm (version 2. 0, MatrixScience) was used for searching against the NCBInr database that was available on the MatrixScience server.
QUANTIFICATION AND STATISTICAL ANALYSIS For calculations of Fourier shell correlations (FSC), the FSC cut-off criterion of 0. 143 was used. The experiments were not randomized. The investigators were not blinded to allocation during experiments and outcome assessment. For SPR, non-linear regression curve fitting was performed using GraphPad Prism (www. graphpad. com). SEC-MALS scattering data were analyzed and molecular weight was calculated using ASTRA 6 software (Wyatt). PLA statical analysis was carried out using a two-tailed, unpaired t-test from 3 individual, independent experiments. Growth cone collapse was quantified for more than 100 neurons per condition, for three to six independent experiments. The criterion for the collapsed growth cones was loss of lamellipodia and the presence of only two or fewer filopodia.
Under reducing conditions, a fraction of RGMC ECD dissociates into two fragments (labelled N-term. and C-term. ) as observed for RGMA ECD (E). (H) SEC and SDS-PAGE analysis of the ternary NET1-NEO1-RGMC complex. The ternary NEO1-NET1-RGMC complex elutes as two major peaks (12. 5 and 13. 9 ml peaks) at lower elution volume compared to the binary NEO1-RGMC complex (16. 3 ml, G) or NET1 in isolation, suggesting that the NEO1-NET1-RGMC ternary complex forms in solution. SEC running buffer: 150 mM NaCl, 10 mM HEPES pH 7. 5, 2 mM CaCl 2 , 1 mM sucrose octasulfate, 0. 02% NaN 3 (flow rate 0. 3 ml/min; Superose 6 Increase 10/300 GL column; 21 C). SEC input was 0. 6 ml of the ternary complex at 2. 6 mg/ml. (A-C) Model for BMP2-dependent clustering of the ternary 3:3:3 NEO1-NET1-RGM complex. (A) Ribbon presentation of the ternary NEO1-NET1-RGM complex, with modelled RGMB N-terminal domain based on the full-length RGMB structure (PDB ID.
n = 3 experiments, one-way ANOVA followed by Tukey's multiple comparison test. *p < 0. 05. Data are shown as means ± SEM. (H-J) Comparison of binary NEO1-RGM (PDB ID 4BQ6 [Bell et al. , 2013] ) and the ternary NEO1-NET1-RGMB complexes shown as ribbons. The ternary NEO1-NET1-RGMB protomer complex architecture (I) clashes with the NEO1-RGM dimer-of-dimers signaling conformation (H) when superimposed on NEO1 (marked with an asterisk) (J). See also Figures S3, S4, and S5.
The relative orientation of the plasma membrane is depicted. The region marked corresponds to the protomer in (A). (D) Cartoon representation of the previously published DCC FN45 -NET1 DNTR complex (PDB Id 4PLO [Xu et al. , 2014]) shown in the same orientation as the NET1 DNTR -NEO1 FN456 complex from C. Both complexes form a similar, continuous array in the crystal. The DCC FN6 domain missing in the DCC-NET1 complex is depicted schematically. (E and F) Sedimentation velocity AUC experiments of the binary NET1 DNTR -NEO1 FN456 complex. The complex reveals concentration-dependent increase of oligomerization, characterized by a shift to higher s(S) values (E). This can be inhibited by NET1 interface-1 and -2 mutants that both result in a reduction of the apparent molecular weight (F), corresponding to a 1:1 NET1-NEO1 complex stoichiometry.
ACKNOWLEDGMENTS We thank the staff of beamlines  I03  and  B21  at the  Diamond Light Source (DLS) ,  UK , and  M. Broekhoven ,  K. Harlos ,  N. Mitakidis ,  D. Staunton , and  T. Walter  for technical support. We thank the following people for their generous gifts of reagents:  A. Berns ,  A. Che  ´dotal,  D. Davis ,  R. Giger ,  K. -L. Guan ,  M. Kiliman ,  C. River ,  T. Skutella , and  G. Smit. Work was supported by  Cancer Research UK  ( C20724/A14414  and  C20724/A26752  to C. S. ),  European Research Council  ( 647278  to C. S. ),  Medical Research Council UK  ( MR/ L017776/1  to C. S. and A. R. A. ;  MR/L009609/1  and  MC_UP_1201/15  to A. R. A. ), the  Netherlands Organisation for Scientific Research (ALW-VICI) ,  The People Program  ( Marie Curie Actions ) of the European Union's  Seventh Framework  ( FP7)  under  REA  grant agreement number  289581  (NPlast), the  UU Strategic Theme ''Dynamics of Youth'', ALS Stichting Nederland (TOTALS) , and  Stichting ParkinsonFonds  (to R.
Software and Algorithms autoBUSTER  (Bricogne et al. , 2011)  https://www. globalphasing. com/buster/ REFMAC5  (Murshudov et al. , 2011)  http://www. ccp4. ac. uk/download PHASER (McCoy et al. , 2007) http://www. ccp4. ac. uk/download PDBsum (Laskowski, 2001) http://www. ebi. ac. uk/pdbsum PISA (Krissinel and Henrick, 2007) http://www. ebi. ac. uk/pdbe/pisa/ Coot (Emsley and Cowtan, 2004) http://www2. mrc-lmb. cam. ac. uk/personal/ pemsley/coot/ PyMOL (Schrodinger, 2010) https://www. pymol. org/ Consurf (Ashkenazy et al. , 2010) http://consurf. tau. ac. il/2016/ ATSAS (Petoukhov et al. , 2012) https://www. embl-hamburg. de/biosaxs/ software. html ScA ˚tter (Rambo and Tainer, 2013) http://www. bioisis. net/ MolProbity (Davis et al. , 2007) http://molprobity. biochem. duke. edu/ AllosMod-FoXS (Guttman et al.
, 2013) http://modbase. compbio. ucsf. edu/allosmod-foxs/ MultiFoxs (Schneidman-Duhovny et al. , 2016) https://modbase. compbio. ucsf. edu/multifoxs/ Scrubber2 BioLogic Software http://www. biologic. com. au/ PRIVATEER (Agirre et al. , 2015a) https://github. com/agirre/privateer Sedfit (Brown and Schuck, 2006) http://www. analyticalultracentrifugation. com/ default. htm ImageJ (Schneider et al. , 2012) https://imagej. nih. gov/ij/download. html Clustal Omega (Chojnacki et al. , 2017) https://www. ebi. ac. uk/Tools/msa/clustalo/ GraphPad Prism GraphPad Software http://www. graphpad. com/scientific-software/ prism/ ASTRA 6 Wyatt https://www. wyatt. com/products/software/ astra. html EPU FEI https://www. fei. com/software/epu-automatedsingle-particles-software-for-life-sciences/ RELION 3. 1 (Zivanov et al.
, 2018) https://www3. mrc-lmb. cam. ac. uk/relion/ index. php/Main_Page cryoSPARC (Punjani et al. , 2017) https://cryosparc. com CTFFIND 4. 1 (Rohou and Grigorieff, 2015) https://grigoriefflab. umassmed. edu/ctffind4 UCSF Chimera (Goddard et al. , 2007) https://www. cgl. ucsf. edu/chimera/download. html Phenix (Afonine et al. , 2018) https://www. phenix-online. org/download/ XIA2 (Winter, 2010) https://xia2. github. io/.
(C) Overall arrangement of the NET1-NEO1 complex, which forms a continuous array in the crystal. The relative orientation of the plasma membrane is depicted. The region marked corresponds to the protomer in (A). (D) Cartoon representation of the previously published DCC FN45 -NET1 DNTR complex (PDB Id 4PLO [Xu et al. , 2014]) shown in the same orientation as the NET1 DNTR -NEO1 FN456 complex from C. Both complexes form a similar, continuous array in the crystal. The DCC FN6 domain missing in the DCC-NET1 complex is depicted schematically. (E and F) Sedimentation velocity AUC experiments of the binary NET1 DNTR -NEO1 FN456 complex. The complex reveals concentration-dependent increase of oligomerization, characterized by a shift to higher s(S) values (E). This can be inhibited by NET1 interface-1 and -2 mutants that both result in a reduction of the apparent molecular weight (F), corresponding to a 1:1 NET1-NEO1 complex stoichiometry.
(D) scRNAseq dataset analysis (Mizrak et al 2019)  for co-expression of RGMA/B, NEO1 and NET1 in adult V-SVZ. Single-cell expression levels of cluster-specific marker genes in adult ventricular-subventricular zone (V-SVZ) cells plotted on UMAP embedding(Cldn10, Mog, Ccnd2, Tmem119, Meg3, Egfl7, Ccdc153, Vtn, Pdgfra, Fyn). In addition, expression levels of Neogenin (NEO1), Netrin-1 (NET1), RGMA and RGMB are shown. Clusters marked as[clusterID]. OPC, oligodendrocyte precursor; COP, committed oligodendrocyte precursors.
Animals were fed ad libitum. All experiments were approved by the Animal Ethics CommitteeMETHOD DETAILSExpression and purification of recombinant proteins List of cDNAs and construct boundaries for secreted protein production: human NET1 (GenBank ID U75586; NET1 DNTR : 25-453, NET1 FL : 25-604), mouse NEO1 (GenBank ID NM_001042752. 1,eNEO1:42-1117,NEO1FN56 :867-1117, NEO1 FN456 : 766-1117, NEO1 FL : 42-1465), human DCC (GenBank ID AC011155; DCC FN56 : 842-1097, DCC FN456 : 720-1097, DCC FL : 26-1447), chicken RGMA (GenBank ID AY128507; RGMA ECD : 29-403), human RGMA (GenBank ID AL136826; RGMA ECD : 47-423), human RGMB (GenBank ID AK074887; full-length GPI-anchored RGMB: 50-437, RGMB ECD : 53-412, RGMB DN : 140-414, RGMB core : 137-334) and human RGMC (GenBank ID AY372521; RGMC ECD : 36-400).
105 enriched cells were incubated in serum-free medium for 1h at 37°C with 150nM CHIK-sE2-A488 or left untreated. Where indicated, CHIK-sE2-A488 was preincubated for 20min with anti-CHIK-sE2 mAb before addition of CD14+ dAPCs. Cells were stained with antibodies against HLA-DR, CD1a, CD14 and CD1c and analyzed by flow cytometry. (h) Relative MFI comparing the fluorescence intensity of CHIK-sE2-A488-treated vs. untreated cells (n=3-6 donors). (i) Confocal microscopy images of CD14+ dAPCs exposed to CHIK-sE2-A488 for 30 min at 37°C. Cells were labelled for cell-surface HLA-DR, fixed and visualized by fluorescence microscopy. DAPI labels nuclei in blue. Scale bars: 10µm. Data were obtained from at least three different donors and are presented as mean ±SEM. Statistical comparisons: ANOVA followed by post-hoc tests (ns: non significant, *p<0.
Antibodies and media The following antibodies were used for flow cytometry: HLA-DR (clones Tü39 or L243), CD206/MR (19. 2), CD209/DC-SIGN (DCN46), CD1a (HI149), CD86 (FUN-1), IFN-γ (B27), CD3 (UCHT1) from BD, CD14 (MEM-18, Immunotools), CD1c (AD5-8E7) and CD4 (REA623) from Miltenyi Biotec, and CD207/Langerin (DCGM4, Dendritics). Staining buffer was PBS containing 2% fetal calf serum (FCS; Dutscher) and 2. 5mM EDTA (SE buffer). Dead cells were labelled by Fixable Viability Dye-eFluor450 (eBioscience) or Sytox Red dye (Invitrogen). Cells were collected on FACSCalibur (BD) or Gallios (Beckman-Coulter) flow cytometers. Data were analysed with CellQuest (BD), Kaluza (Beckman-Coulter) or FlowJo (Treestar) softwares. Complete medium was RPMI1640 supplemented with 10µg/mL gentamycin, 100 units/mL penicillin, 100μg/mL streptomycin, 10mM HEPES (all from Lonza) and 10% FCS.
Recombinant CHIK-sE2 protein production Stably transfected Drosophila melanogaster S2 cell line inducible for the secretion of the ectodomain of CHIKV envelope E2 protein (CHIK-sE2; residues 4-364) were described elsewhere  (Aubry et al. , 2015). Briefly, a SNAP adaptor sequence (New England Biolabs) was fused in-frame with the C-terminus of recombinant CHIK-sE2, resulting in a chimeric protein that was purified from the supernatants of S2 cells. SNAP is the catalytic site of O6-alkylguanine-DNA-alkyltransférase. 3D rendition of CHIK-sE2-SNAP was created with the Yasara software based on the available crystal structures (CHIK-sE2: PDB 3J2W; SNAP-tag: PDB 3KZY).
The sensor chip surface was regenerated after each experiment by injecting 10µL EDTA 0. 5M pH 8. 0. The kinetic parameters were calculated using the BIAeval 4. 1 software. Analysis was performed using the simple Langmuir binding 1:1 model with separate ka/kd (kon/koff). The specific binding profiles were obtained after subtracting the response signal from the control channel and from blank-buffer injection. The fitting to each model was judged by the chi-square value and randomness of residue distribution compared to the theoretical model.
10 5 enriched cells were incubated in serum-free medium for 1h at 37°C with 150nM CHIK-sE2-A488 or left untreated. Where indicated, CHIK-sE2-A488 was preincubated for 20min with anti-CHIK-sE2 mAb before addition of CD14 + dAPCs. Cells were stained with antibodies against HLA-DR, CD1a, CD14 and CD1c and analyzed by flow cytometry. (h) Relative MFI comparing the fluorescence intensity of CHIK-sE2-A488-treated vs. untreated cells (n=3-6 donors). (i) Confocal microscopy images of CD14 + dAPCs exposed to CHIK-sE2-A488 for 30 min at 37°C. Cells were labelled for cell-surface HLA-DR, fixed and visualized by fluorescence microscopy. DAPI labels nuclei in blue. Scale bars: 10µm. Data were obtained from at least three different donors and are presented as mean ±SEM. Statistical comparisons: ANOVA followed by posthoc tests (ns: non significant, *p<0.
10 5 enriched cells were incubated in serum-free medium for 1h at 37°C with 150nM CHIK-sE2-A488 or left untreated. Where indicated, CHIK-sE2-A488 was preincubated for 20min with anti-CHIK-sE2 mAb before addition of CD14 + dAPCs. Cells were stained with antibodies against HLA-DR, CD1a, CD14 and CD1c and analyzed by flow cytometry. (H) Relative MFI comparing the fluorescence intensity of CHIK-sE2-A488-treated vs. untreated cells (n=3-6 donors). (I) Confocal microscopy images of CD14 + dAPCs exposed to CHIK-sE2-A488 for 30 min at 37°C. Cells were labelled for cell-surface HLA-DR, fixed and visualized by fluorescence microscopy. DAPI labels nuclei in blue. Scale bars: 10µm. Data were obtained from at least three different donors and are presented as mean ±SEM. Statistical comparisons: ANOVA followed by post-hoc tests (ns: non significant, *p<0.
Acknowledgements PD, CGM and VF designed the research. JR and CM provided EBNA-1-specific T cell lines and methods for antigen-specific assays. JBM and OC produced antigenic peptides. OC performed surface plasmon resonance assays. AB, MK, MC, AS, AH, HHG, CGM and VF performed experiments. AB, MK, CGM and VF analyzed the data. AB, PD, CGM and VF wrote the manuscript. The authors wish to thank  Dr. Teunis Geijtenbeek  ( University of Amsterdam, NL ) for anti-DC-SIGN mAb clone AZN-D1, as well as  Drs. Sylvie Tourne  and  Henri De La Salle  ( Etablissement Français du Sang, Strasbourg, France ) for their advice on HLA typing assays. This work was Acknowledgements PD, CGM and VF designed the research. JR and CM provided EBNA-1-specific T cell lines and methods for antigen-specific assays. JBM and OC produced antigenic peptides.
OC performed surface plasmon resonance assays. AB, MK, MC, AS, AH, HHG, CGM and VF performed experiments. AB, MK, CGM and VF analyzed the data. AB, PD, CGM and VF wrote the manuscript. The authors wish to thank  Dr. Teunis Geijtenbeek  ( University of Amsterdam, NL ) for anti-DC-SIGN mAb clone AZN-D1, as well as  Drs. Sylvie Tourne  and  Henri De La Salle  ( Etablissement Français du Sang, Strasbourg, France ) for their advice on HLA typing assays. This work was supported by the  European Union   Marie-Slodowska-Curie Career Integration Grant  of  Dr. V. Flacher  ( PCIG12-GA-2012-334011 -DERMACRO ) and by the  Agence Nationale pour la Recherche  ( Program ''Investissements d'Avenir,' '  ANR-10-LABX-0034   MEDALIS  and  ANR-11-EQPX-022 ). CRediT statement Conceptualization: PD, CGM, VF; Data Curation: AB, CGM, VF; Formal Analysis: AB, CGM, VF; Funding Acquisition: CGM, VF; Investigation: AB, MK, MC, AS, AH, HHG, CGM, VF; Methodology: OC, CM, PD, CGM, VF; Project administration: CGM, VF; Resources: JBM, OC, PD, JR, CM, PD; Supervision: PD, CGM, VF; Validation: AB, MK, MC, AS, AH, HHG, JR, JBM, OC, CM, PD, CGM, VF; Visualization: AB, OC, CGM, VF; Writing -Original Draft Preparation: AB, PD, CGM, VF; Writing -Review and Editing: AB, PD, CGM, VF.
supported by the  European Union   Marie-Slodowska-Curie Career Integration Grant  of  Dr. V. Flacher  ( PCIG12-GA-2012-334011 -DERMACRO ) and by the  Agence Nationale pour la Recherche  ( Program ''Investissements d'Avenir' '  ANR-10-LABX-0034   MEDALIS  and  ANR-11-EQPX-022 ;  ANR  ERAPerMed  ANR-18-PERM-0001  BATMAN). ; Data Curation: AB, CGM, VF; Formal Analysis: AB, CGM, VF;.
All plants infested with aphids were kept in a growth chamber adjusted to a 16:8-hour light:dark photoperiod, a temperature of 23 °C, and a relative humidity of 65%. To obtain cohorts of the same age for both aphid species, 10 or 15 wingless parthenogenetic adult females were introduced with a fine brush on uninfested threeweek-old plants, potato or tomato for the foxglove aphid and cucumber for the melon aphid. Adults were removed after 48 hours, and the resulting nymphs were considered synchronous cohorts. Bacteria. Spore suspensions of both strains, Bacillus pumilus PTB180 (GenBank accession number MW036295. 1) and Bacillus subtilis PTB185 (GenBank accession number MW246959. 1), were provided by Premier Tech (Rivière-du-Loup, Québec, Canada). These solutions contained 1 × 10 9 colony-forming units per millilitre and were always kept at 4 °C.
Greenhouse tests The tests were conducted in a greenhouse at Université Laval (Québec, Québec, Canada), adjusted to a 16:8-hour light:dark photoperiod, a temperature of 25 °C during the day and 21 °C at night, and a relative humidity of 65%. Environmental parameters were continuously recorded during the experiments with HOBO data loggers (Onset Computer Corporation, Bourne, Massachusetts, United States of America). Tomato and cucumber plants were watered daily using a drip irrigation system and fertilised weekly with 150 mL of a solution containing 200 mg/L of the 20-20-20 fertiliser (Plant Prod 20-20-20 Classic, Plant Prod, Brampton, Ontario, Canada; 5. 9% nitrate nitrogen, 3. 9% ammoniacal nitrogen, 10. 2% urea nitrogen, 8. 7% soluble phosphorus, 16. 6% soluble potassium). The experimental design was a completely randomised block design with four treatments and five replicate blocks, for a total of 20 plants.
Statistical analysis All statistical analyses were performed using the Mixed procedure of SAS software, release 9. 4 (SAS Institute Inc. , Cary, North Carolina, United States of America) at the 0. 05 level of significance. For the laboratory tests, the mortality rates of the two aphid species were used as the response variables. These data were analysed using a generalised randomised block analysis of variance model, in which the treatments were considered a fixed factor and the repeated trials and the replication of each treatment within each block were considered random factors. Following a significant treatment effect, multiple pairwise least significant-difference comparisons were used to determine which treatments differ. The normality assumption was verified using the Shapiro Wilk's test, and the homogeneity of the variances was verified by the residual plot.
For the greenhouse tests, the same statistical analyses described previously were applied. The response variable was the mortality rate for both aphids, but for the melon aphid, the number of live aphids found on the sampled cucumber leaves was also examined. Finally, for the tests on the persistence of bacteria, the concentrations calculated at the two measurement times (day 1 and day 9) were analysed as a function of the different treatments with an analysis of variance with repeated measures using the Mixed procedure (SAS software, release 9. 4).
Acknowledgements. The authors thank  Premier Tech 's team, especially  Catherine Viel  and  Alain Bélanger. They also extend special thanks to  Mathieu Bouchard Rochette ,  Elizabeth Demeule ,  Jean Bélanger ,  Victor Bérubé Girouard ,  Marine Daniel ,  Catherine Bolduc ,  Aurélie Boilard ,  Thaïs Andro ,  Guillaume Guengard ,  Clémence Landreau ,  Lucie Alexandre , and  Andréa Duclos  for their assistance in the laboratory, and they are also grateful to  Gaétan Daigle  for assistance with statistical analysis. The authors thank the  Consortium de recherche et innovations en bioprocédés industriels au Québec (CRIBIQ) ,  Premier Tech ,  Anatis Bioprotection , and the  Natural Sciences and Engineering Research Council of Canada (NSERC)  for financial support.
Clinical Data Set The following clinical and biologic parameters were collected for each patient at the time of their renal biopsy and at time of immune complex measurement: age, sex, weight, height, clinical presentation at disease onset, time from onset to renal biopsy, presence of a macroscopic hematuria at diagnosis, history of tonsillectomy, familial IgAN history (either proven by renal biopsy or suspected because of a medical history of microscopic and/or macroscopic hematuria in a next-of-kin), systolic and diastolic blood pressure, serum albumin, serum IgA levels, serum creatinine (expressed in micromoles per liter), estimated glomerular filtration rate (eGFR), urine protein-tocreatinine ratio (in grams per millimole, used as an estimation of 24-hour protein excretion adjusted for body surface area).
Sequencing and Genetic Analysis of COL4A Genes We sequenced COL4A3, COL4A5, and COL4A4 coding sequences with targeted capture sequencing (MiSeq; Illumina, San Diego, CA) in cIgAN patients and in both parents when available. For the exome study, genomic DNA was isolated from blood samples, and exons (33 megabases) were captured with the Twist Human Core Exome kit (Twist Bioscience, South San Francisco, CA) and sequenced on a NovaSeq 6000 instrument on Illumina platforms. Data were analyzed using dedicated software (SeqOne, Montpellier, France) to identify diagnostic variants for patients' renal disease. We used the Geneome Aggregation Database version 2. 1 to estimate allele frequency. For the exome data analysis, the assessment was restricted to COL4A3, COL4A5, and COL4A4 genes for consistent comparison with the initial exon capture.
Statistical Analysis Median (interquartile range) values and frequencies are provided for description of continuous and categorical variables, respectively. The Shapiro-Wilk test was used to test the normality of the data distribution for the t test. The mean values and proportions of 2 groups were compared using Mann-Whitney and Fisher exact tests, respectively. All tests were 2-sided, and P < 0. 05 was considered statistically significant. All statistical analyses were performed with GraphPad Prism version 7 (GraphPad, La Jolla, CA) and SPSS version 25 (IBM Corp, Armonk, NY).
Remerciements Les recherches menant à ces résultats ont reçu un co-financement de l' Agence Nationale de la Recherche en France  (n°  ANR-20-COVI-0088-01 ) et de la  Région Occitanie  (arrêté n°2000-7460). Ces résultats s'inscrivent dans le programme interdisciplinaire EPIDEMIC ( 2020-2021 ) de l' Institut Fédératif d'Études et de Recherches Interdisciplinaires Santé Société -IFERISS FED 4142. Nous remercions également tous les participants et toutes les participantes aux enquêtes et études utiles aux analyses présentés ici.
Method of analysis of results The sample of answers to the questionnaire was not constructed on a representative basis but on an exploratory one according to Tukey's exploratory approach  [10]. The two authors took part in a one-day training for primary school trainers in two different regional areas, one in Paris area in October 2018, and the other one in East of France in December 2018. Two weeks before the training, each participant received the online questionnaire and could voluntarily and anonymously answer: we got 124 answers. The statistical analysis uses SPAD software which provides frequency tables, cross-tabulation and cluster analysis. Every question can be considered as a variable and the different answers to this question as the different modalities of the variable. We begin with a frequency analysis that enables to choose the active variables for the following cluster analysis.