dataesr/scientific-paragraphs-categorization huggingface dataset:
The predicted model by I-TASSER software  [25]  showed that the four sequences have a 3D-structure typical of lipocalins, with eight β-strands forming a β-barrel in addition to an α-helix, and a disulphide bridge (Cys63-Cys155) conserved in all Mammalian OBPs except in the bovine one  [17]. If the two OBP2 have a 3D-structure very similar to porcine OBP  [26] , a second disulphide bridge is formed in the OBP4 between Cys44 and Cys48 (Fig. 4 ). This bridge is only found in rodents OBP, more specifically in Cricetidae, in proteins expressed in fluids involved in chemical communication, such as hamster aphrodisin  [27]  and bank vole glareosin  [28]. In aphrodisin, the disulphide bridge forms a loop where an asparagine, not conserved in OBP4, is N-glycosylated  [29]. Hence, the two OBP4 seem rather specific to the small ungulates, and could have a role in the binding of specific odours of these species.
The strong signal in SA could be due to Oari-SAL1 and Oari-SAL2 that are not expressed in SR (Table  1 ). Indeed, pig SAL, which is phylogenetically close to Oari-SALs (Fig. 3 ) is N-glycosylated  [31]. Four sites of N-glycosylation were indeed predicted by the NetNGlyc software (http://www. cbs. dtu. dk/services/NetNGlyc/) for Oari-and Chir-SAL. These results suggest the existence of two groups of SAL-like proteins in ewe, one group of isoforms in the 25 kDa string in SA, N-glycosylated, and one group of isoforms in the 20 kDa string (Table  2 ), which are not N-glycosylated. As one site of N-glycosylation was predicted by NetNGlyc for Oari-OBP2, its isoforms in the 20 kDa string could be N-glycosylated as well.
The map of labelled spots can be found in Additional file 1: Figure  S5 (a-d ). The same samples were digested with alkaline phosphatase to assess the specificity of Q5 antibodies (Additional file 1: Figure  S6a ). Indeed, dephosphorylated samples were not labelled by this antibody after western-blot. Comparing the proteins identified in these spots and the antibody labelling, we propose that OBP2 and OBP4 could carry this modification in both species. The physiological status of the female could have an impact on the number of phosphorylated isoforms expressed in the secretome, leading to more phosphorylation in SA in ewe and more phosphorylation in SR in goat. Conversely, antibody Q7, raised against phosphothreonine labelled all samples (Additional file 1: Figure  S7 ). To confirm and if possible, localize the phosphorylation sites in ewe and goat OBPs, nano-LC-MS/MS data were analysed with Scaffold software.
It was proposed that porcine OBP O-GlcNAcylation  [21]  could be performed by a ER-resident enzyme, primarily identified in Drosophila  [42] , the EOGT glycosyltransferase (EGF-domain Olinked N-acetylglucosaminyl transferase). The encoding gene is present in sheep and goat genome at accession numbers W5PKW4 and XP_017893891. 1, respectively. The porcine, ovine and caprine EOGT protein sequences share 95% of homology suggesting a common role in OBP O-GlcNAcylation. Is the olfactory secretome a phenotype of the female physiological status? The three olfactory secretomes of ewe, goat and pig yet studied show a specificity of the 2D-profile for a species, despite phylogenetically close primary sequences (Fig. 3 ) and common post-translational modifications  [21]. The isoforms are dispatched in gels with a high specify from one species to another, and these profiles vary under hormonal control (this study,  [21] ).
For GlcNAc competition assays, proteins were separated by SDS-PAGE, transferred onto PVDF membranes, which were blocked as above. Then, membranes were incubated 1 h (RT) with a pre-incubated mixture (1 h at RT) of CTD110. 6 antibodies and 1 M GlcNAc (TCI) in TBS-T-5% BSA. They were washed and processed as above until ECL detection. Phosphorylated proteins were detected using anti-phospho-Threonine (Q7) or anti-phospho-Serine (Q5) antibodies (Qiagen) according to manufacturer's protocol (Phosphoprotein Purification kit, Qiagen). The signal detection was performed as described above. Scanned images of stained gels and blots were merged using Image J software (NIH). To assess the specificity of Q5 antibodies, 15 μg of total proteins were digested by 20 U of Alkaline Phosphatase (Sigma-Aldrich) at 37 °C overnight in enzyme buffer (10 mM Tris, 5 mM MgCl 2 , 10 mM ZnCl 2 ).
Homology modelling Three-dimensional structure of OBP2 and OBP4 proteins from both species were predicted by I-TASSER software, available at https://zhanglab. ccmb. med. umich. edu/I-TASSER/  [25]. For each OBP2 sequence, only one model was generated, with C-score of 0. 84 (Oari-OBP2) and 0. 87 (Chir-OBP2). Among the Top 10 identified structural analogues in the protein data bank (PDB) used to generate the model, the two OBP2 shared 31% of sequences with the dog lipocalin (PDB entry code 5X7Y, doi: https://doi. org/10. 2210/pdb5X7Y/pdb), and 99% with the model superimposed with 5X7Y, at a root mean square deviation of 3. 2 Å. For each OBP4, again only one model was generated with C-score of 1. 03 (Oari-OBP4) and 1. 08 (Chir-OBP4), with the allergen Bos d2 (from Bos taurus, PDB entry code 4WFV, doi: https://doi.
4). Membranes were washed three times during 10 min in TBS-T (TBS-0. 1% Tween 20) and three times during 15 min in TBS buffer. The signal was revealed by chemiluminescence with the SuperSignal™ West Dura Extended Duration Substrate (Pierce, Fisher Scientific). RNase B (0. 5 μg) was used as positive control. In silico search for O. aries and C. hircus OBP sequences Putative OBP sequences were searched in goat genome, available at Ensembl database (not annotated), by performing a BlastX search (default parameters, Ensembl v. 87, Dec 2016) with porcine OBP, VEG and SAL nucleotide sequences as query. The sheep genome is partially annotated and available in GenBank database, we thus searched putative O. aries OBPs by BlastP (v. 2. 6. 0 Jan 2017) using porcine and bovine OBPs as query protein sequences (Table  3 ).
Peptides were solubilized in 0. 1% trifluoroacetic acid and mixed with 10 mg/mL α-Cyano-4-hydroxycinnamic acid matrix. MALDI-TOF MS analysis was performed on an Applied Biosystems, Voyager DE Pro mass spectrometer. The instrument was used in positive reflector mode, measuring peptide masses on a range of 500-4000 Da. Spectra were analysed with Data Explorer V4. 6 (Applied Biosystems).
Nano-LC-MS/MS Spots were excised from stained gels and analysed by the P3M platform of "Institut Pasteur de Lille" for trypsin digestion and mass spectrometry proteomics analysis. Digestion of in-gel proteins was performed as previously described  [48]. An UltiMate 3000 RSLC nano System (Thermo Fisher Scientific) was used for the separation of protein digests. Peptides were automatically fractionated Up to one trypsin missed cleavage was allowed. For each sample, peptides were filtered out according to the cutoff set for proteins hits with two or more peptides larger than nine residues, ion score > 15, no false positive protein was identified. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD014833 and https://doi.
org/10. 6019/ PXD014833". Amplification of the full-length nucleotide sequences of OBPs by rapid amplification of cDNA ends-polymerase chain reaction (RACE-PCR) Total mRNA was extracted from 30 mg of nasal mucosa conserved in RNAlater (Qiagen) with the RNeasy Mini Kit (Qiagen). For amplification of the 5′ end, 5 μg of mRNA was first dephosphorylated with 10 U of CIAP (Calf Intestinal Alkaline Phosphatase, Invitrogen). Cap structures were removed with 5 U of RppH (5′ Pyrophosphohydrolase, New England BioLabs®), then mRNA was ligated to GeneRacer™RNA Oligo (GeneRacer™ kit, Invitrogen, 5′-CGACUGGAGCACGAGGACACUGACAUGGACUGA AGGAGUAGAAA-3′) with 5 U of T4 RNA ligase 1 (New England BioLabs®). Between each step, mRNA was cleaned up with the RNeasy MinElute CleanUp Kit (Qiagen). Capped mRNA (5'RACE) and native mRNA (3'RACE) were reverse transcribed using SuperScript™ IV RT kit (Invitrogen, Fisher Scientific) with 5′-gene specific primer (Additional file 1: Table  S8 ) or GeneRacer™ Oligo dT primer (GeneRacer™ kit, Invitrogen), respectively.
Molecular phylogenetic analysis by maximum likelihood method The evolutionary history was inferred by using the Maximum Likelihood method based on the Tamura-Nei model  [49]. The tree with the highest log likelihood (-7216. 11) was built. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbour-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The tree was drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 23 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 451 positions in the final dataset. Evolutionary analyses were conducted in MEGA7  [50].
4. 0, Matrix Science, London, UK) installed on a local server. Searches were performed with a tolerance on mass measurement of 0. 2 Da for the precursor and 0. 02 Da for the ion fragment, against two composite target decoy databases built with C. hircus NCBI databases (TaxID = 9925, 05 January 2017, 46,032 entries) or O. aries UniProt database (TaxID: 9940, 20 March 2017, 27,139 entries), both fused with the sequences of recombinant trypsin and a list of classical contaminants (118 entries). Cysteine carbamidomethylation, methionine oxidation, protein N-terminal acetylation, cysteine propionamidation, serine and threonine phosphorylation were searched as variable modifications.
Availability of data and materials The datasets supporting the conclusions of this article are included within the article and its Additional file 1. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  [24]  partner repository with the dataset identifier PXD011371 and https://doi. org/10. 6019/PXD01137. The full-length sequences of Chir-OBP2, Chir-OBP4, Oari-OBP2, and Oari-OBP4 were deposited in GenBank database with accession numbers: MK908982, MK908983, MK908984 and MK908985, respectively.
4. 0, Matrix Science, London, UK) installed on a local server. Searches were performed with a tolerance on mass measurement of 0. 2 Da for the precursor and 0. 02 Da for the ion fragment, against two composite target decoy databases built with C. hircus NCBI databases (TaxID = 9925, 05 January 2017, 46,032 entries) or O. aries UniProt database (TaxID: 9940, 20 March 2017, 27,139 entries), both fused with the sequences of recombinant trypsin and a list of classical contaminants (118 entries). Cysteine carbamidomethylation, methionine oxidation, protein N-terminal acetylation, cysteine propionamidation, serine and threonine phosphorylation were searched as variable modifications. Uniprot accession # GenBank accession # for sheep OBP search for goat OBP search Porcine OBP P81245 NM_213796. 1 Bovine OBP P07435 XM_002700469.
II. THEORETICAL FRAMEWORK We proceed to estimations in two steps. In the first step we use individual data from the 2010 Brazilian census and decompose the gender gap through the Blinder-Oaxaca procedure using two levels of geographical disaggregation: states (26) and micro regions (558). In the second step we compare the resulting components of those decompositions with GDP per capita and inequality levels of the states and micro regions, respectively. In order to identify regional disparities in Brazil it is essential to geographically disaggregate the analysis. Most papers detail the analysis by political regions  (Scorzafave and Pazello 2007; Madalozzo 2010; Madalozzo and Mauriz 2012)  or states  (Lovell 2000b). Such levels of disaggregation permit the identification of many aspects of inequality in Brazil, but they are insufficient to capture intrastate differences (e.
III. DATA The main data source is the 2010 Brazilian census, which provides individual data on earnings and hourly load. The data for GDP and population are from IPEAdata. 14 We restrict the sample to those individuals in the labor market aged from 24 to 64 years, which includes about 7. 2 million people: 4. 2 million males and 3 million females. 15 he hourly income used in this study is calculated as the logarithm of the income from principal job divided by the hours worked by week in that job. The Brazilian census provides detailed data on income as income from principal job, income from other jobs, and income from sources other than jobs. However, these declared values are very sensitive information from the respondents' point of view, and measurement errors may compromise their quality.
Methods The health economic evaluation of COMET was based on clinical data from the trial and resource-use data from the four participating countries. 11 Country-specific costs were evaluated from a national health care payer perspective, and country-specific cost-effectiveness evaluations were performed in addition to a pooled analysis of all participating countries. The within-trial cost-effectiveness model was developed using the statistical programming language R (RStudio software version 0. 99. 447 © ; RStudio, Inc. , Boston, MA, USA). The analysis included patient characteristics and clinical outcomes. Data on country-specific health resource consumption collected during the trial and published cost estimates were used to evaluate direct medical and direct nonmedical costs for each country with over 25 patients in each treatment group (hospitalizations, medical and paramedical consultations, components such as coaching sessions, and technical costs of the DM intervention).
Patient population and clinical data The pooled analysis was based on the ITT population from COMET (NCT01241526), which comprised 319 patients from the four countries with 157 patients in the DM group and 162 patients in the UM group. The trial was approved by the local or national ethics committees and competent authority per country for each investigational center where applicable, and all patients provided written, informed consent (Table  S1 ). For the country-specific analyses, only France, Germany, and Spain were considered as they presented more than 25 patients in both DM and UM groups. The cohort characteristics and clinical outcomes from COMET have been published by Kessler et al. 10  The economic evaluation captured unscheduled all-cause hospital days, acute exacerbations, health-related quality of life (HRQoL), and mortality from the trial.
Qol In COMET, HRQoL data were collected using the 15D HRQoL instrument. It is a generic, 15-dimensional, standardized, self-administered measure of HRQoL in validated local language versions (http://www. 15d-instrument. net/15d/). The 15D HRQoL instrument was self-completed by study patients at study entry and every 6 months during the followup period. The collected data were not utilities, and needed to be mapped to utility scores using the validated Finnish algorithm. Utilities are preference health state values used to estimate quality-adjusted life years (QALYs).
statistical approach Statistical analysis was performed in the programming language R (using RStudio software version 0. 99. 447 © ). KMSA methods were used over 12 months to generate annualized costs and clinical outcomes from monthly estimates during the follow-up period. 12 The proportion of patients still alive at the beginning of the month was estimated, using the probability of survival in a given month. Mean estimates were then weighted and applied to all subsequent months to obtain the mean adjusted costs/outcomes per patient. This method was applied to the mean number of unscheduled hospital days, mean number of deaths, mean QALYs per patient, and the mean overall costs. Significance testing was performed on differences in costs between the two study groups in each country by calculating the CI of the cost difference, via a nonparametric bootstrapping approach (if the 95% CI of the cost difference included zero, the cost difference was considered as not statistically significant).
QoL data were collected using the 15D HRQoL instrument. While there is no published evidence and validated tools for utility score generation by country of interest from 15D HRQoL instrument, the EuroQol project provides indirect evidence supporting the use of a reference algorithm (such as the Finnish one used in the present study) to provide utility scores for different countries. Sintonen et al reported that it is largely unnecessary to replicate expensive valuation studies in Western industrialized countries to arrive at valid preference-based instruments, owing to the degree of concordance between health state valuations across European settings. 19 In the pooled analysis, DM was associated with improvements in QoL vs UM, and this was also true when all three countries were analyzed separately.
Acknowledgments This study was supported by funding from  Air Liquide Santé International , and health economic analysis was performed by HEVA HEOR. The authors thank all the COMET personnel who participated in this study, in particular the VitalAire case managers from the four countries, the three members of the  Endpoint Validation Committee  ( Dr Bucknall ,  Respiratory Medicine ,  Glasgow Royal Infirmary, Scotland, UK ;  Prof Burgel ,  Pneumologie et Centre de Mucoviscidose de l'adulte, Hôpital Cochin, Paris, France ;  Prof Vogelmeier ,  Pulmonary Division, Marburg University Hospital, Marburg, Germany ), and the.
ACKNOWLEDGEMENTS We thank  A. Ferrera ,  V. Muñoz-Fuentes ,  S. Saavedra ,  A. M. Neutel , and two anonymous referees for useful suggestions and comments. Simulations were made on the ScienceCloud of the  University of Zurich. Funding was provided by the  European Research Council  through an  Advanced Grant  (J. B. and M. S. ), the  Swiss National Science Foundation  (Grant  31003A_169671  to J. B. ), and the  Netherlands Earth System Science Centre  ( NESSC 024. 002. 001 , I. A. L, M. S. , and E. W. ).
Slug/Snail2 belongs to the Snail family of transcription factor and is involved in epithelialmesenchymal transition (EMT). In contrast to other EMT-inducing transcription factors, Slug is highly expressed in adult basal/progenitor cells in both mouse and human normal airway epitheliums  (7, 8). We hypothesized that Slug is involved in the fate of basal/progenitor cells, and, as such, deregulation of its function could lead to the decrease in count and functional ability of progenitors observed in COPD. To test this hypothesis, we exploited the Gene Expression Omnibus (GEO) dataset GSE123129 that we generated from a microarray analysis of Slug knockdown in basal/progenitor cells of COPD and normal subjects  (9). Transforming Growth Factor (TGF)-b is found at higher levels in COPD lung tissues and, as it has been shown to regulate Slug expression and to play a role in stem/progenitor cell fate, we also used the GEO dataset GSE122957 to select genes downstream of Slug in COPD that respond to TGF-β  (9) (10) (11) (12).
Quantitative Real-Time Polymerase Chain Reaction (qPCR) Quantitative PCR was done on the QuantStudio6 Flex with the QuantStudio Real-Time PCR software using SYBR green PCR master mix (Applied BioSystems). Primers (see additional le 3) were designed to be used with an annealing temperature of 60°C and an elongation time of 1min. For a given gene target, cDNA volume used was chosen to be in a Ct range from 20 to 30, using 0. 125mM each forward and reverse primer. Glyceraldehyde-3-Phosphate Dehydrogenase (GAPDH) was used to normalize cDNA amounts between samples.
Gene expression pro ling Microarray analysis was performed on biological triplicate samples. Total RNA were ampli ed and labeled before hybridization onto Affymetrix human Gene 2. 1ST GeneChip according to the manufacturer, by the Genomics platform at Curie Institute, Paris  (14). Array datasets were controlled using Expression console (Affymetrix) and further analyses and visualization were made using EASANA (GenoSplice, www. genosplice. com), which is based on the FAST DB annotations  (15, 16). Gene Array data were normalized using quantile normalization. Background corrections were made with antigenomic probes and probes were selected as described previously  (17). Only probes targeting exons annotated from FAST DB transcripts were selected to focus on well-annotated genes whose mRNA sequences are in public databases (16).
A search for enriched gene pathways using KEGG, REACTOME and Gene Ontology (GO) databases (18-20) identi ed 2 pathways related to stem cells, Somatic stem cell population maintenance and transcriptional regulation of pluripotent stem cell, comprising 5 genes coding all for transcription factors. We rst con rmed by RT-qPCR the fold-change induced by Slug knockdown in COPD and normal cells and Fig. 1b  shows the correlation with the values obtained in the microarray. The good correlation (R 2 values of 0. 7309 and 0. 5519, respectively for normal and COPD), validates the microarray analysis and con rms that all the genes are repressed downstream of Slug in COPD cells while they are not downstream of Slug in normal cells, except for ELF5 that is also repressed in normal cells but less than in COPD.
Acknowledgements We thank the  Pulmonary Department , the  Pathology Department  and the  Thoracic Surgery Department at Bichat-Claude Bernard University Hospital (Paris, France)  and  INSERM UMR 1152  for providing lung tissues and isolating the cells. We thank  Audrey Rapinat  and  David Gentien  at the  Genomics platform, Curie Institute (Paris, France ) for Affymetrix GeneChip hybridization.
2016). In this way, we obtained the Transcripts Per Kilobase Million (TPM) value for each gene in each sample as its normalized expression level, which is directly comparable both among different genes and among different samples. Sleuth (0. 30. 0)  (Pimentel et al. 2017 ) was further used to assess the statistical difference of the same gene between different samples by decoupling biological differences from experimental noise. False discovery rate (FDR; α = 0. 05) adjustment  (Benjamini and Hochberg 1995)  was further applied for multiple test correction. Total RNA was extracted from two biological replicates either during exponential growth or after 7 days of aging in SDC or in RM. Global expression level was analysed by pairwise comparison of the NA/WA hybrids hemizygotes for WA and NA-HPF1 within each environment and time point to identify differentially expressed transcripts.
Acknowledgments This work was supported by  Agence Nationale de la Recherche  ( ANR-11-LABX-0028-01 ,  ANR-13-BSV6-0006-01 ,  ANR-15-IDEX-01 ,  ANR-16-CE12-0019  and  ANR-18-CE12-0004 ) and the  Swedish Research Council  (2014Council ( -6547, 2014Council ( -4605 and  2018-03638)-03638 ).
Hence, the spin-restricted formalism is used for other computations. Furthermore, the DFT approach was proved sufficiently accurate in studying the reactivity of ruthenium alkylidene complexes  [12, 13, 18, [28] [29] [30] [31] [32] [33]. However, it shall be noticed, that for more difficult cases (e. g. , open-shell transition metal complexes), singledeterminant DFT shall be applied with special caution due to the approximated character of electron correlation, as well as a possible multireference character of wavefunction. All the above calculations were done with the Gaussian 09 software  [43]. For the Grubbs type catalysts, the charge and energy decomposition ETS-NOCV  [19, 20]  analysis was performed. DFT (BLYP  [44, 45] ) calculations were carried out with the Amsterdam Density Functional (ADF) program  [21, 22] , in which the ETS-NOCV scheme was implemented.