dataesr/scientific-paragraphs-categorization huggingface dataset:
Experiments were conducted using nine different patient samples per condition. Analyses were performed on Fortessa flow cytometer (Becton Dickinson, France) and results were analyzed using Flowlogic software (Miltenyi Biotec). Microarray data mining. Transcriptome data obtained using the Affymetrix Human Genome U133 Plus 2. 0 platform were downloaded from the NCBI repository Gene Expression Omnibus (GEO) database; the dataset accession number is GSE13811 28 including B-CLL cells alone (n = 9) or B-CLL cells co-cultured with NLC (n = 9). The BDNF probe ID was 239367_at. Data treatment and statistical analysis. Graphical representations were generated using GraphPad Prism 7 software. Immunohistochemistry and western blot analysis were quantified using ImageJ software (NIH). Results were analyzed by one-way ANOVA, followed by Fisher's post-hoc test.
Analyses were performed using StatView 5. 0 software (Abacus Concepts, Piscataway, NJ, USA). A p value < 0. 05 was considered significant. Data were obtained from at least three independent experiments and are presented as the mean and standard error of the mean (SEM). ethical approval and consent to participate. The study was approved by the Limoges University Hospital Institutional Review Board, AC 72-2011-18. All patients provided informed consent to participate, all experiments were performed in accordance with relevant named guidelines and regulation.
Acknowledgements The authors thank  Hafidha Bentayeb  for technical advice and valuable suggestions. We are grateful to the  Hematology laboratory of Limoges University Hospital  for collecting CLL blood samples. This work was supported and funded by grants from the  FEDER (Fonds Européen de Développement Régional) , the Limousin regional council, and  La Ligue Nationale Contre le Cancer  ( Comité Départemental de La Haute-Vienne ).
However, MATS is performed only in a few laboratories selected by the 4CMenB producer, therefore estimates of coverage are often limited to those based on genotypic analysis of all four antigens. The Bexsero antigen sequence type (BAST) provides a means of indexing distinct combinations of 4CMenB antigens that may then be combined with chosen genotypic coverage criteria  [15] [16] [17]. Recently, a genetic MATS assay (gMATS) was proposed that linked antigen genotyping and MATS data of 3481 MenB isolates from European and non-European countries. This led to the generation of a defined list of fHbp and NHBA peptides that were classed as covered, not covered or unpredictable. Only PorA P1. 4 was considered covered while NadA was always regarded as not covered. When gMATS is applied to large national datasets, the proportion of isolates with indeterminate coverage is divided equally into covered and not covered  [18].
DNA plasmid Microinjection and time-lapse microscopy For time-lapse experiments, sub confluent MS2-eGFP HeLa cells plated on glass coverslips (in a 12 well plate at 1. 5×10 5 cells/mL the day prior the experiment) were mounted in a Ludin Chamber (Life Imaging Services, Basel, Switzerland) following the protocol described in  (44). The cells were then placed on a Leica DMIRE2 microscope equipped with a chamber at 37 °C, with 5% CO2 (Life Imaging Services). A mixture of plasmids (72% pIntro, 17% Rev, 5. 5% Gag and 5. 5% mCH-Gag or Gag mutants in the NC domain) were microinjected into the nucleus at 0. 1 μg/μL with a fluorescent microinjection reporter solution (0. 5 μg/μL rhodamine dextran; Invitrogen), using a Femtojet/InjectMan NI2 microinjector (Eppendorf). The coordinates of several microinjected cells were memorized using a Märzhäuser (Wetzlar, Germany) automated stage piloted by the Leica FW4000 software.
Images were then acquired with a 100 × HCX PL APO (1. 4 NA) objective every 5 min during 2-4 h using a Leica DC350FX CCD camera controlled by the FW4000 software. Time-lapse movies were then analyzed using the MetaMorph (Molecular Devices, Sunnyvale, USA) and ImageJ (National Institutes of Health, USA) software in order to determine at which time the GFP signal appears at the PM (fluorescently labeled gRNA), as well as when Gag multimers appear at the PM.
Data from the NRC for antimicrobial resistance Associated laboratory responsible for CREs: for all strains received for analysis, identification was carried out by MALDI-TOF mass spectrometry (Microflex, Bruker Daltonics). For all enterobacterial strains, the following analyses were performed: • Mueller-Hinton agar diffusion susceptibility test (Bio-Rad); • carbapenemase activity assay using the Carba NP test  [8] ; • search for one of the five major families of carbapenemases (KPC, NDM, VIM, IMP, and OXA-48-like) by immunochromatographic strip NG-Test Carba5 (NG-Biotech)  [9]. For any strain detected as producing carbapenemase (Carba NP test and/or Carba5-positive NG-Test), the complete genome of the strain was sequenced. In 2018, the determination of the minimum inhibitory concentration for colistin and the search for mcr-(1 to 5) genes were systematically performed for all strains received at the NRC  [10].
Search of Iflavirus sequences: We first searched sequences matching iflaviruses in all available public transcriptome assemblies for ticks (available from TSA, Genbank). We searched assemblies (TSA files) rather than raw read (SRA database) because i) an exhaustive search of raw reads would have implied re-assembling de novo all RNA-Seq data sets for all tick species, which represent a considerable volume of data ii) most RNA-Seq projects for ticks have been assembled de novo and the assemblies are available in TSA iii) virus sequences are not filtered out from de novo assemblies by Genbank, in our experience iv) searches of unfiltered de novo assemblies using raw reads, which our group produced recently for 27 different tick species  [15]  gave the same results as a search to TSA assemblies, regarding positive or negative detection of iflaviruses.
ricinus transcriptomes and detected a third complete iflavirus genome (IricIV-3) in the recently published GIDG data set (TSA accession from NCBI). Last, we identified two iflavirus genomes in transcriptomes of pooled whole bodies of nymphs (Rispe et al. , in prep. ) collected on the vegetation, respectively in Switzerland (IricIV-4) and north-east France (IricIV-5). All viral genomes obtained in I. ricinus were highly similar to the ISIV sequence obtained from a cell line of I. scapularis (~98%, amino acid identity based on tblastn matches, while higher variation was detected at the nucleotide level, as shown below). All other data sets of reads from I. ricinus either showed absence of matches, or in one case, small fragmented contigs (GCJO data set) which we will not further consider here.
Although the ISIV sequence was found in a cell line transcriptome of I. scapularis, there was no match with this sequence in de novo assemblies obtained for three other independently sequenced transcriptomes of I. scapularis (two of them at least obtained from large collections of wild ticks, including a total of ~200 males and females from three locations for the GGIX01 accession number). Then, we also screened published assemblies for other tick species, as available in Genbank-TSA: this search was positive for I. frontalis (IfronIV) and I. vespertilionis (IvespIV) but in both cases the retrieved sequences were incomplete (5' partial), and the obtained ORF comprised respectively 2437 and 1945 amino acids (representing ~81% and ~65% of the complete genome respectively). Additionally, a 5' partial sequence was also found in a transcriptome assembly of I.
holocyclus (2039 amino acids, IhIV-2). This sequence (and the corresponding samples and sequencing) was different from the first iflavirus genome (IhIV) identified for that tick species. We also found a matching contig sequence in an assembled transcriptome (GFGI01 TSA assembly) of the tick Hyalomma dromaderii. The match was in two frames suggesting a likely frameshift, probably due to sequence errors in the reads, or in the assembly. We tentatively corrected the frameshift manually (with one base deletion) and obtained a complete iflavirus genome sequence for this species. All other assemblies, including several genera of hard and soft ticks proved negative for this search. Finally, other sequences were found after a blast (blastp) to the Genbank nucleotide database (nr): this allowed to include sequences of iflaviruses associated respectively with Amblyomma americanum, Haemaphysalis flava, Hamephysalis asiaticum, Ixodes holocyclus, Ixodes uriae, or with pools of tick species (Table  1 ).
We suggest that a more systematic use of RNA-Seq, based on large pools of wild individuals, would maximize chances of detecting that type of sequences even in case of low prevalence -see for example  [31]. More generally, this would enhance progress in the description of the virome associated with ticks, comprising viruses pathogenic for their vertebrate hosts, including humans  [32]. Table  1. List of iflavirus sequences found in tick transcriptomes (with tblastn or blastp, using the ISIV genome, associated with the ISE6 cell line of Ixodes scapularis as a query). Columns: Species, Tissues (HEM: haematocytes, MG: midgut, MT: Malpighian tubules, OV: ovaries, SG: salivary glands, SYN: synganglion, WB: whole bodies) followed by details on the stages or conditions between parentheses, when available, Location of the sampling (or source of the strains), Accessions: Genbank accession and if available, related TSA or BioProject accession between parentheses, Publication (or authors of the sequences), Percent identity with ISIV -% id at the amino acid level of the first hsp (tblastn)-and range of the match, which indicates genome completion.
Supplemental material : the file suppl_rispe. txt contains the Genbank format sequences of the newly identified iflavirus genomes. Author Contributions: Conceptualization and Methodology: C. R. and O. P. ; Ressources and Funding acquisition: C. H. , D. S. , A. J. , J. -M. A. , K. L. , O. P. ; Formal analysis and Data curation: C. R, R. D. , L. S. ; Writing: C. R. , O. P. and R. D. All authors have read and agreed to this version of the manuscript.
Acknowledgements: we thank  O. Rais ,  M. Voordouw  and  Franck Boué  who provided part of the material used for transcriptome sequencing of I. ricinus. We acknowledge the support of the  Genotoul bioinformatics platform Toulouse Midi-Pyrénées (Bioinfo Genotoul ) for bioinformatic analyses. This work was supported by the  Genoscope , the  Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA) and France Génomique  ( ANR-10-INBS-09-08 ), by the  Italian Ministry of Education, University and Research (MIUR) :  Dipartimenti di Eccellenza Program  ( 2018-2022 ) -Dept. of  Biology and Biotechnology "L. Spallanzani", University of Pavia  (to D. S. ), by a grant form the  Institut Carnot France Futur Elevage  ( XENOBIOTICK  project). Thanks to  Sara Moutailler  ( ANSES ) for helpful comments on the manuscript.
The effect of HLA matching after single unrelated cord blood transplantation (UCBT) in the Japanese population is discussed in the current issue of the journal. The first article, "Impact of HLA Allele Mismatch at HLA-A, -B, -C, and -DRB1 in Single Cord Blood Transplantation," by Yokoyama et al  [1] , describes the influence of allele-level matching on outcomes after transplantation for malignant hematologic diseases. Outcome data for 4050 transplantations from the Japanese Transplant Registry Unified Management Program with an adequate record of allele-level HLA typing were included in the study, and separate analyses for pediatric patients (n = 513) and adult patients (n = 3537) were performed. There were notable differences between the adult and the pediatric groups in terms of disease risk, cell dose, and preparative regimen that justified the need for 2 separate analyses.
Among other factors, ethnicity may play an important role in transplantation outcomes. We analyzed prognostic factors for adult single cord blood transplantation among European and Japanese populations on behalf of Eurocord/Acute Leukemia Working Party of the European Society for Blood and Marrow Transplantation and the Japan Society for Hematopoietic Cell Transplantation/Japanese Data Center for Hematopoietic Cell Transplantation  [8]. In total, 3764 patients of the Japanese registry and 1027 patients of the European registry were included. There were considerable differences between the 2 cohorts, leading to a separate analysis of each registry. The 3-year OS was 41% in Japan and 33% in Europe. TNC dose and HLA matching had no significant effect on OS in either cohort, whereas year of transplantation, age, and refined disease risk index affected OS in both cohorts.
Methods and results In a subset of 80 patients with complete data in a study assessing the effects of hydralazine and nitrates in patients with AHF (BAHEF trial; NCT01822808), NT-pro-BNP and galectin-3 analyses were performed, and the association with various characteristics and outcome measures assessed. The mean age of the patients for whom the aforementioned biomarkers were measured was 52. 6 years, with 52. 5% women. Galectin-3 at baseline predicted changes (Week 24 to baseline) in left ventricular ejection fraction, left ventricular end-systolic diameter, left ventricular end-diastolic diameter, and tricuspid annular plane systolic excursion. Biomarkers and their changes were not associated with changes in 6 min walk test at 24 weeks. Baseline galectin-3 and change in NT-pro-BNP were associated with improvements in dyspnoea at 24 weeks.
Patients who completed the 24 weeks of double-blind phase were given the option of continuing open-label treatment with active medication for up to 24 weeks. Approval was obtained from the ethics committee of each participating institution, and the study conformed to the principles of the Declaration of Helsinki. The study was governed by a Steering Committee and monitored by an independent Data and Safety Monitoring Committee. Randomized patients underwent full clinical evaluation including physical examination, collection of patient's self-report of dyspnoea severity by a Visual analogue scale (VAS), 6 min walk test, and physician's assessment of HF signs and symptoms. Other information obtained included demographic data, date of diagnosis of HF and pre-admission history (previous HF-related admissions), New York Heart Association (NYHA) functional class, self-reported CV risk factors, co-morbidities, and medications history.
Acknowledgements We would like to thank the staff at the  Neglected Tropical Disease Laboratory of Jimma University  who collected the data and did the laboratory examinations. Special thanks to the students, parents and school leaders who facilitated the data collection. The development of the manuscript was supported through the  Structured Operational Research and Training Initiative (SORT IT ), which is a global partnership coordinated by the  Special Program for Research and Training in Tropical Diseases (TDR)  hosted at  World Health Organization.
Cell culture The near-haploid myeloid cell line KBM7, derived from human myeloid leukaemia (kindly provided by Prof. T. Brummelkamp) was cultured in Iscove's Modified Dulbecco's Medium plus 10% FCS and penicillin/streptomycin in 5% CO 2 at 37 C. 293FT (cat. #R70007 RRID: CVCL_6911; Thermo Fisher Scientific, Waltham, MA) cells were cultured in DMEM plus 10% FCS and penicillin/streptomycin in 5% CO 2 at 37 C. Macrophages were obtained as published in Decalf et al. 33  Plasmapheresis residues were obtained from healthy adult donors (EFS Blood Bank, Paris, France). asmids pTRH1 NF-jB destabilized copepod GFP (dscGFP) was a gift from Prof. Hidde Ploegh. 35 Its promoter contains four repeats of the NF-jB binding site GGGACTTTCC; pTRH1 NF-jB RFP was produced from pTRH1 NF-jB dscGFP by introducing TagRFP in place of dscGFP by overlapping PCR (forward 5 0 -gtcaaagcttaccatggtgtctaagggcgaaga-3 0 ; reverse 5 0 -tg acgtcgactattaattaagtttgtgcccca -3 0 ) and the restriction sites HindIII and SalI.
1% Tween-20 (PBS-Tween) for 1 h at room temperature (20 C). Membranes were then probed with an appropriate dilution of primary Ab overnight (14 h) at 4 C. Membranes were washed three times in PBS-Tween before incubation in diluted secondary Ab for 1 h at room temperature. Membranes were washed as before and developed with ECL (#1705061; Bio-Rad; or 34096; Thermo Fisher Scientific) using a Bio-Rad Chemi Doc system setting for signal accumulation. Pictures were analysed and prepared using the Image Lab (Bio-Rad) software.
Acknowledgements The authors would like to thank  Francesca Graziano ,  Franc¸ois-Xavier Gobert  and  Elodie Segura  from the  Institut Curie , as well as Xavier Coumoul from  Universit e Paris Descartes , for helpful discussions. Vasco Rodrigues  and  Francesca Graziano  are thanked for their critical reading of the manuscript.
Funding The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This work was supported by  Institut Curie, INSERM, CNRS  and by grants from the  ANR-10-IDEX-0001-02 PSL  and  ANR-11-LABX-0043  to N. M. and P. B. ;  INCA 40832 ,  LNCC PARIS -RS19/75-1 ,  ARC PJA 20181208045 ,  Sidaction 2018-1-AEQ-11984 ,  ANRS  and  ANR 15-CE13-0009-01  to P. B. ; and Sidaction  VIH2016126002 ,  ANRS ECTZ25472 ,  ANRS ECTZ36691 ,  ANR-14-CE14-0004-02  and  ANR-17-CE15-0025-01  to N. M. L. Z. -T. was supported by a doctoral fellowship from  E ´cole normale sup erieure de Lyon , followed by another one from the  Association de la Recherche contre le Cancer (ARC).
Statistical analysis The effect of the dietary choice selection was tested by one-way ANOVA. To evaluate the effect of the diet on time course changes in daily and cumulative feed preferences for each diet (Figures 1, 2, 3 and 4 and Supporting information 2), values were analyzed using frequency analysis (one-sample t-tests). The total food consumed and total uneaten pellets (Figure  5 ), values were analysed by t-tests. All data are expressed as mean ± S. E. A P-value of 0. 05 or less was indicated as statistically significant. Statistical analyses were performed using R software (v3. 5. 2)/R Commander package. Analyses were carried out on untransformed data since criteria for normality and homogeneity of variances were fulfilled (Shapiro-Wilk's and Levene's test respectively).
MATERIAL AND METHOD This index case occurred in an outdoor breeding duck farm of 6,400 ducks, located in the commune of Bénesse-Maremne (Southwest France). The farm produces 12-week-old mule ducks that are sold to fattening farms where they are raised for 12 days before being sent to slaughter. At the time of the outbreak, ducks were nine-week old. Data on daily duck mortality for the 30 days prior to the day of confirmation were obtained from the farm log book and confirmed by interviewing the farmer. Until the 3 December, daily mortality was stable ranging between zero and eight dead ducks. Subsequently, daily mortality rocketed to 40 dead ducks on the 4 December and 250 on the 5 December. In the morning of the 6 December, when the flock was culled, more than 300 ducks were found dead. The within-flock transmission of the virus was modelled using a stochastic SEIR epidemic model, as described in detail in  (Guinat et al.
ACKNOWLEDGEMENTS The authors would like to thank the  French Ministry of Agriculture  and the veterinary services of the  Landes department  for their support in implementing this study. The work was carried out within the framework of the  Chaire de Biosécurité  aviaire at the  École Nationale Vétérinaire de Toulouse , which is funded by the  French Ministry of Agriculture. CG has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Sklodowska-Curie  grant agreement No  842621. SG was funded by the  Biotechnology and Biological Sciences Research Council  ( BB/E/I/00007036  and  BB/E/I/00007037 ).
Given, that the pharmaceutical landscape is continuously evolving in terms of regulatory practices and drug development processes, using latest data and a longer time-series provides new insights. Moreover, the data we used include a period when regulatory pressures were at the peak and many countries started adopting price regulation methods. This generates substantial variation in our price regulation measure over time. Second, in most prior literature, either the link between price regulation and profitability or that between profitability and R&D investment is investigated. 1 In this paper, we examined the link between price regulation (measured by relative market share in EU/USA) and R&D intensity, exploring the role of cash flow and expected profitability as possible mechanisms, thus providing a comprehensive picture.
Data Panel data from 2000 to 2017 for the top ten pharmaceutical firms was compiled from different sources. Firms included in the analysis were Astra Zeneca PLC (UK), Bayer AG (DE), Eli Lilly & Co. (USA), GlaxoSmithKline PLC (UK), Johnson & Johnson (USA), Merck & Co. (USA), Novartis AG (CH), Pfizer Inc. (USA), Hoffmann-La Roche AG (CH), and Sanofi SA (FR). 2  These ten companies are key players in terms of revenue and R&D activity. For the year 2017, the value of the R&D investments of these companies alone accounted for more than 50% of the total value of R&D investments on the top 50 pharmaceutical companies by revenue and R&D spending  [21]. Financial data were retrieved from the Fundamental Annual section of the Compustat database accessible through the Wharton Research Data Services (https :// wrds-www.
whart on. upenn. edu/demo/compu stat/form/). These data were complemented with additional data on financials, sales volume in Europe and USA, and mergers collected from the annual financial statements and reports published by the companies and accessible through their websites. In some cases the data were partially expressed in different currencies other than US dollars (British Pound, Swiss Franc, Euro), these figures were all converted to US dollars by using the average yearly exchange rates provided by the Federal Reserve of the United States of America  [22]. Variable description and sources are provided in detail in the supplementary material (Table  A1 ).
Independent Variable The degree of exposure to price regulation was captured using a similar strategy to that in Vernon  [15]. Specifically, Vernon  [15]  argues that the USA is a largely unregulated market in terms of prices, as a result firms that sell proportionately more in the US market than in the non-US market are exposed to lower price regulation. In contrast, the European market is directly regulated in terms of pricing of drugs; different price regulations both on the supply and demand side have been introduced. Therefore, the share of sales of a firm in Europe relative to that in the USA is a plausible measure of exposure to price regulation. The data on the sales volume by region were collected from the financial and annual reports published by the firms.
Discussion The trade-off between affordability of drugs today and the necessity to incentivize pharmaceutical firms to engage in future R&D to produce new and better drugs is well known. This paper revisited the relationship between pharmaceutical price regulation and R&D intensity by firms. We measured exposure to price regulation byexploiting the stylized fact that firms that sell more in Europe are exposed to greater price regulation than those that sell more in the USA, i. e. the share of sales of a firm in Europe relative to that in the USA is a plausible measure of price regulation. Adopting a similar framework as in Vernon  [15] , we estimated the relationship between this measure and R&D intensity and explored the role of cash flow and profitability as intermediate mechanisms. 4 To this end, we use the latest available data from 2000 to 2017 for the top 10 pharmaceutical companies and exploited variation between and within firms to assess how exposure to price regulation (measured by relative market share in EU/USA) relates to R&D investment.