dataesr/scientific-paragraphs-categorization huggingface dataset:
Cell lines and infection with a lentiviral vector Blood samples were collected for hormonal and genetic studies and for the production of EBVimmortalized lymphoblastoid cell lines, which was performed at the Genopole, Evry, France, following a standard in-house protocol. EBV-immortalized cells were obtained for patient 2 and her mother. HEK293 (Research Resource Identifier/RRID:CVCL_0045) cells and FANC pathway-proficient (HSC-93 (RRID:CVCL_G049)), and -deficient (HSC-72 (RRID:CVCL_G047), HSC-536 (RRID:CVCL_ G045) and GM16756 (RRID:CVCL_G041)) cells have been previously described  (Bourseguin et al. , 2016). HSC-72, HSC-536 and GM16756 bring bi-allelic inactivating mutations in FANCA, FANCC and FANCD2, respectively. Lymphoblastoid cells were cultured in RPMI 1640 medium, supplemented with 12% FCS and antibiotics.
Whole-exome and Sanger sequencing Library preparation, exome capture, sequencing and data processing were performed by IntegraGen SA (Evry, France) according to their in-house procedures. Data analysis was performed as described in  (Fauchereau et al. , 2016). Briefly, genomic DNA libraries were prepared from 600 ng of genomic DNA from three individuals (the mother and the two affected sisters) with NEBNext Ultra kit (New England Biolabs). Target capture, enrichment and elution were performed according to Figure  3  continued monoubiquitination in the same lymphocytes than in A and B. Immunoblot analysis were performed using mouse monoclonal anti-FANCM antibody (CV5. 1), mouse monoclonal anti-FANCD2, (Santa-Cruz Biotechnology, Dallas, Texas, USA), rabbit anti-FANCA (Abcam, Cambridge, UK), mouse antivinculin (Abcam).
Libraries were sequenced on an Illumina HiSEQ 2500 as paired-end 75 bp reads. Image analysis and base calling was performed using Illumina Real Time Analysis (RTA 1. 18. 64) with default parameters. The various metrics of the NGS sequencing are detailed in the Table  2. The sequencing data was analyzed with the Illumina pipeline (CASAVA 1. 8. 2) for read alignment and variant calling, and an IntegraGen in-house pipeline was used for variant annotation. Annotation of kown variants was performed according to the following databases: dbSNP144 (RRID:SCR_ 002338), 1000 Genomes Project (release_v3. 20101123) (RRID:SCR_008801), Exome Variant Server (ESP6500SI-V2-SSA137) (RRID:SCR_012761), HapMap3 (RRID:SCR_002846), ExAC r3. 0 (RRID:SCR_ 004068), COSMIC 71 (RRID:SCR_002260), ClinVar 201507 (RRID:SCR_006169) and an Integragen internal database (containing 201 control exomes for SNPs and 130 control exomes for Indels).
Acknowledgements The authors declare they have no conflict of interest. We thank the  Universities Paris Sud , the  INSERM , and the  CNRS  for providing supports for this study. RV and FR are respectively ' Equipe labellisee' de la Fondation pour la Recherche Medicale  (grant  DEQ20150331757 ) et de la Ligue nationale contre le cancer. We thank  M. Bogliolo  ( Barcelona ) for the gift of FANCM cDNA expressing lentiviral vectors. K. U. was supported by a fellowship from the  Warsaw University of Life Sciences, Warsaw, Poland.
Funding Funder Grant reference number  Author Fondation pour la Recherche Medicale DEQ20150331757 Baptiste Fouquet Sandrine Caburet Reiner A Veitia Micheline Misrahi Ligue Contre le Cancer Patrycja Pawlikowska Filippo Rosselli The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
2015; Huchra et al. 2012). This exploits the linear relationship between the peculiar velocity and mass density fields smoothed on scales larger than about 8h -1 Mpc, and the constant of proportionality can be determined by com-parison with radial peculiar velocities of individual galaxies estimated from e. g. Tully-Fisher and Type Ia supernovae distances. Using these reconstructed peculiar velocities, which have a larger associated uncertainty  (Carrick et al. 2015 ) of 150 km s -1 , at the position of NGC 4993 we find a Hubble velocity in the CMB frame of v H = 3047 km s -1 -in excellent agreement with the result derived using 6dF. We adopt this larger uncertainty on the peculiar velocity correction in recognition that the peculiar velocity estimated from the 6dF data may represent an imperfect model of the true bulk flow at the location of NGC 4993.
In practice, we wait for a GW event to trigger the analysis and this introduces potential selection effects which we must consider. We will see below that the simple analysis described above does give results that are consistent with a more careful analysis for this first detection. However, the simple analysis cannot be readily extended to include second and subsequent detections, so we now describe a more general framework that does not suffer from these limitations. We suppose that we have observed a GW event, which generated data x GW in our detectors, and that we have also measured a recessional velocity for the host, v r , and the peculiar velocity field, v p , in the vicinity of the host. These observations are statistically independent and so the combined likelihood is p(x GW , v r , v p | d, cos ι, v p , H 0 ) = p(x GW | d, cos ι) p(v r | d, v p , H 0 ) p( v p | v p ).
3% credible interval of 70. 0 +12. 0 -8. 0 km s -1 Mpc -1 , as quoted in the main article. The posterior mean is 78 km s -1 Mpc -1 and the standard deviation is 15 km s -1 Mpc -1. Various other summary statistics are given in Extended Data Table  1. ROBUSTNESS TO PRIOR SPECIFICATION d cos v p H 0 x GW v r v p Extended Data Figure  1. Graphical model illustrating the statistical relationships between the data and parameters. Open circles indicate parameters which require a prior; filled circles described measured data, which are conditioned on in the analysis. Here we assume we have measurements of the GW data, x GW , a recessional velocity (i. e. redshift), v r , and the mean peculiar velocity in the neighborhood of NGC 4993, v p. Arrows flowing into a node indicate that the conditional probability density for the node depends on the source parameters; for example, the conditional distribution for the observed GW data, p (x GW | d, cos ι), discussed in the text, depends on the distance and inclination of the source (and additional parameters, here marginalized out).
Setting priors on distance and redshift, the simple analysis gives the same result as the canonical analysis, but now we set a prior on redshift and H 0 and obtain a different result. This is to be expected because we are making different assumptions about the underlying population, and it arises for similar reasons as the different biases in peculiar velocity measurements based on redshiftselected or distance-selected samples  (Strauss & Willick 1995). As can be seen in Extended Data Table  1 , the results change by less than 1σ, as measured by the statistical error of the canonical analysis. By increasing the uncertainty in the peculiar velocity prior, we test the assumptions in our canonical analysis that (1) NGC 4993 is a member of the nearby group of galaxies, and (2) that this group has a center-of-mass velocity close to the Hubble flow.
8 +2. 9 -6. 9 41. 1 The UCSC group is supported in part by NSF grant AST-1518052, the Gordon & Betty Moore Foundation, the Heising-Simons Foundation, generous donations from many individuals through a UCSC Giving Day grant, and from fellowships from the Alfred P. Sloan Foundation (R. J. F), the David and Lucile Packard Foundation (R. J. F. and E. R. This research has made use of the NASA/IPAC Extragalactic Database (NED) which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.
The DES Data Management System is supported by the NSF under Grant Numbers AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2015-71825, ESP2015-88861, FPA2015-68048, and Centro de Excelencia SEV-2012-0234, SEV-2016-0597 and MDM-2015-0509. Research leading to these results has received funding from the ERC under the EU's 7 th Framework Programme including grants ERC 240672, 291329 and 306478. We acknowledge support from the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through project number CE110001020. This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U. S. Department of Energy, Office of Science, Office of High Energy Physics.
" This program was supported by the the Kavli Foundation, Danish National Research Foundation, the Niels Bohr International Academy, and the DARK Cosmology Centre. Science, Technology, Innovations, and Commu- nications, the International Center for Theoretical Physics South American Institute for Fundamen- tal Research (ICTP-SAIFR), the Research Grants Council of Hong Kong, the National Natural Sci- ence Foundation of China (NSFC), the Leverhulme Trust, the Research Corporation, the Ministry of Science and Technology (MOST), Taiwan and the Kavli Foundation. The authors gratefully acknowl- edge the support of the NSF, STFC, MPS, INFN, CNRS and the State of Niedersachsen/Germany for provision of computational resources. This article has been assigned the document number LIGO-P1700296. +5. 6 -12.
Modelling the basic reproduction number The daily basic reproduction number (R0) is an indicator for the potential spread of an infectious disease through a naïve population. R0 was calculated with the temperature-dependent transmission model by Rubel  [8]  taking various drivers of disease emergence such as host immunity, extrinsic incubation period and vector reproduction rate, into consideration. Daily mean temperature data on a 0. 25° regular latitude-longitude grid (E-OBS dataset, January 2009-September 2016) were downloaded from http://www. ecad. eu [12]. For each grid cell, R0 values were averaged for the period from June to September 2016. The averaged R0 could be interpreted as average number of secondary infections arising from the introduction of a single infected individual into a completely susceptible population during this period  [8].
Detection and phylogenetic analysis of USUV To investigate the genetic relationship between the USUV strains responsible for the 2016 European outbreaks and those available in databases, phylogenetic reconstructions were performed using Bayesian Monte Carlo Markov Chain (MCMC) sampling method implemented in BEAST v. 1. 8. 3  [24]  and in parallel a maximum likelihood inference in PhyML v3. 1  [25]  based on partial NS5 gene coding sequences. The MCMC and PhyML trees (data not shown) were reconstructed using Tamura Nei (TN93) model (TN)93 plus Gamma evolutionary model placed by JModelltest2  [26]  as the nt substitution model best fit the data. Sequences were aligned using the MAFFT algorithm and then visually inspected in Geneious v9. 1. 4.
Acknowledgements We acknowledge the E-OBS dataset from the  EU-FP6  project  ENSEMBLES  (http://ensembles-eu. metoffice. com) and the data providers in the  ECA&D  project (http://www. ecad. eu). We thank  Heike Baum ,  Alexandra Bialonski ,  Anne van der Linde ,  Robert Kohl  and  Claudia Schapendonk  for assistance in the laboratory work. We acknowledge the valuable contributions of the Dutch bird ringers. Funding statement: This work was financially supported by the  German Federal Ministry of Food and Agriculture (BMEL)  through the  Federal Office for Agriculture and Food (BLE)  with the grant numbers  2819104315. The  WBA-Zoo wild bird pathogen surveillance and sequencing  project is supported by the  German Centre for Infection Research (DZIF). Scanning surveillance of dead wild birds is funded by the  Dutch Ministry of Economic Affairs  grant number  1300022600.
The EMCal provides two hierarchically-configured trigger levels (Level-0 and Level-1). For this analysis the data were recorded with the L1 trigger in coincidence with the V0 minimum-bias trigger. The trigger logic of the Level-1 trigger employed a sliding window algorithm of 4×4 towers with a sliding step of 2 towers along either of the surface axes. An event was rejected unless the energy summed within at least one set of the 16 adjacent towers was greater than a threshold. Additionally, the trigger logic was configured to adjust the online threshold according to the event centrality estimated from the analogue sum of the V0 detector signals. The threshold was adjusted such that the rejection rate was approximately constant as a function of the event centrality. The thresholds varied from 7 GeV in 10% most central events to 2 GeV in the most peripheral events.
sociodemographic and lifestyle data Sociodemographic and lifestyle data were collected through self-administered questionnaires and included age, sex, education (no diploma and up to secondary education, university ≤2 years, university >2 years), marital status (in couple, single/divorced/widowed), income per household unit 43 (<€1200, €1200-€1800, €1800-€2700, ≥€2700 per month) and smoking status (current smoker, former smoker and never smoker). Physical activity was computed using self-declared data from the validated International Physical Activity Questionnaire (low, moderate and high physical activity levels). 44 The data collected in the questionnaire closest in time to the questionnaire on the perceptions of FOP labels were taken into account for the analyses.
dietary data Dietary data were derived from three repeated 24 hours records randomly distributed in a 2-week period, with 2 weekdays and 1 weekend day. Food consumption was weighted according to the day of the week of each record. The participants are asked to estimate the portion size for each reported food and beverage item using validated photographs. 45 Nutrient intake was computed using a published food composition database reflecting foods usually consumed in the French diet. 46 Under-reporters for energy intake were identified using Goldberg/Black's method and were excluded. 47 The dietary data from the 24 hours dietary record in the NutriNet-Santé study have been validated against interviewer-led dietary recalls conducted by trained dietitians and against biomarkers of nutritional status.
40 48 49 atistical analysis For the present study, all participants who had completed the questionnaire on the perception of FOP labels and having completed information on all covariates were eligible to the present study. Subjects were excluded if they stated that they never engaged in grocery shopping. The records and questionnaires closest to the questionnaire on the perceptions of FOP labels were taken into account for the analyses. Weighting of the data All data were weighted using the SAS CALMAR (CALage sur MARges) macro developed in France by the Institute of National Statistics to weight survey data to be representative of the French census population. 50 Data used for weighting were sex, age, educational level, occupation and area of residence.
Dietary cluster identification The responses from the 13 'perception' questions were used in a multiple correspondence analysis, which yielded four dimensions of FOP labelling perception. The dimensions were selected based on their adjusted inertia (33. 6%, 23. 0%, 18. 4% and 17. 2%, respectively, for a total of 92. 3%). The selected dimensions were used as input variables in a two-way clustering procedure based on hierarchical and K-means methods (SAS CLUSTER and FASCLUST procedures). The plot of semipartial R 2 , the semipartial T 2 and the cubic clustering criterion by the number of clusters were used to identify the optimal number of clusters.
Statistical analysis All analyses were weighted according to the CALMAR macro, except the clustering procedure for which no weighting option is available. The responses to each of the 13 questions were mapped across clusters, in order to identify the FOP perception characteristics of each cluster. Sociodemographic, lifestyle and dietary variables were mutually adjusted against clusters in a multivariable multinomial regression. Adjusted percentages for each sociodemographic, lifestyle and dietary characteristic were extracted from this procedure across clusters. All tests were two sided and a p value <0. 01 was considered significant, given the high number of statistical tests performed and the large sample size. Statistical analyses Open Access were performed using SAS software (V. 9. 3, SAS Institute, Cary, NC, USA).
results Overall, 38 604 subjects completed the questionnaire on the perceptions of FOP labels. Among these, 714 (1. 85%) were excluded because they never engaged in grocery shopping. Among the 37 890 remaining subjects, 16 188 (42. 72%) were excluded for incomplete data on covariates (the vast majority of which (n=13 066, 80. 71% of excluded subjects) for incomplete data on mPNNS-GS computation, which requires the presence of three 24 hours records, frequency questionnaire on alcohol consumption and frequency of seafood consumption), leading to an overall sample of 21 702 participants for analysis (eg, 56. 22%). Characteristics of the crude and weighted sample are presented in table 1. The crude sample exhibited a higher percentage of females (73. 42%), older subjects (68. 36% were ≥50 years old), educated (37.
Moreover, the data used for the investigation of dietary intakes used validated data collection tools, using repeated dietary records. 40 We were also able to investigate multiple dimensions of the perception of FOP labels (awareness, liking, perceived cognitive workload and trustworthiness), across various formats that are currently proposed in the French debate on FOP nutrition labelling. Finally, we were able to identify clustered preferences toward each type of format and relate them to sociodemographic and dietary factors, which highly contributed to the interpretation of such preferences in a public health perspective. Our study is subject to some limitations. First, our sample consists of volunteer subjects included in a cohort study on nutrition, who are therefore more likely health conscious.
Acknowledgements The authors especially thank  Nathalie Arnault  for data management, data cleaning and statistical analyses. We especially thank  Younes Esseddik ,  Paul Flanzy  and  Thi Hong Van Duong , computer scientists;  Veronique Gourlet ,  Fabien Szabo ,  Nathalie Arnault ,  Laurent Bourhis  and  Stephen Besseau , statisticians; and  Cédric Agaësse  and  Claudia Chahine , dieticians. We warmly thank all of the dedicated and conscientious volunteers involved in the Nutrinet-Santé cohort.
Determining the phosphate-solubilizing efficiency of endophytic bacteria in NBRIP liquid medium Aliquots of 0. 1 mL of each isolate cultured in trypticase soy broth were incubated and subsequently transferred to the NBRIP medium containing 40 g/L glucose and incubated with stirring at a temperature of 30°C. The optimum times of incubation for maximum phosphate solubilization were six and nine days as revealed by previous tests (data not shown). The pH values were measured in water and the phosphorus content released in the culture supernatants was determined by the ammonium molybdate colorimetric method.
Statistical analysis The data were analyzed according to a randomized design with three replicates per sample, except for phosphate solubilization in solid medium, where four replicates were used per sample. The analysis of variance for each test was made using the Sisvar 5. 3 program  (Ferreira, 2010). Significant differences were analyzed by the F test (P ≤ 0. 05), and the means were compared using the Scott-Knott test at 5% probability. To verify the association between P-solubilization and pH, the Pearson correlation analysis was performed using the R software (http://www. R-project. org) at 5% probability.
ACKNOWLEDGMENTS Research supported by grants from  Universidade Federal de São João Del Rei (UFSJ)  to  Crísia Santos de Abreu ,  Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) ,  Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ,  Embrapa Milho e Sorgo (CNPMS) , and  Universidade Federal de Minas Gerais (UFMG).
Materials and Methods Study animals, context of the study and video recordings. The presence of orcas in the Kalkfjord (Norway) is directly linked to the massive presence of specific prey, i. e. atlantic herrings (Clupea harengus). As a result, the same population of orcas comes back to this location every year  84. Individuals are identified based on classic criterion for that species, such as the size and the shape of the dorsal fin and the saddle patch as well as bodies scars  85. Only individuals clearly identified and observed at least twice during the study have been included in the data set, i. e. 60 adult females, 18 adult males, 11 unsexed subadults. The underwater videos used for the analyses have been made by Pierre Robert de Latour during ecotouristic dives organised in Norway on winters 2014 and 2015 (November to February).
8, ISO: automatic limited at 3200, White Balance: 4800 k). All in all, 902 video sequences (collected with an ad libitum sampling method, i. e. at various times of the diving session and with various durations) have been analysed, that is 540 minutes of film sampled (2014: 323 video sequences lasting 163 minutes in total; 2015: 579 video sequences lasting 377 minutes in total). Our study is observational and totally non-invasive, based on video scoring. Videos come from the archive of the USEA -Orques Sans Frontieres program (permit #USEA2017-0007). Behavioural repertoire and data collection. A detailed behavioural repertoire has been established to sample the different movements and other exploratory behaviours of orcas when approaching the divers (see photo examples in Fig. 5 ). Here, an approach is defined as follows 1 : an approach is systematically an animal movement oriented in the direction of the divers 2 ; an approach starts from the moment where an orca enters the camera range and ends as soon as it gets out.
Acknowledgements: This research has been made possible thanks to the digital collections of manuscripts of the  École française d'Extrême-Orient  ( Pondicherry Centre ), the  Institut français de Pondichéry, the Centre for the Study of Manuscript Cultures  ( CSMC, SFB 950 'Manuskriptkulturen in Asien, Afrika und Europa', University of Hamburg ) and  NETamil  ( ERC Advanced Grant , project No. 339470 ). I would like first to thank the amici from  Cambridge-Vincenzo Vergiani ,  Daniele Cuneo  and  Camillo Formigatti- for having organised the workshop at Cambridge in September 2014 and accepted my presentation, of which this paper is the outcome. Hearty thanks are also due to many other colleagues. Marco Franceschini  helped me to convert the internal dates of the manuscripts into the Gregorian calendar.
Search strategy and selection criteria The PubMed database was searched using the keywords "Clostridium difficile infection"; "extraintestinal C. difficile infection" (ECD); "Clostridium difficile bacteremia" (CDB); and C. difficile pathogenesis. Pertinent references included in some of the search results were also reviewed. Relevant articles and abstracts published in English; French and Japanese between 1962 (the first published CDB case) and November 2016 were selected. Among these articles; about 28 with descriptive cases of CDB and 10 other reports including other CDB cases were retrieved. The published reports were heterogeneous. The majority were published as case reports and the others were epidemiological or retrospective studies. The other main publications were related to CDB subject or to the particular features of Clostridium difficile pathogenesis.