dataesr/scientific-paragraphs-categorization huggingface dataset:
Study management The DIRECTAVI study is planned to be a randomized open-label trial, conducted and sponsored by the University Hospital of Montpellier (France). Funding has been obtained from Edwards Lifesciences. An Executive Committee composed of experienced clinical investigators will provide trial leadership. A Clinical Events Committee, blinded to the assignment strategy, will adjudicate all clinical events and a DMSC in operation. The committee will comprise physicians who are provided with all the data from medical records necessary to perform optimal adjudication. The study conforms to the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) 2013 guidelines (see Additional file 1).
Depletion of rRNA was obtained by treating 5 µg of total RNA with the Gram-negative RiboZero Magnetic kit (Tebu-Bio) according to the manufacturer's protocol. cDNA Library Preparation, Sequencing and Data Normalization rRNA-depleted RNA (50-60 ng in 5 µL) were fragmented by adding 13 µL of the "Fragment, prime, finish mix" of the "Purify and fragment mRNA" kit (Illumina). Then, cDNA libraries were constructed with the TruSeq stranded mRNA LT kit (Illumina) following the manufacturer's protocol. Obtained cDNA libraries were quality checked (Bioanalyzer, DNA 1000 kit, Agilent Technologies) prior to HiSeq2000 sequencing. Paired-end sequence mapping was used to limit mapping artifacts and remove mapping ambiguities between gene paralogs. Factor size normalization of the raw counts was performed using a set of 55 reference "housekeeping" genes instead of the standard method using the complete set of CDS  (Anders et al.
, 2013) , as a few genes had very high read numbers in growth with chlorinated methanes only. The 55 reference genes cover a wide range of expression levels but had unchanged transcript abundance in the tested biological replicates (log 2 fc value between -0. 9 and 1. 2) (Table  S2 ). Normalization was validated by comparison with the complete set of CDS for the methanol dataset (Figure  S1 ). Gene transcripts were defined as differentially abundant when the log 2 of fold-change values (log 2 fc) between cultures grown with chlorinated methanes and methanol were ≥2. 0 or ≤ -2  (Yang et al. , 2015). Each condition was analyzed in duplicate, with the average of read sense and antisense for each condition. Data were considered significant when False Discovery Rate (i. e. , FDR) was ≤0. 1 as previously described  (Benjamini and Hochberg, 1995).
RT-qPCR Retrotranscription was performed from 2. 0 µg of DNA-depleted RNA extracted using the Nucleospin RNA plus kit (Macherey Nagel) combined with Turbo DNase and Turbo DNA free kit (Invitrogen) using Superscript III (Invitrogen) and random hexanucleotide primers (Invitrogen) following manufacturers' protocols, except that RNaseOUT TM was replaced by RNasin TM (40 U. µL -1 ; Invitrogen), with inclusion of appropriate controls (reactions without RNA template or Superscript III enzyme). Amplification was performed in qPCR 96 wells plates (Agilent Technologies) covered with Microseal B adhesive seals (Bio-Rad) using the Thermocycler Stratagene Mx3005P (MxPro software v4. 10; Agilent Technologies). Master mix containing 7. 5 µL Brilliant III SYBR TM Green low ROX qPCR master mix (Agilent Technologies), 0.
225 µL of each primer (Eurofins) at 20 µM and 3. 3 µL molecular biology grade water was mixed with 3. 75 µL template cDNA. After 3 min pre-denaturation at 95 • C, 40 cycles of 20 s at 95 • C and 20 s at 60 • C, a final one-cycle step of 1 min at 95 • C with ramping from 60 to 95 • C was applied to obtain dissociation curves for quality control of PCR products. For each biological triplicate, technical duplicates were analyzed and compared to standard curves with gDNA (0. 1-1. 10 -5 ng. µL -1 ) and a no template control. SYBR TM green fluorescence data normalized with Rox fluorescence were analyzed using the package qpcR (v1. 40) within R for Ct determination  (Ritz and Spiess, 2008). Fold change values were calculated by the 2 -Ct method  (Schmittgen and Livak, 2008) , with rrsA as internal control and dcmA in DM4 cultures grown with methanol as the reference condition.
Comparative Genomics Analysis Comparative analysis of M. extorquens genomes was done in MaGe on the Genoscope MicroScope online platform  (Vallenet et al. , 2017) , with the sequenced genomes of 5 strains of M. extorquens, i. e. , the 2 dehalogenating strains CM4 (Genbank accession numbers CP001298, CP001299, CP001300) and DM4 (FP103042, FP103043, and FP103044), and 3 other strains AM1 (CP001511, CP001512, CP001513, and CP001514), PA1 (CP000908), and BJ001 (CP001029, CP001030, and CP001031)  (Vuilleumier et al. , 2009; Marx et al. , 2012)  Other genes were assigned either to the variable genome when present in at least 2 genomes, to the dehalogenationassociated genome when shared only by strains CM4 and DM4, and to the strain-specific genome when found only in one genome, respectively. Genomic islands of at least 5 kb were defined using the MaGe "Regions of Genomic Plasticity" tool (https://www.
, 2016) , and 4 genes of the dcm islet for strain DM4  (Muller et al. , 2011a, respectively) ], few strain-specific genes shared by CM-and DCM-dehalogenating strains were identified through comparison with 3 other high quality assembled genomes from M. extorquens (Figure  1A ). The strains AM1, PA1, and BJ001 were experimentally checked for their inability to grow on chloromethane or dichloromethane (data not shown). The gene content in the 5 M. extorquens genomes totals 12,273 unique CDS, representing 12. 3 Mb. The core genome shared by all 5 M. extorquens genomes is extensive (3,489 CDS) ranging from 55 to 68% (55% for CM4; 61% for DM4). M. extorquens strains CM4 and DM4 share most of their genome content (75%, 4,424 CDS) and extensive gene synteny (Figure  1B ). The specific genome for strain CM4 comprises 1,512 CDS (24% of total), and that of strain DM4 952 CDS (17%), respectively.
DISCUSSION We studied the bacterial colonization status of TIVAPs suspected or not of infection in two French hospitals. Whereas routine microbiology analysis yielded negative culture results for almost all asymptomatic samples, culture-independent 16S rRNA gene clone library generation identified bacteria as present in all clinically symptomatic as well as asymptomatic chambers. This is consistent with the literature showing that, irrespective of development of infection, devices become colonized after insertion  (12, 15). Overall, culture and molecular data corresponded well. The latter confirmed the species identified by culture as dominant OTUs in all but 5 cases. In these samples, the cultured organism was detected in very low numbers. It is likely that these organisms were outcompeted or underrepresented due to PCR bias by OTUs not selected for under the culture conditions.
Primer sequences were trimmed off, and sequences were compared to GenBank (NCBI) with BLAST and to the Ribosomal Database Project with SeqMatch. A 98% similarity cutoff was used for operational taxonomic unit (OTU) determination, and a 95% cutoff was used for genus determination. Sample staining and microscopy. Eight TIVAP chamber septa were collected separately from Limoges Hospital; four septa originated from clinically symptomatic patients, and four were from clinically asymptomatic patients. Septa were removed from their respective TIVAP chambers under sterile conditions. The septum side residing in the chamber was stained with approximately 10 M SYTO9 and approximately 50 M propidium iodide nucleic acid stains (LIVE/DEAD BacLight bacterial viability kits; Molecular Probes, Invitrogen) and incubated for 15 to 60 min in the dark.
Two-tailed t tests for the comparison of two data sets were carried out in SPSS software, version 20 (Chicago, IL), with P being considered significant when it was Ͻ0. 05. Correlation analysis was also carried out in SPSS using Pearson's correlation coefficient R to determine linear relationships between clinical and microbiological variables and their significance P. Bonferroni corrections were applied to eliminate false-positive results due to the high number of multiple comparisons. Accession number(s). Sequences have been deposited in GenBank under accession numbers MF377637 to MF378601 and MF399825 to MF400811.
A. S. was a Marie Curie Fellow, and this work was supported by grants from the Institut Pasteur and Institut Pasteur-Institut Curie PTR/PIC "Nosocomial Infections program," the Institut Pasteur-Institut Mérieux Collaborative Research program, the French Government's Investissement d'avenir program, Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases" (grant ANR-10-LABX-62-IBEID), and the "Fondation Pour la Recherche Médicale" grant (Equipe FRM DEQ20140329508).
F. A. S. was a Marie Curie Fellow, and this work was supported by grants from the Institut Pasteur and Institut Pasteur-Institut Curie PTR/PIC "Nosocomial Infections program," the Institut Pasteur-Institut Mérieux Collaborative Research program, the French Government's Investissement d'avenir program, Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases" (grant ANR-10-LABX-62-IBEID), and the "Fondation Pour la Recherche Médicale" grant (Equipe FRM DEQ20140329508).
The n TOF neutron time-of-flight facility at CERN is used for high quality nuclear data measurements from thermal energy up to hundreds of MeV. In line with the CERN open data policy, the n TOF Collaboration takes actions to preserve its unique data, facilitate access to them in standardised format, and allow their re-use by a wide community in the fields of nuclear physics, nuclear astrophysics and various nuclear technologies. The present contribution briefly describes the n TOF outcomes, as well as the status of dissemination and preservation of n TOF final data in the international EXFOR library.
Data dissemination Publication of results is obviously essential for knowledge transfer and preservation, but this is not enough when dealing with nuclear data for applications. Indeed, these data should be usable and actually used. Hence, once the data are finalized, published and fully exploited by the n TOF Collaboration, it is essential to make them widely available to all users. In the field of nuclear technologies especially, the EXFOR library is known as the "Mother of all libraries" and is the ground for the development of all evaluated nuclear reaction libraries for particle transport, activation, dosimetry, standards, etc. Moreover, EXFOR has been successfully maintained for decades and is continuously updated by the NRDC network. These two reasons make EXFOR an appropriate place for both an efficient dissemination and preservation of n TOF data.
energy with the best possible resolution. The status of n TOF data available in EXFOR with this necessary information is considered as acceptable. The dissemination and preservation in EXFOR of more comprehensive datasets is obviously encouraged, and actually done on a case-by-case basis, depending on the end-use of the data and interactions with expert users such as evaluators. Figure  1  and Table  2  illustrate the excellent data dissemination status of n TOF data for fission. It shows the strong commitment of the fission team, which took the initiative early 2015 to make these data widely available to the nuclear data community. Figure  2  shows the progress for the dissemination of capture data measured during Phase-I. The situation is not as satisfactory as for fission yet, essentially because capture measurements were performed by different teams, which partly turned to other activities along the different  n TOF phases.
Nevertheless, the situation is improving and contacts have been established with authors in order to retrieve old data and complement current EXFOR entries. Table  2  shows the global dissemination status of n TOF data, as of March 2017. Overall, 75% of the datasets with a final publication are available in EXFOR with an acceptable status, i. e. , all necessary data available. The current objective is to reach dissemination values higher than 80% for all reactions and phases. This should be possible thanks to ongoing efforts to retrieve as much as possible Phase-I capture yields from backups.
Outlook Experimental data are useful and unique, accordingly they must be usable, actually used, and preserved. In order to improve the usability and long-term preservation of n TOF outcomes, the data dissemination is continuously monitored: new data are systematically released after the final publication, whereas the backlog of final data not available is being reduced. This is made possible thanks to an improved organisation for the data dissemination, and of course to the involvement of the whole n TOF Collaboration, especially for the retrieval of old datasets. A list of measurements since 2001 is available on the n TOF public TWiki webpage  [13]. That list includes detailed information on the measured reactions: n TOF phase, experimental area, detectors, energy range, data status (preliminary or final), main publications and corresponding EXFOR entries.
To date, molecular analyses of soft ticks focused on the 16S rRNA gene, which has the potential for resolving phylogenetic relationships among closely related species in Argasidae  [6]. In addition to this gene, the 5' region of the mitochondrial cytochrome c oxidase subunit 1 (cox1) gene was chosen for phylogenetic analysis of A. vespertilionis in the present study, because it is regarded as the standard marker for tick species identification by DNA barcoding  [11] , and is particularly suitable to track separation among soft tick species  [12]. Since there are few soft tick cox1 reference sequences in GenBank, a South African isolate of A. transgariepinus and a neotropical isolate of an Ornithodoros sp. were also included in the cox1 phylogenetic analysis. The nomenclature used in the manuscript complies with the valid tick names listed by Guglielmone et al.
Sample collection and morphological analyses Soft ticks were collected from bats captured for ringing and monitoring purposes (Table  1 ). All ticks were stored in 70% ethanol. Morphological identification was based on the description of A. vespertilionis and A. transgariepinus larvae by Hoogstraal  [7, 13] , and of Ornithodoros larvae (on the genus level) according to Barros-Battesti et al. [14] , and Jones & Clifford  [15]. Structures of representative specimens from each country (A. vespertilionis: eight larvae from Vietnam, three larvae from Italy, four larvae from Romania; except A. vespertilionis from Kenya, which was damaged) were measured under a Jenaval light microscope (Carl Zeiss GmbH, Jena, Germany) after clearance with lactic acid. The means of these data sets were compared by using two-tailed Student's t-test, and were considered significantly different if P < 0.
(Gödöllő, Hungary). Obtained sequences were manually edited, then aligned and compared to reference GenBank sequences by nucleotide BLASTN program (https://blast. ncbi. nlm. nih. gov). Representative sequences were submitted to GenBank (see accession numbers in Table  1 ). The MEGA model selection method was applied to choose the appropriate model for phylogenetic analyses. In the phylogenetic analyses reference sequences with high coverage (i. e. 98-100% of the region amplified here) were retrieved from GenBank, and trimmed to the same start and stop positions (cox1: 652 bp in length, 16S rRNA gene: 439-442 bp in length). This dataset was resampled 1,000 times to generate bootstrap values. Phylogenetic analyses were conducted with the Maximum Likelihood method and Tamura-Nei model by using MEGA version 6.
Conclusions In its evaluated geographical range, no larval phenotypic differences justify the existence of separate species under Accession numbers of sequences from this study are highlighted in bold. Branch lengths represent the number of substitutions per site inferred according to the scale shown the name A. vespertilionis. However, phylogenetic analyses based on two mitochondrial markers suggest that it represents a complex of at least two putative cryptic species. The broad host range of A. vespertilionis might partly explain its lower degree of mitochondrial gene heterogeneity in comparison with ixodid bat tick species over the same geographical region of Eurasia.
Acknowledgements The survey was organized in the framework of the  EurNegVec COST Action   TD1303. Financial support was provided by  OTKA K112440  and  OTKA 115854  (to SH) and  Domus Hungarica  (to ADS). The publication of this research was supported by the  11475-4/2016/FEKUT  grant of the  Hungarian Ministry of Human Resources. The authors would like to thank the contributions of  Dávid Kováts ,  Sándor Boldogh ,  Gábor Kemenesi  and  Anna Horváth  to the samples. GF was supported by the  János Bolyai Research Scholarship of the Hungarian Academy of Sciences.
We present predictions of stem biomass productivity under elevated CO 2 , decreased precip-Published by Copernicus Publications on behalf of the European Geosciences Union. R. Q. Thomas et al. :  Leveraging 35 years of Pinus taeda research itation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.
, 2015). The Southeast Tree Research and Education Site (SE-TRES) study was located at a single location and included replicated control, irrigation (∼ 650 mm of added water per year), nutrient fertilization (∼ 100 kg N ha -1 + 17 kg P ha -1 with micronutrients applied annually with absolute amount depending on foliar nutrient ratios), and fertilization by irrigation treatments  (Albaugh et al. , 2004). The Waycross study was a single site with a non-replicated fertilization treatment. The annual application of nutrient fertilization was focused on satisfying the nutrient demand by the trees and resulted in one of the most productive stands in the region  (Bryars et al. , 2013). These five studies included data streams of stand stem biomass (defined as the sum of stem wood, stem bark, and branches) and live stem density.
Waycross and SETRES included LAI measurements from litterfall traps (Waycross) or estimates from LI-COR  LAI-2000 (SETRES). SETRES also included fine root and coarse root measurements. In the PINEMAP, SETRES, and RW18 studies we only used foliage biomass estimates from the control plots. We excluded the foliage biomass estimates from the treatment plots because they were derived from allometric models that may not have captured changes in allometry due to the experimental treatment. We did use LAI measurements from both control and treatment plots where available (SETRES). We also included observations from the Duke Free-Air Carbon Enrichment (FACE) study where the atmospheric CO 2 was increased by 200 ppm above ambient concentrations. Based on the data presented in  McCarthy et al. (2010) , the study included six control plots, four CO 2 fumigated rings (including the unfertilized half of the prototype), two nitrogen fertilization treatments (115 kg N ha -1 yr -1 applied annually), and one CO 2 by nitrogen addition treatment (fertilized half of prototype).
The monthly GEP and ET were gap-filled by the site principal investigator. The GEP was a flux-partitioned product created by the site principal investigator. The biometric data from the US-DK3 site were assumed to be the same as the first control ring. The biometric data from the US-NC2 site included observations of stem biomass (loblolly pine and hardwood), coarse root biomass (loblolly pine and hardwood), fine root biomass (combined loblolly pine and hardwood), stem density (loblolly pine only), leaf turnover (combined loblolly pine and hardwood), and fine root production (combined loblolly pine and hardwood).
The initialized ASW was assumed to be equal to the maximum ASW because most plots were initialized in winter months when plant demand for water was minimal. The maximum ASW in each plot was extracted from the Soil Survey Geographic Database (SSURGO) soils dataset  (Soil Survey Staff, 2013). The value we used corresponded to the maximum ASW for the top 1. 5 m of the soil. We assumed that the minimum ASW was zero. Because we focused on a region-wide optimization, we used region-wide 4 km estimates of observed monthly meteorology as inputs and to calculate the 35-year MAT for each plot  (Abatzoglou, 2013). SI was based on height measurements at age 25 in each plot or calculated by combining observations of height at younger ages with an empirical model  (Dieguez-Aranda et al. , 2006). We simulated ecosystem manipulation experiments in the 3-PG model by altering the environmental modifiers or by modifying the environmental inputs.
Data assimilation evaluation Using the observations, model, and hierarchical Bayesian method described above, we assimilated both the nonmanipulated and manipulated plots (Base assimilation; Table  4 ). We assessed model performance first by calculating the RMSE and bias of stem biomass predictions (the most common data stream). In the evaluation, we only used the most recent observed values to increase the time length between initialization and validation. Second, we assessed the predictive capacity by comparing model predictions to data not used in the parameter optimization in a cross-validation study. In this evaluation, we repeated the Base assimilation without 160 FMRC thinning study plots (Table  2 ), predicted the 160 plots using the median parameter values, and calculated the RMSE and bias stem biomass of the independent set of plots.
Sensitivity to the inclusion of ecosystem experiments We also evaluated how parameter distributions and the associated environmental sensitivity of model predictions depended on the inclusion of ecosystem experiments in data as-similation. First, we repeated the Base assimilation, this time excluding the plots that included the manipulated treatments (NoExp). We removed all manipulation types at once, rather than individual experimental types, because all experimental types involved multi-factor studies. The NoExp assimilation had the same number of data streams as the Base assimilation because it included the control treatments from the experimental studies. The NoExp assimilation represented the situation where only observations across environmental gradients were available. Second, we compared the parameterization of the ASW, soil fertility, and atmospheric CO 2 environmental modifiers from the Base to the NoExp assimilation.
Our finding demonstrated that DA efforts should test for bias in unique ecosystem experiments before finalizing a set of model parameters used in optimization. In particular, we found that the parameter governing the photosynthetic response to elevated CO 2 (fCalpha700) was substantially lower when all parameters were assumed to be shared across all plots than when the CO 2 fertilization experiment was allowed to have unique parameters. The need for the three unique parameters at the Duke FACE study parameters can be explained by the constraint provided by multiple data streams and multiple plots. An assumption of the model was that an increase in stem biomass caused a decrease in stem density through self-thinning, unless the average tree stem biomass was below a parameterized threshold (WSx1000).