dataesr/scientific-paragraphs-categorization huggingface dataset:
Kinetic assay Catalytic activity experiments were performed fluorometrically as described by  Fischer et al. (2005)  with some modifications. Explicitly, reaction mixtures consisted of 50 mM potassium phosphate buffer pH 7. 0 and 50 nM RS (subunits). 6,7-Dimethyl-8-ribityllumazine was then added at a broad range of concentrations (0-1000 mM) in a final volume of 1 ml. Riboflavin fluorescence was monitored as described above every 0. 5 s for 20 min. Assays were always performed in duplicate. To correct for systematic variations from the spectrofluorometer, riboflavin dilution series were measured in conjunction with each experiment. These measurements were used to define both the linear range and the response of the instrument. Relative fluorescence intensities were converted to absolute riboflavin concentrations using the slope from the linear regression of the fluorescence measurements of a riboflavin dilution series (data not shown).
This work was supported by the  Argentinian Research Council (CONICET)  and the  Argentinian Agency for Scientific and Technological Development (ANPCyT). We acknowledge access to the X-ray facilities at the  Institut Pasteur Montevideo, Uruguay , the  SOLEIL synchrotron, France  and the  NSLS, USA. The X6A beamline at the NSLS is funded by the  National Institute of General Medical Sciences, National Institutes of Health  under agreement  GM-0080. The  NSLS, Brookhaven National Laboratory  is supported by the  US Department of Energy  under contract No. DE-AC02-98CH10886. We are grateful to the  Center for Structural Biology of the Mercosur (CEBEM)  and the  Argentinian Ministry of Science (MINCyT)  for travel support.
Moreover, glider observations for May 2013 are available in the Coriolis data base (available through My-Ocean service) sampling over the whole month in a small 1/2 • × 1/2 • box centred on 16. 25 • W and 48. 55 • N. The physical variable chosen for this study is the mixed layer depth, since the ocean stratifies during the spring months and some mixing events occur which are directly linked to atmospheric forcing. Other studies quantifying the uncertainties in the ocean forecast for several oceanic fields  (Lermusiaux et al. , 2006) , made use of super ensemble techniques  (Vandenbulcke et al. , 2009; Lenartz et al. , 2010; Pistoia, 2012; Scott et al. , 2012)  or have quantified the impact of medium range atmospheric forecasting on the ocean  (Drillet et al. , 2009). An ensemble approach is also used in oceanography for estimating variability at a more climatic scale, for example in  Zhu et al.
Back Close Full using the atmospheric forecast analysis to the end of May 2013. The results of this experiment will be discussed in  Sect. 4. 3. 4. This study focuses on May 2013, where the four systems described above were available, and where the Coriolis in situ database contains repetitive in situ profiles obtained from glider observations around 16. 5 • W and 48. 5 • N (Fig. 2 ). 2004 ) defined a 0. 2 • C criterion which is used both for the model and the observations in computing the mixed layer depth, and reapplied here in a slightly different context. In their paper, this criterion was used to compute global mixed layer depth climatology based on in situ observations; Fig. 3  shows the availability of the criterion in our area of interest. When the mixed layer is really pronounced as for one profile on 11 May and for the 3 profiles of 28 May, the criterion detects the base of the mixed layer.
These gliders were deployed under the OSMOSIS (Ocean Surface Mixing, Ocean Sub-mesoscale Interaction Study, http://www. bodc. ac. uk/projects/uk/osmosis/introduction/) project, in which care is taken to apply a near real time quality control, disseminating the observations to the Coriolis data centre in real time. The observations used in this study do not represent the full data set but a subsampled one as carried out in the system for all type of in situ observations. For each instrument (in this case gliders) only one profile per day is retained to avoid over sampling (in time and space) of the observations since the global model cannot represent processes at such high resolution. In our subsample database, 74 vertical profiles are available for May 2013 with almost one profile per day.
Sequencing of VNTR loci showed that the number of alleles per locus ranged from 7 to 17 (Table  1 ). Locus G1_29 was the most polymorphic VNTR with 17 different alleles, ranging from 1 to 23 repeats (Table  1 ). The data sets supporting the results of this article are available in the GenBank database (Accession numbers XaG1_02: KJ736838 -KJ736944; XaG1_29: KJ736945 -KJ737053; XaG2_52: KJ737163 -KJ737268; XaG1_67: KJ737269 -KJ737369; XaG1_73: KJ737054 -KJ737162) and in the Dryad Digital Repository: http://doi. org/10. 5061/dryad. t173v.
Acknowledgements The authors would like to thank to the  Faculty of Sciences from Universidad de los Andes , the  Evaluation-orientation de la Coopération Scientifique  ( ECOS  project No. C11A02 ) and the  National Science Foundation/BREAD (Basic Research  to  Enable Agricultural Development) grant  ( Award 0965418 ) for funding this study. We also thank the  International Center for Tropical Agriculture (CIAT)  for enabling the sampling at their experimental cassava field located in Corpoica ( La Libertad , Meta). We also thank  Daniela Osorio  for help in the edition of manuscript style. Finally we thank  Estefanía Luengas  for help in figure editing.
Availability of supporting data The data sets supporting the results of this article are available in the Dryad Digital Repository: http://doi. org/ 10. 5061/dryad. t173v. DNA sequences are available in Genbank database: (Accession numbers XaG1_02: KJ736838 -KJ736944; XaG1_29: KJ736945 -KJ737053; XaG2_52: KJ737163 -KJ737268; XaG1_67: KJ737269 -KJ737369; XaG1_73: KJ737054 -KJ737162).
The different colours correspond to the results obtained with three increasingly conservative calibration regimes taking fossil age uncertainty into account (sky blue: calibration I; Orange: calibration II; bluish-green: calibration III; see Methods for details). The box for each calibration and rates represents the first and third quartiles, whiskers represent 1. 5 the interquartile range and the thick bar is the median rates (sample size ¼ 1,000). incongruence among partitions. The data sets used in the present study can be obtained from http://purl. org/phylo/treebase/phylows/study/TB2:S15950?x-access-code=98d94511d8c016de8eae6f21c851826e&format=html). Molecular dating. We used an exponential uncorrelated molecular clock that implements evolutionary rate heterogeneity in BEAST 1. 7. 5 (ref.
Acknowledgements We thank  M. Carine ,  C. Nieberding  and  P. Linder  for their comments on the manuscript. This research was supported by a multi-institutional, collaborative grant from the  Assembling the Tree of Life programme at NSF. The following NSF grants supported this work:  EF-0531730-002  (to A. J. S. ),  EF-0531680  (to M. V. K. and J. E. ) and  EF-0531750  (to B. C. -S. and  Raymond E. Stotler ). Data generation at RBGE was funded by the  Scottish Government's Rural and Environment Science and Analytical Services Division. The work of B. L. has been supported by a  BeiPD-cofund Marie Curie fellowship.
Cohort and collection of samples This work has been carried out as part of the "SchistoVAN" project (clinicaltrials. gov ID NCT01553552), sponsored by the Biomedical Research Centre EPLS (Saint-Louis, Senegal) (www. espoir-sante. org). The present study was approved by the National Ethics Committee of the Ministry of Health of Senegal (September 2011; protocol number SEN11/43, clinicaltrials. gov: NCT01553552). Oral and written informed consents were obtained from the parents or the legal guardians of the children in accordance with the Code of Ethics of the World Medical association (Declaration of Helsinki). Children enrolled in the present study formed a sub-cohort of the "AnoPalAno-Vac" project (clinicaltrials. gov ID NCT01545115) and were recruited on the basis of their age (6 to 10 years of age in October 2011) through village nurses, healthcare workers in the community and school directors.
Mean temperature ranges between 20°C and 30°C during the cool season (November to February) and between 25°C and 38°C during the warm season (March to October). In this study, stool samples were collected from 93 symptomatic and asymptomatic children (Agniam = 17; Fanaye = 38; Niandane = 38) presenting or not gastrointestinal disorders. These boys (n = 46) and girls (n = 47) were aged 6 to 10 years (median age 8. 4; quartiles: 6. 6; 9. 5) (Table  1 ). Children presented no symptoms of severe illness and/or fever and were subject to a questionnaire that was designed to collect clinical data especially regarding recent diarrhea, vomiting, and abdominal pain. For storage and transport at -20°C to Lille, stool samples were added in Stool Transport and Recovery (S. T. A. R. ) buffer (Roche) in a ratio of 1:3 according to the manufacturer's recommendations then homogenized by shaking.
The DNA samples negative by non-qPCRs were subsequently amplified using the real time qPCR assay developed by Poirier et al. [20]. Due to the high sensitivity of this detection method, various controls were performed to prevent artifacts related to contamination through different sources: DNA extraction controls (isolation of DNAs without stool and from a Blastocystis sp. -negative stool) subsequently used in qPCR assays and negative (DNA matrix replaced by water) and positive (DNA obtained from a Blastocystis sp. ST4 culture) qPCR controls. The expected 320 bp-amplified variable region of the SSU rRNA gene was directly sequenced for subtyping. The SSU rRNA gene sequences obtained in this study have been deposited in GenBank under accession numbers KF848509 to KF848624. Obtained sequences were compared with all Blastocystis sp.
[40]  and Poirier et al. [20] , respectively. b Determined in the common region of clones belonging to the same ST and sequenced for each sample. case, we have considered in the following analysis of our data that two different clones of the same ST identified in the same patient derived from the same isolate of Blastocystis sp. For the last 8 samples, mixed infections with two (6 samples) or three STs (2 samples) were identified (Table  2 ). The majority of the subtyped samples included in the present study (85/93) represented single infections. With the addition of 8 mixed infections consisting of two or three different isolates, we analyzed a total of 103 isolates. As summarized in Table  3 , ST3 was the most common Blastocystis sp. ST in our Senegalese population (49. 5%) followed by ST1 (28.
Acknowledgements This work was supported by grants from the  Programme Orientations Stratégiques  from the  University of Lille 2 , the  Centre National de la Recherche Scientifique , the  Institut Pasteur of Lille  and the  Biomedical Research Center EPLS (Sn). DES and MO were both supported by PhD fellowships from the  Conseil National de la Recherche Scientifique  and the  Azm & Saade Association from Lebanon , DM by a PhD fellowship from the  Regione Autonoma della Sardegna  and a post-doctoral grant from the  Japanese Society for Promotion of Science (JSPS)  and AC by a PhD fellowship from the  Ministère Français de l'Education Nationale, de la Recherche et de la Technologie.
The detection was made considering a mass range of 80-2000 m/z. Compounds were identified by analysis of their UV, MS and MS/MS spectra and quantified with UV chromatogram at 280 nm using MassHunter Qualitative Analysis (Agilent Technologies). For absolute quantification of serotonin, tryptophan and tryptamine, samples were analyzed by HPLC on a Symmetry 5 μm C18 column (250 × 4. 6 mm, Waters Corporation). We used two methods. The first one was used for serotonin and tryptophan. Samples were subjected to HPLC with 0. 1% aqueous TFA as solvent A and acetonitrile with 0. 1% TFA as solvent B, at a flow rate of 1. 3 ml/min with the same gradient as described by Hagemeier et al. [29]. Peak detection was performed with a DAD (200-600 nm) as part of the Waters system (Waters Corporation). HPLC chromatograms were analyzed at 280 nm using Empower Pro Software (Waters Corporation).
Transcriptome analysis of Bd spikes infected by Fusarium graminearum To analyze the responses of Bd to Fg infection and to discriminate the responses due solely to the DON mycotoxin, a transcriptome analysis was performed using the Fg DON + and Fg DON -strains. Affymetrix GeneChip® Brachypodium Genome Array was used to examine transcript accumulation in Bd21 ecotype inoculated spikelets 96 hai by either the Fg DON + or the Fg DON -strain and compared to the mock inoculated spikelets. The 96 hai timepoint was chosen as it corresponded to the early time point which best discriminated the extent of spikelet colonization between the two strains. The analyses of the GeneChip data are presented in the Methods section. In all, 4,633 transcripts exhibiting a significant differential expression between the different conditions were retrieved (p-value ≤ 0.
Finally, 60 transcripts are specific for the Fg DON -inoculated plants: 51 are up-regulated and 9 are down-regulated. To validate the microarray results, we selected twenty candidate genes and performed qRT-PCR analysis using the same RNA samples used for microarray analysis. These genes were chosen because encoding proteins potentially related to plant defense and general detoxification, but also as a representative sample of all differential regulation patterns detected following the analysis of microarray results. The results of the expression analysis strongly correlated (Table  1 , R 2 = 0. 81) with the microarray data in all three treatments.
Functional annotation using the KEGG (Kyoto Encyclopedia of Genes and Genomes) database allowed us to identify genes potentially encoding the enzymes in the metabolic pathway from anthranilate to serotonin (Figure  5A  and Additional file 4) as those described in rice infected by Bipolaris oryzae  [38]. More precisely, 4 genes encoding proteins related to the putative Trp decarboxylase (TDC) enzymes (Bradi3g14730; Bradi3g14760; Bradi3g14750; Bradi3g14740) and a gene encoding a putative indole-3-glycerol phosphate lyase (Bradi1g05450) were more induced after infection with the Fg DON + strain compared to the infection with the Fg DON - strain (Additional file 4). Particularly interesting was the Bradi4g39240 gene encoding a cytochrome P450 monooxygenase (CYP71P1) that catalyzes the conversion of tryptamine to serotonine in rice  [39].
Finally, our data from the Additional file 2 pointed to 5 genes encoding putative hydroxycinnamoyl transferases classified into the phenolamide biosynthesis category. No genes belonging to the benzoxazinoid pathway could be retrieved from our transcriptomic analysis. We then performed a metabolic profiling analysis of soluble metabolites on the same biological samples used for microarray and qRT-PCR analyses. A typical chromatogram obtained from Fg DON + strain-infected plant tissues at 96 hai is shown in Figure  5B. In this chromatogram, 18 peaks could be clearly individualized (Additional file 5). Among these, 5 peaks exhibited significant difference both with the control samples and between the two infection treatments (t test, p-value ≤ 0. 02). These peaks could be identified as Trp (peak 4) or Trp-derived compounds: tryptamine (peak 5), serotonin (peak 2) and coumaroyl (Cou)-and feruloyl (Fer)-serotonin (peaks 17 and 18, respectively).
Acknowledgments This work was funded by the  National Centre of Scientific Research (CNRS)  and a grant "Attractivité" from  Université Paris-Sud  obtained by MD. JCP has a PhD fellowship from the  Ministère de l'Enseignement Supérieur et de la Recherche. The authors are particularly grateful to  Martin Urban  for supplying the MU102 (tri5 or Fg DON -) mutant strain.
Background and data collection The study area covers Chenzhou, located in a subtropical region of Hunan Province in Central China. Chenzhou is located between latitude 24u539 and 26u509 north, and longitude 112u139 and 114u149 east. It is 217 km wide and 202 km long, with a total land area of 19,400 km 2. The region consists of two municipal districts (Beihu and Suxian) and nine counties (Guiyang, Yizhang, Yongxing, Jiahe, Linwu, Rucheng, Guidong, Anren and Zixing), and a total population of about 4. 6 million people (Figure  1 ). From 2006 to 2010, data from cases of HFRS in Chenzhou were obtained from the Hunan Center for Disease Control and Prevention (CDC). All of the cases were initially diagnosed based on clinical symptoms using diagnostic criteria from the Ministry of Health of the People's Republic of China.
Meteorological data (monthly average temperature, monthly average relative humidity, and monthly precipitation) for the 2006 to 2010 period were obtained from the China Meteorological Data Sharing Service System (http://cdc. cma. gov. cn/index. jsp). GDP and the urbanization rate of the population were obtained from the Hunan Statistics Yearbook. Immigrant population data were obtained from Hunan Public Security Department. Data for the estimation of the NDVI was obtained from the International Scientific Data Service Platform (1 km spatial resolution; http://datamirror. csdb. cn/). The NDVI was generated from a transformation of the near infrared (NIR) and red wavelengths (RED) using the equation: NDVI~N IR{RED NIRzRED ð1Þ Author Summary Hemorrhagic fever with renal syndrome (HFRS), a rodentborne disease caused by hantaviruses, is characterized by fever, haemorrhage, headache, back pain, abdominal pain, and acute kidney injury.
The results will be helpful for making and prioritizing preventive measures. Land use data were obtained from the Second National Land Survey and were categorized as to cultivated land, forest, grass, or residential land. The data set was analyzed in ArcGIS 9. 3 (ESRI Inc. , Redlands, CA, USA) and included a digital map of Chenzhou (1:50000), geocoding, case information, and population information. The data for each variable were converted to the same geographic projection and clipped to the study area.
Data analysis The principal component analysis was performed using the 2006-2010 data on natural factors (relative rodent density, NDVI, monthly average temperature, monthly rainfall and monthly average relative humidity) and social factors (GDP and urbanization rate). Four principal components that included three natural  components (F1: rodent density, NDVI for rice paddies and temperature; F2: rainfall and relative humidity, and F3: rodent density and relative humidity) and one social component (F4: GDP and the urbanization rate of the population) were extracted. Cross correlation analysis, adjusted for seasonality, was performed to infer the time-lag effects between variables. Each sequence of variables was filtered to convert it to white noise before proceeding with the cross correlation analysis.
Based on survey data coming from three countries (Benin, Burkina Faso, and Senegal), they find a significant number of large firms that nonetheless remain in the informal sector in this part of Africa. They conclude that even when size is considered in the definition of informality, it must be combined with other criteria to have a good understanding of the phenomenon. Similarly,  Gelb et al (2009)  demonstrate from a database of 7 southern and eastern African countries that among the micro firms in their dataset, a large number are actually formal enterprises, and thus defining the informal sector based only on firm size is not applicable.
The problem with these criteria is that they bear more relation to making comparison of national economies and give rise to fewer applications of firm-level survey data. Focusing on Africa,  Steel and Snodgrass (2008)  refute the notion of the informal sector as an entity unknown to the fiscal authorities. According to them, informal activity is well-known and taxed by public powers that often allocate the stands that informal firms use for their business at the public market. Benjamin and Mbaye (2012)  point out the presumptive tax that applies to the informal sector in Africa. They demonstrate from the tax database that even certain very small, informal firms without a known location are sometimes identified and listed by the tax department in Senegal. According to them, the registration and administrative recognition criteria are not easily applied, because even if informal firms are not always recorded at the level of central authorities, they are recorded at the local level where they also pay taxes.
delbrueckii subsp. bulgaricus strain ATCC 11842  (2). In spite of this abundance of IS elements, which might have resulted in massive gene inactivation and genomic rearrangements, strain CNRZ327 appears to have more extensive metabolic capacities than strain ATCC 11842, and the genomes of the two strains appear to be essentially colinear. Nucleotide sequence accession number. The genome sequence of L. delbrueckii subsp. lactis CNRZ327 has been deposited in the European Nucleotide Archive (http://www. ebi. ac. uk/ena) under accession no. CCDV01000001.
gorillae sp. nov. strain G1 T exhibited the phenotypic differences detailed in Table  2. Matrix-assisted laser-desorption/ionization timeof-flight (MALDI-TOF) MS protein analysis was carried out as previously described  [14]  using a Microflex spectrometer (Bruker Daltonics, Leipzig, Germany). Twelve distinct deposits were made for strain G1 T from 12 isolated colonies. The 12 G1 T spectra were imported into the MALDI BioTyper software (version 2. 0, Bruker) and analyzed by standard pattern matching (with default parameter settings) against 6,252 bacterial spectra including 123 spectra from 67 Paenibacillus species, used as reference data, in the BioTyper database. Interpretation of scores was as follows: a score > 2 to a validly published species enabled the identification at the species level, a score > 1.
7 but < 2 enabled the identification at the genus level; and a score < 1. 7 did not enable any identification. For strain G1 T , the obtained scores ranged from 1. 177 to 1. 343, thus suggesting that our isolate was not a member of a known species. We incremented our database with the spectrum from strain G1 T (Figure  4 ). Spectrum differences with other of Paenibacillus species are shown in Figure  5.
Genome project history The organism was selected for sequencing on the basis of its phylogenetic position and 16S rRNA similarity to other members of the genus Paenibacillus, and is part of a "culturomics" study of the gorilla flora which aims to isolate all bacterial species within gorilla feces. It is the 44 th genome of a Paenibacillus species sequenced and the first genome of Paenibacillus gorillae sp. nov. sequenced. A summary of the project information is shown in Table  3. The Genbank accession number is CBVJ000000000 and consists of 167 contigs (150 large contigs). Table  3  shows the project information and its association with MIGS version 2. 0 compliance  [48]. Growth conditions and DNA isolation P. gorillae sp. nov. strain G1 T , CSUR P205, DSM 26181, was grown aerobically on 5% sheep bloodenriched Columbia agar at 25°C.
Genome annotation Open Reading Frames (ORFs) were predicted using Prodigal  [49]  with default parameters but the predicted ORFs were excluded if they spanned a sequencing gap region. The predicted bacterial protein sequences were searched against the GenBank database  [50]  and the Clusters of Orthologous Groups (COG) databases using BLASTP. The tRNAScanSE tool  [51]  was used to find tRNA genes, whereas ribosomal RNAs were found by using RNAmmer  [52]  and BLASTn against the GenBank database. ORFans were identified if their BLASTP E-value was lower than 1e-03 for alignment length greater than 80 amino acids. If alignment lengths were smaller than 80 amino acids, we used an E-value of 1e-05. To estimate the mean level of nucleotide sequence similarity at the genome level between P. gorillae sp nov.