dataesr/scientific-paragraphs-categorization huggingface dataset:
Genome sequencing and assembly The genome was sequenced using a combination of Illumina and 454 sequencing platforms. All general aspects of library construction and sequencing can be found at the JGI website  [38]. Pyrosequencing reads were assembled using the Newbler assembler (Roche). The initial Newbler assembly consisting of 103 contigs in four scaffolds was converted into a phrap  [39]  assembly by making fake reads from the consensus, to collect the read pairs in the 454 paired end library. Illumina GAii sequencing data (500. 5 Mb) was assembled with Velvet  [40]  and the consensus sequences were shredded into 2. 0 kb overlapped fake reads and assembled together with the 454 data. The 454 draft assembly was based on 160. 8 Mb 454 draft data and all of the 454 paired end data. Newbler parameters are -consed -a 50 -l 350 -g -m -ml 20.
The Phred/Phrap/Consed software package  [39]  was used for sequence assembly and quality assessment in the subsequent finishing process. After the shotgun stage, reads were assembled with parallel phrap (High Performance Software, LLC). Possible mis-assemblies were corrected with gapResolution [38], Dupfinisher  [41] , or sequencing cloned bridging PCR fragments with subcloning. Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR pri-mer walks (J. -F. Chang, unpublished). A total of 696 additional reactions and 2 shatter libraries were necessary to close gaps and to raise the quality of the finished sequence. Illumina reads were also used to correct potential base errors and increase consensus quality using a software Polisher developed at JGI  [42]. The error rate of the completed genome sequence is less than 1 in 100,000.
Genome annotation Genes were identified using Prodigal  [43]  as part of the DOE-JGI genome annotation pipeline  [47] , followed by a round of manual curation using the JGI GenePRIMP pipeline  [44]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) nonredundant database, UniProt, TIGR-Fam, Pfam, PRIAM, KEGG, COG, and InterPro databases. Additional gene prediction analysis and functional annotation was performed within the Integrated Microbial Genomes -Expert Review (IMG-ER) platform  [45]. Standards in Genomic Sciences.
Acknowledgements We would like to gratefully acknowledge the help of  Sabine Welnitz  for growing A. finegoldii cultures, and  Evelyne-Marie Brambilla  for DNA extraction and quality control (both at DSMZ). This work was performed under the auspices of the  US Department of Energy Office of Science, Biological and Environmental Research Program , and by the  University of California ,  Lawrence Berkeley National Laboratory  under contract No. DE-AC02-05CH11231 ,  Lawrence Livermore National Laboratory  under Contract No. DE-AC52-07NA27344 , and  Los Alamos National Laboratory  under contract No. DE-AC02-06NA25396 ,  UT-Battelle  and  Oak Ridge National Laboratory  under contract  DE-AC05-00OR22725.
The nuclear DNA was stained with 1 mg/ml Hoechst 33342 in PBS (pH 7. 2) for 4 min. Cells were mounted in Shandon Immu-Mount medium (Thermo Scientific). Samples were observed with a DMR Leica microscope, and images were captured with a Cool Snap HQ camera (Roper Scientific) controlled by Metamorph software (Roper Scientific). Final images are composed of arithmetic stacks of 15-25 deconvoluted images, each 0. 2 mM in z-step. Stacks of 15-30 images (16-bit grayscale) were acquired with a z-step of 0. 2 mm with low illumination intensity.
Flow cytometry Cells were cultured in presence or absence of 1 mM of 12459. Cells were always seeded at the same density (7. 5 Â 10 5 cells/75 cm 2 flask) in the same medium volume (15 ml). At indicated time points, cells were harvested with trypsin and either seeded for the next time point or collected for subsequent cell cycle analysis. They were then washed in PBS containing 20 mM EDTA and fixed with 70% ethanol at À20 C. When the experiment was completed, cells were collected by centrifugation, washed in PBS containing 20 mM EDTA and incubated in PBS containing 20 mM EDTA, 100 mg/ml RNase A (Sigma) and 20 mg/ml propidium iodide (Sigma) for 30 min at 37 C. Cell cycle analysis was assessed on a C6 Accuri flow cytometer (Becton Dickinson) and data treated with the FCS Express 4 software.
Similar spaceborne observations of a maritime mesoscale cloud system (MCS) located off the Brazilian coast between 0 • and 3 • N latitude on 20 June 2008 are then analysed. Near cloud-top backscatter anomalies are evidenced in a region which corresponds to the coldest temperatures with maximum cloud top altitudes derived from collocated CALIPSO/IIR and Meteosat-9/SEVIRI infrared brightness temperatures. The interpretation of CALIOP (Cloud Aerosol Lidar with Orthogonal Polarization) data highlights signifi-cant differences in microphysical properties from those observed in the continental isolated convective cloud. Indeed, SEVIRI (Spinning Enhanced Visible and InfraRed Imager) retrievals in the visible spectrum confirm much smaller ice particles near the top of the isolated continental convective cloud, i.
The objectives of this paper are first to apply PL's analysis to the CALIPSO lidar (CALIOP) backscatter properties related to the isolated continental convective cloud  (26 May 2007 CIRCLE2 situation). CloudSat and MET-9/SEVIRI observations combined with available quasi-collocated in situ measurements are analysed in order to obtain a consistent interpretation of these spaceborne remote sensing observations. Then, for comparison purposes we analyse similar spaceborne observations (from measured near-cloud top backscatter anomalies) regarding a maritime MCS on the 20 June 2008 located off the Brazilian coast between 0 • and 3 • N latitude, in order to select the most-active MCS regions, which are likely to have the densest clouds and strongest updrafts. The use of collocated MET-9/SEVIRI real-time data is then discussed to describe the properties of the MCS regions most likely to be active, which could be encountered by commercial aircraft at usual cruise altitudes (FL 350 or ∼ 10 700 m level).
Satellite data In this paper we use CALIPSO, CloudSat and MET-9 observations. Satellite data have been described in detail in GA. We summarize the main payload and technical characteristics of the available observations below. The payload of the CALIPSO satellite includes the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR) and the Wide Field Camera (WFC)  (Winker et al. , 2010). CALIOP is a laser operating at 532 nm and 1064 nm, with parallel and orthogonal polarization detectors at 532 nm  (Winker et al. , 2003; Hunt et al. , 2009). The vertical and horizontal resolutions of the attenuated backscatter coefficient product used here are 60 m and 1 km, respectively. IIR is a non-scanning imaging radiometer, nadir-viewing with a 69 km swath, and a pixel size of 1 km, which provides measurements in the thermal infrared atmospheric window region at 8.
The reflectivity is obtained from the 2B GEOPROF product and is available from the data processing centre (DPC) operated by the Colorado State University. The results in Fig. 2  show a sharp increase of the extinction coefficient from the cloud top (11 000 m) to 10 450 m (up to 5 km -1 ), and then the signal is rapidly attenuated at lower altitudes. The reflectivity factor reveals detectable signal (> -30 dBZ) even near the cloud top, indicating the presence of ice particles large enough to be detected by CloudSat radar. According to PL, the minimum detectable particle size is 30-40 µm in terms of the effective radius of a distribution of equivalentmass spheres, values which are within the range of in situ observations (see GA). To conclude, similar backscatter anomalies as reported by PL in maritime MCS were observed for the first time near the top of an isolated continental convective cloud during the CIRCLE2 experiment.
We shall first analyse the MET-9/SEVIRI observations available in this area in order to assess the activity of the MCS in terms of cloud top temperature and altitude near the CALIPSO/CloudSat overpasses, as well as microphysical parameters. Then we shall discuss the active sensing measurements, and finally we will analyse the parameters retrieved from CloudSat data (ice water content and effective radius) in order to describe cloud properties at the usual cruise altitudes of commercial aircraft, which likely prevailed in the most active parts of the MCS in the mid-tropical troposphere. Figure  3c -g represent the evolution of retrieved parameters from SEVIRI observations along the CALIPSO track, namely: the brightness temperature in the IR channel at 10. 8 µm, the optical depth, the effective radius, the differences in the brightness temperatures ( BT1) between the 12.
3 • N and 1. 9 • N latitude. Therefore the active cloud cells do not overshoot the tropopause near the CALIPSO overpass. CALIOP profiles (see Fig. 4b  next section) reveal apparent blow-off cirrus due to gravity wave breaking that may transport water vapour through the tropopause  (Wang, 2007). Note that such cirrus clouds are not detected by the CloudSat radar (see Fig. 4c  next section); this indicates the presence of small ice particles no larger than 30 µm in diameter. To summarize, the analysis of the MET-9/SEVERI observations reveals pixels along the CALIOP/CloudSat track that represent very cold areas. This is the location of the active updraft that produces new cloud material in the upper troposphere. In the next section we analyse the CALIOP/CloudSat data in the same way as previously described in Sect.
Retrieved MCS cloud properties at usual cruise altitudes of commercial aircraft In this section the cloud ice water content (IWC) and effective radius (R eff ) retrieved with both the CloudSat 2B-IWC algorithm  (Benedetti et al. , 2003, called C2B hereafter)  and the DARDAR (raDAR/liDAR, called DAR hereafter) icecloud products  (Delanoë and Hogan, 2008, 2010)  are analysed. The C2B retrieval is designed to use CloudSat Radar (CPR) radar reflectivity and visible optical depth if both data streams are available. The source for the visible optical depth is the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument on the Aqua platform. The retrieval technique described in detail by  Benedetti et al. (2003)  was adapted from the study by  Austin and Stephens (2001). This technique is based on minimization of a cost function which calculates the distance between the model-derived and the observations variables.
Discussion and conclusions Two complementary case studies have been presented to analyse the properties of convective systems in the region where strong cloud-top backscatter anomalies are observed as reported by PL. These anomalies are observed for the first time in an isolated continental convective cloud over Germany during the CIRCLE2 experiment (26 May 2007). Quasi-collocated in situ observations confirm that these regions represent the most active and dense convective cloud parts with likely the strongest core updrafts and unusually high values for the concentration of small ice particles, extinction and ice water content. Moreover, the theoretical shape derived from CALIOP data interpretation may roughly fit with the observed dominant ice particle shape (chain-like aggregate). Similar spaceborne data are observed in a maritime mesoscale cloud system (MCS) on the 20 June 2008 located off the Brazilian coast between 0 • and 3 • N latitude.
The analysis of the MET-9/SEVIRI observations reveals pixels along the collocated CALIPSO/CloudSat track (a time lag of max 3 min) that represent cold areas. This is the area of active updraft that produces new dense cloud material in the upper troposphere. This feature is confirmed by concurrent near cloud-top backscatter anomalies from CALIOP data and CloudSat reflectivities. Near-top cloud properties in terms of integrated depolarization ratios ( ) may indicate signatures of microphysical characteristics. They are found to be significantly different from those observed in the continental isolated convective cloud. Indeed, SEVIRI retrievals confirm much smaller ice particles near the top of the isolated continental convective cloud, i. e. R eff ∼ 15 µm versus 22-27 µm in the MCS. Near-top cloud properties may also indicate signatures of microphysical characteristics according to the cloud-stage evolution, as revealed by SEVIRI images, to identify the development of new cells within the MCS cluster.
Eur. Phys. J. A (2013) 49 : 27 The authors are indebted to the national and international funding agencies that have supported the n TOF Collaboration since its inception. In particular, this work was supported by the  European Commission  within the  Fifth Framework Programme through nTOF-ND-ADS  (contract no. FIKW-CT-2000-00107 ), the  Sixth Framework Programme  through  EU-ROTRANS  ( FI6W-CT-2004-516520 ) and the  Seventh Framework Programme  through ERINDA (contract no. FP7-269499 ) and ANDES (contract no. FP7-249671 ). Furthermore, many measurements would not have been possible without the support from the  CERN mechanical workshops (D. Grenier) , the collaboration with JRC-IRMM through which most of the samples were obtained, the help and guidance of  CERN/RP  for the use of the radioactive samples, and the detectors fabricated at the  CERN MicroMegas lab  ( R.
Acknowledgments We acknowledge the members of the  International Alliance  for the Control of Scabies:  Ross Andrews ,  Menzies School of Health Research, Australia Larry Arlian, Wright State University, Ohio, USA Kassahun Bilcha, University of Gondar Hospital, Ethiopia Jonathan Carapetis, Telethon Institute for Child Health Research, Australia Guadalupe Chavez-Lopez, General Hospital, Health Secretary, Acapulco, Mexico Bart Currie, Menzies School of Health Research, Australia Guadalupe Estrada-Chavez, Guerrero State University, Guerrero, Mexico Roberto Estrada, General Hospital, Health Secretary, Acapulco ,  Mexico Ousmane Faye ,  CNAM-Ex Institut Marchoux ,  Mali Hermann Feldmeier ,  Institute of Microbiology and Hygiene at ChariteUniversity Medicine, Germany Alan Fenwick, NTD/Imperial College, United Kingdom Katja Fischer, Queensland Institute of Medical Research, Australia Lucy Goh, LBJ Tropical Medical Centre, American Samoa Brook Goodhew, Centers for Disease Control and Prevention, USA Karin Haar, Robert Koch Institute, Germany David Hendrickx, Telethon Institute for Child Health Research, Australia Jo ¨rg Heukelbach, Federal University of Ceara, Brazil Janet Hickman, Women's Dermatologic Society, USA Deborah Holt, Menzies School of Health Research, Australia Adrian Hopkins, Mectizan Donation Program, USA Peter Hotez, George Washington University, USA Camille Introcaso, Pennsylvania Center for Dermatology, USA John Kaldor, The Kirby Institute, Australia Therese Kearns, Menzies School of Health Research, Australia Sidney Klaus, Dartmouth Medical School, USA Josefa Koroivueta, Ministry of Health, Fiji Carrie Kovarik, University of Pennsylvania, USA Sophie La Vincente, Centre for International Child Health, Australia Fatimata Ly, Institut d'Hygiene Sociale, Senegal Antoine Mahe, Dermatologie Hopital Pastuer, France Diana Martin, Centers for Disease Control and Prevention, USA John Masenga, Regional Dermatology Training Centre, Tanzania Toby Maurer, University of California, USA Marjorie Morgan, Wright State University, USA Kate Mounsey, University of the Sunshine Coast, Australia Scott Norton, Children's National Medical Centre, Georgetown University, USA Eric Ottesen, Research Triangle Institute, USA Sam Prince, One Disease at a Time, Australia Wingfield Rehmus, University of British Columbia, Canada Simone Reynolds, Queensland Institute of Medical Research, Australia Lucia Romani, The University of New South Wales, Australia Pearl Swe, Queensland Institute of Medical Research, Australia Lisi Tikoduadua, Ministry of Health, Fiji Meciusela Tuicakau, Colonial War Memorial Hospital ,  Fiji Chris Van Beneden ,  Centers for Disease Control and Prevention, USA Shelley Walton, University of the Sunshine Coast, Australia Margot Whitfeld, St Vincent's Hospital, Sydney , Australia.
Bacterial Strains, Media and Antimicrobial Peptides Bacterial strains used in this study are listed in Table  1. Transposon mutants PAO1-pqsE and PA14-mexH were confirmed by PCR (data not shown). All experiments were performed in Mueller Hinton (MH) broth (Merck, Darmstadt, Germany). Bacteria were routinely grown at 37uC with shaking at 170 rpm. Antimicrobial peptides were kindly provided by Prof. Robert Hancock (University of British Columbia, Vancouver, Canada) or purchased from Anaspec (Fremont, CA, USA). The amino acid sequences of antimicrobial peptides used and their minimal inhibitory concentrations (MIC) against PAO1 WT are shown in Table  2. Peptide stock solutions of 2 mg/ml were prepared in sterile ultra pure DI water and stored at 220uC until needed.
South Natick, MA, USA) at a flow rate of 10 ml/min. To quantify PQS with high selectivity and sensitivity, MRM experiments were performed using the transitions from precursor ion to fragment ion: 260/175 (quantifier), 260/146, 260/147 and 260/188 (qualifier). An external calibration was performed using PQS standard solutions with concentrations ranging from 10 ng/ml up to 1000 ng/ml. PQS concentrations were normalized against the cell density of each sample (OD 600 ). Analyses were performed with six independent bacterial cultures and data was statistically analyzed using the non-parametric Mann-Whitney test.
Figure1. Summarized microarray data of dysregulated P. aeruginosa genes in response to LL-37. Mid-log phase cultures of P. aeruginosa PAO1 were grown in MH broth containing either 20 mg/ml LL-37 or no LL-37 for 2 h at 37uC following RNA extraction and microarray analysis. The graph shows functions of more than 1. 5-fold up-or downregulated genes according to the Pseudomonas Genome Database [28]. Hypothetical genes are not shown. doi:10. 1371/journal. pone. 0082240. g001.
MicroRNA Array Analysis Total RNA was extracted from MSCs and MSC-derived chondrocytes (12 h; day 3) using miRNeasy kit (Qiagen S. A. , Courtaboeuf, France). MiRNA expression profiling was performed by the MGX IRB Affymetrix platform using Affymetrix microarrays and sequences were obtained from the Sanger miRBase, release 11. 0. Labeling and hybridization were performed according to manufacturer's protocol with 800 ng RNA. Raw data were normalized and additional data analysis was performed as described previously  [16]. All data comply with the MIAME guidelines and the complete dataset has been deposited in the Gene Expression Omnibus (GEO) online database under the accession number E-MTAB-1544. MiRNA level fold change (FC) at 12 h or day 3 versus day 0 was calculated and results are expressed as the ratio of miRNA in differentiation conditions on control conditions.
Ectopic in vivo Bone Formation SCID mice aged 9-10 weeks were grown in our animal facility. The protocol was approved by the Committee on the Ethics of Animal Experiments in Languedoc-Roussillon (CEEA-LR 36) (Permit Number: CEEA-LR-1042). hMSCs transfected with premiR or antagomiR oligonucleotides were mixed with BMP-2expressing C3H10T1/2 cells (ratio 1:10 respectively) and 5610 4 cells were implanted in the Tibialis anterior muscle as described  [20]. Mice were euthanatized 15 days later and hind paws fixed in 4% paraformaldehyde for 7 days. Limbs were analyzed by Micro Computed Tomography (mCT) using SkyScan (Bruker, Kontich, Belgium). The 3D reconstruction of X-ray imaging and bone volume measurements were performed using AvizoH software (VSG, Merignac, France). Histological sections from muscles after paraffin embedding were stained with Safranin O and Fast Green.
miR-574-3p is Positively Modulated by Sox9 In order to determine whether the up-regulation of miR-574-3p at early stages of differentiation is transcriptionally dependent on Sox9, the master gene of chondrogenesis, we analyzed the promoter region of miR-574-3p using the MIR@nt@n software  [23]. Three putative binding sites for Sox9 were identified in the promoter sequence suggesting that Sox9 may modulate miR-574-3p expression (Fig. 3A ). After Sox9 transfection in the C-20/A4 chondrocyte line, the expression levels of Sox9 and miR-574-3p are concomitantly and significantly increased (Fig. 3B ). The regulation of miR-574-3p by Sox9 was further investigated using a reporter plasmid containing the Firefly luciferase gene under control of the 2 kb sequence upstream of the start codon for miR-574-3p.
Acknowledgments We are very grateful to  Charles Lecellier  ( CNRS UMR5535 , Montpellier, France) for helpful discussions and  Ph. Blache  ( UMR 5237, Montpellier, France ) for providing the Sox9 plasmid [19]. We thank the  ''Reseau des Animaleries de Montpellier'' animal facility, the ''Reseau d'Histologie Experimentale de Montpellier'' histology facility  for processing our animal tissues and the '' Montpellier RIO Imaging '' platform.
Water vapour (H 2 O) is one of the operationally retrieved key species of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument aboard the Environmental Satellite (ENVISAT) which was launched into its sun-synchronous orbit on 1 March 2002 and operated until April 2012. Within the MIPAS validation activities, independent observations from balloons, aircraft, satellites, and ground-based stations have been compared to European Space Agency (ESA) version 4. 61 operational H 2 O data comprising the time period from July 2002 until March 2004 where MIPAS measured with full spectral resolution. No significant bias in the MIPAS H 2 O data is seen in the lower stratosphere (above the hygropause) between about 15 and 30 km. Differences of H 2 O quantities observed by MIPAS and the validation instruments are mostly well within the combined total errors in this altitude region.
In the upper stratosphere (above about 30 km), a tendency towards a small positive bias (up to about 10 %) is present in the MIPAS data when compared to its balloon-borne counterpart MIPAS-B, to the satellite instruments HALOE (Halogen Occultation Experiment) and ACE-FTS (Atmospheric Chemistry Experiment, Fourier Transform Spectrometer), and to the millimeter-wave airborne sensor AMSOS (Airborne Microwave Stratospheric Observing System). In the mesosphere the situation is unclear due to the occurrence of different biases when comparing HALOE and ACE-FTS data. Pronounced deviations between MIPAS and the correlative instruments occur in the lowermost stratosphere and.
It belongs to a series of validation studies of MIPAS operational products which were performed in a consistent manner: temperature  (Ridolfi et al. , 2007) , O 3  (Cortesi et al. , 2007) , HNO 3  (Wang et al. , 2007) , CH 4 , N 2 O  (Payan et al. , 2009) , and NO 2  (Wetzel et al. , 2007). In accordance with these validation studies, the H 2 O assessment is restricted to the time period from July 2002 until March 2004 where MIPAS was operated at full spectral resolution. H 2 O profile comparisons between version 4. 61 and the newly processed ML2PP V6 data  (Raspollini et al. , 2013)  have shown that differences in retrieved H 2 O volume mixing ratios are less than 5 % in the stratosphere except in the Antarctic winter where differences can be around 10 % or larger. In the following section, an overview of the MIPAS data analysis is given.