dataesr/scientific-paragraphs-categorization huggingface dataset:
DISCUSSION Can multidrug transporters be identified on the basis of their sequences? In this study, we addressed this fundamental question by characterizing seven heterodimeric ABC exporters of E. faecalis. According to their entries in the National Center for Biotechnology Information (NCBI) database, these enterococcal transporters are all predicted to function as "ABC-type multidrug transport systems. " One of them, EfrAB, was previously described as a multidrug efflux pump when overexpressed in E. coli  (12). We thoroughly investigated the transporters in three complementary experimental settings. First, gene deletions in E. faecalis permitted us to study the transporters' contributions to drug efflux in the native context of this pathogenic bacterium. Second, overexpression in L. lactis, a closely related cousin of E.
ACKNOWLEDGMENTS We thank  Christopher Kristich  of the  Medical College of Wisconsin  for the pCJK245 plasmid and for helpful advice concerning the generation of E. faecalis gene deletions. Michael Hombach  of the  Institute of Medical Microbiology  is acknowledged for the identification of drug-sensitive E. faecalis strains. We thank all members of the  Seeger lab  for suggestions and discussions. D. P. T. holds the  Alberta Innovates Technology Futures Strategic Chair in (Bio)Molecular Simulation  and is an  Alberta Innovates Health Solutions (AIHS) Scientist.
HIF-1α and mTOR phosphorylation analyses using western blotting Western blotting was performed as described previously  [16]  using the appropriate primary and secondary antibodies: anti-rat HIF-1α mouse monoclonal antibody (R&D Systems, Minneapolis, USA; 1/1000); anti-rat mTOR and phosphorylated mTOR (Ser2448) rabbit polyclonal antibodies (Cell Signalling, Ozyme, St Quentin Yvelines, France; 1/500); anti-mouse goat peroxidase (HRP)-conjugated and anti-rabbit goat peroxidase (HRP)-conjugated antibodies (Sigma-Aldrich, St Louis, MO, USA; 1/8000). Proteins were visualized with the Luminata™ Forte Western HRP Substrate (Millipore) and detected using enhanced chemilumiscence (Bio-Rad). The integrated optical density of each band was quantified using the ImageJ v. 1. 34 software and normalised against β-actin (anti-mouse β-actin monoclonal antibody, 1/10000, Santa Cruz Biotechnology Inc.
The relative quantity of SOX and MOX symbiont was estimated by using the comparative Ct method formula: Relative quantification = 2 -ΔCt , (ΔCt = Ct 16S -Ct MDH ). Lysozymes characterisation: sequences, structure and phylogeny All B. azoricus lysozymes sequences used in this study have been obtained from previous existing transcriptome database. Briefly, RNA was extracted from various tissues (gill, mantle, and digestive gland) of B. azoricus samples collected in Menez Gwen site (37°50' N, 31°31' W, 850 m depth) during a previous cruise (BIOBAZ initiale in 2011). Sequencing was performed at Marine Genomics Unit of Okinawa Institute of Science and Technology (OIST-Japan) using the standard Illumina RNA library preparation protocol and a single lane of the HiSeq 36 bases pair-end approach. Contigs were de novo assembled with Velvet-Oases version 0.
2. 08  [36]  using the Bioinformatic platform of Roscoff. Optimal kmer length was determined by assembling one genotype at all possible kmer values from 20 to 60 using Velvet version 0. 7. 55  [37]. The kmer length of 51 was selected for further assemblies. The Velvet assembly generated 62987 contigs and all consensus transcript sequences were searched against protein databases including NCBI non-redundant (nr) database and Swiss-Prot using BLASTx with a cutoff evalue of e-03. BLAST2GO was used to assign gene ontology (GO) annotation  [38]. Illumina sequences generated in this study have been deposited in Data Bank of Japan (DDBJ) Sequence Read Archive (DRA, http://trace. ddbj. nig. ac. jp/dra/) with accession number DRA 004082. The amino acid sequences of Ba-lysozymes were determined using the Expert Protein Analysis System (http://www.
expasy. org/tanslate/). Multiple alignments were conducted with the ClustalW program (http://npsa-prabi. ibcp. fr/). Signal peptides were predicted by SignalP4. 1 server (http//www. cbs. dtu. dk/services/SignalP/). The three-dimensional model of Ba-lysozyme 4, 5 and 6 were constructed by comparative modelling with Modeller 9v13 program. The structure of the i-type lysozyme isolated from the common orient clam Metrix lusaria, crystallized with 3 N-Acetyl-D-Glucosamine (NAG) as substrates (pdb entry: 3AB6), was used as template. One hundred models were generated for each Ba-lysozyme paralog and their quality assessed using the Modeller Objective Function parameter. The reliability of modelled structures was validated by Ramachandran plot analysis using PROCHECK (http://www. ebi. ac. uk/thorntonsrv/databases/pdbsum/Generate.
html). A phylogenetic tree of bivalve lysozymes, based on the alignment of 68 residues within the lysozyme domain, was constructed with Seaview 4. 5. 4 software using the neighbor-joining (BioNJ) method with 1000 bootstrap resampling of the data set. Lyzozymes expressions: RNA extraction and qPCR. The mRNA expression of lysozymes paralogs was analysed by real-time PCR. Total RNA was extracted from mussel gills, digestive gland and mantle by using Tri-Reagent (Sigma) according to the manufacturer's instructions. Both quantity and quality of RNA were assessed via UV absorbance (OD260/280/230) using a Nanodrop ND-1000 spectrophotometer (Nanodrop Technologies, Delaware, USA). Two μg of total RNA were reverse transcripted using M-MLV reverse transcriptase (Promega), an anchor-oligo(dT) primer (5 0 -CGCTCTAGAACTAGTGGATCT-3 0 ) and random hexamers (Promega).
Characterisation and phylogenetic position of Ba-lysozymes among bivalve homologs The analysis of the EST database of Bathymodiolus azoricus revealed the existence of six paralogs of lysozymes, referred Ba-lysozymes 1 to 6. With the exception of Ba-lysozyme 5 that is incomplete in its C-terminal region, all Ba-lysozymes identified are full-length, and contain 111 to 201 residues (Fig This large range of pI was also observed in i-types lysozymes from the oyster Crassostrea virginica by Xue et al. [40]  who suggested that the varying pI values could be linked to different functions. Indeed, in 2007 Xue et al. [28]  stipulated that lysozymes that contain less proteasecutting sites and lower pI values could be associated with a digestive function as shown in other species  [41, 42]. In their mature form, the full-length Ba-lysozymes contain 12 to 20 cysteine residues, allowing the formation of 5 to 6 disulfide bridges, in accordance with the 3D structural models (Figure B in S1 File).
Acknowledgments We would like to thank the crew and pilot of the N/O Pourquoi pas? and the ROV Victor 6000 for their assistance and technical support as well as the chief scientist of the Momarsat 2013 cruise,  Jérôme Blandin. We also want to thank  Celine Wichlacz  and  Aurélie Tasiemski  from the  Université de Lille  for their help on lysozyme activity measurements and  Didier Jollivet  for his help on phylogeny. We are very grateful to the  Region Bretagne  and to  JST/CNRS program  for funding.
Acknowledgements The authors are grateful to  Professor Jean-Michel Vallat  ( Department of Neurology, University Hospital Dupuytren, Limoges, France ) for his invaluable opinion and advice on this review. The authors thank  Dr. Rosalind King  and  Professor Lionel Ginsberg  ( Departments of Neuropathology and Neurology, Royal Free Hospital, UK ) for kindly providing figures 2 and 3. Contributors YAR, DA and SA were involved in the literature review and drafting manuscript. PL was involved in the revising manuscript for important intellectual content.
First, we used Imaris software to quantify the volume of all voxels containing H2B-GFP fluorescence which is approximately the volume of the nucleus. Second, we used ImageJ software (NIH, Bethesda) to quantify TMRE intensity. We defined a region of interest (ROI) surrounding a cell of interest. We then sum the intensity of all pixels containing TMRE fluorescence in this ROI in all optical sections of each z-stack (on a 32 bits scale). We calculated the mean pixel intensity of TMRE fluorescence in this ROI for each time point. Finally, as we evidenced that TMRE outside of mitochondria produced a faint fluorescence which disappeared after the first hour of the experiment, we decided to analyze the changes of TMRE intensity relatively to its value reached at time 1 hour. We selected one optical section from each DIC z-stack for investigation of the morphological changes occurring within the whole cell or within the cytoplasm or the nucleus during AMD treatment.
Time-lapse imaging of cells following the induction of apoptosis by actinomycin D We investigated the timing of nuclear modifications relative to the loss of mitochondrial potential  [18]  during apoptosis induced by actinomycin D (AMD, 500 ng/mL) in HeLa H2B-GFP cells loaded with TMRE. We recorded Z-stacks of optical sections by two-photon excitation every five minutes, for 7. 15 hours after the addition of AMD for the simultaneous imaging of DIC contrast, of green (H2B-GFP) and red (TMRE) signals. After 3D processing of data recorded in many different fields of view and of different cell cultures, we found that 30 to 60% of cells shrunk between 3. 45 and 6. 30 h after the addition of AMD (S1 and S2 Movies and S1 Table ). In each single cell engaged in apoptosis, we quantified both the relative intensity of the TMRE signal in mitochondria and the relative nuclear volume ( Movie) showed that active mitochondria constituted a 3D network of filaments.
Acknowledgements We wish to thank the  French Embassy in the USA  for the Chateaubriand Fellowship as well as the  National Science Foundation Partnership for International Research and Education (PIRE)  grant ( NSF   OISE-0968313 ). We are grateful to  Thomas Bonometti  for many stimulating ideas and comments on the manuscript. The three anonymous reviewers are thanked for their excellent and intuitive comments which greatly improved the quality of the paper.
Introduction The World Digital Magnetic Anomaly Map (WDMAM) task force is part of the working group V-mod of the International Association of Geomagnetism and Aeronomy (IAGA). It was formed in 2003 and aims at collecting aeromagnetic and marine data worldwide to provide the scientific community with a compilation of these data on a global, 5-km cell size, grid. The first version of the WDMAM was released in 2007  (Korhonen et al. 2007 ). Several groups proposed candidates for this first version of the map (e. g. Hamoudi et al. 2007; Maus et al. 2007) , not all associated with a publication, but each with its own way of processing and merging the same data set. None of the candidates was significantly better than the others, and the final map was built by merging and reprocessing several of the candidates.
Marine data sets Marine magnetic data acquired by a variety of oceanographic institutions and ships worldwide are gathered by the World Data Service (WDS) for Geophysics operated by the National Oceanic and Atmospheric Administration (NOAA), Boulder, CO, USA (see http://www. ngdc. noaa. gov/mgg/geodas/trackline. html). These data have been carefully reprocessed by  Quesnel et al. (2009) , who performed extensive data cleaning, removal of the core and external fields using the comprehensive model CM4  (Sabaka et al. 2004) , and line levelling. The data set produced by these authors  (Quesnel et al. 2009 ) has been the base of the WDMAM version 1  (Korhonen et al. 2007 ) over the oceans. We use the same data set, complemented by additional marine data made available by NOAA between 2006 and 2010 and processed in the same way  (Takemi Ishihara and Manuel Catalan, personal communication, 2011) , as the base of the WDMAM version 2 over the oceans.
Western part of the Indian grid that was constructed from ground stations has not been considered in this version. Northern India is not covered by the data. A data set has been recently made available over Afghanistan, but it is not included yet in this version of the grid. There were several versions for Russian data sets that have been tested. We used the most recent. Also, the fifth version of the Australian compilation  (Milligan et al. 2010 ) has been preferred to previous version. Finally, we used a recently revised version of the North American compilation  (Ravat et al. 2009 ). In the first version of the WDMAM, the compilation of  Wonik et al. (1992)  covered most of Europe. Unfortunately, the datum associated with this compilation is unknown, resulting in an erroneous location of the anomaly patterns.
We used as little as possible this compilation in the new version of the map. Instead, we collected the national compilation and rebuilt a grid over Europe. In particular, over Western Europe, we used national grids for Portugal, Spain, France, Italy, Austria, Germany and UK. As for the first version of the WDMAM candidates  (Hamoudi et al. 2007; Maus et al. 2007) , three data sets of low resolution were added to fill the most important data gaps before constructing the final grid (See Getech data setindex = 46). In the remaining area where no data were available, the gaps have been filled by synthetic data estimated from the lithospheric field model GRIMM_L120  (Lesur et al. 2013)  derived from satellite data. The processing technique applied on individual data set is the same as for the candidate  (Hamoudi et al.
For example, the data set with the highest preference order is the marine data set (index = 11), not because of its quality but simply because marine data are given at sea level, whereas other data compilations are upwardly continued to 5-km altitude. Similarly, the Australian data set, which is known for its homogeneity and quality, has a low preference order (index = 37), but the data set remains unmodified because it is isolated from other data compilations. The permitted overlaps between data sets is typically 5 cells of the final grid (i. e. 25 km); if the overlap is larger than 5 cells, the data with lower priority order are cutout. Exceptions to this 5-cell rules are the marine data, the marine model data and the long wavelength synthetic data derived from the GRIMM_L120 magnetic model.
Long wavelength handling When compiling a magnetic data set of national extent, scientists try to handle properly the longest magnetic anomaly wavelengths. However, it is practically impossible to account for the anomalies of neighbouring countries, and therefore the long wavelengths of a merged grid of several aeromagnetic and marine data sets are necessarily wrong. In the WDMAM compilation, we use a geomagnetic lithospheric model derived from satellite data to correct for the wavelengths corresponding to SH degrees 16 to 100. Larger wavelengths, for SH degrees 1 to 15, correspond to the core field. They are filtered out. For wavelengths shorter than SH degree 100, no accurate information is available from the satellite data and we have to rely exclusively on aeromagnetic and marine data even if we have little trust on their long wavelength content.
These two SH expansions are then truncated to SH degree 100 and their differences calculated. Finally, these differences are subtracted from the merged grid, giving the final candidate grid for the WDMAM. It shall be noted that the SH expansion of the anomaly field of a lithospheric model is not the SH expansion of this model. In particular, these two SH expansions do not have the same SH degree bounds. As a result, the long wavelengths of the WDMAM data are different from the long wavelengths of the magnetic field model GRIMM_L120. They are also different from the long wavelengths of the anomaly field calculated from the GRIMM_L120 model truncated to SH degree 100.
High-resolution lithospheric magnetic field model The WDMAM is a grid of 25,927,200 total intensity anomaly values, that in principle should allow to build a magnetic field model to a maximum SH degree larger than 5000. However, there is very little interest in building such a model given the limited accuracy of the grid. We nonetheless built a model to SH degree 800 in order to study the spectral content of the grid and also its local variations. To build this model, we first reduced the size of the data set to a 0. 2 × 0. 2 degree cell size grid using the GMT function blockmedian applied on the compilation. We are therefore left with a grid of 1,620,000 total intensity anomaly values. Each data point position was evaluated in geocentric spherical coordinates system accounting for the difference in altitude between marine and continental data.
Catalan (personal communication). Second, the synthetic magnetic anomaly model now takes into account the plate tectonic evolution to simulate the remanent magnetisation vector direction, whereas this vector was parallel to the present-day field in the previous version. Third and most noticeable is the adjustment of the synthetic magnetic anomaly model to the data, performed by comparing the standard deviation of synthetic and observed anomalies on sliding windows along the real ship tracks. This adjustment leads by construction to much smoother transitions between the oceanic areas where sufficient data are available to define a grid and those where the model has to be used instead. This makes the WDMAM version 2 map more realistic in such areas. It should be noted that, because various processing applied by different data compilations result in considerable and variable smoothing of the seafloor spreading magnetic anomalies, we gave precedence to the original data and the synthetic anomalies adjusted on these original data over these compilations.
This includes the oceanic plateaus, aseismic ridges, and the Cretaceous and so-called Jurassic Quiet Zones where the model generates no magnetic anomaly. In the areas where both marine data and synthetic data are unavailable, the gaps are filled  with anomaly values obtained from a magnetic field models derived from satellite data. A final advantage of our approach is the derivation of a global grid of adjustment factors derived from the comparison of observed and synthetic anomalies. Once corrected for the constant magnetisation used to compute the synthetic anomalies, this adjustment factor grid has the dimension of an equivalent magnetisation. The derivation of such a global distribution of equivalent magnetisation, computed with a more realistic source geometry considering the bathymetry and sediment thickness, has been derived and is described elsewhere  (Dyment et al.
Conclusion In this paper, we have described the derivation of the second version of the World Digital Magnetic Anomaly Map (WDMAM). The approach we followed differs in different aspects from the first version of the map. First, we tried to modify as little as possible the data sets and compilations provided for building this map. In particular, we always limit to a few kilometres the overlap between adjacent data sets. Second, we give the highest priority to the marine data, and therefore they are preferred to national grids that extend over oceans. This has two consequences: (1) the WDMAM over the marine area has a reference altitude of 0 km above the WGS84-this altitude was 5 km in the first version of the map, (2) All data over marine area have been interpolated in a consistent way. Third, we have filled the gap over marine area with a fully revised model of the signal generated by the oceanic floor magnetisation.
The former and latter anomaly values are the quantities that have been added and subtracted, respectively, to the collected magnetic anomaly data so that the long wavelength content of the map is as close as possible from the true lithospheric anomaly field. With these provided anomaly values, the long wavelength content of the map can be easily corrected again by the user. Another useful product is a spherical harmonic model of the anomaly map up to degree 800. The maximum degree is not so important since, as it has been shown, in numerous areas, there is insufficient data to build an accurate model up to this wavelength. This model can nonetheless be used, e. g. to control the long wavelength content of a new data set acquired on a limited area anywhere on Earth. The analysis of the WDMAM and the associated field model confirm the weakness and smoothness of the lithospheric magnetic field over Europe and possibly over Northern Africa.
Other continental area may present a weak field, but this is likely due to the weakness of the inducing main field in these area. Finally, we insist on the fact that building this compilation is only a small contribution compared to the enormous amount of work that was involved in collecting and processing aeromagnetic and marine data. The quality of the final compilation depends mainly on the availability of these data. Since the official release of the WDMAM during the IUGG-2015, several new compilations have been offered to the WDMAM task force. These will be incorporated soon in a new version of the WDMAM compilation: namely WDMAM v2. 1. This and following versions 2. x will be computed and distributed as new data become available. The same methods described in this paper will be used, until the need for methodological improvements is required.
Acknowledgements WDMAM data contributors (see Table 1) and evaluators, together with members of the WDMAM task force, are fully acknowledged for their work and constant support. We thank also the reviewers of this paper. VL started his contribution to this work while he was at GFZ; further, a significant part of the data processing has been done while MH was a visiting scientist in GFZ and in IPGP. This work was partly funded by the  Centre National des Etudes Spatiales (CNES)  within the context of the project of the " Travaux préparatoires et exploitation de la mission Swarm ". This is IPGP contribution 3717.
Acknowledgements. The data used for simulations in this work were collected during the project " Concordiasi ," which is supported by the following agencies:  Météo-France ,  CNES ,  CNRS/INSU ,  NSF ,  NCAR ,  University of Wyoming, Purdue University, University of Colorado, Alfred Wegener Institute, Met Office , and  ECMWF. Concordiasi also benefited from the logistic and financial support of the  Institut polaire français Paul Emile Victor (IPEV) ,  Programma Nazionale di Ricerche in Antartide (PNRA) ,  United States Antarctic Program (USAP) ,  British Antarctic Survey (BAS) , and from measurements by the  Baseline Surface Radiation Network (BSRN) at Concordia. Tra Dinh  acknowledges support from the  NOAA Climate and Global Change Postdoctoral Fellowship Program  and  NSF  grant  AGS-1417659.
This collaborative research emerged from  Tra Dinh 's visit to the  Laboratoire de Météorologie Dynamique , which was supported by the  "Tropical Cirrus" project of École Polytechnique's "Chaire pour le Développement Durable". Aurélien Podglajen ,  Albert Hertzog ,  Bernard Legras , and  Riwal Plougonven  received support from the  ANR  project  "Stradyvarius"  ( ANR-13-BS06-0011-01 ). Additional support was provided by the  EU   7th Framework Program  under grant  603557  (StratoClim). The authors would like to thank three anonymous reviewers and  Martina Krämer ,  Bernd Kärcher , and  Daniel Knopf  for helpful questions and comments that led to significant improvements of this work. Edited by:  M. Krämer.
Of 47 subjects, 43 (91. 5%) subjects had JE neutralizing antibody titers ≥10 (reciprocal serum dilution) against the homologous strain before JE-CV boost; all were seroprotected up to year 5 after the JE-CV boost. Baseline WT seroprotection ranged between 78. 7% and 87. 2%; all subjects were seroprotected against the 4 WT strains at 28 days and 6 months; year 5 seroprotection ranged between 95. 7% and 97. 9%. Similar rates of protection against 3 additional WT isolates were observed at year 5. Conclusions. The long-term immune responses induced after a JE-CV booster dose in toddlers were able to neutralize WT viruses from various genotypes circulating in Southeast Asia and India. Clinical Trials Registration. NCT00621764.