dataesr/scientific-paragraphs-categorization huggingface dataset:
Only the differentially expressed probes showing a significant variation (False Discovery Rate (FDR) ,1. 5%; Fold change (FC). 1. 5) have been selected. A more systematic, functional interpretation of significant genes was then obtained through enrichment analysis using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) software  [32]. ''KEGG Pathway'', ''Biological process'' (BP), ''Molecular function'' (MF) and ''Cellular component'' (CC) annotation categories were used by setting the gene count equal to 3 and the ease value equal to 0. 1. Because DAVID database contains functional annotation data for a limited number of species, it was necessary to link the V. decussata transcripts with sequence identifiers that could be recognized in DAVID. This process was accomplished using UniProtKB/SwissProt feature identifiers corresponding to each probe.
Principal component analysis A Principal Component Analysis (PCA) was applied to the selected gene expression dataset (31,862 probes, see Methods) for the 15 oocytes samples. As shown in Figure  1 , a distinct clustering of three different groups of samples was observed. The group of spawned oocytes was clearly separated into 2 sub-groups, which also differ from their D larval rates, defined and already employed successfully as a good proxy of oocyte quality  [19]. Therefore we then considered three groups for further analysis: stripped oocytes (STR), spawned oocytes with low hatching rate (LHR, 5%-21% of D-larval rate) and spawned oocytes with medium hatching rate (MHR, 40%-47% of D-larval rate). STR, LHR and MHR eggs were clearly separated along the Principal Component 1 (x axis), which explained 29% of the variation.
The expression profiles were also separated along the Principal Component 2 (y axis, 11% of the variation), but in this case STR and LHR oocytes did not show a marked divergence in expression patterns, while the separation of MHR eggs was remarkable. Notably, the expression patterns of the five stripped oocytes appeared to be similar, while spawned eggs of the two groups seemed less homogeneous. Finally, the PCA outcome allowed the identification of the probes which maximally contributed to the PC1 or PC2 variance. Among the 1,593 probes (5% out of the total amount of probes) with the highest PC1 eigenvector values, 990 were annotated against the UniProtKB/SwissProt database and represented 852 unique genes. With regards to the PC2, 925 out of the 1,593 probes with the highest load were annotated and a total of 826 unique genes were recovered.
A comparison between significant probes in the two analyses allowed us the identification of a set of 439 transcripts (1. 4% of all probes) that were differentially expressed between stripped and spawned oocytes, irrespective of Dlarval rate. Except for one probe (lacking putative annotation), which showed an opposite trend of expression in the two comparisons (expression higher in STR than in LHR and lower in STR than in MHR), all significant variations reported for the remaining 438 probes had concordant direction (Figure  2 ). A putative UniProtKB/SwissProt accession ID was obtained for 235 out of 439 probes, corresponding to 198 unique genes (see Table  S2 ), which were differentially expressed between the two oocyte conditions (stripped and spawned). Among the shared Differentially Expressed Genes (DEGs), important transcripts encoding regulators of sex steroids synthesis and activity, such as a progestin and adipoQ receptor family member 3 (PAQR3) and steroid 17-alpha-hydroxylase/17,20 lyase (CYP450-C17), were expressed at a higher level in the stripped oocytes.
Discussion Gene expression analysis and evaluation of DEGs comparing oocytes before and after spawning pointed out significant results and provided a first overview on transcriptome changes that are correlated with stripped oocytes infertility. The PCA applied to the selected gene expression dataset clearly emphasized three different clusters for the 15 oocyte samples, stripped and spawned oocytes, this latter being divided into two sub-groups. When looking at these two sub-groups, the subsequent D larval rates obtained by fertilization of the remaining oocytes for each female that spawned, appeared clearly different, less than 21% for the subgroup named low hatching rate (LHR) and higher than 40% for the other one, named with medium hatching rate (MHR). These limits of D larval rates for defining oocyte quality are similar to those already considered in a proteomicbased analysis of oocyte quality in the Pacific oyster C.
Supporting Information Table  S1. Principal Component 1 and Principal Component 2 highest eigenvector values. The table lists the 1,593 probes (5% out of the total amount of probes) with the highest eigenvector values in both PC1 and PC2. The eigenvector values and the putative annotation against UniProtKB/SwissProt database are also reported. doi:10. 1371/journal. pone. 0113925. s001 (XLSX) Table  S2. Significance Analysis of Microarray (SAM). List of annotated probes that were differentially expressed (FDR ,1. 5%; FC. 1. 5) in both the two comparisons LHR vs STR oocytes and MHR vs STR oocytes with the corresponding fold change value. Shared significant probes between the two comparisons were also summarized. Colors identify transcripts more abundant in spawned (green) and stripped oocytes (red).
Data set Data on the foraging behaviour of chick-rearing Adelie penguins were collected from Dec 21 to Jan 7 each year from 1997/1998 to 2009/2010 at Cape Crozier (77u279S, 169u129E; ,164 000 pairs; Fig. 1 ) using an automated weighbridge  [59]  (Fig. 2 ). This system recorded the date, time, direction, body mass and identification for each crossing of 22 to 74 breeding penguins per year, implanted with a radio frequency identification (RFID) tag. Some were also banded on the left flipper  [60] , and the potential effect of banding on foraging efficiency was statistically taken into account by including the type of marking as a fixed effect in the full starting model. Over the 13 years of study, we collected data from a total of 229 individuals (22 to 74 each year), who performed 1,759 provisioning trips.
Each bird was followed within the breeding season, and over multiple breeding seasons. On average, there was a total of 7. 7 foraging trips per individual, ranging from 1 to 42 trips (median: 6). Individual catch per unit effort (CPUE), an index of foraging efficiency  [21] , was calculated by dividing grams of food returned by the time required to collect it (minutes away). The quantity of food returned was calculated from weighbridge data as the mass that an individual parent weighed when entering the nesting area after a trip at sea minus its mass when it left the nesting area for a new foraging trip. This is a measure of how much food a parent brought back to the colony and includes the food both delivered to chicks and that digested by the parent while attending the nest. Birds were primarily sexed by copulatory position, but we also employed a combination of size (especially head and bill) and behavior cues (e.
g. timing of arrival to the colony) to discriminate sexes  [34]. As we were interested in the direct effect of SIC on foraging behaviour, daily SIC data derived from passive microwave imagery  [61]  were extracted for the penguin foraging area determined by telemetry  [44] between 1997/1998 and 2008/2009 (Fig. 1 ). No telemetry data were collected in 2009/2010. Therefore, each bird was associated with a sex, a type of marking (RFID tag only or RFID tag and band) and a number of years since marking. Each trip of a given bird was associated with a year, 1997-2010, the presence or absence of giant icebergs (present between 2001/2002 and 2005/2006 austral summers), a day within the year, a CPUE and a measure of the mean SIC within the foraging area during the trip. The dataset used for this paper is deposited at the California Avian Data Center, available at http://data.
Financial support was provided by  NSF  grants  OPP 9526865 ,  9814882 ,  0125608 ,  0440643  and  0944411. DG is funded by  CNRS  and the  French Polar Institut (IPEV)  within the  ADACLIM program  (grant  388 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Acknowledgements. This work was supported by the  Ligue Nationale Contre le Cancer , the  Region Nord Pas de Calais , and the  SIRIC OncoLille , grant number  INCa-DGOS-Inserm 6041aa. We thank  Francis Ka-Ming Chan  for providing the RIP3 mutant cDNAs,  Yousef Abu-Amer  for the IKKb mutants,  Isabelle Vanseuningen  for the kB-luc reporter, and  Inder Verma  for the IkBaM mutant.
Anisotropic swelling pressure experimental setup The experimental setup is presented in Fig. 2. The compacted sample is placed between two porous stones and filter papers. On top, a piston is fixed with a screw to prevent any axial displacement upon swelling. During the test, the sample is saturated from the bottom with synthetic water having the same chemical composition as the pore water from the Bure underground research laboratory (Andra, see details in Table  1 ). A total pressure sensor is mounted on the cell inner wall to measure the radial swelling pressure. A force transducer is mounted axially in order to measure the axial force generated by the soil swelling. All data are recorded by a data logger. A series of tests have been performed using two cells, with samples being compacted either inside (In-cell) or outside (Outcell) the cell.
, 2005). The scans presented here were carried out with the mCT of the Navier laboratory (Ecole des Ponts ParisTech), an "Ultratom" device specifically designed and manufactured by RXsolutions (France). Images were reconstructed using the software Xact-reconstruction developed by RXsolutions. The final 3D image is a 16 bit type with a size of 1840 Â 1840 Â 386 voxels. The image analysis and treatment were then carried out using ImageJ, a public domain Java image processing program  (Rasband, 1997e2012). Note that the image was first converted to 8 bits for size reasons. Two scanned samples are shown in this paper. The first one was at the initial state, compacted like an Out-cell sample with a diameter of 50 mm and a height of 10 mm and with a sand content of 35%. Its dry density is 1. 8 Mg/m 3 (bentonite dry density r db of 1.
Further investigation of the microstructure was carried out using the "ImageJ" image analysis software. The first step consisted in reducing the noise in the image by applying a 3D median filter with a 1 pixel radius. Then, a segmentation of the image was performed in order to isolate pores from the other phases. The grey threshold value used to segment the image was found after analysing the histogram and using the "mixture modelling" function that gave the value of 73 as the grey threshold value separating pores from the other phases. Fig. 5  shows an image at different stages before segmentation: initial state, after applying a 3D median filter, while applying 73 as a threshold value and finally the segmented image. The porosity was calculated from the histogram of the segmented image by dividing the number of black voxels by the total number of voxels.
Bioinformatic analyses BLAST search was performed using the NCBI-BLASTp (http://blast. ncbi. nlm. nih. gov/Blast. cgi) with proteomes of M. ulcerans and M. marinum as target and desired protein sequence as query. The sequences of M. ulcerans STPKs were extracted using NCBI. These sequences were used for multiple sequence alignments, performed using ClustalW (http://www. ebi. ac. uk/ Tools/msa/clustalw2). Phylogenetic analysis was performed using the sequences of STPKs in PHYLIP and phylogenetic tree was constructed  [22]. The presence of conserved domains was detected by NCBI-conserved domain database (http://www. ncbi. nlm. nih. gov/Structure/cdd/cdd. shtml).
Homology modeling To generate the structure of PknQ, intracellular kinase domain of M. tuberculosis PknB (PDB ID: 1MRU) that shows 42% identity with the PknQ sequence, was chosen as template. We focused on the predicted catalytic domain of PknQ (1 to 280 aa). The threedimensional models for PknQ were generated using MODELLER version 9v1. General features were evaluated on the basis of the MODELLER's energy and DOPE scores while detailed reliability indices were obtained by the PROCHECK program. The PROSA Z-score was calculated using PROSA-II. Best models were chosen and further refinements were carried out. Disordered activation loop region was identified and loop refinement procedure was applied using the automatic loop refinement method provided in MODELLER 9v1 auto-model class protocol.
In order to use the maximum benefits of sequence identities and to model the maximum part of sequence contacting FHA domain, multi-template approach provided by MODELLER 9v1 was utilized and the two templates of Rv0020c FHA domain (PDB ID: 2LC1, 3PO8) were used to predict the three dimensional homology model of MupFHA. The 3D models for native FHA domain and mutants were generated, on the basis of previously generated structures of Rv0020c and pThr peptide  [24, 25]. The templates were pair-wise structurally aligned. Further models were built and validated as described for PknQ homology modeling.
1 ps and 2 ps, respectively. The production run was performed with suitable parameters for 10 ns at a temperature and pressure of 300 K and 1 atm, respectively. Coordinate sampling was performed at every 2 fs time interval. Bond-lengths were constrained using the Linear Constraint Solver (LINCS) algorithm  [29]. Various utilities of GROMACS-4. 5. 5 package were used for detailed analysis of MD trajectories. All of the Gromacs MD simulations were run in the HPC-Supercomputer facility (CSIR-IGIB, India) on 32 Cores at 11. 4 ns/day maximum performance speed.
In silico analysis of M. ulcerans STPKs To identify the total number of STPKs present in M. ulcerans, we performed a BLASTp search using the sequence of the catalytic domain of M. tuberculosis PknB (1-331 aa), corresponding to the most conserved mycobacterial STPK  [37]. Using this approach we identified 13 distinct ORFs encoding for STPKs, of which twelve are encoded on the chromosome and one (Mup011 or PknQ) is encoded on the virulence-associated plasmid pMUM001 (Fig. 1A ). Analysis of the M. ulcerans STPKs showed that they possess unique kinase modules that are divergent from its close homolog, M. marinum. Out of the 24 putative STPK encoding genes present in M. marinum, only 13 are retained in M. ulcerans. This finding suggests that although M. ulcerans has evolved from M. marinum, it has retained only those STPKs that are necessary for its survival in humans while excluding those that may confer adaptation to M.
marinum, which has ten FHA domain containing proteins, including the one encoded by the pMUM003 plasmid in M. marinum DL240490). A domain analysis and homology search showed that all of the proteins have functional homologs in M. tuberculosis except MupFHA (Table  2 ). To further explain the relationships of MupFHA with other FHA domain homologs in other bacteria that carry a megaplasmid, for example non-pathogenic bacteria Mesorhizobium cicero, we performed BLASTp search with MupFHA sequence in the M. cicero database. There are two FHA domain containing proteins encoded by the M. cicero megaplasmid. However, the two proteins named Mesci_6382 and Mesci_6368 are annotated as type-VI secretion system FHA domain proteins and thus, are different from MupFHA. Similarly, in another pathogenic bacterium, Yersinia pestis, the virulence-associated plasmid pLB1 encodes an FHA domain protein YscD that is a part of the type-III secretion apparatus.
Acknowledgments We thank  Timothy P. Stinear  ( Department of Microbiology and Immunology, University of Melbourne, Parkville, Victoria, Australia ) for valuable suggestions and providing BAC clones of pMUM001 DNA. We are grateful to  Prof. Bouke de Jong  ( Institute of Tropical Medicine, Belgium ) for her inputs and suggestions for the project. We thank  Dr. Souvik Maiti  ( CSIR-IGIB, India ) for providing the random unphosphorylated peptide. We also thank  Dr. Christopher Brooks  ( Bioscience Editing Solutions services ) for help in editing the manuscript.
Methods In January 2012, we reviewed articles published in English or French from 1965 to January 1, 2012 and listed in the Medline database. The terms ''Southeastern Asia/epidemiology,'' ''Encephalitis,'' ''Arboviral encephalitis,'' ''Encephalitis, viruses,'' and ''Anti-N-Methyl-D-Aspartate Receptor Encephalitis'' were used alone and in combination. A case of acute encephalitis syndrome was defined as any person presenting a fever with neurological signs (altered mental status AND/OR motor deficit AND/OR sensory deficit AND/OR seizures of new onset, excluding simple febrile seizures) of sudden onset (fewer than seven days). Meningoencephalitis cases present the abovementioned signs plus meningism (nuchal rigidity). References on human and animal health were taken into consideration. These were consulted and extracted using the Institut Pasteur's distance bibliographical resources or HINARI (http://hinari-gw.
Encephalitis, however, is about individuals, families, and communities. Epidemiologists would make the irreplaceable laboratory findings more accurate, representative, and interpretable through rigorous selection and documentation of patients. They would also add further value to these findings by helping identify hotspots, investigate trends and outbreaks, assess sequelae or associated risk factors, and generate a database and map documenting which pathogen was identified where. Finally, ecoepidemiological investigations of what are often zoonotic pathogens using a one-health approach would provide insights on pathogens' circulation and prevention on a larger scale. Such studies and collaborative projects are urgently needed to improve human capacity, diagnostic techniques, and strategies, and to further document the macroepidemiology of encephalitis as well as the microepidemiology of certain pathogens, whether known or yet to be discovered, in the Mekong region.
DATA ACQUISITION A N D P RO C E S S I N G The ∼250-km-long MCS profile traversing the Kermadec subduction system south of the LRSC collision zone was acquired from the 2011 April 29 to May 1 as part of R/V Sonne cruise SO215  (Peirce & Watts 2011) , which followed on from the Tonga Thrust earthquake Asperity at Louisville Ridge (TOTAL) project  (Grevemeyer & Flüh 2008). This MCS line, Profile D in  Peirce & Watts (2011) , was located to study 'background' processes and structures associated with the subduction of Pacific oceanic lithosphere uninfluenced by LRSC subduction. The profile runs perpendicular to the trench-arc system, from ∼50 km to the east of the trench to 35 km west of the present-day Kermadec arc (Fig. 2 ). Gravity, magnetic, Parasound and multibeam bathymetry data were acquired contemporaneously.
The seismic source consisted of a 10 G-gun array, with a combined volume of 4400 in 3 (68 l), which was towed at a depth of 7. 5 m and fired at a pressure of 2400 psi (170 bar). Shots were fired every 30 s which, at the ship speed of ∼4. 5 kn, resulted in an ∼70 m interval between shots. The acquisition system also included a 3 km multichannel streamer, comprising 240 channels at 12. 5 m group interval, towed at 10 m depth. The data set collected consists of 29 s long traces, recorded at a sampling rate of 1 ms. Each common midpoint (CMP), separated by 6. 25 m, has a maximum theoretical fold of ∼20. Initial analysis of the MCS data indicated a low signal-to-noise ratio, as might be expected of a subduction zone where the seabed is rough and scattering, and the subsurface geology is complex.
The application of a post-stack, constant velocity (1500 m s -1 ) Kirchhoff migration reduced the appearance of high amplitude diffraction tails generated by the rough seabed. For display purposes, a mute was applied before the primary seabed reflection, and a long time-gate (2000 ms) automatic gain control (AGC) equalized reflection amplitudes along each trace. The MCS data were not time-to-depth converted due to a lack of actual velocity control other than stacking velocities derived from velocity analysis. High-resolution, shallow subseabed imaging data, collected by the shipboard Atlas Parasound P70, were recorded in ∼800 ms windows around the seabed. The recording delay was determined by the swath-derived seabed depth, and stored in the SEG-Y headers. Application of a bandpass filter (2.
0-2. 5-5. 5-6. 0 kHz) around the dominant signal frequency of 4 kHz reduced noise, and an AGC of 200 ms improved the appearance for display. A shipboard SIMRAD EM120 multibeam echo sounding system acquired swath bathymetry data throughout the cruise. Processing of the raw data in MB-System included the flagging of data that had deviated from the local median depth by more than 100 m between beams to enable the removal of bathymetric artefacts introduced during acquisition  (Caress & Chayes 1996). The cleaned swath bathymetry and backscatter amplitude data were gridded at 50 m intervals before being merged with existing ship-track data to produce an updated, but still sparse, high-resolution map of the seafloor (Fig. 2 ). These data were then combined with the General Bathymetric Chart of the Oceans  (GEBCO-IOC et al.
A C K N O W L E D G E M E N T S We would like to thank all those involved in the data acquisition for the R/V Sonne cruise SO215, including the captain, crew and seagoing technicians from the U. K. 's Natural Environment Research Council (NERC) National Marine Facility Sea Systems and Exploration Electronics Ltd. We are grateful to the two anonymous reviewers for their thoughtful and helpful comments on this paper. The MCS data were processed and plotted using Claritas TM. All other figures were generated with the Generic Mapping Tools (Wessel & Smith 1998). This research was funded by the NERC (grant reference NE/F004273/1) in collaboration with the TOTAL project  (Peirce & Watts 2011). All data from cruise SO215 are archived at the NERC's British Oceanographic Data Centre (BODC), and the final submitted version of this manuscript is available through Durham Research Online (dro.
A total of 674 genes were mutated. We classified the products of the nonsynonymous genes in COG categories. Forty-one proteins were classified in category J, 6 in K, 37 in L, 5 in D, 14 in V, 12 in T, 46 in M, 8 in U, 21 in O, 24 in C, 27 in G, 33 in E, 9 in F, 27 in H, 14 in I, 16 in P, 8 in Q, 58 in R, 42 in S, 34 belonged to multiple classes, and 192 were not annotated. Statistical tests showed that for categories V and M, the proportions of mutated proteins were higher than for other protein categories (14/20 versus 660/1,878; bilateral chi-square test, P ϭ 0. 001; and 46/104 versus 628/1,794; P ϭ 0. 056, respectively). Nucleotide sequence accession numbers. Strain Cb196_ Saudi_Arabia has been deposited in GenBank under the project accession no. PRJEB7092, and the accession numbers are CCXO01000001 to CCXO01000003.
Patients included in the subpopulation analyses were required to have non-missing baseline BDI and post-baseline TDI assessments. Treatment comparisons on continuous variables were performed at week 52 (last observation carried forward [LOCF]) using analysis of covariance with terms for treatment group, BDI, age, smoking status, sex, ICS pretreatment, country/region, and study. Treatment comparisons on dichotomous/categorical variables were performed using a Cochran-Mantel-Haenszel test (pooled data were stratified by study) at week 52 (LOCF) and weeks 4, 8, 12, 20, 28, 36, 44, and 52 (observed cases). Statistical significance was assessed using an alpha level of 0. 05.