dataesr/scientific-paragraphs-categorization huggingface dataset:
We also would like to thank the  Center National de Genotypage, Evry, France  for genotyping the ProtecT samples. Financial Support: The ProtecT study is funded by the  U. K. Health Technology Assessment (HTA)  Programme of the  NIH Research  ( HTA 96/20/99 ;  ISRCTN20141297 ). D. W. Knipe is funded by the  Wellcome Trust   4-year studentship  ( WT099874MA ). D. M. Evans ,  J. P. Kemp ,  G. Davey-Smith , and  R. M. Martin  work in an MRC Unit that is supported by the  UK Medical Research Council  ( MC_UU_12013/1-9 ) and the  University of Bristol. D. F. Easton  is supported by a  Cancer Research UK  Grant ( C1287/A10118 ). R. A. Eeles and Z. Kote-Jarai are supported by  Cancer Research UK  Grant ( C5047/A7357 ) and support from the  NIHR  to the  Biomedical Research Centre at The Institute of Cancer Research and Royal Marsden NHS Foundation Trust.
75 mg/mL RNase A. Cell cycle analysis was performed using a BD LSR II flow cytometer. 10,000 events per sample were acquired and results were analyzed using using Flowing Software 2. 5. 1 (Turku Centre for Biotechnology, University of Turku, Finland). For apoptosis assay, U87 cells were either left untreated (control) or treated for 72 h with Bevacizumab (0. 1 mg/mL) or SU1498 (10 mM) in triplicate wells. After trypsinization, apoptosis was assessed using the Annexin V-FITC Apoptosis Detection Kit (eBioscience, Paris, France) following the manufacturer's instructions. 5,000 events per sample were acquired on a BD LSR II flow cytometer. Results were analyzed using the Cyflogic sofware (Cyflo, Turku, Finland). For morphological studies, U87 cells were seeded in 24-well plates (0. 6610 6 cells/well), and treated for 48 hours with 0.
The loadings plot is showing the distribution of the corresponding variables responsible for the separation observed in the scores plot. PCA and OPLS were conducted using SIMCA-P12 (Umetrics) and in-house Matlab (Mathworks) code based on Trygg and Wold method  [24]. For metabolites considered as discriminant by the multivariate analysis, an univariate analysis of variance (ANOVA) was Figure  3. Effect of SU1498 and Bevacizumab on U87 cell proliferation. U87 cells were seeded in 24-well plates (30,000 cells/well) and were treated with different concentrations of SU1498 (from 1 mM to 30 mM) or Bevacizumab (from 10 ng/mL to 250 mg/mL). Viability was then assessed by a standard MTT assay. Bevacizumab has no significant impact on cell proliferation. SU1498 reduces cell proliferation with concentrations above 10 mM after a 72 h treatment, but no effect is seen at 24 hours.
Impact of SU1498 and Bevacizumab on U87 proliferation The effect of Bevacizumab and SU1498 on cell proliferation was then assessed. U87 cells were treated for 24 h and 72 h with different concentrations of Bevacizumab (10 ng/mL to 1 mg/mL) and SU1498 (1 mM to 30 mM). Bevacizumab had no significant impact on cell proliferation as assessed by a MTT Assay. SU1498 reduced cell proliferation with concentrations above 10 mM after a 72 h treatment, but no effect was seen at 24 hours (figure  3 ). Concentrations of 0. 1 mg/mL Bevacizumab and 10 mM SU1498 which are clinically relevant were selected for HRMAS experiments. Using these concentrations of Bevacizumab and SU1498, the doubling times of U87 cell population were 21. 1, 21. 5 and 26. 3 hours respectively for control, Bevacizumab-and SU1498treated cells as determined by growth curve analysis on a 72-hour incubation period (data not shown).
In this PCA, the first axis represents the direction of maximum variation of the data, which corresponds to 23. 1% of the whole variability. As shown on figure  7A , the first two directions are necessary to discriminate between SU1498 and other samples. Consequently, an OPLS model has been calculated to characterize the metabolomic effect of SU1498 on U87 cells. The score plot is presented in figure  7B. The predictive ability of the model (Q2Y) is 0. 87. The area under the curve (AUC) is 1. The corresponding loadings coefficients plot is represented in figure  8A. Using 2D experiments and HMDB database, the main metabolites modified by SU1498 treatment were identified as lipids (the CH = CH and CH = CHCH 2 CH = CH signals being the most impacted, with increases of 1130% and 504% respectively), and to a lesser extent, glycerophosphocholine (2 225%) and myoinositol (+88%) (figure  8B ).
Optical setup and imaging conditions Multiphoton imaging was performed using a custom-built scanning microscope providing several contrast modalities including two-photon excited fluorescence (2PEF), second-harmonic and third-harmonic generation (SHG, THG). The microscope incorporated a femtosecond Titanium:Sapphire (Ti:S) laser (920 nm, 80 MHz, Mira, Coherent Inc. , CA, USA) an optical parametric oscillator (1080-1180 nm, KTP-OPO, APE, Germany), galvanometric mirrors (GSI Lumonics, Poole, United Kingdom), a 0. 95 NA 20x water-immersion objective (XLUMPFL, Olympus, Tokyo, Japan), photomultiplier modules (Electron Tubes, Ruislip, United Kingdom), and lab-designed counting electronics. Scanning and acquisition were synchronized using lab-written Lab-VIEW software and a multichannel I/O board (PCI-6115, National Instruments, USA).
Data analysis N 1D-kymograph analysis for monitoring the rate of cellulariza- tion front invagination (CFI) was performed using ImageJ (W. Rasband, National Institutes of Health, Bethesda, MD) according to  [8]. Briefly, the XYT stacks of images of the relevant region of the embryo were projected along the X axis for improved signal-to-noise ratio, thereby obtaining YT images with Y axis in the direction of cellularization front progression showing the displacement of the CFI over time as a line whose slope is directly related to the CFI speed. This speed naturally varies during the progression of invagination (see figure  2 ), defining four phases with different rates  [54]. Imaging was performed during phases 3 and 4 of CFI, and subsequent gastrulation. We therefore determined from these kymographs the CFI speed during these two phases.
Observations Cassini ISS images used in this work come mainly from SATELLORB image sequences. These sequences form part of a campaign of observations of the small inner satellites of Saturn in progress throughout the Cassini tour, a campaign which by end-of-mission will have provided dense coverage between 2004 and 2017. In addition, we include observations from image sequences designed to study Saturn's F ring, many of which contain opportunistic sightings of Atlas, Prometheus and Pandora, in addition to Pan and Daphnis (though these satellites do not form part of the current work). Of the 2580 observations presented here, the majority (2567) used narrow angle camera (NAC) images while the remaining 13 came from wide-angle camera (WAC) images. Astrometric measurements were made using the Caviar software package.
Caviar (CAssini Visual Image Analysis Release) was developed at Queen Mary University of London for the analysis and astrometric reduction of Cassini ISS images and uses the IDL data language (Exelis Visual Information Solutions, Boulder, Colorado). Data reduction consisted of a correction to the camera pointing orientation together with a measurement of the pixel coordinates (line and sample) of the astrometric position of each satellite in a given image (we use the Cassini convention of referring to the x-coordinate as 'sample' and y-coordinate as 'line'). The camera pointing was corrected using the positions of reference stars extracted from the UCAC2 and Tycho-2 catalogues  (Zacharias et al. 2004; Høg et al. 2000). We obtain a typical pointing accuracy of 0. 1 pixel (0. 12357 arc sec) or less.
Lyapunov time of about 10 years. Future work will involve a detailed analytical study of this system. This work was supported by the  Science and Technology Facilities Council  (Grant No. ST/F007566/1 ) and Cooper and Murray are grateful to them for financial assistance. Murray is grateful to The  Leverhulme Trust  for the award of a Research Fellowship. The authors thank the members and associates of the Cassini ISS team, particularly  Kevin Beurle  for assisting in the design of the image sequences used in this work. Thanks also to  Bob Jacobson  for discussions. Cooper expresses gratitude to  University of Lille  1 for additional funding while he was an invited researcher at the  Lille Observatory. Renner thanks  Marc Fouchard  for discussions concerning numerical indicators of chaos. Cooper, Renner and Murray also thank their colleagues in the Encelade working group at the  IMCCE of the Paris Observatory  (http://www.
In vitro enzyme kinetic study First, TKI metabolites were identified (see Material and Method). For instance, the formation of 2 nilotinib oxidized metabolites, mass-to-charge ratio (m/z) at 546. 3, were revealed by LC-MS analysis. Five MS 2 product ions were similar in the fragmentation of nilotinib and these 2 metabolites (Figure  S1 ). Using GraphPad Prism software, the affinity (Km) and maximum velocity (Vmax) of metabolite production were calculated (Figure  S1  for nilotinib metabolites against nilotinib concentrations for CYP2J2 and 3A4). Table  2  shows the calculated Km values of CYP1A1, 1B1, 2J2 and 3A4 for the identified metabolites. In Table  2 , we can observe that, in contrast to CYP1A1, 1B1 and 2J2, CYP3A4 is capable of producing all identified metabolites, indicating low substrate specificity of CYP3A4 and high chemical variability of metabolites produced by this isozyme.
Therefore, the velocities of metabolite production were calculated in arbitrary units (arb) as LC-MS peak area/time. Using GraphPad Prism software version 4, a nonlinear regression analysis was performed for the determination of the kinetic constants: affinity, Km in mM, maximum velocity Vmax in arb and intrinsic clearance, IC ( = Vmax/Km) in arb. Km and Vmax constant determinations for all 4 CYP were performed the same day and analyzed at the same time.
Briefly, extracts of in vitro incubations were injected in our LC-MS system. Product ion scan and data dependant scan acquisitions were performed. The presence of $2 similar ions between metabolite and parent drug in MS 2 spectra as well as the increase of metabolite amounts over time confirmed the identification. TKI and their metabolites were detected by selective reaction monitoring (SRM). Ion transitions and collision energies are given in Figure  S2.
Acknowledgments The authors are grateful to  Agnes Mery ,  Sabine Lahrichi  and  Emmanuel Kottelat  for laboratory works,  Prof. Bernard Testa  and  Dr. Patrick Dansette  for fruitful comments, to  Dr Imad Hanna  for his fruitful discussion about CYP2J2 activity. We would like to thank the  Biobanque de Lausanne (BbdL)  and especially  Christine Currat ,  Cindy Roth  and  Laurence Chapatte  for their help in the submission of this research to the  Ethics Committee  and for tissue withdrawals.
In addition, the sulfurtransferase AtSufE1 contains a C-terminal BolA domain ( SufE1 BolA) that is only present in plant members  (10). From a previously established classification, these AtBolAs can be separated into two groups that contain either a conserved histidine (AtBolA1, AtBolA4, and SufE1 BolA; BolA_H group) or cysteine (AtBolA2; □ S This article contains supplemental Figs. S1-S3. The resonance assignments and relaxation data of AtBolA2 and the NMR chemical shift mapping of AtGrxS14-BolA2 are available at the Biological Magnetic Resonance Data Bank  (codes 19849 and 19850). The atomic coordinates and structure factors (codes 2MM9, 2MMA, 4PUG, and 4PUI) have been deposited in the Protein Data Bank (http://wwpdb. org/). 1 Supported by a grant overseen by ANR (Grant 2010BLAN1616) as part of the "Investissements d'Avenir" program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE).
Crystallization, Data Collection, Structure Determination, and Refinement-AtBolA1 and SufE1 BolA were crystallized by the microbatch under oil method at 278 K. 2 l of AtBolA1 (8. 25 mg/ml) were crystallized by mixing with 2. 1 l of crystallization solution containing a mixture of 18% PEG4000, 6% 2-propanol, 6% 2. 5 hexanediol, 4% xylitol, and 0. 07 M sodium acetate. 2 l of SufE1 BolA (8. 60 mg/ml) were crystallized by mix- ing with 1. 6 l of crystallization solution containing a mixture of 12% PEG20000, 6% ethylene glycol, 0. 02 M trimethylamine HCl, and 0. 1 M MES, pH 6. 5. They were flash-cooled in liquid nitrogen after a short soak in crystallization solution premixed with 20% glycerol as a cryoprotectant. X-ray diffraction experiments were performed at 100 K at beamline FIP-BM30A (European Synchrotron Radiation Facility, Grenoble, France) for AtBolA1 and at beamline PROXIMA 1 (SOLEIL, Saint-Aubin, France) for SufE1 BolA.
Their data sets at 2. 0 and 1. 7Å, respectively, were indexed and processed using XDS  (15)  and scaled and merged with Scala (16) from the CCP4 program package  (17). Both structures were solved by molecular replacement with Molrep (18) using the Mus musculus BolA1 coordinates (PDB entry 1V60) as first search model. Structures were refined using automatic calculations from PHENIX  (19)  with manual inspection and corrections using Coot (20) (Table  1 ). The validation of the crystal structures was performed with MolProbity  (21). The atomic coordinates for AtBolA1 (PDB entry 4PUG) and SufE1 BolA crystal (PDB entry 4PUI) structures are available at the Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank. NMR Analyses-The AtBolA2 NMR samples typically contained 0. 9 mM uniformly 15 N or 13 C, 15 N-labeled protein in 50 mM phosphate, pH 6.
0, 10% (v/v) D 2 O and 0. 02% (w/v) sodium azide under nitrogen atmosphere. All NMR experiments were carried out at 298 K on a Bruker spectrometer (600 MHz) equipped with a cryogenic probe. NMR data were processed with NMRPipe  (22)  and analyzed with NMRViewJ  (23). 1 H, 13 C, and 15 N assignment was obtained from 1 H, 15 N HSQC, 1 H, 15 N TOCSY (two-dimensional total correlation spectroscopy)-HSQC (mixing time Tm ϭ 80 ms), 1 H, 15 N NOESY-HSQC (Tm ϭ 100 ms and 150 ms), HNHA, HNHB, HNCA, HNCO, HN(CA)CO, and CBCA(CO)NH spectra. Aromatic side chains signals were assigned using COSY, TOCSY, and NOESY homonuclear experiments in D 2 O. 2248 distance restraints were derived from NOESY experiments. 150 dihedral restraints were obtained by DANGLE program  (24)  or from 3 J HNH␣ in CcpNmr  (25). 59 hydrogen bond restraints were inferred from slowly exchanging amide protons identified on a 1 H, 15 N HSQC recorded after redissolving lyophilized protein in D 2 O.
12 mM uniformly 15 N-labeled AtBolA2 (or AtGrxS14) samples. 0. 1, 0. 2, 0. 5, 1, and 2 eq of unlabeled AtGrxS14/GrxS17 (or AtBolA2/BolA1) were successively added using a 0. 4 mM stock sample. The apo-heterodimer AtGrxS14-BolA2 structure was obtained by docking using GRAMM-X Protein-Protein Docking Web Server v. 1. 2. 0 (28) coupled to an energy refinement using YAMBER force field from YASARA  (29). Residues exhibiting either chemical shift variations above 2 S. D. or large signal broadening were defined as interface residues in the docking protocol. The atomic coordinates for AtBolA2 NMR structures (PDB entry 2MM9) and the AtGrxS14-BolA2 apo-heterodimer model (2MMA) are available at the Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank. Intrinsic Fluorescence Properties of AtGrxS14 -Fluorescence was recorded with a Cary Eclipse spectrofluorometer (Agilent) with 1-cm path length cuvettes.
Prior to measurement, 10 M AtGrxS14 in Tris-HCl 30 mM pH 8. 0 buffer was incubated or not with varying concentrations of AtBolA1 ranging from 5 to 30 M at 25 °C for 10 min. The resulting fluorescence was recorded between 280 and 450 nm after excitation at 270 nm. For determining the apparent K d value, the decrease in AtGrxS14 fluorescence at 337 nm was plotted against AtBolA1 concentration using the one binding site hyperbola model (GraphPad Prism 6 software) and the following equation: fluorescence intensity ϭ B max * [AtBolA1]/(K d ϩ [AtBolA1]), where B max represents the fluorescence intensity of maximal binding. Sequence Analyses-All proteins of the BolA/YrbA family and all proteins that contain a BolA domain, i. e. around 12,000 sequences from Uniprot database, have been retrieved. After removing identical sequences but also transit peptides and protein regions that do not strictly belong to a BolA domain, 2444 sequences were aligned using MAFFT  (31).
e. with carbonyl group of Phe-119 (in 2), Met-122 (in 2-␣3 loop), and Ser-150 (in ␤3) and with Glu-155 carboxylate group (in ␣4) (Fig. 1B ). This last interaction probably governs ␣4-helix formation because it is the sole polar link between ␣4 and the rest of the protein. Accordingly, in Ehrlichia chaffeensis and Rickettsia prowazekii BolA structures (PDB entry 2KZ0 and 2MCQ, respectively), two examples where the arginine residue is replaced by a glutamine, the C-terminal end is shorter by seven residues, and ␣4 is missing. The Helix-turn-helix (HTH) Motif of BolAs Is Potentially Involved in DNA Binding-Currently, only bacterial BolA_H members have been shown to act as transcriptional regulators by binding to gene promoters  (34, 35) , whereas Uvi31ϩ, a BolA_H from Chlamydomonas reinhardtii, likely exhibits endonuclease activity  (36).
Acknowledgments We thank all members of the  Jackson laboratory  for help and support,  J. Forment  for discussions,  K. Dry  and  J. Travers  for discussions and critical reading of the manuscript. We thank  Rimma Belotserkovskaya  for the GFP-H2B U2OS cell line and  Sonja Heidorn  and  Mathew Garnett  ( Wellcome Trust Sanger Institute ) for providing us with the cancer cells used in the Lamin A/C expression screen. We thank  Imagif  and  Institut de Chimie des Substances Naturelles, centre de recherche CNRS de Gif-sur-Yvette, France , for proteomic analysis. Research in the Jackson laboratory is funded by  Cancer Research UK program  grant  C6/A11224 , the  European Research Council , and the  European Community Seventh Framework Programme  grant agreement no. HEALTH-F2-2010-259893  (DDR).
Core funding is provided by  CRUK  ( C6946/A14492 ) and the  Wellcome Trust  ( WT092096 ). S. P. J. receives his salary from the  University of Cambridge, UK , supplemented by  CRUK. D. L is funded by an  EMBO  Long-term fellowship ALTF 834-2011 and by a Project Grant from the  Medical Research Council ,  UK MR/L019116/1 , S. B. was funded by an  EMBO Long-Term  fellowship  ALTF 93-2010  and  Cancer Research UK. R. R. is supported by the  Centre National de la Recherche Scientifique. M. D. is supported by the  European Research Council  grant DDREAM. The data in this publication form part of the subject matter of a patent application number  1405991. 9.
The Genomicus web server (http://www. genomicus. biologie. ens. fr/genomicus) is a visualization tool allowing comparative genomics in four different phyla (Vertebrate, Fungi, Metazoan and Plants). It provides access to genomic information from extant species, as well as ancestral gene content and gene order for vertebrates and flowering plants. Here we present the new features available for vertebrate genome with a focus on new graphical tools. The interface to enter the database has been improved, two pairwise genome comparison tools are now available (KaryoView and MatrixView) and the multiple genome comparison tools (PhyloView and Align-View) propose three new kinds of representation and a more intuitive menu. These new developments have been implemented for Genomicus portal dedicated to vertebrates.
INTRODUCTION The rise of high-throughput DNA sequencing has revolutionized the field of genomics by creating an abundance of genome information in all domains of life. This volume and diversity of data enables ever more powerful evolutionary studies aimed at understanding past genomic events, and generally, to reconstruct the History of life, including the genomic characteristics of the common ancestors of ex-tant species. Advanced tools facilitating the intuitive manipulation of such complex data are thus needed, because the interpretation of specific evolutionary events often requires a broad evolutionary perspective that includes deep branches and many species. Toward this end, we continue to develop, maintain and improve the Genomicus server to offer innovative ways to access genomes data.
The Genomicus software is a dynamic visualization interface that enables comparisons between potentially unlimited numbers of genomes. It provides a comprehensive overview of genome organization between modern species and in the case of vertebrates and flowering plants, Genomicus also provides extensive information on reconstructed ancestral genomic organization. Users can intuitively query and navigate within and between genomes in a phylogenetic context to examine the evolution and the conservation of a specific locus in a species of interest. Navigation in Genomicus can be performed in three dimensions: linearly along the axes and the position of chromosomal genes, transversally between different species and chronologically along an evolutionary axis. For 4 years now, Genomicus is a web server that facilitates comparative genomics projects across a broad phylogenetic range.
Data sources All of the data about extant genes that are available on the Genomicus web servers come from the Ensembl (2) and En-Nucleic Acids Research, 2015, Vol. 43, Database issue D683 semblGenome (3) databases. The current (November 2014) Genomicus server dedicated to vertebrates is more specifically based on Ensembl release 76, which contains genome annotations for 68 extant species. From Ensembl, we have downloaded all the protein-coding sequences together with their gene location, the gene family they belong to, the percentage of similarity between pairs of proteins and the computed dN/dS ratio (the ratio of non-synonymous to synonymous mutations in coding sequences, an indicator of the rate of sequence diversification).
Improved queries, top menu features Based on usage survey and suggestions from users, querying Genomicus has been improved (Figure  1A ). The standard query interface accessible using a gene name, HGNC symbol or an Ensembl gene ID remains as before, but has been extended to include free text to be matched to Ensembl gene descriptions without loss in response time. CNEs can also be queried by names using their nomenclature (RegHsaxxxxxxx). Context-sensitive name completion is now in place, and is activated when the user has entered at least three letters. The second major change is the possibility to query the server with a protein sequence, through a BLASTP search. On the home page, users can paste in a protein sequence, select a query database and compare the sequence against all the proteins available in the chosen database.
Multiple genome comparison: update of AlignView and PhyloView displays The aim of the Genomicus web server is to provide a way to explore spatial information related to gene organization within and between genomes. The two multiple genome comparison views, PhyloView and AlignView, available since 2010, allow the study of gene and genome evolution with schematic display of genes. Gene positions are defined according to the shortest transcripts of every gene (to minimize cases of overlapping genes). Orthology and paralogy information is shown through colors (Figure  2A ). One of the advantages of comparative genomics is to facilitate genome annotation. Typically, predicted proteins from one genome are 'projected' to another genome through sequence comparisons. However, the target genome may not be assembled correctly at the position of a given gene, and this artefact may go unnoticed until a locus-specific analysis is carried out.