dataesr/scientific-paragraphs-categorization huggingface dataset:
Immunohistochemistry Immunohistochemistry was performed as described  (Gordon et al. , 2004). See the Supplemental Experimental Procedures for details. Appropriate isotype and negative controls were included in all experiments. For detection of immunofluorescence, slides were examined with a Leica AOBS (Leica Microsystem, GmbH) or SPE confocal microscope. Images presented are of single optical sections. qRT-PCR qRT-PCR was performed as previously described  (Bredenkamp et al. , 2014b) , on 50 cells per sample. See the Supplemental Experimental Procedures for details. Data are shown after normalization to the geometric mean of three control genes (Hprt, Ywhaz, Hmbs). Data analysis was carried out using Light-Cycler 1. 5 software and the DCt method  (Livak and Schmittgen, 2001). Primers used for qRT-PCR are as shown in Table  S3.
For the purpose of representation, information from the y and z planes are collapsed onto the x axis. Where contribution of GFP + cells to cortical and medullary regions overlaps in this schematic, these regions were contiguous in most but not all cases. (C, C', and D) Images show immunohistochemical analysis of grafts derived from the MHCII hi Ly-51 + PLET1 + input TEC (C and C') and MHCII lo/neg Ly-51 + PLET1 + (D) populations after staining with markers indicative of defined cortical and medullary TEC populations, as shown. MHCII hi Ly-51 + PLET1 + input TECs, n = 4; MHCII lo/neg Ly-51 + PLET1 + , n = 3. Images show representative data from three of four independent grafts for MHCII hi Ly-51 + PLET1 + and two of three independent grafts for MHCII lo/neg Ly-51 + PLET1 + input TECs. Arrowhead in (C 0 ) indicates GFP + PLET1 + cell.
N. R. Manley  for discussion and comments. The research leading to these results received funding  Leukaemia and Lymphoma Research  ( 06008  and  02327  to C. C. B. ), the  Darwin Trust of Edinburgh  (to S. U. ), the  School of Biological Sciences, University of Edinburgh  (to H. J. V. ), the  Medical Research Council  (to A. M. C. ), the  Biotechnology and Biological Sciences Research Council  ( BB/ H021183/1BBSRC  to C. C. B. ), the  NIH  ( 1P01AI076514-01A1  to C. C. B. ) the  European Union Sixth Framework Programme  integrated project EuroStemCell (to C. C. B. ) under grant agreement  503005 , the  European Union Seventh Framework Programme  ( FP7/2007-2013) collaborative projects EuroSyStem  (to C. C. B. ),  OptiStem  (to C. C. B. ),  ThymiStem  (to C. C. B. ) under grant agreement numbers  200720 ,  223098 , and  602587 , respectively, and a  CJ Martin Fellowship  from the  Australian National Health and Medical Research Council (NHMRC)  (to T.
The DNA fragments obtained were cloned into pGEX-4T2 previously digested with the same restriction enzymes (GE Healthcare, Chalfont St Giles, UK). Full-length cDNA from VvSDH3 and VvSDH4 were cloned in parallel into the pENTR/D-TOPO vector (Invitrogen, Courtaboeuf, France) and transferred in the pH2GW7 vector  (Karimi et al. , 2002)  by the LR reaction (LR clonase II, Invitrogen). The complete sequence of VvSDH4 cloned in pH2GW7 was used for sequence analysis. Competent cells of E. coli DH5α were used to incorporate and propagate all vectors, except pGEX-4T2 for which BL21 (DE3) cells (Stratagene, La Jolla, California, USA) were used. The Genbank accession numbers corresponding to full length nucleotide sequences are KU163040 (VvSDH1), KU163041 (VvSDH2), KU163042 (VvSDH3), and KU163043 (VvSDH4).
Phylogenetic analysis Protein sequences of plant DQD/SDHs were collected from the NCBI public database and Phytozome 10. 0. Phylogenetic analyses were performed using MEGA version 6  (Tamura et al. , 2013). Protein sequences were aligned using ClustalW with a gap open penalty of 10, and a gap extension penalty of 0. 2. A Neighbor-Joining tree with the evolutionary distances was computed using the p-distance model. The statistical support for tree nodes was evaluated by the Bootstrap method (1 000 bootstrap replicates). The presence of a putative chloroplastic transit peptide has been predicted using ChloroP 1. 1  (Emanuelsson et al. , 2006). Heterologous expression in E. coli Heterologous expression, purification, and quantification of VvSDH were performed as described in  Khater et al. (2012).
The optimal pH for each enzyme has been determined using a buffer with a pH range from 6. 5 to 9. K m for SA (K m (SA) ) was determined at pH 7 and pH 9, with reaction mixtures containing 2 mM NADP + and variable SA concentrations. K m (NADP+) was determined at the same pH with 4 mM SA and variable NADP + concentrations. K m (3-DHS) was determined at pH 7 for VvSDH1 and VvSDH3 using 4 mM 3-DHS and NADPH as the cofactor (0. 4 mM). For each substrate or cofactor concentration, OD 340 was plotted as a function of time to determine the slope at the origin. Initial velocity (V i ) was calculated with the NADPH molar extinction coefficient (ε=6. 18 × 10 3 mol l -1 ). V i data was fitted with Michaelis-Menten hyperbola to yield K m and V max values (Hyper32 program, Version 1. 0. 0, 2003). The turnover number (k cat ) was calculated, taking into account the quantity of enzyme introduced in the reaction volume.
Transmembrane domains prediction The TOPPRED 1. 10 membrane proteins topology prediction program  [28]  was used, with default parameters: GES (Goldman-Engelman-Steitz) hydrophobicity scale, certain and putative cuttofs 1. 0 and 0. 6, respectively. Hydrophobicity was calculated using a core window size of 11 and a full window of 21 amino-acids. The Constrained Consensus TOPology (CCTOP) server  [29] , which utilizes ten different topology prediction methods, was used in parallel to validate the results.
The developed TLC plates were then visualized using a Typhoon multi-purpose imager (GE Healthcare). Fluorescent products were quantified using Multi Gauge software, version 3. 0 (Fujifilm, Tokyo, Japan). DGAT activity was expressed as picomoles of TG formed per minute per milligram of purified protein, using a calibration curve of the NBD-DG substrate. The DGAT inhibitor niacin used for some experiments was from Sigma-Aldrich.
Overexpression and purification of soluble forms of Dga1p from Yarrowia lipolytica The oleaginous yeast Y. lipolytica contains two DGAT enzymes; the major TG synthesizing enzyme is Dga1p which belongs to the DGAT2 family. Dga1p is encoded by the YALI0E32769g gene (GenBank accession number NC_006071) which codes a 515-residues protein with a molecular mass of 57. 8 kDa. Hydropathy plot on Dga1p amino-acid sequence was generated by TOPPRED 1. 10. The resulting topology prediction indicates three putative transmembrane domains (Fig  1A ). The first one, the higher score of which indicates a strong probability of existence, is located in the N-terminal part of the protein (residues 51-71), and the two other ones, which hydrophobicity values are significantly lower, correspond to residues 279-299 and 302-322.
Acknowledgments We thank  Dr Jean-Marc Nicaud  for providing pMal-c2X vector,  Sébastien Baud  for critical reading of the manuscript, and  Laure Aymé  for fruitful discussions. This work was carried out within  Probio3  project  ANR-11-BTBR-0003 , with financial support from  French government. NH and JL were supported by this project.
Multistate characters account for 74% of the characters, and among them 23% are ordered (nonmetrical morphological characters 2,  4, 18, 32, 92, 99, 103, 106, 108, 109, 114, 119, 120 and metrical characters 125, 126, 129, 130, 137, 140, 142, 143, 145, 146, 147, 148, 149, 152, 153, 154, 155, 156, 165, 166, 167, 179, 182, 183, 184, 192, 193, 194, 199, 200, 201, 202, 226, 227, 237, 240, 246, 259, 260, 261, 283, 286, 291, 293, 294, 297, 300, 301, 303, 304, 305, 306, 307, 308, 309, 330, 384, 385, 388, 389, 416, 423, 424, 435, 437 and 441). We used 613 measurements to produce metric (ratio) characters that represent the frontal bone (154 measurements), the parietal (84), the temporal (72), the occipital (51), and the calvaria as a whole (252). These data (chords and arches, measured between all the landmarks on a calvaria) are transformed into 345 metrical indices (Appendix 2) and allow to discriminate the various taxa (e.
Questioning the single former cladistic analysis of LB1 Argue et al. 's (  2009 ) study took into account only a nonmetric morphological dataset and is based on the a priori grouping of specimens that may not reflect their phylogenetic affinities. In that study  (Argue et al. , 2009) , Homo erectus was represented by three specimens (Sangiran 2, Sangiran 17, Trinil 2), Homo ergaster by two specimens (KNM-ER3733 and KNM-ER 3883), Homo rhodesiensis by a single specimen (Kabwe 1), Homo habilis by two specimens (KNM-ER 1813 and OH 24), and finally, Australopithecus africanus was represented by three specimens (Stw 505, Sts 71 and Sts 5). On the basis of these OTUs defined a priori, Argue et al. 's cladistic analysis suggests that LB1 is the sister group of the australopithecines (e. g. Stw 505, Sts 71 and Sts 5) and that the new taxon Homo floresiensis is characterized by four autapomorphies: the presence of an obelionic depression, the absence of a postglenoid process, an orifice of the incisive canal that is on a plane with the second premolar, and a P4 Tomes'root.
Acknowledgments We would like to thank  Tony Djubiantono  for his authorisation to study the Liang Bua specimens and  Patrick Semal  for his interesting information concerning the Pacific area. We thank  Maciej Henneberg  and  Robert Eckhardt  for informative data and discussions, as well as  Louise Byrne  and  Kevin Padian  for improving our English and four reviewers for their constructive comments. Last but not least, thanks to  Michel Laurin  for his advice. The initial stage of this work was supported by the  Fyssen Foundation.
RNA isolation and Affymetrix exon array data processing Total RNA was extracted from snap frozen skeletal muscle biopsies using Trizol (Invitrogen) according to the manufacturer's instructions. RNA samples were quantified using a ND-1000 NanoDrop spectrophotometer (NanoDrop Technologies) and purity/integrity were assessed using disposable RNA chips (Agilent RNA 6000 Nano LabChip kit) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Waldbrunn, Germany). The average RIN value of total RNAs was 7. 16  (6. 1-7. 8). Each RNA (n = 8; four controls and four OPMD) was analyzed individually. Affymetrix Human Exon 1. 0 ST arrays were hybridized by GenoSplice technology (www. genosplice. com) according the Ambion WT protocol (Life technologies, France) and Affymetrix (Santa Clara, CA, USA) labelling and hybridization recommendations.
Raw data were controlled with the Expression console (Affymetrix). Affymetrix Human Exon 1. 0 ST Array dataset analysis and visualization were made using EASANA ® (GenoSplice technology), which is based on the GenoSplice's FAST DB ® annotations  (42). Exon Array data were normalized using quantile normalization. Background corrections were made with antigenomic probes and probes were selected as described previously  (43, 44). Only probes targeting exons annotated from FAST DB ® transcripts were selected to focus on well-annotated genes whose mRNA sequences are in public databases  (42, 45). Badquality selected probes (e. g. probes labelled by Affymetrix as 'cross-hybridizing') and probes whose intensity signal was too low compared to antigenomic background probes with the same GC content were removed from the analysis.
Results were considered statistically significant for uncorrected P-values ≤0. 05 and fold-changes ≥2. 0. To filter and classify exons predicted to be differentially included, manual inspection was performed after uploading the Exon Array data into the EASANA ® visualization module, which is based on the FAST DB ® Client Edition annotations. By computational comparison of publicly available mRNA sequences with genomic sequences, alternative exons were annotated in FAST DB ® as alternative first exons, alternative terminal exons, cassette exons, mutually exclusive exons, alternative 5 donor sites, alternative 3 acceptor sites, intron retention and exonic internal deletion (Supplementary Figure  S1  and Table  S1 ).
Image acquisition and analysis Images were visualized using an Olympus BX60 microscope (Olympus Optical, Hamburg, Germany), digitalised using a CCD camera (Photometrics CoolSNAP fx; Roper Scientific) and analyzed using MetaView image analysis system (Universal Imaging, Downington, PA, USA), MetaMorph imaging system (Roper Scientific, Tucson, AZ, USA) software, and ImageJ 1. 44o (http://imagej. nih. gov/ij) for quantification analysis.
Statistical analysis All data are presented as mean values ± standard error of the mean (SEM) (cohort size stated per experiment). All statistical analyses were performed using either the Student's ttest, or the ANOVA one-way analysis of variance followed by the Bonferroni post-test, using GraphPad Prism (version 4. 0b; GraphPad Software, San Diego California, USA). A difference was considered to be significant at P < 0. 05 (*), P < 0. 01 (**) or P < 0. 001 (***).
SC35 splicing factor regulates TNNT3 mutually exclusive exons To determine which splicing factor is involved in the regulation of TNNT3 mutually exclusive exons, a minigene containing exons 16 and 17 of human TNNT3 bordered by exon 15, 18 and their intronic regions (Figure  3A ) was cloned from human genomic DNA in a plasmid expression vector. This minigene construct was cotransfected into HEK293T cells--which do not express TNNT3--together with various vectors expressing wellcharacterized splicing regulatory factors. These included members of the hnRNP, SR, MBNL and CELF families and were selected using prediction software (SpliceAid2 and ESEFinder publically available at http://193. 206. 120. 249/ splicing tissue. html and http://rulai. cshl. edu/cgi-bin/tools/ ESE3/esefinder. cgi?process=home respectively) (57,58) (Table  3 ).
ACKNOWLEDGEMENTS We are grateful to  D. Auboeuf ,  D. Weil  and  N. Charlet-Berguerand  for their gifts of splicing factor expressing vectors. We thank  I. Behm  for the ASF/SF2 antibody and  N. Vignier  for qPCR primers. We thank  Glenn Morris  at the  Centre for Inherited Neuromuscular Disease  for supplying antibody Mb1a to detect MBNL1. We thank  J. Marie  for fruitful discussion and careful reading of the manuscript. We thank  N. Beltchenko  for the construction of the murine Tnnt3 minigene and  Elisa Negroni  for image processing. The authors acknowledge the OPMD patients for their collaboration.
Mass spectra were acquired using a so called TOP10 method, i. e. , full scan spectra were acquired using a mass range of m/z 300 to 1650 with a resolution of 70000, followed by up to ten high energy collision dissociation (HCD) MS/MS scans at a resolution of 17500 of the most intense at least doubly charged ions. The dynamic exclusion was set to 20 s. Data evaluation was performed using MaxQuant software  62  (v. 1. 4. 1. 2) including the Andromeda search algorithm and searching the yeast reference proteome of the uniprot database. Briefly, the search was performed for full enzymatic trypsin cleavages allowing two miscleavages. For protein modifications carbamidomethylation was chosen as fixed and oxidation of methionine and acetylation of the N-terminus as variable modifications. The mass accuracy for full mass spectra was set to 20 ppm for the first and 4.
29 Si MAS-NMR measurements were performed on a wide bore 14. 1 T Bruker Avance II spectrometer on a 4 mm probe with a spinning frequency of 8 kHz. The spectra were acquired using cross polarisation (CP) and 1024 scans per sample, and referenced using silicone rubber at À22. 3 ppm as indirect reference. Additional  29  Si data were acquired using direct excitation with a pulse delay of 600 s, and in the Me 3 Si-graed sample pulse delays of 900 s were also used to check that sites were fully relaxed and hence that the relative intensities of features were fairly quantitative. 13 C MAS NMR data were acquired using 1024 CP scans. The axis was calibrated using adamantane at À38. 5 ppm as indirect reference. Nitrogen adsorption-desorption measurements were performed on powder samples using a Micromeritic 3Flex Surface Characterisation Analyser.
Acknowledgements The authors thank  EPSRC  for funding under the  Supercritical Fluids Electrodeposition project  ( SCFED ,  EP/I033394/1 ) and for funding the Smartlab diffractometer ( EP/K00509X/1  and  EP/ K009877/1 ). The  SCFED  Project (www. scfed. net) is a multidisciplinary collaboration of British universities investigating the fundamental and applied aspects of supercritical uids. Marina Carravetta  thanks the  Royal Society  for a  University Research Fellowship.
Analysis of Illumina raw reads using the UNEAK GBS pipeline The raw reads of the sequenced GBS libraries were analyzed using the Universal Network Enabled Analysis Kit (UNEAK) GBS pipeline which is designed for taxa without a reference genome and is part of the TASSEL 3. 0 bioinformatics analysis package  [35, 36]. In this method, a tag (haplotype) is considered to be a unique sequence representing a group of reads. The default parameters in the UNEAK pipeline were used. Reads were retained if they contained a barcode, a cut site, and had no indeterminate bases within the first 64 bp after the barcode. From the raw reads, each sequence was trimmed to 64 bp in length. Reads were first merged into individual taxon tag count files and then merged into a 'master' tag to include all the tags from the same taxon, keeping tags with total reads count greater than or equal to 5 per sample.
Post-UNEAK pipeline analysis Isolated SNPs were analysed using R script  [37]  that we developed in this study (Additional file 1). The script filtered the Culicoides individuals with more than or equal to 5 % of the total SNPs isolated (8145 SNPs) and the SNPs present in more than or equal to 10 % of the total individuals (96 individuals). Once the SNPs and the samples selected, the script was used to calculate a genetic distance matrix and obtain a hierarchical cluster dendrogram. To limit the ordering bias of SNPs and samples in the data matrix, Pvclust  [38]  was used for assessing the uncertainty in hierarchical cluster analysis. P values are calculated through multiscale bootstrap resampling, by randomly shuffling the samples and/or SNPs a number of times (here 1000 times). Pvclustgenerated dendogram has two types of p values-AU (Approximately Unbiased) and BP (Bootstrap Probability) value.
Amplification and sequencing of standard mitochondrial gene cytochrome c oxidase subunit I (COI) As described previously  [32] , primers Bc1 Culic Fm and JerR2m were used to PCR amplify a 692 bp segment of the COI gene from 76 C. brevitarsis individuals with accession numbers [GenBank: KX247448-KX247523]. A total of four previously identified and published haplotypes was added with the following accession numbers: [GenBank: KJ162968, KJ162967, KJ162975 and KJ162957]. These sequences included one of C. asiatica, the most closely related species to C. brevitarsis  [7]. The PCR amplicons were purified using QIAquick PCR purification kit (Qiagen) and 20 μl was sequenced using the Sanger sequencing method (Macrogen, Geumchun-gu, Seoul).
Acknowledgement M. G. Onyango  was supported by a scholarship from the  Australian Department of Foreign Affairs (AusAID). We would like to express our gratitude to  Peter Mee  for providing C. brevitarsis samples from Queensland. We would also like to acknowledge the critical review and comments of an early version of this manuscript by  Drs David Boyle ,  Cadhla Firth  and  Kim Blasdell. We would also like to extend our gratitude to  Justin O Borevitz  for contributing resources towards GBS sequencing,  Norman Warthman  for initiating the collaboration and  Doreen Busigye  for helping with map construction. Laboratory work at AAHL were partly performed thanks to the  National Collaborative Research Infrastructure Strategy of Australia. Thanks to  Dr Prasad Paradkar  for final reading.
As depicted in Fig. 1 , the 16 sampling points were connected via stopcocks such that gas was sampled from a single sampling point at a time to a Sievers 280i NO analyzer (General Electric; USA). The sampling flow rate was held constant throughout experiments at 200 ml/ min. The NO analyzer was connected via serial communication to a personal computer, and a LabView (National Instruments, USA) based virtual instrument was written for data acquisition. For a given experimental run, steady flow rates of air and of NO-containing gas were set, and then NO concentration at each sampling point was measured. A sampling interval of 5 s was used at each point, and the average NO concentration over the interval was calculated and recorded. Experiments were repeated in triplicate, with rotameter and mass flow controller set points reset between repetitions.
If this lightest supersymmetric particle is also electromagnetically neutral, it is a natural WIMP candidate for dark matter. This lightest particle can annihilate into pairs of standard model particles. Neutrinos, in particular, are the final product of a large variety of decay processes, being therefore a good candidate for an indirect search for dark matter. WIMPs tend to accumulate in celestial objects due to scattering with ordinary matter and the gravitation pull of these objects. This is why indirect searches for dark matter concentrate on massive astrophysical bodies such as the Earth, the centre of our Galaxy, galaxy clusters or, as in this case, the Sun. In this letter, an indirect search for neutrinos coming from WIMP annihilations in the Sun is presented, using data recorded by the ANTARES neutrino telescope from 2007 to 2012.
Since muons cannot cross the entire Earth, this cut rejects all atmospheric muons except for a small fraction of misreconstructed events. The atmospheric neutrinos represent the irreducible background for this search. Atmospheric neutrinos from 10 GeV to 20 TeV are generated in the simulation using the standard ANTARES simulation chain  [6, 7, 8, 9, 10, 11]. The expected neutrino energy spectra from WIMP annihilations in the Sun are calculated with the WIMPSim simulation package  [12]. The code takes into account the absorption of neutrinos in the solar plasma and the neutrino oscillation inside the Sun and on their way from the Sun to the detector. Neutrino spectra are calculated for 15 WIMP masses ranging from 50 GeV to 5 TeV and three annihilation channels assuming a branching ratio of 100%: WIMP + WIMP → b b, τ + τ -, W + W -.
Conclusion A new analysis searching for a signal of dark matter annihilations in the Sun has been conducted using the ANTARES data from 2007 to 2012. The unblinded data showed no significant excess above the background estimate and 90% confidence level exclusion limits have been calculated for the three annihilation channels WIMP + WIMP → b b, W + W -, τ + τ -and WIMP masses ranging from 50 GeV to 5 TeV. Table  1 : Upper limits to neutrino flux, spin-dependent and spin-independent cross-section for different annihilation channels and WIMP masses. Limits for the W + W -channel cannot be produced for WIMP masses below the mass of the W boson.