dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We thank  T Fujita ,  J Perrault ,  C Rice ,  S Goodbourn ,  D Garcin  and  Y Jacob  for providing us with useful reagents; and  T Lunardi ,  M Lethier  and  I Ivanov  for their help in protein production and mutagenesis. We used the qPCR ( B Blanquier ) facilities of the  SFR Biosciences Gerland-Lyon Sud  ( UMS344/US8 ). This work was supported by grants from  FINOVI  and  ANR CARDINNATE  ( ANR12-BSV3-0010-01 ) to DG and SC, and  ERC  Advanced Grant V-RNA ( 322586 ) to SC. Materials and data are available upon request (plasmids via Addgene repository).
ChIP-chip procedure and data analysis ChIP assays were performed as previously described  [45]  using an H3K27me3 antibody (07-449 from EMD Millipore, Billerica, MA, USA) and analysed as described previously  [19, 20]. ChIP-chip data have been deposited under Gene Expression Omnibus accession number [GSE:68536]. Two replicates of each experiment are available and show similar results. Raw data were analysed using the Tobias Straub protocol (http://www. epigenesys. eu/images/stories/protocols/ pdf/20111025114444_p43. pdf ) with the Bioconductor R interface. This protocol includes quality assessment, data normalisation and transformation. The gene expression data of TS cells were extracted from [GSE:15519]  [33].
Raw efficiencies of each PCR assay and allelic specificity were measured on control DNA within each experiment. Transcript levels were extrapolated using the raw PCR efficiencies, thus allowing the direct comparison of different genes. Controls for allelic specificities of PCR assays are available upon request. Three housekeeping control RNAs (Gapdh, Hist2h2a and Rplp0) were systematically quantified in parallel in each single cell. See Additional file 7 for raw quantifications. Detailed analyses and statistical tests have been performed using the Qlucore Omics Explorer 2. 3 (QLUCORE Company). For primer sequences, see  [19].
Acknowledgements We thank the  Centre d'Immunologie Humaine (CIH-Human Immunology Centre)  for allowing and facilitating the use of the Biomark thermocycler. We thank  Ann Holmberg  from the  QLUCORE Company  for her help with the analysis of single-cell RT-qPCR results. We thank  Graham Hayhurst  for critical reading of the manuscript. This work was supported by recurrent funding from the  Pasteur Institute  and from the  French National Centre for Scientific Research (CNRS)  and by grants from the  French National Agency for Research (ANR) , the  Epigenome Network of Excellence , the  REVIVE Labex  and the  Louis D Foundation of the Institut de France  ( Louis D Prize  awarded to PA). J. P. was supported by a doctoral fellowship from the  Région Ile-de-France  ( DIM-Biothérapies ), and by a grant from the  REVIVE Labex.
However, in contrast to VDR null mice, VDR gem mice do not develop alopecia even at 1 year of age (Figures  3A  and 5A ; data not shown). These results indicate that VDR gem exhibits the typical hallmarks of 1,25(OH) 2 D 3 deficiency. To determine whether gemini ligands induce VDR gem activity in vivo, we first evaluated serum calcium levels in VDR gem mice to which Gemini-72 was administered every second day at 0. 3 mg/kg for 3 weeks. Such treatment does not induce hypercalcemia in WT mice, but restores serum calcium levels in VDR gem mice (Figure  4A ), demonstrating that VDR-dependent calcium homeostasis is normalized by Gemini-72 in these mutant mice. In contrast, 1,25(OH) 2 D 3 administration at similar doses does not increase calcium levels in VDR gem mice. We next determined the transcript levels of Cyp24a1 in the duodenum 6 hr after ligand treatment.
2 or <0. 8 relative to WT were considered. Whereas the transcript levels of 322 genes are decreased in VDR gem duodenum (Figure  6A , left), only 141 genes are downregulated in VDR null mice  (Figure 6B, left). Gene ontology analysis with DAVID software revealed that among the top 100 downregulated genes in VDR gem mice (Figure  6C ), 38% are involved in mineral ion homeostasis (Figure  6D ). In contrast, 562 genes are upregulated in VDR null mice (Figure  6B  (Figure  6E ), 41% are involved in inflammatory and defense responses and 14% in mineral ion homeostasis (Figure  6F ). Thus, these results show that the transcriptional program is differentially altered in duodenum of VDR gem and VDR null mice, with 2-fold more downregulated genes in VDR gem mice than in VDR null mice and 3-fold more upregulated genes in VDR null mice than in VDR gem mice.
Four hours after transfections, cells were washed with freshly prepared PBS. 1,25(OH) 2 D 3 , gemini, Gemini-72 ligands or solvent (DMSO) were added to the cells in phenol red-free DMEM, supplemented with 10% FCS. Twentyfour hours after the onset of stimulation, cells were washed in PBS and treated with 100 ml of reporter gene lysis buffer (Roche Diagnostics). Lysates were assayed for luciferase activity as recommended by the supplier (Perkin-Elmer). Luciferase activities were normalized to b-galactosidase or GFP expression. Data represent one triplicate.
Transcriptomic Analysis Biotinylated single-strand cDNA targets were prepared, starting from 150 ng of total RNA, using the Ambion WT Expression Kit (catalog number 4411974) and the Affymetrix GeneChip WT Terminal Labeling Kit (catalog number 900671) according to Affymetrix recommendations. Following fragmentation and end labeling, 3 mg of cDNAs were hybridized for 16 hr at 45 C on GeneChip Mouse Gene 2. 0 ST arrays (Affymetrix) interrogating 35240 RefSeq transcripts represented by approximately 27 probes spread across the full length of the transcript. The chips were washed and stained in the GeneChip Fluidics Station 450 (Affymetrix) and scanned with the GeneChip Scanner 3000 7G (Affymetrix) at a resolution of 0. 7 mm. Raw data (. CEL Intensity files) were extracted from the scanned images using the Affymetrix GeneChip Command Console (AGCC), v.
4. 0. CEL files were further processed with Affymetrix Expression Console software v. 1. 3. 1 to calculate probe set signal intensities using Robust Multi-array Average algorithms with default settings. The FCROS method (Dembeleand Kastner, 2014) was used to select the statistically significant list of differentially expressed genes. The error level and the fold change were set to 5% and 1. 2%, respectively.
ACCESSION NUMBERS Coordinates and structure factors are deposited into the Protein Data Bank with accession numbers 4RUJ for VDR gem -1,25(OH) 2 D 3 , 4RUO for VDR gemgemini, and 4RUP for VDR gem -Gemini72. for discussions, P. Eberling for the peptide synthesis, the IGBMC microarray and sequencing platform for data generation and bioinformatics support, the staff of the mouse, biochemistry and genetic engineering facilities from ICS and IGBMC for technical assistance, and the staff of the beamline at the ESRF for the experimental assistance during data collection. The project was supported by the Centre National de la Recherche Scientifique, the Institut National de la Santeet de la Recherche Medicale, the Agence Nationale de la Recherche (ANR-13-BSV8-0024-01), the Fondation ARC pour la Recherche sur le Cancer, Instruct, part of the European Strategy Forum on Research Infrastructures, and the French Infrastructure for Integrated Structural Biology (ANR-10-INSB-05-01) and by French state funds through the Agence Nationale de la Recherche ANR-10-LABX-0030-INRT under the frame programme Investissements d'Avenir labelled ANR-10-IDEX-0002-02.
In this context, this study aims to develop a simple theoretical approach to estimate Tends independently from LST images. Soil Tends are simulated by a soil energy balance model, and two formulations of aerodynamic resistance are tested over bare soil. Vegetation Tends are obtained from soil Tends and air temperature. Model-derived soil Tends are first evaluated with the in situ measurements made in an irrigated area in Morocco. They are next compared to the soil Tends retrieved from 90-m resolution ASTER data collected over two irrigated areas in Spain and Mexico using an algorithm that combines both LST -α and LST -f vg spaces. Model-derived and image-based Tends are then used as input to a contextual (SEB-1S,  [14] ) ET model, and results in terms of 90-m resolution and 1-km resolution ET estimates are evaluated over the Mexican site, where ground-based ET measurements are available.
Continuous measurements of T s,wet and T s,dry were taken between 10:00 a. m. and 11:30 a. m. UTC (Coordinated Universal Time). The observation time is compatible with the overpass times of ASTER, Landsat-7/Landsat-8 and MODIS thermal sensors. The soil temperature for dry and wet soils were monitored using DS1921G-F5 Thermochron iButton sensors. These sensors are rugged, low-cost and self-sufficient systems that record and store time and temperature. They are equipped with a wide (from -40-85 • C) temperature range and fit for a moderately long (from 1-255 min) logging rate. Their accuracy spans from ± 1 • C in the -30-70 • C range to ± 1. 3 • C outside this range, with a field resolution of 0. 5 • C ([28]). In order to increase the confidence in the experimental data and to have a better estimate of the uncertainty in measurements, several Thermochron iButtons were set up at each soil plot.
In practice, iButtons were fixed on 7 cm by 7 cm acrylic glass plates, for a set of three iButtons per plate. Because more variability was found in the dry soil measurements, two plates (six iButtons) were used to measure T s,dry , whereas one plate was used to estimate T s,wet. The plates were buried very close to the soil surface, by making sure that iButtons were not directly exposed to solar radiation. Thermochron data were logged at a 5-min time interval. Entries registered by all Thermochron iButtons were averaged per soil plot, and per 30-min bin, cumulated at 10:30 a. m. , 11:00 a. m. and 11:30 a. m. UTC. This resulted in a total of three sets (T s,wet and T s,dry ) of values per day. In addition to soil temperature measurements, meteorological data, such as air temperature, relative air humidity, solar radiation and wind speed, were acquired every half hour by a permanent meteorological station located in an alfalfa crop field about 200 m from the dry/wet soil plots.
Urgell Site The Urgell area presents a semi-arid continental Mediterranean climate, with a mean yearly air temperature of 16 • C, precipitation of 400 mm and a number of days with rain of 60. The area of interest includes both irrigated crops consisting of wheat, maize, alfalfa and various fruit (apple and pear) trees, as well as dryland crops, such as barley, olive trees, vineyards and almond trees  [29]. The Urgell experiment, conducted in 2011, focused on a 20 km by 20 km area, situated within the Urgell irrigation region. Meteorological data are continuously acquired over the area. The meteorological data were collected by the automatic weather station of Golmes (WC) as part of the XEMA network operated by the Meteorological Service of Catalonia (SMC). Air temperature, relative air humidity, solar radiation and wind speed were recorded every 30 min at a 2-m height by the Golmes (WC) station.
ASTER ASTER is an imaging instrument on-board NASA's Terra satellite, launched in 1999 and having an equator crossing time at 11 a. m. , with a 16-day revisit cycle. The ASTER thermal sensor has five thermal bands, with a spatial resolution of 90 m. ASTER official surface kinetic temperature products (AST_08) were downloaded from the Earth Observing System Data Gateway and extracted over the  16   In order to test the contextual ET models at multiple resolutions, ASTER data are also used at a 1-km (MODIS thermal) resolution by aggregating the original 90-m resolution ASTER temperature using a simple average  [31].
Formosat-2 The Formosat-2 satellite is an Earth observation satellite of the National Space Organization of Taiwan, launched in 2004. Its high (8 m) resolution images are provided daily at 9:30 a. m. equator-crossing time. The reason behind using Formosat-2 derived albedo resides in the unusability of the ASTER shortwave infrared data on its seven overpass days over the Yaqui site  [30]. Its high temporal resolution (one day revisit cycle) enabled us to use data collected on the nearest date from each of the seven ASTER overpass dates in order to estimate both NDVI and α from the red and near-infrared reflectances, aggregated at ASTER thermal sensor resolution.
LST, Fractional Green Vegetation Cover, NDVI and Surface Albedo In order to retrieve the LST, the "temperature and emissivity separation" algorithm  [33, 34]  was applied. Fractional green (photosynthetically active) vegetation cover and surface albedo are derived over the Urgell and Yaqui study areas from satellite surface reflectances in the red and near-infrared bands. For the Urgell area, reflectance data are obtained from 15-m resolution ASTER red and near-infrared data on its two overpass days. For the Yaqui area, reflectance data are obtained from Formosat-2 data, available on dates closest to the ASTER overpass dates. In both cases, surface reflectances are aggregated from the observation resolution to ASTER thermal resolution (90 m) beforehand. The Gutman and Ignatov (1998) formula is applied in order to obtain the fractional green vegetation cover (f vg ): f vg = NDVI -NDVI s NDVI vg -NDVI s (1) with NDVI vg corresponding to fully-covering green vegetation and NDVI s to bare soil or to bare soil partially covered by senescent (non-photosynthetically active) vegetation.
The other Tends are estimated by combining the Tends retrieved from the LST -α and LST -f vg spaces separately. The minimum soil temperature for each space is computed by extrapolating the wet edge passing through the well-watered full-cover green vegetation index until the bare soil line. The maximum vegetation temperature is computed such that all data points are located in between the dry [AD] and the wet [BC] edges. This process is first undertaken for each space separately and then sets T v,dry to the average of the two retrieved values. Please refer to Appendix A for further details concerning the original version of the algorithm and the adjustments made to it.
In addition, a fairly strong bias is present on net radiation, which tends to worsen ET estimations  [30]. Note that the significant difference in RMSD when using image-based versus model-derived Tends as input to SEB-1S could be attributed to uncertainties in the vegetation Tends (simply derived from soil Tends and air temperature). Nonetheless, the MO r ah still provides acceptable ET estimates at 90-m resolution. Figure  12  plots the ET simulated by SEB-1S at 1-km resolution (from aggregated ASTER data) versus the 1-km resolution ET chosen as a reference over the Yaqui area, on all seven ASTER overpass days. Given the good results obtained with Tends_RS_90m in terms of 90-m resolution ET estimates, the reference dataset for evaluating the 1-km resolution ET models is obtained by aggregating the 90-m resolution Tends_RS_90m-forced SEB-1S ET at 1-km resolution.
The Tends used as input to EF_SEB-1S consist of Tends simulated by EBsoil with the RI and MO aerodynamic resistance and the Tends retrieved from 1-km resolution data (RS). At 1-km resolution, the Tends_EBsoil algorithm with MO formulation improves ET predictions. However, the presence of a significant bias can be observed on the ET estimates computed using the MO-derived Tends, on 6 May. In fact, Tends_EBsoil are computed independently of the LST dataset and, thus, can lead to the polygon not being centered on the cluster points in the LST -α and LST -f vg spaces. This can introduce a bias in model-derived Tends and, as a result, in EF/ET. In contrast, the polygon obtained from Tends_RS_1km is centered on the cluster points, because the computation of Tends is made using the observed data points.
Acknowledgments This study was supported by  TREMA (Télédétection et Ressources en Eau en Méditerranée semi-Aride) international laboratory ,  IRD (Institut de Recherche pour le Développement) ,  CNRS  ( Centre National de la Recherche Scientifique ) and  ANR (Agence Nationale de la Recherche )  MIXMOD-E ANR-13-JS06-0003-01  funding.
Acknowledgements We would like to thank  Eudaldo González  for the elm surveys he has carried out all over Spain, and  Diego Maya  for collecting samples in Huelva. We are also grateful to  Pablo Sanjuanbenito , and  Cuenca Alta del Manzanares , park managers, for their support. This study was funded by the  Ministerio de Agricultura, Alimentación y Medio Ambiente (MAGRAMA) , and by the  Comunidad de Madrid  (project  S2009AMB-1668 ). M. V. was sponsored by a  Technical University of Madrid "PIF" Pre-Doctoral.
Furthermore, Ingenuity Pathway Analysis suggested that T cells from patient CD46-3 lacked activation-induced expression of several key AA transporters. Specifically, of the top five gene networks modeled by the software, two were functionally involved in AA metabolism (Figures  3Bi  and 3Bii  and Figures  S3Bi  and S3Bii ). Upregulation of the glucose transporter GLUT1 (Macintyre et al. , 2014) and L-type AA transporter LAT1 (SLC7A5; reduced in T cells from patient CD46-3 [Figure  3Bii ]) are required for successful CD4 + T cell activation in mice  (Sinclair et al. , 2013)  and humans  (Hayashi et al. , 2013). When assessing activated T cells 36 hr post stimulation for the expression of GLUT1 and LAT1, we found that CD3+CD46 activation induced strongest expression of these channels when compared to CD3 or CD3+CD28-activated cells (Figures  3Ci  and 3Cii ), while CD46 activation alone had no effect on GLUT1 or LAT1 expression (data not shown).
Gene Arrays and Array Analyses Transcriptome profiling was performed using Illumina HT12V4 microarrays (Illumina, Great Chesterford, UK) on technical triplicates using CD3+CD46activated T cells isolated from patient CD46-3 and an age-and sex-matched healthy donor. Expression data were analyzed using Partek Genomics Suite (Partek, St. Louis, USA) version 6. 6, Ingenuity Pathway Analysis (QIAGEN) and Gene Set Enrichment Analysis, GSEA  (Subramanian et al. , 2005)  (Broad Institute of MIT and Harvard). For details, see Supplemental Experimental Procedures. The raw data of all arrays are deposited with the Gene Expression Omnibus (GEO) repository under the accession number GEO: GSE69090.
Statistical Analysis Analyses were performed on GraphPad Prism (La Jolla, CA). Data are presented as mean ± SD or median (interquartile range, IQR) for parametric and non-parametric data, respectively, and compared using paired t tests with Bonferroni correction for multiple comparisons, Wilcoxon signed rank tests, the two-tailed Mann-Whitney test, one-way or two-way ANOVA with a Tukey multiple comparison post hoc test, as appropriate. p values < 0. 05 denoted statistical significance throughout.
ACKNOWLEDGMENTS We thank the donors and the patients for their support,  Margaret So  ( University of Arizona ) for the anti-CD46 CYT-1 and CYT-2 antibodies and  Erez Dror  ( University of Basel ) for help with nutrient uptake studies. This work was supported by the  MRC  grants  G1002165 (C. K. )  and  MR/J006742/1 , an  EU-funded Innovative Medicines Initiative BTCURE  (C. K. ), a  Wellcome Trust   Investigator Award  (C. K), a  Wellcome Trust   Intermediate Research Fellowship  (B. A. ), the  National Institute for Health Research (NIHR) Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust , and  King's College London. S. D. was supported by the  Roche Postdoctoral Fellowship Program , C. H. by the  Gebert Ru ¨f Foundation  ( GRS-058/14 ), and both C. H. and M. F. by the  Swiss National Science Foundation  ( 310030-153059  and  323530-139181 , respectively).
Nobody is perfect: the DNA polymerases-enzymes imperfecta Eukaryotic cells usually possess more than 10 DNA polymerases. For example, S. cerevisiae contains 11 (polymerases: α, β, γ , δ, ε σ, ϕ, θ, ζ , η and Rev1) (Saccharomyces Genome Database. http://www. yeastgenome. org/, 12 November 2014 date last accessed), Sc. pombe contains 12 (all homologs of S. cerevisiae polymerases plus Pol κ) (PomBase database. http://www. pombase. org/, 12 November 2014 date last accessed) and human cells contain up to  18 (polymerases: α, β, γ , δ, ε ι, κ, λ, μ, ν, σ , ϕ, θ, ζ , η, REV1, PRIMPOL and DNTT)  (GeneCards. http://www. genecards. org/, 12 November 2014 date last accessed) (Table  1 ). These DNA polymerases belong to several polymerase families including A, B, X and Y. The role they play in cells is determined by their fidelity and processivity (Table  1 ).
DNA polymerases and their functions in budding and fission yeast. 2  is available at (Saccharomyces Genome Database. http://www. yeastgenome. org/; PomBase. http://www. pombase. org/on-line database) and the reader is referred to these sources, and the references therein for further details. Additional data have been published in  (Kunkel et al. 1989; Shcherbakova et al. 2003; Fortune et al. 2005; Zhong et al. 2006; McCulloch et al. 2007; McCulloch and Kunkel 2008; Burgers 2009 ). a Gene Ontology annotations for S. cerevisiae protein. Orthologs in other fungi mostly play similar role in the cell. In some cases more information is available for gene product from other fungi than for its S. cerevisiae  recognized. Each polymerase also has its own function in the cell, such as acting on the leading or lagging strand, gap filling and synthesizing mitochondrial DNA (mtDNA).
Since 2014 the Mission Archéologique Française au Myanmar has been excavating a prehistoric cemetery, Oakaie 1, adjacent to the famous Nyaung'gan Bronze Age cemetery in Sagaing Division. Oakaie 1 (OAI1) was selected as a Nyaung'gan proxy in order to better understand the Neolithic-Bronze Age-Iron Age chronological transitions in upper-central Myanmar, for eventual regional-scale synthesis. An initial attempt to AMS 14 C date 13 human femurs failed due to a lack of collagen but a subsequent effort using an apatite dating methodology on 5 femurs was successful. These preliminary data bracket part of the cemetery from the 9 th to 6 th c. BC with a 4 th -3 rd c. BC outlier. Typological and technological analogies between OAI1 and Nyaung'gan pottery grave goods likewise suggest an early 1 st millennium BC date for the local Bronze Age.
Of the above transitions, resolving the début of the Mainland Southeast Asian Neolithic and Bronze Ages has arguably involved the greatest expenditure of effort by regional prehistorians over the last five decades, as competing models for the derivation of 'Chinese' cultural behaviours were tested and refined with ever improved datasets (see  Higham, 2014, Higham, in press  and papers cited therein). The current paper is a preliminary contribution to the task of defining the Neolithic-Bronze Age transition in westernmost Mainland Southeast Asia. This is important as the current regional dataset is heavily biased in favour of Thailand, in terms both of quantity and quality of data. An initial Thai Bronze Age date of 1100-1000 BC is now widely accepted but this should not mask the potential for substantial and historically relevant regional variation.
RESULTS All five apatite determinations, performed at Queen's University Belfast (QUB), were successful and produced archaeologically-coherent dates with low standard deviations ranging between 2242±38 and 2584±39 BP (Table  1 ). These data were then calibrated using the IntCal13 calibration curve and Oxcal v4 software (Figure  11 ,  Reimer et al. , 2013). Four of the five determinations indicate a late-9 th to mid-6 th c. BC range for the cemetery at two standard deviations. The S15 determination is an outlier at early-4 th to late-3 rd c. BC at two standard deviations.