dataesr/scientific-paragraphs-categorization huggingface dataset:
Combined with CBP and PTX NCT00753038 III Active not recruiting i. v. Combined with CBP and PTX NCT01166542 Combined with NCT00861627 Lung cancer II recruiting i. v. CBP and PTX NCT00998192 Combined with DCX or pemetrexed NCT01708993 reolysin® Active not recruiting i. v. As single agent NCT00651157 Melanoma II recruiting i. v. Combined with CBP and PTX NCT00984464 Multiple myeloma I recruiting i. v. As single agent NCT01533194 Pancreatic cancer II recruiting i. v. Combined with CBP and PTX NCT01280058 Active not recruiting i. v. Combined with gemcitabine NCT00998322 Pediatric solid tumors I recruiting i. v. Combined with cyclophosphamide NCT01240538 Prostate cancer II recruiting n. a. Combined with DCX and prednisone NCT01619813 reproductive I recruiting i. v. + i. p. As single agent NCT00602277 tract tumors II recruiting i.
v. Combined with PTX NCT01199263 I/II recruiting i. t. Combined with ipilimumab NCT01740297 Talimogene laherparepvec Melanoma III Active not recruiting enrolling by invitation i. t. i. t. As single agent As single agent NCT00769704 NCT01368276 Toca 511 Astrocytoma GBM Oligoastrocytoma Oligodendroglioma I I/II recruiting recruiting resection cavity i. t. As single agent Combined with 5-FC NCT01470794 NCT01156584 vSv-IFN-β HCC I recruiting i. t. As single agent NCT01628640 Abbreviations: 5-FC, 5-fluorocytosine; BvC, bevacizumab; CBP, carboplatin; CrC, colorectal cancer; DCX, docetaxel; FOLFIrI, folinic acid, 5-fluorouracil, irinotecan;.
• Individual whistles  (Hausberger, 1997). • Species-specific warbling (high-pitched trills taken from the terminal, non-individual part of warbling that is found in the repertoire of all male starlings). • Individual warbling (individual motifs taken from the initial, individual part of warbling). The total duration of each stimulus was 16 s and consisted of two elements (A and B) of the same type of song repeated in a [(AABB) × 4] fashion (Figure  1 ). The intensity of each song was normalized (in terms of matched root-mean-square) before being integrated into the complete stimulus (songs and silence periods). These manipulations were done using Praat software (University of Amsterdam, The Netherlands). During imaging experiments, auditory signals were presented to the birds with magnetless dynamic speakers connected to an amplifier as described by  Van Meir et al.
(2005). Stimulus presentation was controlled by Presentation software 0. 76  (Neurobehavioral Systems). Frequencies between 2500 and 5000 Hz are known to be enhanced in the setup  (Poirier et al. , 2009). To compensate for this artificial enhancement, an equalizer function was applied to each stimulus using WaveLab software (Steinberg). The function consisted of a Gaussian kernel with the following parameters: maximum amplitude: -20 dB, centered on 3750 Hz, width: 0. 05 octaves (corresponding to the range 2500-5000 Hz). During the experiments, stimuli were delivered to both ears with a sampling frequency of 22050 Hz and their global intensity was 67 dB sound pressure level. By comparison, the magnet noise was 65 dB.
IMAGE ACQUISITION Imaging was performed on a horizontal MR system (Pharmascan 70/16 US, Bruker Biospin, Germany) with a magnetic field strength of 7 Tesla. Specifications of the coils used for the experiment can be found in  Van Meir et al. (2005). BOLD fMRI data were acquired using a T 2 -weighted Fast Spin Echo sequence [echo time/repetition time: 60/2000 ms]  (Poirier et al. , 2010). Each whole-brain volume contained 15 sagittal slices, 1 mm thick, with a gap of 0. 066 mm between slices. In-plane resolution was 0. 34 × 0. 34 mm 2 and matrix size was 64 × 64 voxels. Anatomical three-dimensional (3D) images required for localization of the functional data (see below) were obtained for each bird using a RARE T 2 -weighted sequence with TE/TR: 60/2000 ms. Voxel size was 0. 085 × 0. 085 × 0.
IMAGE PROCESSING Intra-individual head motion (from the 2 sessions) was corrected using a six-parameter rigid body spatial transformation using the Statistical Parametric Mapping toolbox (SPM8; Wellcome Department of Cognitive Neurology, London, UK; http://www. fil. ion. ucl. ac. uk/spm/). The realigned fMRI images for each subject were then coregistered to each individual anatomical 3D dataset. In parallel, the 3D dataset was spatially normalized using SPM8 with a high-resolution ex-vivo starling MRI image/atlas that we developed in our lab (unpublished data). The transformation matrix of this spatial normalization was then applied to the realigned and co-registered functional data, resulting in functional data precisely coregistered to the atlas dataset. Finally, functional data were smoothed with a 0.
ACKNOWLEDGMENTS This research was supported by a  joint "Tournesol" grant  (project  Nr   20371TA ) from the  Flemish and French governments  to  Colline Poirier  and  Isabelle George , a  "PICS" grant  (project Nr 5992) from the  French CNRS  to  Isabelle George  and  Geert De Groof  and grants from the  Research Foundation-Flanders  ( FWO , project  Nr   G042002  and  G044311N ), the  Hercules Foundation  (Grant Nr AUHA0012),  Concerted Research Actions  (GOA funding) from the  University of Antwerp and Interuniversity Attraction Poles (IAP)  ("PLASTOCINE":  P7/17 ) to  Annemie Van der Linden. Isabelle George  and  Martine Hausberger  are supported by the  University of Rennes  1 and by the  French CNRS. Geert De Groof  is a Postdoctoral Fellow of the  Research Foundation-Flanders (FWO).
Photographs were realized in the edge ( = 4) and in the centre ( = 4) of the tumour. Intensity of fluorescence emitted by the perfused cells was quantified with ImageJ. 2. 8. Immunostaining Quantitative Analysis. For the characterization of the tumour vascularization, we developed a method for the quantification of various markers using the ImageJ software  [19]. The images were first segmented to isolate the positive structure of interest and the images were then transformed into binary ones. Finally, the edges of the stained cells were selected and the various parameters, such as counts and areas, were determined. Microvascular density (MVD) corresponds to the mean of the number of vessels per mm 2 , per tumour, and per time point.
Assessment of Tumour Volume. In order to determine the tumour volume, Gradient Echo imaging sequence was performed. Thirty axial slices of 0. 83 mm thickness with a plane resolution of 0. 208 mm were acquired during 3 min, which cover the entire volume of the tumour. For the calculation of the tumour volume, the tumour region was delineated on each section with ImageJ software  [19]. The area of each region of interest (in mm 2 ) was multiplied by the thickness of the slices (0. 83 mm) to calculate the volume (in mm 3 ) of each slice. To obtain the volume of the tumour, the volume of each slice was summed.
Dynamic Contrast Enhanced (DCE) MRI for the Assessment of Tumour Blood Perfusion. Multislice relaxation rate ( 1 = 1/ 1 ) maps were obtained by using saturation recovery gradient echo images with variable flip angles before and after contrast agent administration  [21]. After baseline acquisitions, DOTAREM was administrated i. v. at a dose of 0. 4 mmol/kg, and postcontrast DCE images were acquired over approximately 15 min. Axial images were collected from at least two to three slices through the whole tumour. Muscles were sampled to estimate the concentration of contrast agent in the blood. Images processing, region of interest (ROI), selection and MR data analyses were carried out using Paravision 5 and ImageJ. The  1 and maximal signal intensity ( max ) were calculated according to Seshadri et al.
2009 ). The latter were excluded from the calculation of EVIP, because neither production nor price data were available for the individual crops, which the commodities comprised. Moreover, crops within commodities often depend on pollinators to a variable degree, rendering the use of average dependencies rather problematic. For Q i and P i , we used the production and price data provided by FAO, respectively. Production is given in tons and price in US dollars per ton. The FAO database generally provides a large data set, but production or price figures are missing for some years and for some countries. Where production values for the year t of the country c were missing we could not calculate EVIP. If values for prices, but not for production were missing for a crop i* in the country c* at time t*, we used the 'moving average methodology' to calculate the price at this particular year (t*): p t * c * i * = (P t * -3 + P t * -2 + P t * -1 )/3.
Wild bee and honeybee data Numbers of managed honeybee colonies per country were obtained from the FAO (http://www. fao. org) and averaged for 1991-2009. The data had been compiled and provided to the FAO by the countries' governments. Data for the number of wild bee species per country was retrieved from the online database "Checklist of Western Palaearctic Bees"  (Kuhlmann et al. 2012 ). The checklist is a compilation of taxonomic and distribution data on country level that is largely based on information assembled for the "Discover Life bee species guide and world checklist (Hymenoptera: Apoidea: Anthophila)"  (Ascher & Pickering 2012). It contains regularly updated information from both published and unpublished sources including data from a whole range of private and public collections that are provided by European wild bee experts.
To test for spatial autocorrelation of residuals, we visually assessed the data using a variogram based on the residuals of the linear model and Euclidean distances among countries (R software, gstat package, variogram function). The variogram did not show any autocorrelation of residuals. Where necessary we log 10 transformed the response variables to achieve normality and homogeneity of variances. All statistical tests were run in R (R Development Core Team 2012). Results are given in Tables 1, 2a and 2b.
Acknowledgements We thank  Henrik von Wehrden  for help with data analysis as well as an anonymous reviewer and  Klaus Hövemeyer  whose comments greatly improved our manuscript. SDL is funded by the  German Science Foundation  ( DFG  project:  LE 2750/1-1 ) and LAG by  UBACYT  ( 20020100300014 ) and PIP 2012-2014. The study is part of the  STEP (Status and Trends of European Pollinators , Grant No. 244090-STEP-CP-FP ) funded by the  European Commission  in the 7th  Framework Programmes for Research and Technological Development.
Sampling and Molecular Protocols We used 16 oysters from four different natural populations collected on the Atlantic and Mediterranean coasts, in Italy, Greece and France. Genomic DNA was extracted from samples of gill tissue using the Wizard DNA Clean-Up System (Promega) according to the manufacturer's recommendations. Quality and concentration were assessed on a 1% agarose gel and by using an Eppendorf BioPhotometer. Concentrations were equilibrated to 100 ng. mL 21 per DNA sample. Primers were designed from 114 EST sequences by using the online software Primer3  (Rozen and Skaletsky 2000). Expected fragment lengths in the absence of introns varied between 160 bp and 660 bp depending on the EST used. The polymerase chain reaction (PCR) protocol was the same as in  Sauvage et al. (2007).
Analysis of DNA sequence polymorphism Sequence alignment was performed with ClustalW via the BioEdit interface  (Hall 1999). Verification by eye and multiple alignments of sequences obtained from different PCR and sequencing reactions for the same individual were used to correct for artifactual mutations. All sites with two simultaneous fluorescent signals were carefully individually inspected and considered to be heterozygous sites if the intensity of the least intense peak was greater than 30% of the intensity of the most intense peak. The cDNA was used to identify intronic regions. A BLAST homology search was performed on GenBank (http://blast. ncbi. nlm. nih. gov/Blast. cgi) to identify orthologous sequences which, together with ORF-Finder  (Rombel et al. 2002) , enabled the annotation of open reading frames (ORFs) and untranslated regions (UTRs).
The format of our dataset did not allow us to estimate a more detailed distribution of fitness effects (e. g. ,  Eyre-Walker et al. 2006). Although simpler, the method of  Fay et al. (2001)  does not rely on a specific population genetic model (e. g. , the Wright-Fisher model), and in the spirit of the McDonald-Kreitman approach (1991), it capitalizes on the fact that neutral and potentially selected sites are interspersed with each other throughout a gene. Such sites are therefore expected to have the same evolutionary history and sampling (i. e. , a shared genealogy). A possible deviation from the standard coalescent, as could be expected in marine species with a skewed offspring distribution  (Eldon and Wakeley 2009) , is not expected to bias the method, which simply assumes shared genealogies for the two categories of mutations whatever their shapes (e.
DNA polymorphism in O. edulis From the 114 loci that we attempted to amplify, 13 presented no amplification signal, which could be explained by the presence of an intron within the priming sequences or a long intron between the two primers, and 47 presented a multibanded pattern. Among the 54 loci that produced a single-banded pattern on agarose gel, 10 produced unreadable electropherograms (overlapping peaks), two were composed of very large introns (. 1000 bp), which precluded a forward/ reverse sequencing double check, and two could not be aligned with their corresponding cDNA, indicating a lack of specificity of the primers or PCR conditions. Forty loci produced usable sequence sets and were long enough to be annotated and deposed in the GenBank database (accession nos. JN680816 to JN680855).
A similarly high u n /u si was estimated for every functional group, including ribosomal proteins, which are known to be highly constrained in other species. Representativeness of the genome diversity was also checked by computing GC3 and ENC on our set of 37 loci and on the full EST database (Figure  S3 ). Codon bias proved to be low (high value of ENC) and GC3 moderately low. The distribution of the two measures was not significantly different between the two datasets. We also tested whether codon biases were correlated with diversity indices. Neither u s nor u nc or u n were significantly correlated with ENC (u s : r = 20. 12, P = 0. 49, u nc : r = 20. 04, P = 0. 79, u n : r = 0. 13, P = 0. 45). Finally, we verified if some errors in the annotation of the ORFs could have biased the results by removing every loci with an annotated UTR, and the results were not profoundly modified (p n = 0.
0023, u n = 0. 003, p n /p si = 0. 31, and u n /u si = 0. 48). Tajima's D was computed with silent mutations for each polymorphic locus. Negative values were obtained for 24 loci (ranged from 22. 01 to 20. 15) and positive values for 10 loci (ranged from 0. 12 to 2. 43). Among these values, none were statistically different from zero after a correction for multiple testing. The average Tajima's D was D = 20. 38 with the 37 loci dataset and D = 20. 5 with the 35 loci dataset. Distribution of F ST values for nonsynonymous and silent SNPs between all populations, and between Mediterranean and Atlantic populations, are presented on Figure  S4. Although a large variance is observed among loci due to the small size of our samples, this analysis shows that the genetic differentiation was low overall and did not differ between the two categories of mutations.
2001) , the fraction of amino acid-changing mutations that behave as neutral (or at least as silent mutations do). We then estimated that 44% of amino acid mutations are strongly deleterious and not found in the sample, and 33% are slightly selected and segregate at low frequency. We observed 68 nonsynonymous SNPs in the sample (35 loci dataset) whereas 110 would have been expected from the number of silent SNPs if nonsynonymous mutations were all neutral. From the calculation above, a fraction f 0 = 0. 23 of nonsynonymous mutations are estimated to be neutral, which allowed us to infer that 25 of the 68 observed nonsynonymous SNPs were expected to be neutral and the remaining 43 were expected to be non-neutral in our sample of 16 oysters. By assuming non-neutral nonsynonymous alleles are present only once in the sample  (Fay et al.
Figure2(A) Nonsynonymous-to-silent diversity ratio (un/usi) in the O. edulis nuclear genome. All SNPs: full dataset; without singletons: when singletons are removed from the dataset;. 0. 1: SNPs with a minor variant frequency greater 0. 1;. 0. 2: SNPs with a minor frequency greater than 0. 2. ; shared: SNPs shared between at least two populations from the Atlantic or the Mediterranean Sea. (B) Allele frequency spectrum of nonsynonymous (dark), silent (gray), and expected under the neutral Wright-Fisher model (light). 020. 1: SNPs with a minor variant frequency below 0. 1; 0. 120. 2: SNPs with a minor variant frequency between 0. 1 and 0. 2;. 0. 2: SNPs with a minor variant frequency greater than 0. 2. 35 loci dataset.
ACKNOWLEDGMENTS We would like to thank  Toni Gossmann  for sharing his dataset,  John Theodorou  for supplying the sample from Greece,  Luca Bargelloni  and  Pierre Boudry  for the Italian samples, the  French network Repamo  ( REseau PAthologie des MOllusques ) for the French samples,  Helen McCombie-Boudry  for corrections of the manuscript, and two reviewers for helpful comments. This research was funded by the  European Transnational   Seafare project (Sustainable and Environmentally Friendly Aquaculture for the Atlantic Region of Europe ) and co-funded by  Électricité Réseau Distribution France , the  Atlantic Area Transnational Program  (2007Program ( -2013) ) and  Agence National de la Recherche  ( Hi-Flo  project  ANR-08-BLAN-0334-01 ). This is article  2013-002  of  Institut des Sciences de l'Evolution de Montpellier.
Immunostaining Cells were fixed in 4% paraformaldehyde and incubated for 10 min in blocking buffer (phosphate-buffered saline, 1% bovine serum albumin and 0. 1% Triton X-100). Primary antibodies (Supplementary Table  3 ) were diluted in blocking buffer and applied overnight at 4 1C. After three washes in phosphate-buffered saline, secondary antibodies conjugated to Alexa fluorophores (Molecular Probes, Eugene, OR, USA) were diluted at 1:1000 in blocking buffer and applied for 2 h at room temperature. The cells were washed at least three times in phosphate-buffered saline and visualized on a Zeiss inverted fluorescence microscope (Axiovert, Carl Zeiss, LePecq, France). Image acquisition was performed using the Axiovision LE software (Carl Zeiss). For nuclear counterstaining, cells were incubated in 10 mg ml À 1 Hoechst 33258 (Sigma) for 10 min after immunostaining.
Statistical analyses To assess the quality of the assay, the z' factor value was determined. This factor represents a dimensionless parameter, whose value can range between o0 and 1. It is defined as z 0 ¼ 1 À ((3s þ -3s À )/(m þ ± m À )) , where s and m, are the s. d. 's and the means, respectively, of the positive ( þ ) and negative ( À ) controls. 20 he raw data of the screening were subjected to analysis of variance following by a Dunnett's test to evaluate statistical differences between cells treated with tested compounds and dimethyl sulfoxide-treated controls.
ACKNOWLEDGEMENTS We thank  Cecile Denis  and  Dr Mathilde Girard  for their help with the iPSC lines,  Yves Maury  and  Marc Lechuga  for training and constant support on HTS and HCS platforms,  Christine Varela  and  Dr Nathalie Lefort  for karyotyping the cells lines. We also thank the cell bank of  Pitie-Salpe  ´triere hospitals and the  Clinical Investigation Center of Robert Debrehospitals  for their technical assistance. We also thank  Fabienne Giuliano  who helps us with ASD1 sample collection. This study has been in part funded by  Hoffmann-Laroche and Servier's laboratories, region Ile de France (DIM STEM Pole) , the  Bettencourt-Schueller foundation , the  Orange foundation , the  FondaMental foundation , the  Conny-Maeva foundation , the  Cognacq-Jay foundation , the  ANR  ( ANR-08-MNPS-037-01-SynGen ),  Neuron-ERANET (EUHF-AUTISM).
Molecular modelling of GIF mutations Building and optimization of explicit hydrogen atoms onto the heavy atom structure of PDB entry 2PMV  [17]  were performed using the BRUGEL molecular modelling package  [18]. Forces and interaction energies between atoms were calculated using the CHARMm potentials  [19]  implemented in BRUGEL on an O2 R10000 Silicon Graphics station. Accessible surface area (ASA) computation on either wild type or energy-minimized M79T (79 is the position of the mutated amino-acid residue in mature protein, after cleavage of the 18 amino-acid signal peptide and 97, the position that includes the residues of signal peptide) mutant structures was done using unified heavy atoms. Secondary structures were assigned on wild type and mutant M79T structures with the DSSP program  [20]  implemented in BRUGEL.
We determined the ASA of the B12 binding site using a probe radius of 5 A, a value close to the 5. 8 A average gyration radius of vitamin B12. We could thus show that the molecular volume of the cofactor binding site drops from 4372 in wild type GIF to 3557 A 3 in M79T, which represents a change of À19%, sufficient to impair vitamin B12 and/or cubilin binding. To verify this proposition, we took advantage of the fact that helices a3, a5, a7, a8 and a12 and their immediate surroundings remain unperturbed and used these secondary structures elements as "anchors" to fit both structures, using the AZFIT program as implemented in BRUGEL. From this superimposition, we extracted B12 binding-site residues along with bound vitamin B12. This result is illustrated with Rasmol  [21] , which suggests the occurrence of several steric clashes between cobalamin and binding-site residues in the GIF 79T mutant structure as well as impaired interactions for some residues.
The fecal specimen was preserved at -80°C after collection. Strain JC13 T (Table  1 ) was isolated in January 2011 by cultivation on Brain Heart Infusion agar (Becton Dickinson, Pont de Claix, France), after a 10 day preincubation in anaerobic blood culture bottle. The 16S rRNA sequence (GenBank accession number JF824807) of D. fastidiosa strain JC13 T was compared to sequences in GenBank using BLAST  [50]  and showed a highest similarity of 89. 71% with Clostridium innocuum (Figure  1 ). By comparison with type species from genera within the family Erysipelotrichaceae, D. fastidiosa exhibited a 16S rRNA sequence similarity ranging from 69. 90 to 89. 71%. Since these values are lower than the 95% threshold recommended by Stackebrandt and Ebers to delineate new genera without performing DDH  [3] , we propose to classify strain JC13 T within a novel genus.
5% tri-fluoracetic-acid, and allowed to dry for five minutes. Measurements were performed with a Microflex spectrometer (Bruker). Spectra were recorded in the positive linear mode for the mass range of 2,000 to 20,000 Da (parameter settings: ion source 1 (IS1), 20 kV; IS2, 18. 5 kV; lens, 7 kV). A spectrum was obtained after 675 shots at a variable laser power. The time of acquisi-Standards in Genomic Sciences tion was between 30 seconds and 1 minute per spot. The twelve JC13 spectra were imported into the MALDI BioTyper software (version 2. 0, Bruker) and analyzed by standard pattern matching (with default parameter settings) against the reference spectra from 4,334 bacteria (as updated on August 29, 2012), including spectra from 17 species within the Erysipelotrichaceae, contained in the BioTyper database.