dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements This research was funded by two projects: the  blank agronomy  project  ANR-09-BLAN-0083  ANDROPIG ( French National Research Agency)  and the  EC  project  ALCASDE (DG SANCO ). We thank  M. Génissel ,  F. Guérin ,  M. Lefèbvre ,  C. Guérin ,  E. Bobillier ,  A. M. Mounier ,  H. Demay ,  B. Carrissant ,  M. Alix ,  J. Liger  and  J. F. Rouaud  for their technical help.
coli BL21(DE3) for protein expression. After transformation, E. coli BL21(DE3) cells were grown at 37°C in 250 mL LB broth supplemented with 50 μg mL -1 kanamycin. At an OD 600 of 0. 5, IPTG was added to a final concentration of 1 mM, and growth was continued for 4 h. The culture was then centrifuged at 7,000 × g for 15 min at 4°C. The pellet obtained was stored at -20°C until applied onto heparin Sepharose as described above. The GenBank accession numbers for the map-HBHA (strains K-10 and ATCC19698) sequences are L V G I E L P G K A E A A G K* Figure 6 Fragmentation spectrum of the HBHA 154 LVGIELPGKAEAAGK 168 peptide with post-translational modification. Shown is a spectrum obtained by nanoLC-MS/MS analysis with HCD fragmentation mode using LTQ Velos Orbitrap mass spectrometer. The precursor ion had an m/z 733.
In the scan range of m/z 300-1800, the 10 most intense peptide ions with charge states ≥2 were isolated for HCD fragmentation. Raw data files were converted to MGF. The data were searched against nr NCBI database (Eubacteria) using MASCOT search engine (version 2. 3). Carbamidomethylcysteine was set as a fixed modification, and oxidation of methionine, N-terminal acetylation and methylation of lysine were set as variable modifications. Two missed cleavages were allowed. The tolerance of the ions was set to 10 ppm for parent and 0. 1 Da for fragment ion matches. Mascot results were subjected to the Scaffold 3 software (version 3. 2). Peptide identifications were accepted if they could be established at a greater than 95. 0% probability as specified by the Peptide Prophet algorithm  [30]. Protein identifications were accepted if they could be established at a greater than 99.
Experimental design and measurements Experimental data on the change in DFI and BW were obtained for gilts and barrows for which performance was recorded between ,30 and 110 kg. The data originated from 10 batches of 144 pigs each that were raised at the experimental facilities of IFIP  (Romille, France)  between May 2007 and September 2011. Within each batch, 36 barrows and 36 gilts were obtained from Large White 3 Landrace (LW 3 LD) sows inseminated with semen from crossbred Large White 3 Pietrain (LW 3 PP) sires. The other 36 barrows and 36 gilts within a batch were obtained from one of eight other lines of sires used in this study: Pietrain (PP, batches A and B), Pietrain 3 Duroc (PP 3 Du, batch C), Duroc (Du, batches D and E), four commercial synthetic lines (SL1 to SL4, batches F, G, H and I), or Large White dam line (LW, batch J).
The lean content (%) of the carcass was calculated from F34 and M34 (mm), using the equation commonly used in French slaughter plants: 62. 19 -0. 729 3 F34 1 0. 144 3 M34  (Daumas et al. , 2010). Performance and carcass data were submitted to a multifactorial ANOVA with sex (two levels), batch (10 levels), crossbreed within batch (nine levels) and interactions as main effects  (proc MIXED; SAS, 2000). The pig was considered as the experimental unit and the pen within a batch as a random effect. Carcass traits were analyzed using BW at slaughter as a covariate. Model parameters describing feed intake and growth A Broyden-Fletcher-Goldfarb-Shanno optimization method was used to fit simultaneously the DFI and BW equations to data using the InraPorc (2006) model. Feed intake was modeled as a gamma function of BW: DFIðMJNE=dayÞ ¼ a Âðb Â BW Â e ÀbÂBW þ 1Þ Âc Â BW 0:60 where 'a' (dimensionless) and 'b' (per kg) are parameters and 'c' is a constant (0.
75 MJ NE/kg BW 0. 60 per day). With this function, feed intake is described as multiples of the NE intake above maintenance, so that the pig eats for maintenance when it reaches maturity. The expected DFI at 50 (DFI 50 ) and 100 kg (DFI 100 ) were used to replace parameters 'a' and 'b'. The growth curve was parameterized using three parameters: BW at 70 days of age (BW 70 , kg), mean protein deposition rate between 70 days of age and 110 kg BW (PDm, g/day), and the shape parameter of the Gompertz function (B Gompertz , per day) describing the precocity of protein deposition (PD). These three parameters determine the Gompertz function used to model PD (see  van Milgen et al. (2008)  for detailed equations and for the relation between BW and PD). When control started after 70 days of age, BW 70 and PDm were obtained by extrapolating data between the age at control start and 70 days.
The set of five parameters describing the feed intake and growth curves of an individual pig is referred to hereafter as the profile. The duration of the experiment from 70 days of age to 110 kg BW (duration) was also calculated, even though it is not required to characterize the pig (i. e. it is a function of the other model parameters). Forty-eight pigs died or were removed from the pens before slaughter because of sanitary issues. Animals recorded with sanitary issues during the data collection (n 5 19) were also excluded because they may not have been capable to express their growth phenotypic potential. For some other pigs (n 5 85), it was not possible to estimate model parameters because of calibration failure or unrealistic values for the estimated parameters (e. g. negative values of B Gompertz or values of PDm.
Discussion Although the data were obtained from a single experimental farm, a wide range in performance data was obtained for pigs of different crossbreeds and sexes. Most model parameters were affected by batch, especially the characteristics of pigs at the beginning of the fattening period. Differences in BW 70 resulted from differences in ADG during the preceding physiological stages. A significantly lower BW 70 was observed for batches of pigs that were born, suckled or weaned in summer or early fall. During the lactation period, the growth rate of piglets depends on the milk production of sows, which is influenced mainly by ambient temperature (Black et al. , 1993). Ambient temperature was controlled in the experimental fattening rooms, but not in the lactation and post-weaning units, leading to possible differences in performance during this period.
Chromatin immunoprecipitation (ChIP) analysis using a TLX-specific antibody revealed that TLX bound to the promoter and proximal intron regions of TET3 containing the putative TLXbinding sites in both PBT003 and PBT707 cells (Supplementary Fig. 9a, b ). At position 1 (P1, around the promoter region) and position 5 (P5, intron 2), the binding sites of TLX was associated with a higher level of repressive histone mark H3K9me3 than that of active histone mark H3K4me3 in both PBT003 and PBT707 cells (Supplementary Fig. 9c ). These data suggest that TLX could regulate the transcription of TET3 by directly binding to regulatory regions of the TET3 gene. To identify downstream targets of TET3 in GSCs, microarray analysis was performed. The gene expression profile of PBT003 cells treated with TET3 shRNA-expressing lentivirus was compared with PBT003 cells expressing control shRNA.
Data sets from microarray analysis of PBT003 cells transduced with TLX shRNA or control RNA were included for comparison. Among the differentially expressed genes, an inverse correlation in gene expression was observed in TLX knockdown cells and TET3 knockdown cells (Fig. 8f ), consistent with our hypothesis that TLX represses TET3 expression. Specifically, genes related to tumour-suppressive function, including BTG2, TUSC1, BAK1, LATS2, FZD6 and PPP2R1B, were upregulated in TLX knockdown cells, but downregulated in TET3 knockdown cells (Fig. 8g  and Supplementary Fig. 10 ), suggesting that the TLX-TET3 regulatory cascade could regulate the growth and self-renewal of GSCs through regulating these downstream tumour suppressors. Because TET3 is a dioxygenase that converts 5mC to 5hmC, we next tested whether the TLX-TET3 regulatory cascade could regulate 5hmC level in GSCs.
5 nmole siRNA per mouse with N/P ratio of 5, G5/RGDK ratio of 0. 426) by intratumoral injection once a week for 6 weeks. Tumour growth was monitored by bioluminescence imaging once a week for 7 weeks. The bioluminescence intensity, mouse body weight and mouse survival were analysed. Microarray analysis and GBM subtype determination. For GBM subtype characterization, total RNAs were extracted from ten lines of GSCs using RNeasy Mini Kit (Qiagen). Microarray analysis was performed using GeneChip Human Genome U133A 2. 0 Array (Affymetrix). Microarray labelling, hybridization and quality control measurements were performed in the Integrative Genomics Core of City of Hope. The microarray expression data of the ten GSC samples were pooled together with published microarray expression data of 173 TCGA samples  37.
After batch removal, principle component analysis (PCA) was performed on the pooled data set using Partek Genomics Suite software, version 6. 6 (2014 Partek Inc). 747 relevant genes were used for PCA according to the data filtering approach as described  37. Centroids of the four GBM subtype clusters were defined by PCA and the Euclidean distance of each GSC sample to the centroids were calculated. Samples were classified to the GBM subtype that has the least Euclidean distance value. To identify TLX or TET3 downstream target genes, PBT003 cells were transduced with scrambled control RNA or TLX shRNA-expressing lentivirus (for shTLX microarray), or control RNA or TET3 shRNA-expressing lentivirus (for shTET3 microarray). Three days after virus transduction, total RNA was extracted using RNeasy Mini Kit (Qiagen).
Microarray analysis was performed using GeneChip PrimeView Human Gene Expression Array (Affymetrix). Microarray labelling, hybridization and quality control measurements were performed in the Integrative Genomics Core of City of Hope. Microarray analysis was performed using Partek Genomics Suite (Partek, Inc. ). Expression values were robust multi-array average (RMA) normalized  57  , and fold-change values were calculated using least-squares mean between samples. Genes were defined as differentially expressed if they showed an absolute value of fold-change larger than 1. 5. Heat maps to visualize differentially expressed genes were produced in Partek using Euclidian distance for hierarchical clustering of standardized expression values. Microarry a data have been deposited to NCBI's GEO under accession number GSE75945.
Acknowledgements This work was supported by the  Sidney Kimmel Foundation , the  Margaret E. Early Research Trust , the  James S. McDonnell Foundation , the  Sidell Kagan Foundation  and  California Institute for Regenerative Medicine   TR2-01832  and  RB4-06277  (to Y. S. ) and  Agence Nantional de Recherche  project  DENANORNA  (to L. P. ). Research reported in this publication was also supported by the  National Cancer Institute of the National Institutes of Health  under award number  P30CA33572 , and included work performed in.
Acknowledgments This work and the workshop it is based on were funded by the  KNEU  project within the  7th Framework Programme  of the  European Commission  (Contract No. 265299 ). Open Access This article is distributed under the terms of the Creative Commons Attribution 4. 0 International License (http://creativecommons. org/licenses/by/4. 0/),which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Yeast two hybrid screening of a Pf cDNA library To further detect additional Pips in P. falciparum, a cDNA library was screened in a yeast two hybrid (Y2H) system using full-length PfPP1c as bait and clones growing on high stringency selection media to reduce the number of false positive clones. Five independent screens yielded 189 clones from a total of 3. 3 × 10 6 clones screened. After sequencing, all clones showed open reading frames encoding Pf genes with 53 clones in frame with GAL4AD and 136 clones out of frame. Amino acid sequence comparison revealed that 8 proteins in frame with GAL4AD were also found among the out-of-frame clones. These data are in agreement with an earlier observation indicating that out-of-frame proteins could be considered as valid interactors in Y2H screening  [21]  and with recent results suggesting that translational frameshift could be means for yeast to reduce the level of expression of exogenous proteins in order to grow on selective media.
Binding data presented in Fig. 2a  showed that biotin-PfPP1 binds to the 5 proteins tested. These data likely suggests that the identified Pips are direct interactors of PfPP1. Next, we searched to check the direct interactions of Pips identified by Y2H screening and PfPP1. Fifteen recombinant PfPips were produced out of 30 cloned cDNAs tested (Additional file 5: Figure  S1 , Additional file 6: Table  S5 ). The failure for the production of some proteins could be due to the lack of expression and/or to the toxicity for bacteria. For the binding with H2A and H2B, commercially available human recombinant proteins were used as they showed 67 and 63 % identity with PfH2A and PfH2B respectively (Additional file 7: Figure  S2 ). As depicted in Fig. 2b , biotin-PfPP1 was able to bind to 14 recombinant proteins out of 17 tested.
This library-transformed yeast strain is referred below as the prey strain. The cDNA encoding for P. falciparum protein phosphatase type-1 (PfPP1, PlasmoDB accession number: PF3D7_1414400) was cloned in the pGBKT7 vector (Clontech) to generate a PfPP1-pGBKT7 plasmid allowing the production of PfPP1 fused with the GAL4 DNA binding domain. Y187 yeast competent cells (Clontech) were then transformed with this construct according to the manual of Yeastmaker™ Yeast Transformation System 2 (Clontech). The expression of PfPP1 was checked by immunoblot using anti-GAL4BD antibody. This strain was used as a bait to screen protein interactions with the P. falciparum cDNA library by mating.
Identification of potential Pips The prey plasmids from positive yeast clones were isolated using the Plasmid DNA Purification kit (Macherey-Nagel). To facilitate yeast lysis, the equivalent of 100 μl of glass beads (Sigma) was added in the resuspension buffer. To amplify the plasmid obtained, it was transformed to E. coli DH5α cells (Life Technologies) followed by selection on LB/Ampicillin and LB/Kanamycin plates. Plasmids were isolated once again using the Plasmid DNA Purification kit and then to estimate the sizes of the specific inserts on positive prey plasmids, plasmids were digested using the SfiI restriction enzyme. The positive prey plasmids were characterized by sequencing and BLAST searches to identify the corresponding P. falciparum genes in the PlasmoDB database (v24).
In silico screening The consensus sequence used to identify potential interactors of PfPP1, was [KR][KR][ACHKMNQRSTV]V [CHKNQRST][FW]. It was based on the crystal of PP1 with a RRVSFA peptide  [38]  and on consensus sequences defined by different publications  [12, 30, 31]. After identification of the putative partners, the positions -10 to +10 of RVxF motifs were aligned by BioEdit software (v7. 2. 5) to establish a new consensus sequence.
Availability of data and materials All genome and protein sequence files are available through PlasmoDB (http://plasmodb. org/plasmo/) and GenBank (http://www. ncbi. nlm. nih. gov/protein/) and the data are included in the manuscript and in Additional file 1: Table  S1 , Additional file 2: Table  S2 , Additional file 3: Table  S3 , Additional file 4: Table  S4 , Additional file 6: Table  S5 , Additional file 7: Figure  S2 , Additional file 8: Figure  S3 , and Additional file 9: Figure  S4.
The entire dataset is available in Table  S1. Proteins were ranked in order of increasing ratios (Figure  1A ). We identified 21 proteins with a LogRatio R 3 in three independent experiments (Figure  1B ; Table  S1 ). This group included the DNA repair and DNA replication proteins KU80, DNA-PKcs, MCM2, Top2A, and LIG1; the two components of the chromatin-remodeling complex WICH (BAZ1B and SMARCA5); the structural component of the nuclear matrix NUMA1; as well as proteins implicated in RNA metabolism (SNRNP200, KHSRP, PRPF8, USP39, DDX21, DHX15, SRSF3, and PCBP1). To obtain a broader perspective on the chromatin composition in the vicinity of replication forks upon inhibition of Top1, we also considered proteins that exhibited a LogRatio R 4 in two of three independent experiments. This yielded a list of 50 proteins that form an interconnected functional network, as revealed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database analysis (Figure  1C ).
ACKNOWLEDGMENTS We thank  Patrick Varga-Weisz ,  Vjekoslav Dulic , and Gerald Lossaint for reagents;  Philippe Pasero  and the laboratory members for comments on the manuscript; and  Philippe Pourquier  for advice. This work was supported by grants from the  Fondation ARC pour la Recherche sur le Cancer , the  Agence Nationale pour la Recherche , and la  Fondation de France  (to A. C. ),  La Ligue contre le Cancer Herault and Projet Fondation ARC  (to C. R. ), and a  European Research Council Consolidator  (to M. L. ).
AMPK phosphorylates and activates mouse PDE4B in vitro. To test whether PDE4B could be a direct AMPK substrate, we cloned the 721-amino-acid-containing PDE4B isoenzyme (GenBank: AF326555. 1) from primary mouse hepatocyte total cDNA. The recombinant protein was expressed in Escherichia coli as a glutathione S-transferase (GST) fusion protein and purified before removing the tag by specific proteolytic cleavage. Both bacterially expressed recombinant activated AMPK and purified PKA catalytic subunits phosphorylated PDE4B in the presence of [g-32 P] ATP in vitro (Fig. 5a ), and using AMPK, a stoichiometry of B1 mol of phosphate incorporated per mol of PDE protein was reached (Fig. 5c ). With both AMPK and PKA, phosphorylation of PDE4B in the presence of [g-32 P] ATP was additive, suggesting the presence of distinct phosphorylation sites.
The concentrations of cAMP reached in our study in cultured mouse hepatocytes incubated with glucagon (up to 20 pmol per mg of protein in the absence of PDE inhibitors, Figs  1e,2c  and 3b ) fit well with values reported in the literature  [40] [41] [42] [43]. These values were obtained using a commercial ELISA-based assay and were much lower than those measured by radioimmunoassay (B150 pmol per mg of protein, see for example Fig. 1a ) or by HPLC (B100 pmol per mg of protein, data not shown) when the three methods were compared on the same sample. Such differences are likely to be due to differences in sample quenching. For radioimmunoassay, hepatocyte incubations were immediately stopped with HCl. For HPLC, the cells were immediately extracted with perchloric acid, whereas for measurements by ELISA, the stopping mixture used for rapid lysis of hepatocytes was a non-deproteinizing buffer containing detergent and EDTA.
HPA000962), anti-total AMPK b1(R&D Systems, Catalogue No. AF2854) and anti-total AMPK b2 (R&D Systems, Catalogue No. MAB3808), anti-PThr172-AMPK (T172) (Cell Signaling Technologies, Catalogue No. 2535, anti-P-AMPK-substrate (Cell Signaling Technologies, Catalogue No. 5759), anti-P-PKA-substrate (Cell Signaling Technologies, Catalogue No. 9624), anti-total Raptor (Cell Signaling Technologies, Catalogue No. 2280) and anti-P-Ser792-Raptor (Cell Signaling Technologies, Catalogue No. 2083), anti-total CREB (Cell Signaling Technologies, Catalogue No. 9197), anti-phospho-Ser133-CREB (Cell Signaling Technologies, Catalogue No. 9198) and anti-total PDE4B (Origene, Catalogue No. TA503471) antibodies were from the sources cited. Anti-P-Ser14-GP and anti-total AMPK (a1 and a2) antibodies were kindly provided by Grahame Hardie (University of Dundee, UK).
The reaction was stopped on ice, 20 mg of BSA was added as carrier and proteins were precipitated with a final concentration of 10% (w/v) trichloroacetic acid for 45 min on ice. Precipitated proteins were collected by centrifugation (20,000g Â 10 min at 4 °C), washed in acetone, vacuum-dried and resuspended in 50 ml of 50 mM NH 4 HCO 3 , pH 8. 0, for overnight digestion at 30 °C with trypsin. Peptides were separated by reverse-phase narrow-bore HPLC and radioactive peaks were analysed by LC-MS/MS as described  61. Multi-stage activation was enabled for phosphate neutral loss of 98, 49 or 32. 66 with respect to the precursor m/z. Peak lists were generated and searched using SequestHT and PhosphoRS 3. 1 against a home-made protein database containing the human PDE sequences obtained from Uniprot and the different mutants used in this study.
Acknowledgements We thank  Nusrat Hussain  and  Gae ¨tan Herinckx  for expert technical assistance. Y. -C. L. was supported by the  Fund for Medical Scientific Research (FNRS, Belgium)  and the  Interuniversity Attraction Poles (IAP) Programme of the Belgian Science Policy  ( P7/13 ). M. J. was supported by the  Fund for Scientific Research in Industry and Agriculture (FRIA). The work was funded by the  Interuniversity Poles of Attraction Belgian Science Policy  ( P7/13 ), by the  Directorate General Higher Education and Scientific Research French Community of Belgium , by the  Fonds de la Recherche Scientifique (FNRS, Belgium)  under Grant no. 3. 4518. 11 ,by the  Region Ile-de-France (CORDDIM)  and by the  SocieteFrancophone du Diabe  `te (SFD).
RNA preparation and RT-qPCR. Total RNA was isolated from DiFi cells using the RNeasy mini Kit (Qiagen, Hilden, Germany) with a DNAse digestion step. Total RNA (1 mg) was reversetranscribed using the SuperScript III reverse transcriptase (Invitrogen, Life Technologies). Real-time quantitative PCR (qPCR) was performed using the LC480 cycler (Roche Diagnostics, Meylan, France) according to the manufacturer's instruction. The amplification specificity was verified by melting curve analysis. Real-time PCR values were determined by reference to a standard curve that was generated by real-time PCR amplification of a serially diluted cDNA sample using primers specific for p27, BIM and 28s. The quantification data were normalised to the amplification data for the reference gene 28s. Drug sensitivity assay.
Cell growth inhibition and cell viability after cetuximab incubation were assessed using the sulforhodamine B (SRB) assay, as previously described  (Candeil et al, 2004; Paillas et al, 2011). Cell death analysis. Cell death analysis was performed using the Annexin V-FITC/7-AAD Kit (Beckman Coulter, Indianapolis, IN, USA). Cells were incubated with 0. 5 mg ml À 1 cetuximab, 5 mM SB202190, or 0. 5 mg ml À 1 cetuximab þ 5 mM SB202190 for 48 h. Cells (1 Â 10 6 ) and the corresponding supernatants were labelled using the Annexin V-FITC/7-AAD Kit (Beckman Coulter, Indianapolis, IN, USA). Analyses were done on a FC500 Beckman Coulter Flow Cytometer (Beckman Coulter). Annexin V-FITC positive cells were quantified using the Flow Jo analysis software (Treestar, Ashland, OR, USA). Cell cycle analysis.
Cells were treated with 0. 5 mg ml À 1 cetuximab, 5 mM SB202190, or 0. 5 mg ml À 1 cetuximab þ 5 mM SB202190 for 48 h. In all, 1 Â 10 6 cells were pelleted, washed with PBS, fixed in 75% ethanol, treated with 100 mg ml À 1 RNAse (Qiagen) and stained with 40 mg ml À 1 propidium iodide. The cell cycle distribution was determined with a FC500 Beckman Coulter Flow Cytometer using the FL-3 channel. Cells were gated on a dot plot that displayed the DNA-pulse-peak vs the DNA-pulse area to exclude doublets. Cell cycle distributions were illustrated using the Flow Jo analysis software (Treestar, FLOWJO, Ashland, OR, USA). Cell proliferation analysis. Cell proliferation was measured by incorporating 5-ethynyl-2 0 -deoxyuridine (EdU) into DNA during the active DNA synthesis (i. e. , the last 30 h of culture).