dataesr/scientific-paragraphs-categorization huggingface dataset:
Genes differentially expressed between of Viridiflora and Old Blush were investigated using the MA-plot-based method with the random sampling model  (Wang et al. , 2010). 672 unisequences were up-regulated and 666 were down-regulated (Figure  3C ) in Viridiflora compared to Old Blush, with a fold change of at least 3 and a P-value < 0. 001 (Table  1 ). Flower development genes that exhibited significant expression difference between Old Blush and Viridiflora were for RT-qPCR validation. Expression of 24 genes among the differentially expressed genes was analyzed using RT-qPCR (Figures  4A, B ). A good correlation (Pearson correlation coefficient = 0. 98) between RT-qPCR data and the RNA-Seq data was observed for the 24 analyzed genes, suggesting that our transcriptomics data are accurate in the different tissues and experimental conditions (Figure  4C ).
In addition, the bHLH transcription factor UNE10  (Toledo-Ortiz et al. , 2003; c18395_g2)  and homeotic gene BEL1 (c20518_g1) were also significantly up-regulated (Table  2 ). BEL1 is known to act as negative regulator of AG and has a major role in ovule patterning and in determination of integument identity via its interaction with MADS-box factors  (Ray et al. , 1994; Mizumoto et al. , 2011; Sharma et al. , 2014). Taken together these data show that the phyllody phenotype in Viridiflora is mainly associated with modified expression of flowering and flower development related genes.
These data together suggest that the ABCE genetic model of floral organ identity determination is likely conserved in the rose. In Viridiflora flowers, the expression of RcAP1 was significantly increased in the sepal and petal whorls (Figure  6A ). RcAP1 expression was about 1. 7 times induced in whorl 1 and strikingly 20-fold induced in whorls 2 compared to that in Old Blush. The expression of RcAP2 was up-regulated in all whorls of Viridiflora flowers. Interestingly, the expression of RcAP2 was significantly up-regulated in stamens and pistils whorls of Viridiflora (Figure  6B ) and conversely the expression  of the C-class gene RcAG was significantly down-regulated in whorl 4 compared to that in Old Blush (Figure  6E ). It should be noted that RcAG was about eightfold over-expressed in the pistils compared to stamens (Figure  6E ).
Gene expression analysis in flowers early during development, showed that the phyllody phenotype in Viridiflora is associated with ectopic expression of the flowering time gene RcSOC1 and with misexpression of the ABCE flower organ identity genes leading to loss of petal, stamen and pistil organ identity (Figure  7 ). These data indicate that in Viridiflora a shift of the expression of the A-class gene RcAP2 toward the third and fourth whorls together with significantly reduced expression of B, C, and E gene classes are associated with the observed phyllody phenotype. These data also highlights the antagonist effect of the A and C class gene. The A-class gene AP1 is known to be involved in sepal and petal organ identity determination. In R. chinensis cv. Old Blush, RcAP1 showed high expression levels in developing sepals and low expression levels in developing petals (Figure  6A ).
Similar data were observed in R. hybrida  (Mibus et al. , 2011)  and in other flowering plant species  (Huijser et al. , 1992; Mandel et al. , 1992). Interestingly, we observed a strong down-regulation of the B-class genes RcPI and RcAP3 in petals and stamens whorls and of the E class gene RcSEP3 in all whorls. In Arabidopsis genetic and gene expression experiments showed that SEP3 is required for the up-regulation of B and C floral homeotic genes  (Castillejo et al. , 2005; Kaufmann et al. , 2009). It is possible that the downregulation of RcAP3 and RcPI is a result of reduced expression of RcSEP3. In the flowering plants, mutation of the B-class genes leads to conversion of petals into sepals. In Viridiflora the down-regulation of RcPI and RcAP3 cannot explain the leaf-like phenotype of stamens in Viridiflora.
CONCLUSION Taken together, our data with those in the literature suggest that the phyllody phenotype in the rose Viridiflora is associated with an up-regulation and ectopic expression of RcSOC1 and of the A-class flower organ identity genes along with the down-regulation of the B, C, and E floral organ identity genes. Therefore, these data here represent a base for future research to deeply understand the molecular mechanisms associated with ABCE organ identity genes, and the origin of type 1 phyllody phenotype in roses.
Only the decays of the Z boson to charged leptons and leptonic W boson decays are considered. The final-state topology is thus characterised by the presence of three isolated charged leptons, at least two jets, and missing transverse momentum from the undetected neutrino. The paper is organised as follows. A brief description of the ATLAS detector is given in Section 2. The collected data samples and the simulations of signal and SM background processes are described in Section 3. Section 4 presents the object definitions, while the event analysis and kinematic reconstruction are explained in Section 5. Background evaluation and sources of systematic uncertainty are described in Sections 6 and 7. Results are presented in Section 8 and conclusions are drawn in Section 9.
5. Energy deposits over the full coverage of the calorimeters, |η| < 4. 9 are used to reconstruct jets and missing transverse momentum (with magnitude E miss T ). A threelevel trigger system is used to select interesting events. The Level-1 trigger is implemented in hardware and uses a subset of detector information to reduce the event rate to a design value of at most 75 kHz. This is followed by two software-based trigger levels which together reduce the event rate to less than 1 kHz. A detailed description of the ATLAS detector is provided in Ref. [29]. In this paper the full 2012 dataset from proton-proton (pp) collisions at √ s = 8 TeV is used. The analysed events were recorded by single-electron or single-muon triggers and fulfil standard data-quality requirements. Triggers with different transverse momentum thresholds are used to increase the overall efficiency.
8. The simulations of t tZ, t tW(W), tZ and tribosons include events with up to two extra partons in the final state. The simulated samples used to cross-check the data-driven estimation of background with fake leptons are also listed in Table  2. Detailed and fast simulations of the detector and trigger are performed with standard ATLAS software using GEANT4  [52, 53]  and ATLFASTII  [53] , respectively. The same offline reconstruction methods used on data are applied to the simulated samples.
37 < |η cluster | < 1. 52 are excluded. Electron candidates in this analysis must satisfy tight quality requirements on the electromagnetic cluster and associated track which provide discrimination between isolated electrons and jets. In order to suppress multi-jet backgrounds, it is also required that there is little activity in the space surrounding the electron. Two isolation variables are employed: the energy deposited around the electron in the calorimeter in a cone of size ∆R = 0. 2 and the scalar sum of the p T of the tracks within cone of size ∆R = 0. 3 around the electron. Cuts on these two quantities are used to select isolated electrons; the adopted cuts yield a 90% identification efficiency in Z boson decays to e + e -events from the full 2012 dataset. Additionally, the longitudinal impact parameter |z 0 | of the electron track with respect to the selected primary vertex of the event is required to be less than 2 mm.
The E miss T scale uncertainty  [70]  is found to vary the total background yield and the signal efficiency by 3. 2% and 1. 5%, respectively. All these detector systematic uncertainties are treated as fully correlated between signal and background. The uncertainty related to the integrated luminosity for the dataset used in this analysis is 2. 8%. It is derived following the methodology described in Ref. [82]. It only affects the estimations obtained from simulated samples, therefore its impact on the total background yield estimation is 2. 4%.
Presumably, there must be other additional unconserved residues that have played subtle compensatory roles on the pathway towards evolution of TM84 resistance. Why did nature evolve TM84 to target LeuRS At and not another AARSs from A. tumefaciens, and in particular the other Class I AARSs that have similar active site architectures such as IleRS and ValRS. TM84 does appear to be LeuRS specific, as the antibiotic does not inhibit agrobacterial IleRS  12  , and the single LeuRS agnb2 gene is capable of providing agrocin 84-immunity to the pathogen. In silico docking analysis of TM84, from the LeuRS Ec structure (PDB: 3ZGZ), into the catalytic domain of existing IleRS (PDB code: 1JZQ) and ValRS (PDB code: 1GAX) structures reveals steric clashes of the 'leucine-like' region of TM84 with hydrophobic side chains in the active site (Supplementary Fig.
Reactions were pre-incubated with or without substrate and/or inhibitor and then carried out at 28 °C (37 °C-LeuRS Hp ). Aliquots of the reaction (5-10 ml) were quenched on 3 mM filter pads (Whatman, GE Healthcare) presoaked with 5% trichloroacetic acid (TCA). The pads were washed thrice with 5% TCA and 90% ethanol at 4 °C and then dried. The amount of Leu-tRNA Leu was then quantified using scintillation counting. Each reaction was performed in triplicate and analyzed using Kaleidagraph (for K m and k cat determinations) or GraphPad Prism software (for IC 50 determination). Isothermal titration calorimetry. The affinity of TM84 binding to AgnB2, LeuRS At and their mutants was determined using ITC as described earlier  23. Binary interactions (TM84 binding to protein) and ternary interactions (TM84 binding to protein þ tRNA (1:1.
1 M MES (pH 6. 5), 0. 2 M ammonium sulfate and 27% (w/v) PEG 5000 MME. Quality and size of crystals were optimized by macroseeding with protein at 2 mg ml À 1. The crystals were frozen in liquid nitrogen after transfer for a few seconds in the mother liquor plus 15% (v/v) ethylene glycol as cryoprotectant. Structure determination and refinement. The diffraction data sets of the complex AgnB2 LeuRS-tRNA Leu -Leu-AMS were collected at the European Synchrotron Radiation Facility (ESRF, France). The data sets were integrated and scaled with the XDS suite  52. Further data analysis was performed with the CCP4 suite  53. The structure was initially solved by molecular replacement with PHASER  54  using as a model the catalytic and anticodon-binding domains of a model built with SWISS-Model  55  based on homology to LeuRS Tt (PDB 2BTE)  56  and LeuRS Ec (PDB: 4AS1)  25.
The molecular replacement solution was used to search with PHASER for AgnB2 tRNA Leu using as a model the core of E. coli tRNA Leu (bases 1-73, except the bases belonging to the long-variable arm). The obtained model was completed by manual placing of the ZN1 domain, leucine-specific domain, C-terminal domain and editing domain. Manual adjustments were done with COOT  57  and the final model was refined using REFMAC5 (ref. 58). Structure quality was analysed with MOLPROBITY (http://molprobity. biochem. duke. edu/) and showed all residues in allowed regions. Figures were drawn with PYMOL (http://www. pymol. org/). Molecular modelling. A homology model of LeuRS At was built using the Insight II Molecular Modeling System (www. accelrys. com) based upon the template structure of the LeuRS Tt (PDB ID 1H3N)  35.
Figure3| Structure of the AgnB2tRNA Leu Leu-AMS complex. (a) X-ray structure of wild-type AgnB2tRNA Leu Leu-AMS complex with 3 0 -tRNA Leu (blue) bound in the editing site (PDB Code-5AH5). The catalytic, editing, anticodon binding and C-terminal domains are displayed in yellow, cyan blue, red and gold, respectively. Leu-AMS bound to the synthetic active site is represented in a stick structure and the catalytic KQSKS and HIGH loops are highlighted in green. (b,c) Comparison of wt AgnB2tRNALeu-AMS complex and LeuRS Ec tRNA Leu Leu-AMS complex binding site residues. The surface of the catalytic active site of the protein is depicted in yellow with Leu-AMS bound (stick structure).
Figure5| Interactions of key residues in the catalytic active site of AgnB2. Ribbon structure of the catalytic active site of (a) AgnB2tRNA Leu Leu-AMS complex and (b) E. colitRNA Leu Leu-AMS complex. AgnB2 key residues interacting with Leu-AMS (shown as white sticks) or adjacent to the catalytic site are depicted as sticks with the following colour code: residues of the K 572 QSKS 576 and of the H 47 IGH 50 catalytic motifs, are coloured in green; core permissive residues T42 and A102 are shown in yellow; T581 which H-bonds to Q573 in pink; and D567 and R571 which forms the salt bridge mutated in this study and residue L577 are also in pink. E. coli LeuRS equivalent residues in the aminoacylation complex (PDB: 4AQ7) are shown in panel b. Key interactions in both the AgnB2 and the E. coli complexes are shown as red-dashed lines.
Acknowledgements We thank  Meighan LeGrand  and  Dr Ashutosh Tripathy  at  UNC-CH  for their assistance with ITC analysis. We thank  Dr Gary Gilleskie  and the  Biomanufacturing Training and Education Center  at  North Carolina State University  for assistance in large-scale antibiotic preparation and  MeadeWestvaco Corporation  for their charcoal gift. We thank  Prof. David Lynn  at  Emory University  and  Dr Tung Hoang  at the  University of Hawaii  for generously providing plasmids and bacterial strains used in this project. We thank members of the  ESRF-EMBL Joint Structural Biology Group  for access to ESRF beamlines and staff of the EMBL high-throughput crystallization facility, within the  Partnership for Structural Biology (PSB). This work was supported by the  National Science Foundation  [Grant number  1158488  to J.
To test whether GP 2b/3a use and protocol amendment modulate the association between access site and 30-day primary outcomes, the interaction between GP 2b/3a use and access site and the interaction between protocol amendment and access site were examined. Odds ratios (ORs) with 95% CIs are reported. All statistical tests were 2-sided, with P<0. 05 considered as statistically significant. Statistical analyses were performed using SAS software (version 9. 4; SAS Institute Inc. , Cary, NC).
Data collection Physical examination, vital signs, AEs, and concomitant use of medication were recorded at each visit. Food recommendations were provided at each visit. Demographic data, medical history review, height and weight, and waist circumference were collected at V1. Safety parameters were collected at V1 and V3. Dietary instructions were provided to study participants at V1 and V2. Efficacy parameters were collected at V2 and V3, except for insulin (only at V3). Blood collection for determination of plasma glucose and TGs was performed at 0, 30, 60, 90, 120, 240, 360, and 480 min after a high-fat meal. Blood collection for OxLDL was performed at 0, 180, 240, 360, and 480 min after high fat meal. Blood collection for insulin was performed at 0, 30, 60, 90, 120 and 180 min after high-fat meal.
Statistical analyses The primary objective of the study was to evaluate the effect of the CRTE on the reduction of postprandial LDL oxidation in healthy weight men and women. Based on the previous work of Burton-Freeman  (19) , sample size was calculated to detect a decrease of (3. 0 units in OxLDL between the CRTE and placebo groups, with 90% power and an a level of 0. 05, assuming that the common standard deviation for OxLDL is 5. 0 units. Statistical analyses were performed by Medistat with SPSS SAS version 9. 1 (SAS Institute, Cary, NC). OxLDL changes from baseline as well as relative changes (%) on each time point were analyzed using the paired t-test or signed rank test for two means (paired observations), as appropriate, within study arms. Comparative analysis between active and placebo group at any time point was performed using the analysis of variance (ANOVA) model for repeated measurements or the mixedeffect model for repeated measures (MMRM), including the fixed effect time and product and adjusted for baseline measurement and for additional covariates (such as sex) as appropriate.
Study population Each study subject provided a written consent to a study. Questionnaire data on age, weight, height, medical history, and smoking were obtained. The levels of lead and zinc protoporphyrin in the blood served as biomarkers of lead exposure. The study population was divided into three groups. The first group consisted of 34 male workers subchronically exposed to lead for 36-44 days, aged from 22 to 61 years. Subjects in this group worked in lead-zinc works to perform periodic maintenance of blast furnaces and production lines. Among the exposed population, 17 workers were occupationally exposed to lead for the first time, while the other 17 workers had a history of occupational exposure to this xenobiotic. Workers were subjected to high doses of lead because they did not adhere to the occupational safety and health precautions and did not properly use personal protective equipment.
Determination of lead concentration PbB assessments were performed by graphite furnace atomic absorption spectrometry using ICE 3400 instrument (Thermo Fisher Scientific Waltham, MA, USA). The laboratory met the requirements of proficiency tests (Lead and Multielement Proficiency-CDC in Atlanta). Clin-Cal ® Whole Blood Calibrator and ClinCal ® Serum Calibrator (Recipe, Germany) were used for calibration of the instrument and control materials. ClinCheck Whole Blood Control Levels I, II, and III, and ClinCheck Serum Control Levels I and II were used for quality control. Data were expressed as µg/dl.
Determination of total antioxidant capacity (TAC) Total antioxidant capacity was measured in serum according to  Erel (2004). In this colorimetric method, radicals are generated and the antioxidant ability of seminal plasma reduces radical formation. The change in color of ABTS ions (2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonate) is measured as the change in absorbance at 660 nm. This assay was conducted in an automated PerkinElmer analyzer calibrated with Trolox. Data were expressed as mmol/l.
Determination of total oxidant status (TOS) Total oxidant status was measured in serum according to  Erel (2005). The assay is based on the oxidation of ferrous ions to ferric ions in the presence of various oxidizing agents in acidic medium. The color change of xylenol orange by ferric ions is measured as the change in absorbance at 560 nm. This assay was conducted in an automated analyzer (PerkinElmer) calibrated with hydrogen peroxide. Data were expressed as µmol/l.
The third core element is a high-speed digital signal processor that efficiently analyzes the fluorescent output. The principle of these bead-based assays is similar to that of capture-sandwich immunoassays. The samples and standards were incubated with the antibody-coupled beads (antibodies directed against the desired cytokines were covalently coupled to internally dyed beads) in 96-well plates and washed. Next, the biotinylated detection antibodies specific for different cytokine epitopes were added. After incubation and washing, streptavidin (phycoerythrin solution) was added to bind to the biotinylated detection antibodies on the beads. The suspensions of the washed beads were analyzed using the Bio-Plex System. The software presented the data as both median fluorescence intensity and concentration (pg/ml).
Event selection The data sample used for this measurement was collected in 2011 by the CMS experiment at the CERN LHC in proton-proton collisions at a centre-of-mass energy of 7 TeV and corresponds to an integrated luminosity of 5. 3 fb -1. The search for B 0 s → J/ψ f 0 decays is performed in events with two muon candidates selected by the dimuon trigger at the HLT, requiring the muon pair to originate from a displaced vertex. The dimuon candidates are further required to comply with L xy /σ xy > 3, where L xy is the magnitude of the vector L xy , which lies in a plane transverse to the beam axis and points from the interaction point to the dimuon vertex, and σ xy is its uncertainty; cos α J/ψ > 0. 9, where α J/ψ is the angle between the direction of the dimuon transverse momentum and L xy ; p T > 4 GeV and |η| < 2.
Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at  CERN  and at other  CMS institutes  for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies:  BMWFW  and  FWF (Austria) ;  FNRS  and  FWO (Belgium) ;  CNPq ,  CAPES ,  FAPERJ , and  FAPESP (Brazil) ;  MES (Bulgaria) ;  CERN ;  CAS, MoST , and  NSFC (China) ;  COLCIENCIAS (Colombia) ;  MSES  and  CSF (Croatia) ;  RPF (Cyprus) ;  MoER ,  ERC IUT  and  ERDF (Estonia) ;  Academy of Finland ,  MEC , and  HIP (Finland) ;  CEA  and  CNRS/IN2P3  (France);  BMBF ,  DFG , and  HGF (Germany) ;  GSRT (Greece) ;  OTKA  and  NIH (Hungary) ;  DAE  and  DST (India) ;  IPM (Iran) ;  SFI (Ireland) ;  INFN (Italy) ;  MSIP  and  NRF (Republic of Korea) ;  LAS (Lithuania) ;  MOE  and  UM (Malaysia) ;  CINVESTAV ,  CONACYT ,  SEP , and  UASLP-FAI (Mexico) ;  MBIE (New Zealand );  PAEC (Pakistan) ;  MSHE  and  NSC (Poland) ;  FCT (Portugal) ;  JINR (Dubna) ;  MON, RosAtom, RAS  and  RFBR (Russia) ;  MESTD (Serbia) ;  SEIDI  and  CPAN (Spain) ;  Swiss Funding Agencies (Switzerland) ;  MST (Taipei) ; ThEPCenter,.
Mitochondrial target prediction analysis © 2016 Macmillan Publishers Limited. All rights reserved. Putative miRNA targets were identified using the mirDB online database (http://mirdb. org/miRDB/), which is a database for miRNA target prediction and functional annotations. Targets are predicted by an algorithm (MirTarget) that analyzes all NCBI RefSeq 3'-UTRs in order to predict both conserved and non-conserved target motifs. A target prediction score is also computed to inform the user about the confidence of the prediction. The range is from 50 to 100, but caution is recommended for values below 80. Because the microarray analysis was based on a previous version of mirBase (http://www. mirbase. org/) (v. 17), the selected miRNA names were updated based on the current mirBase version (v. 21).
The miRNAs were then compared against the mirDB database in order to retrieve all predicted targets with a prediction score ≥ 80. Using the MitoCarta database (https://www. broadinstitute. org/pubs/MitoCarta/), the selected target genes were then filtered in order to exclusively retrieve specific mitochondrial target genes. The two heat maps presented in Figures  5 A  and  B were generated using a custom R script (https://cran. r-project. org/) containing gplots (https://cran. rproject. org/web/packages/gplots/gplots. pdf). The data were clustered using the Pearson correlation coefficient method and the Heatmap2 function (http://www. insider. org/packages/cran/gplots/docs/heatmap. 2).
Acknowledgments We are grateful to the Montpellier-RIO imaging platform (Montpellier, France), the  Histology Experimental Network of Montpellier , and the IGMM animal facilities. The authors are grateful to  Roscoe Klinck  ( Université de Sherbrooke ),  Pierre de la Grange (Genosplice) , and  Edouard Bertrand  for the SRSF1-GFP HeLa cells. The screening reported in this paper was performed within the  France-BioImaging national research infrastructure, at MRI ,  Montpellier. France-BioImaging  is supported by the  French National Research Agency  through the  ""Investments for the Future"" program  ( ANR-10-INSB-04 ). The authors thank  Julien Bellis ,  Sylvain de Rossi  and  Virginie Georget  for conducting the screening and microscopy imaging. We thank also  Laurie Gayte  for her help during the in vivo experiments.