dataesr/scientific-paragraphs-categorization huggingface dataset:
Densitometric analyses were performed using ImageJ software program (National Institutes of Health, Bethesda, MD, USA; http://imagej. nih. gov/ij/) and normalized against the signal obtained by reprobing the membranes with mouse anti-b-actin or anti-tubulin. The apparent molecular weight of proteins was determined by calibrating the blots with prestained molecular weight markers (Bio-Rad Laboratories, Richmond, CA, USA). Immunofluorescence analysis. Cell cultures were grown on poly-L-lysinecoated glass slides, fixed in 4% paraformaldehyde for 10 min at room temperature, subsequently permeabilized with 0. 1% Triton X-100 for 8 min and washed in PBS. Cells were blocked for 30min in 2% horse serum in PBS and incubated for 1 h at 371C with primary antibodies followed by fluorescein-or Cy3-conjugated secondary antibodies.
After rinsing in PBS, cells were counterstained with 1 mg/ml Hoechst 33342 and examined with a Zeiss LSM 510 Confocal Laser Scanning Microscope. Fluorescence images were processed using ZEN 2009 (Carl Zeiss, Milan, Italy) and Adobe Photoshop software (Adobe, San Jose, CA, USA). Immunoprecipitation. Cell lysis was performed in RIPA buffer as described above, protein content was determined using Bradford protein assay (Bio-Rad) and 500 mg of lysates were incubated at 41C for 2 h with a rabbit polyclonal antiacetyl-lysine antibody diluted 1 : 100. The immunocomplexes were collected by binding to protein A-Agarose beads (Roche), followed by three washes with lysis buffer and then directly resuspended in Laemmli sample buffer 1 Â. Biochemical assays. Caspase 3 activity was measured with a TruePoint Caspase 3 assay kit (PerkinElmer, Waltham, MA, USA), according to the manufacturer's instructions.
Cell viability was assessed by a colorimetric assay using the 3(4,5-dimethylthiazol-2yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) assay (CellTiter 96 Aqueous One Solution Assay, Promega, Madison, WI, USA) according to the manufacturer's instructions. Absorbance at 490 nm was measured in a multilabel counter (Victor3-V, PerkinElmer). The activity of SIRT1 was measured using the SIRT1 Fluorescent Activity Assay Kit (Enzo Life Science) according to the manufacturer's instructions using a fluorescent emission at 460 nm with excitation at 360 nm. Statistical analysis. All data are expressed as means±S. D. of nZ3 independent experiments. One-way analysis of variance (ANOVA) followed by Student's t-test was used for statistical evaluations. Values significantly different from the relative control are indicated with an asterisk, and values significantly different from another group are indicated with a hash.
Acknowledgements. We thank  Jean-Philippe Loeffler  ( INSERM U1118, Strasbourg, France ) and  Mauro Cozzolino  ( CNR, Rome, Italy ) for critical reading of the manuscript and  Monica Nencini  ( Fondazione Santa Lucia ) for skilful technical assistance. Antonio Musaro  `kindly provided C2C12 cells expressing  G93A-SOD1. This work was supported by an ' Association Franc¸aise contre les Myopathies ' grant to LP and an ' Association pour la Recherche sur la Sclerose Laterale Amyotrophique et autres Maladies du Motoneurone ' grant to FR.
Subsequently, the gel pieces were washed three times by vortexing for 10 min in 50 mM NH 4 HCO 3 , pH 8. Following removal of the wash solution, the gel pieces were dried in a SpeedVac concentrator for 30 min and then incubated overnight in 10 µl Bovine Sequencing Grade Trypsin (Roche, Penzberg, Germany) dissolved in 50 mM NH 4 HCO 3, 1 mM CaCl 2. The trypsin solution was subsequently removed and transferred to a low binding tube. 10 µl of trifluoroacetic acid (TFA; 5% wt/vol H 2 O) were then added to the gel pieces and after sonication for 1 min the supernatant was transferred to the tube containing the previous liquid. The same procedure was repeated by adding 10 µl 15% acetonitrile/1% TFA to the gel pieces and combining the liquid with the previous supernatants. Mass spectrometry was performed using an nLC-LTQ-Orbitrap tandem mass spectrometer at Biqualys (Wageningen, The Netherlands), and the data were analysed using the Bioworks software (Thermo Fisher Scientific, Ulm, Germany).
Phototropism experiments Seedlings were grown in the dark at 22°C on vertically oriented half-strength Murashige and Skoog (MS) agar (0. 8%) plates for 3 to 4 days. Agravitropically growing seedlings were reoriented toward the gravity vector in safe green light 2 to 4 hr before the experiment. The seedlings were then transferred to GroBank growth chambers (CLF Plant Climatics, Wertingen, Germany) and illuminated with unilateral white light (100 µmol m -2 s -1 ). Plates were subsequently scanned and hypocotyl bending was measured for each seedling using the NIH ImageJ software.
Acknowledgements The authors are grateful to  Helene Prunkl  and  Hannelore Daniel  ( Technische Universität München, Germany ) for supplying Xenopus laevis oocytes. The authors wish to thank various colleagues for sharing antibodies,  Siv Ahlers ,  Manuel Jeller ,  Susanne Weber , and  Mon Yinnavong  ( Technische Universität München, Germany ) for providing materials, and  Manuela Bog  ( Universität Regensburg, Germany ) for help with statistical analyses. This work was supported by grants from the  Deutsche Forschungsgemeinschaft  (grant numbers  SCHW751/8-1  and  SFB924 ) to CS and  UZH  ( SFB924 ) and by a fellowship from the  Fundação para a Ciência e a Tecnologia  to ICRB.
Based on the potential energy profile obtained from DFT calculations, data presented in Table  3  was used for the kinetic analysis. For each of these stationary points, harmonic vibrational wavenumbers and the rotational constants calculated by the GAUSSIAN09 quantum chemistry program  18  were used. Table  4  summarizes these results at two temperatures and two pressures. While there is no significant direct formation of cresol from OH + cymene, cresol is the main product of the unimolecular decomposition of the stabilized PC ipso -C 3 H 7 as indicated by the factor b. This finding is not in contradiction with product studies that showed no significant (o2%) cresol formation  11  because in the presence of O 2 cresol formation competes with the PC ipso -C 3 H 7 + O 2 reaction that is expected to be much faster under atmospheric conditions.
Moreover, the yield of PC ipso -CH 3 remains below 5% at all temperatures and the predicted main fate of PC ipso -C 3 H 7 is decomposition to cresol + C 3 H 7. Based on the rate constants in Tables  6  and 7 , OH decay curves were simulated numerically using FACSIMILE (MCPA Software Ltd. , Oxfordshire, UK) assuming a realistic OH starting concentration of 1 Â 10 10 cm À3. Additional background loss rate constants of 3 s À1 for all adduct isomers and 10 s À1 for OH were also implemented to improve the comparability with experimental conditions. Decay curves were produced for five p-cymene concentrations in the range 0. 8-4 Â 10 13 cm À3 as in the real experiments for the six temperatures under consideration. The obtained concentration profiles were then converted to count rates including background and finally to count numbers binned exactly as in the real experiments.
Conclusions The reaction p-cymene + OH was reinvestigated using a reaction model assuming formation of two adduct species. This model results in triexponential OH decay curves in the presence of p-cymene that can be evaluated to extract the rate constants of the underlying reaction model. Despite the fact that the reaction between p-cymene and OH radicals can form four different adducts (two ipso-type and two ortho-type adducts) observed OH decays fit to that model within experimental error. Good agreement with literature data was found for the rate constant of OH reaction at room temperature. In a temperature range been 299 and 349 K Arrhenius expressions for rate constants of the reaction model were obtained, as well as the yields of the supposed two adducts. Thermodynamic data were derived from temperature dependent equilibrium constants.
Acknowledgements This work was supported by the  Deutsche Forschungsgemeinschaft  under grant  ZE 792/6-1  and  BO 1580/3-1 , and by  CNRS/INSU  within the  French-German CNRS-INSU/DFG bilateral program  ATMOCHEM. We thank  Rafal Strekowski  ( University of Provence ) for the first, exploratory experiments with p-cymene and OH and the group of  Roger Atkinson  ( University of California, Riverside ) for the determination of the abstraction and dealkylation channels.
Acknowledgments Work is supported by  NSF  TeraGrig Grant no. BCS110013  to  Jacques Beaumont , and in part by the  French Government  through the  Agence National de la Recherche  (http://www. agence-nationale-recherche. fr/) program " Investissements d'avenir " with Grant  ANR-10-IAHU-04  and funding provided by the  Whitaker International Program  administered by the  Institute of International Education  to  Jason D. Bayer. The authors thank  Arkady Pertsov  professor of Pharmacology at  SUNY Upstate Medical University, Andrzej Krol professor of Radiology at SUNY Upstate Medical University , and  Anthony Costantino , research assistant at  Binghamton University  for editorial comments.
Reverse genetics is a key methodology for producing genetically modified RNA viruses and deciphering cellular and viral biological properties, but methods based on the preparation of plasmid-based complete viral genomes are laborious and unpredictable. Here, both wild-type and genetically modified infectious RNA viruses were generated in days using the newly described ISA (infectious-subgenomic-amplicons) method. This new versatile and simple procedure may enhance our capacity to obtain infectious RNA viruses from PCR-amplified genetic material. The GenBank/EMBL/DDBJ accession numbers for the rescued viral RNA sequences of yellow fever virus strain 88/1999, dengue virus strain Dakar HD 34460 and human coxsackievirus B3 strain 2679 are KF907504, KF907503 and KJ489414.
RNA was extracted using the EZ1 mini virus 2. 0 kit and the EZ1 Biorobot (both from Qiagen) according to the manufacturer's instructions. The mixture (final volume: 25 ml) contained a standard quantity of AMV/Tfl 5X Reaction Buffer, 0. 5 mM of each primer, 0. 5 ml dNTP Mix, 0. 5 mM MgSO 4 , 0. 5 ml AMV reverse transcriptase (only for RT-PCR), 0. 5 ml Tfl DNA polymerase, 15. 5 ml nuclease-free water and 2 ml of extracted nucleic acids. Assays were performed using the CFX96 Touch real-time PCR Detection System (Bio-Rad) with the following conditions: 50 uC for 15 min, 95 uC for 2 min, followed by 45 cycles of 95 uC for 15 s, 60 uC for 40 s (Table  S2 ). Data collection occurred during the 60 uC step. The difference between cycle threshold values (C t ) obtained by RT-PCR and real-time RT-PCR assays was used to assess viral RNA production.
Sequence analysis of the full-length genome. Complete genome sequencing was performed using the Ion PGM Sequencer  (Rothberg et al. , 2011)  (Life Technologies) and analyses conducted with the CLC Genomics Workbench 6 software. Virus supernatants were first clarified and treated with the Benzonase nuclease HC. 99 % (Novagen) at 37 uC overnight. Following RNA extraction (no RNA carrier was used, see above) using the EZ1 mini virus 2. 0 kit and the EZ1 Biorobot (both from Qiagen), random amplification of nucleic acids was performed as previously described  (Stang et al. , 2005). Amplified DNA was analysed using the Ion PGM Sequencer according to the manufacturer's instructions. The read sequences obtained were trimmed, first using quality score, then by removing the primers used during the random amplification and finally at the 59 and 39 termini by systematically removing 6 nt.
Data Collection and Image Analysis Patient age, sex, aneurysm location and type (saccular or fusiform), the presence of previous treatment, size, rupture status at presentation, and compressive symptoms were collected. Procedural details (eg, number and size of implanted PEDs and associated coiling) were noted. A single reader evaluated all angiograms. Aneurysm occlusion was assessed by using the O'Kelly-Marotta grading scale. The patency of the ophthalmic artery was reported as normal or slowed anterograde flow, occlusion, or retrograde filling.
Identification of DMRs Genome-wide DNA methylation analysis was performed on 11 corresponding tumor and mucosa samples (screening set) using CpG island arrays. Data were analyzed for differentially methylated probes comparing good versus bad prognosis. Applying the above-mentioned criteria to DMRs, we identified a subset of 20 DMRs located within or close to 17 different genes (Supplementary Table  2 ). The majority of DMRs were distributed over chromosomes 1 (n=4), 19 (n=3), and 20q13 (n=5). This distribution could not be attributed to the frequency of array probes on the diverse chromosomes (p=7. 6*10 -1  , Supplementary Figure  1 ).
Correlation of DMRs with Polycomb Repressor Complex occupancy Like DNA methylation, a number of repressive post-translational histone modifications have been shown to be associated with tumorigenesis. Notably, a recent report suggested that a sequential epigenetic silencing process occurs during colorectal cancer tumor progression. In this model inactive genes are initially "poised" by being epigenetically marked by trimethylation of lysine 27 on histone H3 (H3K27me3) via the Polycomb Repressor Complex-2 component EZH2  [14]. The authors propose a model in which these genes become inactivated by subsequent DNA methylation during tumor progression. Therefore we utilized published chromatin immunoprecipitation sequencing (ChIP-seq) data in various cell types from the ENCODE consortium. Strikingly, six of the ten DMRs (near the ADRA1A, BARHL2, ERAS, ESRRG, RNF220 and ST6GALNAC5 genes) showed an enrichment of EZH2 (Figure  3 ).
MCIp enrichment and CpG island microarray analysis MCIp enrichment of highly methylated DNA and CpG island microarray analysis was performed as described previously with minor modifications  [50, 51]. Briefly, 2. 5 µg DNA was sonicated with the Bioruptor NGS (Diagenode, Liege, Belgium) to fragments of 100 to 600 basepairs (bp). Fragmented DNA was MCIpenriched using an SX-8G IP-Star robot (Diagenode) and 60 µg MBD2-Fc protein coupled to protein A magnetic beads (Diagenode). Proper DNA enrichment was monitored by quantitative real-time PCR targeting the imprinted gene SNRPN. The non-methylated allele elutes at low-salt, while the methylated allele elutes at high-salt concentration. Highly methylated tumor and healthy control DNA (matched normal mucosa from nearby the tumor) were labeled with Alexa Fluor 5 and 3, respectively, and cohybridized to a 244 K human CpG island microarray (Agilent, Germany, Table  1 : Clinical data of enrolled patients: Comparison of basic study parameters between test and validation sets.
ChIP-seq data Processed bigwig files for chromatin-immunoprecipitation sequencing (ChIP-seq) data for EZH2 from the ENCODE consortium  [56]  were downloaded from the UCSC Genome Browser website for H1 human embryonic stem cells (GSM1003524), human umbilical vein endothelial cells (HUVEC, GSM1003518) and normal human astrocytes (GSM1003532). Signal files were overlayed and viewed in the Integrated Genome Viewer (version 2. 3).
Statistical analysis In order to meta-analyse data from multiple studies centrally, each study first natural-log transformed and standardised the phenotype, such that for each variable the mean was equal to zero and SD equal to one. Each study then fit linear regression models on each of these outcomes using the genetic risk scores as exposures, adjusted for age and sex (with and without adjustment for BMI). Genetic risk scores were unweighted and effect sizes expressed per fasting insulin-raising or insulin secretion-lowering allele, respectively. We investigated the association of these risk scores with euglycaemic-hyperinsulinaemic clamp  (22)  and OGTT-based measures of insulin sensitivity and secretion  (23, 24). We also investigated the associations of scores with glycaemia and insulinaemia during the OGTT, lipids, BMI, waist and hip-circumferences, and body fat percentage (assessed by bioimpedance in RISC, and by DXA in Fenland).
We performed fixed-effect, inversevariance weighted meta-analyses using Stata SE-12. 1 software (StataCorp LP, College Station, TX). Associations with T2D in the EPIC-InterAct study were investigated using Prentice-weighted Cox regression with age as the underlying time variable, adjusted for age at entry (to account for potential cohort effects), sex and centre of recruitment. BMI strata were defined by WHO cutoffs and waist circumference strata were defined by sex-specific tertiles. Interactions of risk scores with BMI and waist circumference were tested by including the product term of risk scores and BMI categories or waist circumference tertiles. Effect sizes were expressed as hazard ratios (HR) per-risk allele.
Acknowledgments The  MRC-Ely Study  was funded by the  Medical Research Council  ( MC_U106179471 ) and  Diabetes UK. We are grateful to all the volunteers, and to the staff of  St. Mary's Street Surgery, Ely  and the study team. The  Fenland Study  is funded by the  Medical Research Council  ( MC_U106179471 ) and  Wellcome Trust. We are grateful to all the volunteers for their time and help, and to the General Practitioners and practice staff for assistance with recruitment. We thank the  Fenland Study Investigators, Fenland Study Co-ordination team  and the Epidemiology Field, Data and Laboratory teams. DBS and RKS are funded by the  Wellcome Trust , the  U. K. NIHR Cambridge Biomedical Research Centre  and the  MRC Centre for Obesity and Related Metabolic Disease. Genotyping in ULSAM was performed by the  SNP&SEQ Technology Platform in Uppsala  (www.
e. , loop closure for some amyloid proteins and an hypothetical lock-and-dock mechanism) and off-pathways. As some of these processes depend on polymer size, maturity level and/or concentrations, modelling the whole scheme of the reactions that govern kinetics of fibril growth is quite complex. Prior to the use of fibrils for clarifying amyloid mechanisms or for applied goals, it is necessary to determine well the biophysical parameters of the fibrils. Among these parameters, the measurement of fibril size is a basic requirement that permits, for example. one to determine to what extent fibrils could be a source of infectious protein, by releasing reactive seeds. To focus on size distribution, we have measured the size distribution of prion fibrils from experimental data and compared it to mathematical modelling of size distribution.
For instance, K may be chosen as the Gaussian kernel. To choose the small parameter h, called the "bandwidth" or sometimes the "regularization parameter", there is a trade-off between smoothness of the estimate f and accuracy of the estimation: the smaller h, the smaller the distance between the empirical distribution 1 n n i=1 δ y i and f , but the less smooth the estimate f. Data-driven methods exist, such as the one very recently introduced by Goldenshluger and Lepski  [25, 24, 17] , which permit one to choose the optimal parameter h. Here we used the ksdensity procedure of the Matlab statistical toolbox. We obtained a first estimation of the density in Figure  2  (curve in a full black line). As expected visually from the experimental data (the histograms of Figure  1 ), we obtain a decreasing distribution on the range of measured values.
This could give clues to determine the size of sample that we need: it is unnecessary to collect a sample that would give a value of n -1 3 smaller than the experimental noise. Our dataset (the histograms of Figure  1 ) shows an average size of 706, and noise is at least on the order of an additive noise of 126 monomers (linked to the precision of the measurement, see Section 2 for the description of the data). This means a noise larger than 18% of the average size value. Evaluating the multiplicative noise linked to the error when converting measured volume to the number of monomers is hazardeous, but we know it is present and should be added to this value. Our sample size is n = 626, so that we have n -1 3 ≈ 12% which is already smaller than the minimal noise. This implies that it is unnecessary to collect larger samples, as this would not improve our results.
In Figure  2  we compare the distribution obtained by a kernel density estimation (through the ksdensity algorithm given by Matlab) and the exponential density p λ M LE for the sample y i. Their closeness shows also how much our hypothesis of an exponential distribution may be considered as acceptable. At lowest sizes, the exponential density fits less well than the kernel density estimate, but this is due to boundary effects of the kernel density method, and could also be explained by the truncation of the data.
Model parameters were derived by fitting experimental data to the model equation, using a parameter estimation package. First, the "refolding" parameters involved in step (i) were determined. Then, as lateral aggregation and end-to-end association seemed experimentally negligible at the lowest protein concentration, the parameters involved in filament initiation and elongation could be obtained from the data measured at the lowest protein concentration. Lastly, the parameters describing lateral aggregation and end-to-end association were determined, after considering that filament initiation and filament elongation to be essentially irreversible, i. e. , considering depolymerization as negligible. Their model was able to reproduce their experimental data as, at short times, the average length of filaments or fibrils formed at the lowest monomeric concentration is much higher than the one at higher concentrations, due to the competition between nucleus formation and filament elongation for the consumption of intermediates.
RT-qPCR Stage 19 embryos were treated with cycloheximide (CHX, 10 mg/ml) during 2. 5 hours. Total RNA from 8 embryos was then isolated using the Nucleospin RNA XS kit (Macherey Nagel). Reverse transcription was performed using IscriptcDNA Synthesis Kit (Biorad). RNA quality was evaluated using Experion (BioRad). qPCR reactions were performed in triplicate using SsoFast Eva green Supermix (Biorad) on a C1000 Thermal Cycler (CFX96 Real-Time System, Biorad). All values were normalized to the level of the reference gene ornithine decarboxylase (ODC) using Biorad CFX Manager Software. Primers sequences are: tubb2b forward 59CCCGTGCCATCCTTGTGGATTTT39, tubb2b reverse 59GCCCAGTTATTGCCAGCACCACTT39, Ptf1a forward 59GCCGCTCAGGAACCCCAACA39, Ptf1a reverse 59GGC-AGCCCGTAGTCTGGGTCA39, ODC forward 59CATGG-CATTCTCCCTGAAGTACAAGAA39 and ODC reverse 59GGACAGTGGTAGGGGCAAGCTCA39.
Image analysis and quantification Shown in figures are representative data from one experiment that has been performed at least in duplicate. Fluorescent staining was visualized with a M2 Zeiss microscope. Images were captured with a digital camera AxioCam MRc and AxioVision Rel 7. 8 software. The quantification of in situ hybridization signal intensity in the eyes of whole embryos was quantified using Adobe Photoshop CS4.
Materials and methods Measurements were made on dried herbarium specimens, although certain characters such as shape were observed on alcohol-preserved fl owers or fruits, as well as fi eld notes and photos. All specimens cited in this paper have been seen by the author (see acknowledgments for list of herbaria). I also used online databases for type specimens in order to provide a complete overview of type distribution (e. g. , Global Plants, http:// plants. jstor. org). In cases where the type collection was composed of more than a single sheet without any clear indication that these were part of a series (sheet 1, 2, etc. ), a lectotypifi cation or secondary lectotypifi cation was done to designate a single sheet following recommendation of Article 19. 7 of the International Code of Nomenclature for algae, fungi, and plants (Melbourne Code)  (McNeill et al.