dataesr/scientific-paragraphs-categorization huggingface dataset:
Trait measurements Phenotypic data for the sweet cherry N 9 E and R 9 L populations were collected for 3 years  (2009-2011 and 2008-2010, respectively). For the N 9 E population, in 2009, phenotyping was performed on all the fruiting plants (n = 436), while in 2010 and 2011 phenotyping was conducted on those N 9 E progeny individuals that carried a recombination breakpoint in the fruit weight QTL interval on G2 to enable more precise mapping of the fruit weight QTL. Fruit weight of the N 9 E progeny individuals was measured by weighing five individual fruit that were collected twice and the mean weight was calculated for both collections. For the N 9 E population, mesocarp cell number data that was previously collected in 2006 and 2008 and used to identify the cell number QTL on cherry G2 overlapping with the fruit size QTL  (Zhang et al.
For the tetraploid (sour cherry) case 0, 1, 2, 3 and 4 were assigned for absence, single, two, three and four dosages of particular alleles, respectively. Both main-effect and higher level interactions were considered. b is a n 9 1 unknown fixed effects parameter vector. e is a n 9 1 vector of residuals (random errors). Kruskal-Wallis tests were also conducted, resulting in similar results to the ANOVA. P values \0. 05 were reported as significant. Data for 3 years from each sweet cherry population were initially analyzed separately; then, to combine data from different years, values within each year were standardized using the following formula: x std ¼ ðx À " xÞ r where " x and r are the mean and standard deviation of the data in that year; the mean of standardized values was then calculated for each genotype, obtaining a single dataset for each trait.
The mean trait comparisons among genotypic classes for PavCNR12 and PavCNR20 in sweet cherry were done using the Newman-Keuls test implemented in SAS version 9. 0 (SAS Institute, Cary, NC, USA). In the case of tetraploid sour cherry, a two-tailed Student's t test was used to compare the trait means of two classes, e. g. individuals with the putative allele versus individuals without the putative allele for the SSR marker loci closely linked to both CNR candidate genes. The threshold for significance was set at P \ 0. 05.
Identification of PavCNR20 allelic variants In sweet cherry, the fragments from Emperor Francis, Ambrunes and Cristobalina resulting in readable sequences were from CNR20-C4 through C6. This yielded a contig of approximately 1. 8 kb, corresponding to the 3 0 portion of the gene and encoding 141 C-terminal amino acids. No polymorphisms were found in this region between the three cultivars and the sequence was submitted to Genbank (accession number KC154001). C1 primer pairs did not amplify a product, and C2 and C3 resulted in double peaks indicative of several indels close to the primer sites in these three cultivars. From New York 54, only fragment CNR20-C1 could be amplified and sequenced. All other fragments from the wild mazzard resulted in unreadable chromatograms. In both New York 54 and the cultivars, the CNR20 alleles either were divergent or primer pairs amplified two closely related paralogs rather than a single gene.
To test the likelihood of PavCNR12 being the underlying gene responsible for the G2 fruit size QTL, additional G2 markers were developed between markers CPSCT038 and BPPCT034 and extending to the previously reported SSR MA007a  (Olmstead et al. 2008 ). These marker scores, including Pav-CNR12, were analyzed along with fruit size data in a linear model ANOVA with additive effects and resulting probability values were scaled as -log 10 (P). The majority of markers in the region containing PavCNR12 were significantly associated [P \ 0. 01 or -log 10 (P) [ 2] with fruit size variation (Supplementary Fig. S3 ). In N 9 E, the most probable location of the fruit weight QTL standardized across 3 years was placed on marker G2SSR1576, immediately downstream of PavCNR12. This is also the most probable location of the flesh weight QTL.
Acknowledgments This work was supported in part by grants from the  USDA  ( NIFA-NRI 2008-02259  and  NIFA-SCRI 2009-51181-05808 ). We thank the members of the  International Peach Genome Initiative (IPGI)  for early access to the draft peach genome sequence, and members of the  Iezzoni and van der Knaap labs  for help with cherry harvest and fruit weight evaluations. JA Campoy is holder of a postdoctoral fellowship from the  'Programa de Formacion Postdoctoral de Personal Investigador' of the 'Fundacion Seneca-Agencia de Ciencia y Tecnologı ´a de la Region de Murcia', Spain. Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
Methods Ten DCM patients (54±12 years, 60%men) and 14 agematched controls underwent CMR with cine sequences to determine LV volumes and LVEF. Through plane phase contrast acquisitions were obtained in breathhold (TR = 7. 5 ms, TE = 2. 5 ms, 2 views per segment, temporal resolution = 15 ms, FOV 32 to 36 cm with 126 x 256 matrix) at 2 consecutive levels, at the level of aortic valve and 10 mm below through the LV outflow tract. Total Acceleration (TotalAcc) and its two components, Temporal (TempAcc) and Convective (ConvAcc) Acceleration were derived from velocities at phase contrast sequence by using our home-made previously validated semi-automatic software Art Fun.
The ship machinery comprised four 4-stroke diesel engines, Sulzer 8ZAL40S, with a MRP of 6000 kW each and a nominal engine speed of 510 rpm. All measurements were performed on one of the engines. The measurements were completed on an engine operating on 57 % engine load. The engine load was monitored continuously through the scavenge air pressure. The fuel consumption was calculated from the engine trial report data provided by the engine producer. During the campaign three different fuels were tested: HFO with S content 1 wt%, HFO with S content 0. 5 wt% and MGO (FSC ∼ 0. 1 wt%). For further engine and fuel details, see Tables  S2  and S3 , respectively. The different measurements from this vessel will be abbreviated as S2_HFO1%_MEfull (ME at engine load 57 %), S2_HFO0. 5%_ME-full and S2_MGO_ME-full.
All volatility data presented here are corrected for the particle losses in the thermodenuder. Concentrations of a number of gas constitutes were measured continuously in the hot exhaust. Nitrogen oxides (Horiba PG-250 chemiluminescence instrument), carbon monoxide and carbon dioxide (Horiba PG-250 NDIR), oxygen (Horiba PG-250 galvanic cell), total hydrocarbons (Bernath Atomic BA 3006 FID), and sulphur dioxide (Horiba PG-250 NDIR) were monitored. The temperature and humidity of the engine inlet air were monitored. The exhaust gas flow was measured with a pitot tube during each sampling experiment. The exhaust temperature was measured several times during each sampling period. Further details on the gas measurement methodologies can be found in  Cooper (2001 Cooper ( , 2003)).
L. C. , US as the University of Gothenburg instrument was not available at that time. Some samples from the S1 campaign were also analysed at Cooper Environmental Services L. L. C. to get intercomparison of results from the two laboratories. Agreement between the two laboratories was good. Analyses at the University of Gothenburg were made with a voltage of 50 kV and a current of 25 mA applied to the silver X-ray tube and spectra were collected for 1000 s. The data from the EDXRF analyses were processed and quantified with the Quantitative X-ray Analysis System (QXAS) software developed by the International Atomic Energy Agency (IAEA), Vienna, Austria. For quantification of the detected elements, a calibration file was needed. The calibration file was created from single element standards during previous EDXRF sample analyses at the University of Gothenburg  (Molnár et al.
, 2006). Detection limits were determined by analysis of blank membrane filters  (Boman et al. , 2009). They depend on the element under analysis and vary between 0. 60 ng cm -2 and 90 ng cm -2 of filter area for the elements. Analyses performed at Cooper Environmental Services L. L. C. , US were done on a Quanx EDX-771 energydispersive X-ray spectrometer with a 200 Watt rhodium target tube as an excitation source. The machine operation, data acquisition and spectral processing were handled by Kevex's software. Analyses followed  EPA compendium IO 3. 3 (US EPA, 1999). For measurement of oxidative potential, samples taken on PTFE membrane filters as well as pieces of the quartz fibre filters were used. The samples were tested with the dithiothreitol (DTT) assay based on the method described by  Cho et al.
For S1 there is almost no difference between EF(NO x ) when the engine is at full load and when it is at low (30 %) load. In data from S2 one can see a decrease of EF(NO x ) when HFO fuel is changed to MGO, which is in agreement with a report of EC and Entec UK Limited  (2002). The EFs for SO 2 are presented both as measured and as calculated from the fuel S content. For S1 experiments the measured EF(SO 2 ) were ∼ 5 % lower than the calculated ones, and the differences between measured and calculated EF(SO 2 ) in the S2 experiments were -20--30 % (∼ 4 g kg -1 fuel for HFO in absolute numbers) for the 3 fuels tested. The observed sulphate in particulate phase corresponded to less than 1 % of fuel S and could not be used to explain the discrepancy in the S2 experiment. This large discrepancy between the measured and calculated EF(SO 2 ) persists also when ratios of SO 2 and CO 2 concentrations in the exhaust are compared to ratios of S and C content in the fuel (adjusted for molar weight differences), eliminating possible uncertainties in fuel consumption.
It could be demonstrated that PM 2. 5 more strongly contributes to the main emission peak related to soot structures of higher structural order than to the minor emission peak related to highly disordered soot. Oxidative potential measured as a rate of consumption of DTT was measured for the first time on PM from ship exhaust. The obtained values were between 0. 01 and 0. 04 nmol DTT min -1 µg -1 PM, quite similar to the oxidative potentials of PM collected in urban and traffic sites. The data obtained during the Transphorm experiments add information about emission factors for both gaseous and PMbound compounds from ship engines using different fuels and under different engine-load conditions. The observed variability of the EFs illustrates uncertainties of these emission factors as a result of measurement uncertainties, influences from trace components of fuels and lubricants and from differences between individual engines.
Acknowledgements. The financial support from  EU   FP7  project  TRANSPHORM  (no  243406 ),  IVL foundation, StenaLine and Deutsche Forschungsgemeinschaft (DFG)  are gratefully acknowledged. The authors would also like to thank  Transatlantic ,  StenaLine  and crew on both ships for their generous support of our measurement campaigns. Thanks to colleagues  Kjell Peterson ,  Henrik Fallgren  and  Åsa Jonsson , all  IVL , for assistance with the measurements, to  Peter Molnar ,  Occupational and Environmental Medicine, University of Göteborg  for assistence with the BC analyses on SootScan transmissometer and to  Trine Underdal  at  DNV Petroleum services  for assistance with the fuel and lubricant sample analyses. Edited by:  J. Hjorth.
Adding recombinant (r)Sema3A (chemorepellent) to demyelinated lesions reduced OPC recruitment and remyelination, whereas the addition of rSema3F (chemoattractant), or use of transgenic mice with reduced Sema3A expression increased OPC recruitment and remyelination. 1 3  [30] , Wnt inhibition  [10] , axin-2 stabilization  [11] , loss of cdk2  [2] , noggin  [42] , antibodies antagonizing death receptor-6  [29]  and CXCR4  [3]. The effect of these molecules in humans is not known and only anti-Lingo antibodies have reached clinical trial in MS (Clinicaltrials. gov identifier NCT01244139). Molecules affecting other processes necessary for remyelination, such as migration, have been less studied in spite of a third of demyelinated MS plaques containing few OPCs  [6, 27]. Group 3 semaphorins are secreted factors that attach to extracellular matrix forming gradients for cells to use as migration cues.
Acknowledgments AW is funded by a  Wellcome Trust   Clinical Intermediate Fellowship. HZ is jointly funded by the  University of Edinburgh  and the  Chinese Scholarship Council. Thanks to  Dr F. Roncaroli  (Consultant Neuropathologist,  Imperial College London)  for confirmation of the diagnosis of MS for each case,  Prof. Richard Reynolds  for providing the MS tissue from the UK MS tissue bank,  Dr Maurits Jansen  and  Dr Phil Holland  for help with MRI scanning,  Steve Mitchell  for help with electron microscopy,  Dr Lee Smith  for the HPRT-Cre mouse and  Corrie Watkins  for her help in classifying the MS tissue.
qPCR was performed using Syber-Green (SensiMix TM SYBR Hi-ROX Kit, Bioline) with appropriate primers (See Supplementary Methods for primer sequences). Relative quantification of gene expression was conducted with the Applied Biosystems 7300 Real Time PCR System and data analysis was performed using the comparative ΔΔC T method. U6B and sno202 RNAs were used as internal control for miRNA expression, Actin mRNA as internal control for mRNA expression.
microRNA array profiling 2. 5µg of total amygdala RNA from pooled nuclei (n=12) from naive and stressed mice were Hy3-and Hy5-labeled respectively, using miRCURY TM LNA microRNA Array Power Labeling Kit (Exiqon). Fluorochrome-labeled RNA samples were then combined, denatured and hybridized to custommade slides containing LNA-modified microRNA capture probes targeting all human, mouse and rat miRNAs listed in the miRBase Sequence Database Release v. 11. 0 (http:// microrna. sanger. ac. uk/sequences/), which contains 1769 unique mature miRNA sequences. Slides have been kindly provided by Dr. V. Benes, from the Genomics Core Facility of the European Molecular Biology Laboratory (Heidelberg, Germany). The hybridization was performed according to the miRCURY TM LNA array manual using hybridization chambers (Agilent), for 16 hours at 56°C.
After hybridization, the microarray slides were scanned using a ScanArray Lite Microarray Scanner (Packard Bioscience) and the image analysis was carried out using GenePix® Pro 7 Software (Molecular Devices). Absent and marginal spots were flagged automatically by the software, and then each slide was inspected manually. Data were normalized using different endogenous controls present in the LNA-modified spotted library. The Hy5/ Hy3 ratios were log 2 -transformed. Data from 2 independent experiments were averaged and only probes with a log 2 -ratio above 1 or below -1 were considered. Only probes with log intensity >8 and <14 were taken in account, to avoid non linear effects caused by the noise floor at low intensities or by saturation at high  [19].
DNA constructs miRNA expression vector p135a was obtained by amplifying 301-bp from mmu-miR-135a-1 genomic sequence, containing 111 nt upstream and 100 nt downstream the miRNA stem-loop sequence, according to the miRBase Database (http:// www. mirbase. org/). The PCR fragment was cloned dowstream the U1 promoter of a pSP65 vector  [20]. The complete Nr3c2 3' UTR was amplified from mouse genomic DNA and cloned into the XbaI unique site of the pGL3 control vector (Promega). To generate Nr3c2 mutant constructs Nr3c2 m135a and Nr3c2 m124, mutations of seed binding sites for miR-135a (Nr3c2 m135a) or miR-124 (Nr3c2 m124) were introduced into the Nr3c2 3' UTR using synthetic oligonucleotides, by generating partially complementary PCR fragments. These fragments were used as templates for PCR to generate complete mutated Nr3c2 3' UTR fragments, further cloned as described for wild type 3' UTR.
Acknowledgements The authors would like to thank  Dr Elise  and  Dr Celso Gomez-Sanchez  who kindly provided us the 2B7 anti-MR monoclonal antibody,  Rodolfo Negri  for helpful discussion and comments on the manuscript,  Andrea D'Angerio  for help on pSP65 constructs and  Ubaldo Gioia  for p124 vector. This paper is dedicated to the memory of our colleague and friend  Irene Baldi.
Analyses were performed in reflectron mode with an accelerating voltage of 25 kV and a delayed extraction of 50 ns. The spectra were analyzed using the FlexAnalysis software (version 2. 4, Bruker Daltonik), and autoproteolysis products of trypsin  (molecular weights, 842. 51, 1045. 56, 2211. 10, and 2383. 90)  were used as internal calibrates. Identification of proteins was performed using the Mascot software (version 2. 0. 04, Matrix Science; http://www. matrixscience. com/) against the mouse entries of Sprot or Trembl databases (downloaded on 2005-05-15). The following parameters were used for database interrogation: mass tolerance of 50 ppm (even if the mass accuracy of our analyses was usually better than 20 ppm); fixed chemical modification, carbamidomethylation of cysteines; variable chemical modification, oxidation of methionines; and one missed cleavage accepted and significance threshold p Ͻ 0.
05. In the second procedure, pulled-down proteins were separated by SDS-PAGE and systematically identified by nano-flow liquid chromatography coupled to Fourier transform tandem mass spectrometry (nano-LC-FT-MS/MS) using a LTQ-Orbitrap-XL (Thermo Fisher Scientific), as previously described  (Meffre et al. , 2012). MS/MS spectra were searched against the mouse Complete Proteome Set database (downloaded on 2012-07-15) by using Mascot (version 2. 3) with trypsin enzyme specificity and up to two trypsin missed cleavages. Methionine oxidation was set as variable modification for searches. A peptide mass tolerance of 7 ppm and a fragment mass tolerance of 0. 5 Da were allowed for identification. Peptide validation and peptide counting were performed using the MyProMS version 2. 3 Web server  (Poullet et al.
, 2007) , to obtain a false discovery rate Ͻ1%. Only proteins identified with two or more peptides by MS/MS were considered as potential SERT partners. For each procedure, the experiments were repeated three times to assess reproducibility. Analysis of SERT phosphorylation status by MS/MS. YFP-SERT expressed in HEK-293 cells was immunoprecipitated using the GFP-Trap kit (Chromotek). Immunoprecipitated proteins were separated by SDS-PAGE, and the bands corresponding to SERT were digested with trypsin. Peptides were analyzed by nano-LC-FT-MS/MS and searched against the human Complete Proteome Set database (downloaded on 2012-02-22) as described above, with phosphorylation of Ser, Thr, and Tyr as variable modifications. Ion signals corresponding to phosphorylated peptides were quantified from their extracted ion chromatograms manually extracted using Qual browser version 12.
was performed ina5Lo fplastic container (20 cm diameter) filled (ϳ80% volume) with tap water at 18°C and an Ethovision system (Noldus) for automated video tracking. Recording time was 6 min at a sampling rate of 5 frames per seconds and threshold for immobility at default settings. Both males and females were used, and each mouse was tested only once. Groups consisted of CN279 transgenic mice (n ϭ 10) and their control littermates (mice carrying either no transgene or rtTA2 or tetO-⌬CAM-AI transgene, n ϭ 8), of mixed age and gender: aged (n ϭ 4) and young (n ϭ 14), males (n ϭ 14) and females (n ϭ 4) mice. There was no statistical influence of age or gender. Statistics. Data analysis and statistics were performed by using the GraphPad Prism 5 software. Data on Figures  2, 3.
Data selection and processing The Fermi satellite was launched on June 11, 2008. Its main instrument, the Large Area Telescope (LAT)  [4] , collects high energy gamma rays (∼ 20 MeV to > 300 GeV) with a large effective area (∼ 6200 cm 2 above 1 GeV for P7CLEAN_V6 at normal incidence  [60] ) and a large field of view (2. 4 sr). Further details on the LAT can be found in Ref. [4, 60]. In our analysis we use the LAT photon data measured between August 4, 2008, and June 15, 2012, in the energy range between 1 GeV and 100 GeV. Events with zenith angles < 100 • are selected to reduce the contamination by gamma-ray emission coming from cosmic-ray interactions in the atmosphere. We select events from the P7ULTRACLEAN_V6::FRONT class. This choice reduces the cosmic-ray background contamination and takes advantage of a narrower PSF as compared to back-converting events.
The flux in pixel i is labelled as F i. 3. A mask, defined by three angles θ 1 , θ 2 and |b| as shown in Figure  2 , is introduced to cover the GC, the Galactic plane, and the high galactic latitude regions, where the statistical fluctuations of the Galactic foreground dominate over the expected DM signal. 4. The optimization procedure consists of finding the set of angles that mask a region such that the S/N ratio is the largest for each DM profile considered. What we technically do is to minimize the inverse of the following quantity S/N = i J i i F i ( 11 ) with i running over unmasked pixels, varying masks. We use the numerical routine Fmin of the Python module scipy. optimize 4 , which minimizes a function using the downhill simplex Profile   2. The corresponding values for ∆Ω, J(∆Ω)∆Ω, and observed flux with statistical errors only (in the energy range between 1 -100 GeV) are also shown.
Acknowledgments We gratefully acknowledge  A. Cuoco ,  G. Zaharijas  and  L. Latronico  for valuable comments and helpful discussions during the preparation of the manuscript. This work was supported by the  Spanish MINECO 's  Consolider-Ingenio 2010 Programme  under grant MultiDark  CSD2009-00064. The work of DGC, GAGV, JHH, CM and MP was supported in part by  MINECO  under grants  FPA2009-08958  and  FPA2012-34694 , and under the ' Centro de Excelencia Severo Ochoa' Programme   SEV-2012-0249 , by the  Comunidad de Madrid  under grant  HEPHACOS S2009/ESP-1473 , and by the  European Union  under the  Marie Curie-ITN program  PITN-GA-2009-237920. JHH was also supported by  DOE  grant  DE-FG02-13ER42022. The work of YM was supported by the  French ANR TAPDMS   ANR-09-JCJC-0146  and acknowledge partial support from the  European Union   FP7 ITN INVISIBLES (Marie Curie Actions ,  PITN-GA-2011-289442 ).
This is particularly true at the present time owing to the advent of a new generation of dedicated detectors: the neutrino telescopes IceCube at the South Pole and ANTARES in the Mediterranean Sea, as well as the GW interferometers Virgo in Italy and LIGO in the United States. Starting from 2007, several periods of concomitant data taking involving these detectors have been conducted. More joint datasets are expected with the next generation of advanced detectors that are to be operational by 2015, with other detectors, such as KAGRA in Japan, joining in the future. Combining information from these independent detectors can provide original ways of constraining the physical processes driving the sources, and also help confirm the astrophysical origin of a GW or HEN signal in case of coincident observation.
Section IV. C describes a method for a HEN-triggered GW search: in this case, the search for GW signals is performed only in parts of the sky defined by neutrino candidate events, and within a time window defined by the observational and phenomenological considerations discussed in Section II. B. The outcome of such an analysis, performed recently with data from the construction phase of ANTARES and from the initial LIGO/VIRGO detectors, is also presented. Alternatively, comprehensive searches for space-time coincidences between independent lists of neutrino and GW events can also be performed, as illustrated in Section IV. D through an example baseline search that could be performed with IceCube and LIGO/Virgo. In this case, time-coincident signals are tested for correlation using a combined GW+HEN likelihood skymap, as well as additional information on the individual significance of the HEN and GW candidates (such as their spatial correlation with large-scale matter distribution).