dataesr/scientific-paragraphs-categorization huggingface dataset:
Regression coefficients for additive effects of founder alleles were estimated at each genomic location. Significance thresholds were obtained by performing 1,000 permutations of the genome scans with phenotype data being shuffled among individuals and 2-logarithm of odds (LOD) support intervals from the linear model were determined for significant (p B 0. 05), suggestive (p B 0. 10), and trending (p B 0. 63) QTL peaks. All phenotype and genotype data have been made publicly available through the Mouse Phenome Database (MPD, http://phenome. jax. org/; MPD:470) and the QTL Archive (http://qtlarchive. org/; Recla_2013).
Identification of candidate genes The genomic elements (e. g. , genes, transposable elements, intergenic regions) associated with the QTL detected by genetic linkage mapping were identified using the MGI mouse genome browser (http://gbrowse. informatics. jax. org/ cgi-bin/gbrowse/mouse_current/; NCBI Build 37; analysis conducted August 2011). All genes within the QTL (coding and non-coding) were considered putative candidate genes. SNPs within each gene were examined for the presence of at least one inter-strain polymorphism matching the allelic effect pattern of the genetic mapping results  (Churchill et al. 2012). SNP data were obtained from dbSNP (Build 128, http://www. ncbi. nlm. nih. gov/projects/SNP/) and the Wellcome Trust Sanger Institute (http://www. sanger. ac. uk/cgibin/modelorgs/mousegenomes/snps.
Plausibility analysis of candidate genes In order to begin to explore and understand the biological processes and molecular pathways underlying a complex trait such as pain sensitivity, it is important to understand that while proteins carry out their functions by interacting with each other, they do not necessarily interact physically  (Doerr 2010). The integration of heterogeneous genomewide data can facilitate the development of functional relationship networks revealing the collaborative roles between proteins in carrying out a biological process  (Guan et al. 2008). Genes involved in a complex trait are likely to participate in similar or overlapping pathways and should thus be more likely to share protein domains, biological annotations, and patterns of gene expression. Using these paradigms, the plausibility of each candidate gene's role in pain response was assessed by compiling heterogeneous genomic evidence from a variety of electronic databases.
In order to examine the known functional relationships between each candidate gene and known pain genes, a list of experimentally validated pain-related genes was compiled by querying the online databases described in Table  1  using the terms ''pain'' and ''nociception. '' Ingenuity Pathway Analysis (IPA, http://www. ingenuity. com/), a bioinformatics system based on a manually curated knowledgebase, was used to map the known IPA functional interactions between candidate and known pain genes. MouseMap (http://sonorus. princeton. edu/mousemap/ applet. shtml) is a web-based tool that provides access to tissue-specific predicted functional relationships between mouse genes  (Guan et al. 2012). A list of brain ventricular zone functional relationships predicted by MouseMap was obtained from Dr.
Yuanfang Guan (University of Michigan Medical Center, Ann Arbor, Michigan) and analyzed for direct relationships with the candidate gene Hydin with edge weight scores C0. 9. The functional relationship networks generated by MouseMap and IPA were assessed for enrichment of Gene Ontology (GO)  (Ashburner et al. 2000)  and Mammalian Phenotype (MP)  (Smith and Eppig 2009)  terms using VLAD (http://proto. informatics. jax. org/proto types/vlad-1. 0. 3/), a web-based tool for statistical term enrichment (annotation date: November 2, 2011). For each candidate gene, gene expression annotations were collected from the Allen Brain Atlas  (Lein et al. 2007 ), Gene Expression Omnibus (GEO)  (Barrett et al. 2013) , IPA, and the Mouse Genome Database (MGD)  (Eppig et al. 2012). Serial Pattern of Expression Levels Locator [SPELL  (Hibbs et al.
2007 )], a query-driven search engine for large gene expression microarray compendia, was used to predict genes that share spatial and temporal expression patterns with the candidate genes. InterPro protein domain  (Hunter et al. 2012 ) and MP annotations were obtained from MGD. Pain-related phenotype data were collected from MGD, IPA, PainGenesdb, and Ge-neWeaver, a web-based tool that allows users to integrate phenotype-centered gene sets across species, tissues, and experimental platform  (Baker et al. 2012). GO terms were obtained from MGD and AmiGO  (Carbon et al. 2009) , and IPA canonical pathways were obtained from IPA. All queries were performed July-November of 2011. A summary of the electronic databases mined for biological annotations during this analysis is provided in Table  2.
Real-time quantitative PCR analysis of the candidate gene Hydin Whole brains from male and female pain-sensitive (C57BL/6J) and pain-resistant (A/J) mice (n = 5/group) were dissected and stored in RNAlater Ò (Life Technologies, Carlsbad, CA, USA) prior to homogenization in TRIzol Ò. Total RNA was extracted using the PureLink TM RNA Mini Kit (Life Technologies, Carlsbad, CA, USA) as per manufacturer's protocol. Samples were further purified with on-column DNase I treatment (Qiagen, Venlo, Table  1  Electronic databases queried for experimentally validated pain-related genes using the keywords ''pain'' and ''nociception'' Netherlands). Extracted RNA samples were assessed for integrity and concentration using the Agilent Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) and Nanodrop (ThermoFisher Scientific, Waltham, MA, USA), respectively.
The remaining five DO founder strains are reported to have allelic contributions that condition responses to acute thermal pain that fall between A/J and C57BL/6J in the following order: (1) A/J (least sensitive) (2) WSB/EiJ and 129S1/SvlmJ (3) NOD/ShiLtJ and PWK/PhJ (4) NZO/HlLtJ (5) CAST/EiJ and C57BL/6J (most sensitive) Hot-plate data from inbred DO founder strains have been generated by four independent labs: Jaxwest (2013),  Mogil et al. (2013) ,  Koide et al. (2013), and Chesler et al. (2013). All four datasets recapitulate the inbred strain sensitivity ranking predicted by the allelic contributions at the Tpnr6 locus (the rankings of NOD/ShiLtJ and C57BL/ 6J are reversed in the Chesler study).
The MPV does not incorporate haplotype data from the three wild-derived DO founder strains (WSB/EiJ, PWK/PhJ, CAST/EiJ). To circumvent this limitation, we examined SNP data from the Wellcome Trust Sanger Institute (REL-1211; NCBI build 37) and searched for haplotype regions within Tpnr6 matching the A/J / C57BL/6J | CAST/EiJ allelic effect pattern. We identified a SNP exclusive to A/J near the 5 0 end of the haplotype block reported by the MPV, classified by Sanger as ''upstream_genetic_variant'  ' and ''downstream_ genetic_variant'' (no rsID; chr8:112787281). We observed several CAST/EiJ-exclusive SNPs within the Tpnr6 locus, particularly near the 3 0 end of the candidate gene Hydin. A single CAST/EiJ-exclusive SNP classified as ''upstream_ genetic_variant'' was present near the reported end of the MPV haplotype block (rs245877262; chr8:113018557), just downstream of the 3 0 end of Hydin.
We evaluated the genomic sufficiency of the Tpnr6 locus by examining the SNP variants and allelic effect patterns present within the interval, allowing us to narrow Tpnr6 to the candidate gene Hydin. We then assessed Hydin's functional sufficiency by compiling functional annotation data summarizing Hydin's current relevance to pain response. While none of the tools described here should be used exhaustively or in an exclusionary manner, all were helpful in assessing the pain-related validity of the Tpnr6 locus. While inbred laboratory strains exhibit sufficient genetic and phenotypic variation for behavioral QTL detection, it has been speculated that historical inbreeding processes selected for ease of handling. As previously reported by  Philip et al. (2011) , domestication of inbred strains, including the eight DO progenitors, likely operated on multiple loci throughout the genome.
Acknowledgments This work was supported financially by the  National Science Foundation   IGERT Training Grant ,  NIH   GM076468 , and start-up funding from  The Jackson Laboratory  to EJC. This project was completed by JMR as part of her graduate dissertation research in the  Graduate School of Biomedical Sciences and Engineering (GSBSE)  at the  University of Maine, Orono. The authors would like to thank  Drs. Matthew Hibbs  ( Trinity University ) and  Yuanfang Guan  ( University of Michigan ) for their knowledge and contributions to the MouseMap and SPELL analyses, as well as the reviewers of the manuscript for their insights and timely suggestions.
After washes in PBS, cells were incubated for 1 h with a secondary anti-rabbit Alexa-488 antibody (1/500 in PBS-BSA, Invitrogen/Molecular Probes, Eugene, OR, USA). Cells were then washed and the DNA counterstained with 50 μg/ml propidium iodide for 30 min in the presence of 200-μg/ml RNAse A. To measure the production of ROS, we used the probes 2′,7′-dichlorodihydrofluorescein diacetate (H 2 DCFDA) which fluoresces when oxidised by intracellular ROS and MitoSOX which responds to mitochondrial O 2 -(both obtained from Molecular Probes). Briefly, cells were incubated with 10-μm H 2 DCFDA or MitoSOX during 15 min, washed with PBS and immediately analysed by flow cytometry. All the assays were monitored on a Galaxy flow cytometer (Partec, Münster, Germany) and analysed with the FloMax software (Partec) on at least 100 00 cells.
Fluorescence microscopy. TdT-mediated dUTP Nick-End Labeling (TUNEL) and Hoechst 33342 stainings were used to analyse nuclear morphologies according to the manufacturer's instructions (DeadEnd Fluorometric TUNEL System, Promega, Charbonnières-les-Bains, France). For in vitro assays, adherent and floating cells were cytospun and phenotypes of nuclei were determined by analysing at least 300 cells per experiment. For in vivo staining, tumours were cut in 6-μm sections using a cryostat microtome, mounted on gelatinised slides, processed and analysed by determining the mean pixels intensities of random microscopic fields by using the ImageJ software (NIH). Senescence-associated β-galactosidase (SA-β-gal) determination. Stainings for SA-β-gal activity revealed at pH 6. 0 were performed as previously reported.
The UV detector (Waters 486, Milford, MA, USA) was set at 306 nm. RSV amounts were quantified with an SP4400 ChromJet integrator (Spectra Physics, San Jose, CA, USA). Western blotting. After the indicated treatments, adherent and floating cells were washed in PBS, lysed in a Ripa buffer and western blot analyses were performed as previously described. 18 atistical analysis. The in vitro data are expressed as the mean ± S. D. of three independent experiments. In vivo data are shown as median ± the first and the third quartiles. Statistical significances were evaluated either with the Mann-Whitney or the t-test as required.
Acknowledgements. We thank  Dr Pierre-Yves Risold  and  Ms Annie Laroche ,  EA3922 ,  Faculté de Médecine ,  Université de Franche-Comté, Besançon, France , for their help in analysing the histological samples. We are grateful to  Dr J. A. H. Inkster ,  University of Geneva , for valuable English corrections. This study was supported by grants from the  'Conseil Régional de Bourgogne', and the 'Ligue contre le Cancer', comités de Côte d'Or et du Jura.
Fortunately, the young open cluster NGC 2264 falls within the visibility zone of CoRoT, which enabled it to be observed continuously for over three weeks in March 2008. The resulting dataset offers an unprecedented insight into the variability of PMS stars, and was used to study accretion  (Alencar et al. 2010) , rotation  (Favata et al. 2010; Affer et al. 2013 ) and PMS pulsations  (Zwintz et al. 2011) , as well as to search for eclipsing binaries. NGC 2264 is a very well-studied young star forming region due to its relative proximity, well-defined membership list and low foreground extinction  (Dahm 2008). It is the dominant component of the Mon OB1 association in the Monoceros constellation, situated in the local spiral arm at a distance of ∼700-900 pc (e. g. Sung et al. 1997; Baxter et al.
g. Kepler-16 Doyle et al. 2011 , Kepler-34 and 35 Welsh et al. 2012 , Kepler-38 Orosz et al. 2012a , Kepler-47 Orosz et al. 2012b and Kepler-64 Schwamb et al. 2012). In all of these systems, the orbital angular momentum of the planets is closely aligned with that of the host binary, strongly suggesting in situ formation within a circumbinary disk. Initial theoretical modelling suggests that circumbinary planets around close separation binaries should be a common occurrence  (Alexander 2012). CoRoT 223992193 is a very rich system. This paper focuses on the first step in its characterisation, namely the parameters of the two stars based on the 2008 CoRoT data and follow-up radial velocities. The detailed study of the interaction of the stars with their environment requires additional, multi-band photometry and spectroscopy, and will be the subject of a later paper.
Photometry CoRoT observed NCG 2264 continuously for 23. 4 days between 7 and 31 March 2008 (run SRa01). CoRoT observations are conducted in a broad 300 -1000 nm bandpass with a standard cadence of 512 s, giving 3936 photometric data points for this run. A total of 8150 stars with magnitudes 9. 5 < R < 17 were monitored in the 1. 3×2. 6 degrees field-of-view of CoRoT's exoplanet channel. About 1000 of these were previously known or suspected members of NGC 2264. These observations 2  represent an unprecedented photometric dataset for a young cluster, both in terms of sampling and precision. Basic aperture photometry is carried out on board the satellite, and the data were further processed by the CoRoT pipeline  (Auvergne et al. 2009)  to correct them for known instrumental effects (including background and pointing jitter).
Spectroscopy We performed low resolution spectroscopy to infer the combined spectral type and medium resolution spectroscopy to extract radial velocities. We obtained a low-resolution (∼7 Å) optical spectrum of CoRoT 223992193 on 13 April 2011 (JD 2455665. 3334) using the CAFOS focal reducer  (Meisenheimer 1994 ) on the 2. 2 m Calar Alto telescope equipped with the G-100 grism and the SITe#1d 15 CCD camera, over the 4600-7700 Å wavelength range. The spectrum was acquired at an airmass of 1. 4 using a slit width of 1. 5 arcsec, and an exposure time of 1800 s. A spectrum of the spectrophotometric standard, Feige 34, was obtained immediately after, at an airmass of 1. 0, with the same set-up. The spectra of the two objects were reduced in the same way, namely: the 2D images were bias and flat-field corrected, and the stellar and neighbouring sky spectra were extracted using the iraf/twodspec package 3   (Tody 1993 ).
Out of eclipse variability removal The target displays significant out-of-eclipse (OOE) flux variations, which must be accounted for when modelling the CoRoT light curve to determine the fundamental parameters of the two stars. Given the complex nature of the OOE variations, it is not practical to model them at the same time as the eclipses. We therefore opted to remove the OOE variations before modelling the residuals with standard eclipse modelling software. We first tried fitting cubic splines to the OOE data (masking the in-eclipse regions) and interpolating across the eclipses. This gives fairly satisfactory results, but there is no principled way to propagate uncertainties arising from the OOE removal process through to the residuals. We therefore implemented a second approach, based on Gaussian Process (GP) regression, which provides both a better fit to the OOE data, and a more robust means of interpolating across the eclipses.
Radial Velocities We measured radial velocities by cross-correlating the spectra described in Section 2. 2 with MARCS theoretical model spectra  (Gustafsson et al. 2008). Before performing the cross-correlation, we masked out regions contaminated by telluric emission. We also masked the calcium infrared triplet in the ISIS spectra, as the lines are very broad and tend to smear out the resulting cross correlation function (CCF). The remaining wavelength intervals used were: 8380-8392, 8455-8484, 8510-8525, 8575-8644 and 8685-8745 Å (see Figure  5 ). There were many emission lines present in the FLAMES spectra, not only from the system but also the nebula. These emission lines were not present in the model spectra and inhibited clean cross-correlation. We therefore clipped and interpolated a few data points before and after each emission line to try and fully remove their effect.
We also masked the Hα emission region (6545-6587 Å). The regions used for cross-correlation of the FLAMES spectra were: 6521- 6545, 6587-6598, 6610-6642, 6648-6700 and 6702-6713 Å. After experimenting with a range of parameters for the MARCS model spectra, we opted to use T = 4000 K and log g = 4, which gave the best CCF contrast. We did not broaden the template, as that results in broader CCF features which makes it more difficult to separate the peaks corresponding to the two stars. The CCFs were computed and fitted using purpose written Python code. We initially performed a simple least-squares fit to the largest peak(s) in the CCFs, using a model consisting of either one or two Gaussians plus a constant offset. However, we found that the resulting RVs were significantly affected by the pronounced correlated noise in the CCFs (examples of which are shown in Figure  8 ).
This is a major issue when measuring RVs via cross-correlation, particularly for late-type stars. This correlated noise arises in part from noise in the object spectrum, but also -more critically -from mismatch between the object and template spectra. A number of approaches have been developed to account for it when evaluating the uncertainties. For example, Tonry & Davis (1979) decompose the CCF into components which are symmetric and anti-symmetric with respect to the peak, and use the root mean square (RMS) scatter of the antisymmetric component to estimate the CCF noise, on the basis that any 'real' CCF signal should be symmetric about the peak. This is the most widely used approach, and it is implemented in the iraf cross-correlation package fxcor. Working with VLT/FLAMES spectra of moderately faint stars from the OGLE survey,  Bouchy et al.
Conclusions and future work We report a new double-lined, detached eclipsing binary, which is comprised of two pre-main sequence M-dwarfs, discovered by the CoRoT space telescope in the NGC 2264 star forming region. We have measured the fundamental parameters of both stars using the continuous 23. 4 day light curve obtained by CoRoT in March 2008, as well as 22-epochs of radial velocity data obtained almost four years later with VLT/FLAMES and WHT/ISIS. The orbit is consistent with circular (e = 0. 0037 +0. 0036 -0. 0025 ) and has a period of 3. 8745745 ± 0. 0000014 days and a separation of 10. 921 ± 0. 056 R. The primary and secondary stars have masses of 0. 668 +0. 012 -0. 011 and 0. 4953 +0. 0073 -0. 0072 M , and radii of 1. 295 +0. 040 -0. 037 and 1. 107 +0. 044 -0. 050 R , respectively.
NGC 2264 was re-observed by CoRoT in December 2011 and January 2012, as part of a co-ordinated multiobservatory campaign involving Spitzer, Chandra, MOST 10  (Microvariability and Oscillations of STars) and a host of ground-based observatories, including CFHT ugr photometry and VLT/FLAMES spectroscopy 11. Although the sampling of the observations by other telescopes is significantly sparser than that of the CoRoT data, the widely separated bandpasses of the CFHT, CoRoT and warm Spitzer data should help to disentangle the contributions of starspots and any occultations by dusty material in the out-of-eclipse variability. We will also model the time-dependent Hα emission seen in the FLAMES spectra, which may shed light on any ongoing accretion in the system. A number of other EBs were discovered in the field of NGC 2264 during the same CoRoT observation.
Acknowledgements. We thank  Isabelle Baraffe  for extending her models of stellar evolution (with mixing length α = 1. 9) down to lower masses allowing us to compare the source's masses and radii to these model predictions. We thank  D. Barrado , the Director of  Calar Alto Observatory , for granting  Discretionary Time  to this project. We also thank  Catarina Alves de Oliveira  for providing her automatic fitting method to derive the spectral type of the source from the Calar Alto low resolution spectrum. This research is based on data collected by the CoRoT satellite, which is publicly available via the IAS Data Center at http://idoc-corot. ias. u-psud. fr/. Based on observations made with  ESO Telescopes at the La Silla Paranal Observatory  under programme  ID 088. C-0239 (A). The WHT and INT are operated on the island of  La Palma  by the  Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos  of the  Instituto de Astrofsica de Canarias.
For determination of the capture yield, the evaluated neutron flux Φ(E n ) described in Ref. [17]  was used. With the second collimator in capture mode, the flux of neutrons below 400 keV, integrated over the nearly Gaussian beam profile at the sample position amounts to 2. 2 × 10 5 neutrons per pulse. The electronic signals were recorded by a highperformance digital data acquisition system, based on 8-bit flash-ADC units operating at a sampling rate of 500 MHz. A memory buffer of 48 MB allows us to measure up to 96 ms in neutron time-of-flight, corresponding to a neutron energy of 20 meV. However, data analyses are limited to the region above 27 meV, where the neutron flux has been reliably evaluated. The digitized signals were processed offline by specially developed and optimized data analysis algorithms.
III. CALCULATION OF THE YIELD The aim of the data analysis is to determine the neutron capture yield of the 58 Ni(n,γ) 59 Ni reaction, which is essential for extracting the pointwise cross section and the resonance parameters. The energy calibration of the C 6 D 6 detectors was performed with 137 Cs, 88 Y and Am/Be calibration sources, which were also used to verify the stability of the detector response during the 32 days of the experiment. In addi-tion, the energy resolution of the two C 6 D 6 detectors was assessed from these calibration data. The time-of-flight to energy calibration, that is the determination of the fixed flight path length, was based on the analysis of 197 Au resonances, according to the method described in Ref. [19]. The well-established pulse height weighting technique, originally proposed by Maier-Leibnitz  [20] , was applied to the recorded signals.
For the simulation GEANT4-9. 6. p01 version was employed, which -for the neutroninduced reactions -relies largely on the tabulated cross section data from ENDF/B-VII. 0. A detailed software replica of the experimental area and the materials inside it was implemented in the simulations. The energy deposited in C 6 D 6 detectors, together with the corresponding time information was analyzed in the same manner as the experimental data. The reliability of the simulated neutron background was verified by comparing the GEANT4 results against the yield measured with a highpurity (99,95%) carbon sample of 1 cm thickness and 2 cm diameter. A decade-wise comparison between the experimental and simulated yield is presented in Table  II. A good agreement is observed between the measured and the simulated yield for C in the whole neutron energy range of interest, from near-thermal to 400 keV.
9 eV resonance of 197 Au  [23]. Figure  2  shows the yield measured at n TOF, compared with the one calculated on the basis of ENDF/B-VII. 0 and ENDF/B-VII. 1 resonance parameters. The evaluation from ENDF/B-VII. 0 is also representative of other major libraries such as JENDL-4. 0, JEFF-3. 1. 2, CENDL-3. 1 and ROSFOND-2010  [24]. The difference between two consecutive versions of the ENDF library and their comparison with the n TOF data will be discussed below.