dataesr/scientific-paragraphs-categorization huggingface dataset:
Pathology The collection of pathology and tumor marker information for BCAC has been described previously  (36). Briefly, studies provided information on ER status and grade of differentiation. The most common source of data for ER status was medical records, followed by inmunohistochemistry performed on tumor tissue microarrays or whole section tumor slides. ER-negative status was defined as , 10% of the tumor cells stained for a number of participating studies, where patients were recruited from Europe (n ¼ 30), Australia (n ¼ 3), Canada (n ¼ 2) and the USA (n ¼ 5) from 1972-2011 (median recruitment year ¼ 2004). Histologic grade was reported using the Nottingham combined grading system. For the purpose of this analysis, Grades 1 and 2 were jointly considered 'low grade' while Grade 3 was considered 'high grade'.
FunciSNP annotation The FunciSNP package  (38)  was implemented in R using default parameters with a search window of +500 kb. Analyses were run separately for each of three index SNPs: rs17550038 (TACC2), rs799890 (EIF3H) and rs6762644 (ITPR1). The Fun-ciSNP tool identified all SNPs from the 1000 genomes project (http://www. 1000genomes. org/, last accessed on 19 June 2014) within 500 kb of the index SNP that overlapped with at least one biofeature. The biofeatures included in this analysis were  (1)  built-in consensus promoter regions, ENCODE DNaseI HS and CTCF sites from the getFSNPs function and (2) HS sites, FAIRE signals and histone modification ChIP-seq data (H3K4me1, me2, me3, H3K9Ac and H3K27Ac) downloaded as bed files from ENCODE Build 37 production data (http:// genome. ucsc. edu/ENCODE/, last accessed on 19 June 2014) for HMEC normal mammary epithelial cells, and the MCF7 and T47D breast cancer cell lines when available (Supplementary Material, Table  S12 ).
ACKNOWLEDGEMENTS We thank all the individuals who took part in these studies and all the researchers, clinicians, technicians and administrative staff who have enabled this work to be carried out. This study would not have been possible without the contributions of the following:  Andrew Berchuck  (OCAC),  Rosalind A. Eeles ,  Ali Amin Al Olama ,  Zsofia Kote-Jarai ,  Sara Benlloch  ( PRAC-TICAL ),  Antonis Antoniou ,  Lesley McGuffog ,  Ken Offit  (CIMBA),  Joe Dennis ,  Alison M. Dunning ,  Andrew Lee  and  Ed Dicks ,  Craig Luccarini  and the staff of the  Centre for Genetic Epidemiology Laboratory ,  Anna Gonzalez-Neira  and the staff of the CNIO genotyping unit,  Daniel C. Tessier , Fran-AOCS: We wish to thank  Heather Thorne ,  Eveline Niedermayr , all the kConFab research nurses and staff, the heads and staff of the  Family Cancer Clinics , and the  Clinical Follow-up Study  (which has received funding from the  NHMRC , the  National Breast Cancer Foundation ,  Cancer Australia , and the  National Institute of Health (USA))  for their contributions to this resource, and the many families who contribute to kConFab.
The BCAC is funded by  CR-UK  ( C1287/A10118  and  C1287/A12014 ). Meetings of the BCAC have been funded by the  European Union   COST programme  ( BM0606 ). D. F. E. is a Principal Research Fellow of CR-UK. E. S. is supported by  NIHR Comprehensive Biomedical Research Centre, Guy's and St. Thomas' NHS Foundation Trust  in partnership with  King's College London, UK  I. T. is supported by the  Oxford Biomedical Research Centre. The BSUCH study was supported by the  Dietmar-Hopp Foundation , the  Helmholtz Society  and the  German Cancer Research Center (DKFZ)  The  CECILE study  was funded by  Fondation de France ,  Institut National du Cancer (INCa) ,  Ligue Nationale contre le Cancer, Ligue contre le Cancer Grand Ouest, Agence Nationale de SecuriteSanitaire (ANSES) ,  Agence Nationale de la Recherche (ANR)  The CGPS was supported by the  Chief Physician Johan Boserup and Lise Boserup Fund , the  Danish Medical Research Council and Herlev Hospital  The  CNIO-BCS  was supported by the  Genome Spain Foundation , the  Red Tematica de Investigacion Cooperativa en Cancer  and grants from the  Asociacion Espan ˜ola Contra el Cancer  and the  Fondo de Investigacion Sanitario  ( PI11/00923  and  PI081120 ).
Investing in knowledge society through the  European Social Fund. The ESTHER study was supported by a grant from the  Baden Wu ¨rttemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the  German Cancer Aid (Deutsche Krebshilfe ). The  GC-HBOC  was supported by  Deutsche Krebshilfe  ( 107 352 ) The GENICA was funded by the  Federal Ministry of Education and Research (BMBF)   Germany grants   01KW9975/5 ,  01KW9976/8 ,  01KW9977/0  and  01KW0114 , the  Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ) ,  Heidelberg, Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA) ,  Bochum , as well as the  Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany.
The HEBCS was financilly supported by the  Helsinki University Central Hospital Research Fund ,  Academy of Finland  (  132473 ), the  Finnish Cancer Society, The Nordic Cancer Union  and the  Sigrid Juselius Foundation. The HMBCS was supported by a grant from the  Friends of Hannover Medical School  and by the  Rudolf Bartling Foundation. Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (ALF) between  Stockholm County Council  and  Karolinska Institutet , The  Swedish Cancer Society , the  Stockholm Cancer Foundation , and  Bert von Kantzow 's foundation. The KBCP was financially supported by the special Government Funding (EVO) of  Kuopio University Hospital  grants,  Cancer Fund of North Savo , the  Finnish Cancer Organizations , the  Academy of Finland  and by the strategic funding of the  University of Eastern Finland  kConFab is supported by a grant from the  National Breast Cancer Foundation , and previously by the  National Health and Medical Research Council (NHMRC) , the  Queensland Cancer Fund , the  Cancer Councils of New South Wales, Victoria, Tasmania and South Australia  and the  Cancer Foundation of Western Australia.
and Margaret T. Grohne Family Foundation  and the  Ting Tsung and Wei Fong Chao Foundation. MCCS cohort recruitment in was funded by  VicHealth  and  Cancer Council Victoria. The MCCS was further supported by Australian  NHMRC  grants  209057 ,  251553  and  504711  and by infrastructure provided by  Cancer Council Victoria. The MEC was support by  National Institutes of Health  grants  CA63464 ,  CA54281 ,  CA098758  and  CA132839. The  Canadian Breast Cancer Research Initiative  supported the initial case -control study. This work was supported by the  Quebec Breast Cancer Foundation , the  Canadian Institutes of Health Research for the 'CIHR Team in Familial Risks of Breast Cancer' program -grant #  CRN-87521  and the  Ministry of Economic Development, Innovation and Export Trade -grant #  PSR-SIIRI-701.
The NBCS was supported by grants from the  Norwegian Research council ,  155218/V40 ,  175240/S10  to ALBD,  FUGE-NFR 181600/V11  to VNK and a  Swizz Bridge Award  to ALBD. The NBHS was supported by  National Institutes of Health  grant  R01CA100374. Biological sample preparation was conducted the  Survey and Biospecimen Shared Resource , which is supported by  P30 CA68485. The OBCS was supported by research grants from the  Finnish Cancer Foundation , the  Academy of Finland , the  University of Oulu  and the  Oulu University Hospital. This work for OFBCR was supported by grant  UM1 CA164920  from the  National Cancer Institute. The content of this manuscript does not necessarily reflect.
Similar results were obtained in mutant AVN and PF myocytes under basal conditions or ISO (Fig  4e-l ). DADs were consistently recorded also in AVN and PF myocytes and displayed properties similar to those seen in SAN cells. Apart from longer action potential durations in mutant AVN cells, no differences were found in action potential parameters between mutant and control AVN and PF myocytes at baseline (Supplementary Table  1 ). The very low basal pacemaker activity recorded in mutant PF myocytes was also increased by ISO application, but -similar to our findings in SAN and AVN -the difference in spontaneous beating rates between control and mutant cells remained (Fig  4e  and f ). Taken together, our data show that I f is critical for setting the basal spontaneous beating rate in SAN, AVN, and PF myocytes, but is not required for the sympathetic regulation of pacemaking in these structures.
Cloning of HCN constructs Murine HCN4 and HCN2 (mHCN4 and mHCN2) and human HCN4 (hHCN4) cDNAs (GenBank Acc. NM_001081192, NM_008226, and NM_005477) in pCDNA1 vector were kindly provided by Benjamin Kaupp (Forschungszentrum caesar, Bonn, Germany). A hemagglutinin (HA) epitope tag (YPYDVPDYA) was attached to the N-terminus of the open reading frame of hHCN4  19. The selectivity filter GYG motif was mutated to AYA by overlap PCR-based, site-directed mutagenesis resulting in hHCN4-G480A/G482A (hHCN4-AYA). For two-electrode voltage-clamp experiments mHCN4, mHCN2, and HA-hHCN4-AYA were cloned into an RNA expression vector (pGem-HeJuel 62 ). For the generation of transgenic mice, the Tet-responsive element (Tre-Tight) of pTRE-Tight (Clontech, Mountain View, CA, USA) was cloned into pWHERE2 v. 01 (Invivogen, San Diego, CA, USA).
ECG signals were recorded using a telemetry receiver and an analog-to-digital conversion data acquisition system for display and analysis by Dataquest A. R. T. ™ software. Heart rates were determined from interbeat (RR) intervals of the ECG. Mean heart rate values were obtained from each mouse for a 24-h period. For drug administration or exercise experiments, mean heart rate values were calculated in each mouse by analyzing different periods of 5 min. ECG parameters were measured with ECG Auto 1. 5. 7 software (EMKA, Paris, France). Swimming tests were performed using customized Plexiglas boxes (15×32×13 cm (WxLxH)) filled with pre-warmed water (32°C).
Telemetric blood pressure recordings Mice with a body weight of >24 g were anesthetized by i. p. administration of ketamine/ xylazine adapted to body weight. Telemetric transmitters (Physiotel PA-C10, Data Sciences International) were subcutaneously implanted with the sensing tip placed in the aorta via the left carotid artery. After 10 days of recovery from surgery, interventions and recordings (Dataquest A. R. T. ™ software for acquisition and analysis) were started. For each mouse, blood pressure was continuously recorded for at least 48 h. For data analysis, mean blood pressure data were obtained for each consecutive minute within one recording period. The blood pressure mean data were then sorted by the corresponding activity in 7 bins between "0" (no activity) and "7" (activity >30 arbitrary units (aU)) and averaged over all mice.
Acknowledgments We thank  I. Hermans-Borgmeyer  for transgenic services,  K. Sauter  for technical assistance, and the teams of the  UKE animal facility (Hamburg)  of the RAM animal facility (Montpellier) for animal care. We also thank  N. Lamb  for helpful discussions. The project was supported by the  Agence Nationale pour la Recherche  grant  ANR-06-PHISIO-004-01 ,  ANR-2010-BLAN-1128-01 ,  ANR-09-GENO-034 , and  ANR-13-BSV1-0023-02 , the  NIH   R01HL087120-A2  grant (M. M. ), the  Fondation de France  grant  2008002730  (J. N. ), the  Fondation pour la Recherche Medicale  grant  DPC20111122986  (A. F. ), by the  Deutsche Forschungsgemeinschaft  Grant  IS63/1-1/2  (to D. I. and H. E),  IS63/3-1/2  (D. I. ), and  DFG FOR 604  and  Es 88/10-1  (T. E. ). P. M. was supported by the CavNet, a  Research Training Network (RTN)  funded through the  European Union Research Programme  ( 6FP )  MRTN-CT-2006-035367.
Red points mark radar stations PEY and BEN. The black contour lines show areas where HF radar data are available more than 20 % over the assimilation period for PEY (full) and BEN (dashed) radars and is called the observation domain (OD). The black box sketches the pseudo-observation domain (POD). The meridional magenta line crossing the coastal current will be used for Hovmöller diagrams. Surface currents of free simulation averaged over the assimilation period are shown. Color bars range from 0 (white) to 0. 5 (red) m s -1. The 100, 1000 and 2000 m isobaths are drawn (black thin lines). numerical regional primitive equation model in order to minimize differences between the model and the radar-derived surface currents. Wind optimization is an important issue as, in coastal zones, surface wind errors can explain a large part of the model error regarding surface currents  (He et al.
1  and is hereafter referred to as the observed domain (OD). When measurements from both stations are available, variability in the total coverage is mainly due to the degradation of PEY performance owing to high wind speed. Twenty-eight temperature and salinity profiles from conductivity-temperature-depth (CTD) measurements were also taken into consideration for the analysis of assimilation results. CTD measurements were carried out in the area within the geographical grid defined by coordinates 5. 8-7. 35 • E and 42. 6-43. 3 • N, over the period 11-14 December 2011, during a cruise undertaken in the framework of the European TOSCA (Tracking Oil Spill and Coastal Awareness network, http://www. tosca. med. eu) program. Note that this data set is independent data that can be used for validation of results.
1 day was found to be adequate for win ana. Traditionally, observations are considered within the optimization window. However, depending on the application, the covariances between observations and ensemble simulations at a given time may be low due to a weak causality between forcing and model solution at the observation points. At such a stage we suggest taking into consideration a temporal shift between the observation and optimization windows. Given a time reference that corresponds to the beginning of win ana , the observations before (after) this time are included in win - obs (win + obs ). The values win - obs = 0 day and win + obs = 3 days provide the best results in terms of the overall Er for wind and surface currents. The experiment performed with this data set is hereafter referred to as WindTE.
2b ), and is weakened during the period 4-9 December 2011. A southward shift of the NC vein was also found during the period 10-16 November 2011. Data assimilation performance reduces when moving southward and degradation regions may appear. This may be due to the scarcity of observations when moving away from the radar stations. The norm of vector speed difference U b -U a between free currents U b and analyzed currents U a averaged over the assimilation period and at the surface (Fig. 10a ) and integrated over the first 200 m below the surface (Fig. 10c ) shows that the corrections are primarily located on the surface in the NC vein all along the French coast and over the GoL shelf break and can occur over the whole MD. However, they vanish with depth. Once we have verified that the wind optimization obtained through the assimilation of surface velocities does  not degrade the model solution in the observation area, the question of its impact off the OD, and in the whole water column, in terms of hydrological variables, arises.
The use of a high-resolution regional model configuration with an advanced physical parametrization  (Ourmières et al. , 2011; Guihou et al. , 2013)  could also lead to significant improvements. Acknowledgements. The experiment at sea and the HF radar installation were supported by ECCOP-LEFE/IDAO (CNRS/INSU) and TOSCA (2G-MED09-425). The TOSCA project is cofinanced by the European Regional Development Fund, in the framework of the MED program. This study is also supported by LEFE-INSU GMMC. The calculations were performed using NEC-SX8 from GENCI-IDRIS resources (grant 2012011707). The authors also wish to thank Mercator Ocean and Météo-France for providing numerical data and observations. The MIO RADAR team (Y. Barbin, C. Quentin, J. Gaggelli, P. Guterman) is also acknowledged for its major contribution to radar field campaigns of this study.
Population projections and potential impacts on tropical coastal seas For spatial analyses of tropical coastal seas, we used Environmental Systems Research Institute's (ESRI) ArcGIS software suite (v. 9. 3. 1), including ArcInfo, ArcCatalog and ArcMap; ESRI ArcView (v. 3. 2a); and QGIS (v. 1. 80), defining the tropics as the area bounded by the Tropics of Cancer and Capricorn, 23°26 0 16 00 latitude N and S respectively  (Epoch, 2012) , and coastal seas as those within the continental shelves (depths from 0 to 200 m in the Shuttle Radar Topography Mission (SRTM) 30 Plus, global, gridded terrain data)  (Becker et al. , 2009). SRTM 30 Plus is a globally seamless topography and bathymetry grid, comprised of the shuttle-based topography of the earth (SRTM) dataset, combined with bathymetry from a satellite-gravity model  (Becker et al.
, 2009). Grid cell size is 30-arcseconds, which corresponds to about 926 m at the equator. We used the Millennium Coral Reef Mapping Project (2010) validated and unvalidated data layers of warm water coral, found primarily between 30°N and 30°S latitude, using all coral types represented in the data layer, and then converted the vector-based data layer to a 30 arcsecond cell sized grid in order to facilitate spatial overlay with the human population data. The 2011 LandScan  (Bright et al. , 2012)  global, gridded (30-arcsecond) dataset was used to represent terrestrial human population counts. This data layer is the highest resolution ''ambient population (average over 24 h)'' currently available  (Bright et al. , 2012) , and is based on an algorithm which uses spatial data and image analysis technologies and a multi-variable dasymetric modeling approach to disaggregate census counts within an administrative boundary  (Bright et al.
, 2012). Population counts are reported for each 30-arcsecond grid cell; since grid cells based on Euclidean coordinate systems are not uniform in area as one moves away from the equator, the values are numbers of humans per cell rather than their density. We defined the terrestrial 'coastal region' as the region within 100 km of the shoreline regardless of elevation. We started with the Global Self-consistent Hierarchical High-resolution Shorelines (GSHHS) global coastline polygon data layer  (NOAA, 2013) , then deleted the Antarctic polygons as well as any polygons that did not intersect a polygon version of LandScan land delineation in the high resolution, level 1, GSHHS_h_L1 file. ArcCatalog was used to convert all polygon vertices from the edited GSHHS data layer into points in order to perform a geodesic buffer on said points, thereby accurately representing scale at any given point on the Earth's surface, regardless of a given point's distance from the equator.
Acknowledging this dependence  (Bell et al. , 2006 (Bell et al. , , 2009;; Mills et al. , 2011)  is pivotal to reconciling the largely separate agendas for food security and biodiversity conservation  (Rice and Garcia, 2011; Foale et al. , 2013). A mix of coastal fisheries and appropriate coastal aquaculture is required  (Belton and Thilsted, 2013; Merino et al. , 2012) , and MSP can incorporate both these uses of coastal waters while adjudicating the access conflicts between them and other legitimate uses of the coastal seas  (Lorenzen et al. , 2010b; Agardy et al. , 2012). Beyond addressing food security challenges, MSP can be expected to help address the issues faced by managers of tropical coastal waters in several ways  (Agardy, 2010) : Protecting ecologically critical areas to allow healthy ecosystem function.
Measurements with air-free ice and standard gas reveal a mean process blank of 10. 8 ± 4. 6 ppb. This offset is determined for each extraction vessel separately and is subtracted from the measurements on natural ice. Based on the solubilities of the different gases in the melt-water, a negative process blank would be expected. This implies that the expected loss of CH 4 due to solubility is overcompensated by a small CH 4 contamination of unknown origin in the extraction vessels during extraction. Note that the air-free ice produced at the University of Bern may still contain minute amounts of CH 4 potentially leading to an overestimation of the blank correction. Different blank corrections have to be kept in mind when comparing the data from other labs. The precision of the measurements on natural ice is determined by reproducibility measurements of natural ice samples at 22 NGRIP depths.
, 1997). The LGGE measurements have been performed in parallel to 103 measurements on the Vostok core covering the same climatic period  (Bender et al. , 2006) , which is crucial for a reliable determination of the small interpolar concentration difference (see  Sect. 3. 4). The standard deviation of the residuals calculated on NGRIP (Vostok) duplicates or triplicates is 2. 6 ppb (4. 3 ppb). To check for offsets of the new Bern CH 4 concentrations measurements (performed during the years 2011-2012) compared to previously measured (published or previously unpublished) NGRIP sections, an extensive set of remeasurements has been performed at Bern together with the new measurements. The first part of the previously published data has been analyzed in the years 2002-2004 on the same Bern measurement system  (Schilt et al.
, 2010b; Huber et al. , 2006; Flückiger et al. , 2004). The second part has been measured at LGGE in the years 2009-2012  (Capron et al. , 2010b (Capron et al. , , 2012)). The previously unpublished data from LGGE are from the years 2001-2002 (as mentioned in the preceding paragraph). The remeasurements ensure consistency within the entire NGRIP CH 4 data set, which has been obtained by splicing various different data sets. Amongst others this is crucial for quantification of CH 4 amplitudes at the onset of DO events (see Sect. 3. 2). To quantify the offsets in the past we subtract the previously measured concentrations, which are obtained by interpolation to the depth of the Bern remeasurements, from the concentration of the Bern remeasurements (summary in Table  1 ). Comparing the Bern measurements, 41 remeasurements are 2.
Information from the interpolar difference The CH 4 concentrations reconstructed from Greenland and Antarctica are different by some percent, which yields valuable information on the latitudinal distribution of the CH 4 sources (Fig. 7b ). Baumgartner et al. (2012)  found a relatively stable positive rIPD of about 3-7 % around the LGM (32-11 kyr BP, in green) and revised the zero rIPD estimate from  Dällenbach et al. (2000)  during the LGM. The rIPD results between 80 and 60 kyr BP (in green) from the NGRIP and Vostok ice cores presented in this study (Sect. 4. 4 ± 0. 8% 4. 6 ± 0. 7% 2. 6 ± 1. 4% Fig. 6. Interpolar concentration difference of methane calculated in the stadial periods between 80 and 60 kyr BP. The samples from Greenland (new data from NGRIP in blue) and Vostok (red,  Bender et al.
Timing of CH 4 and NGRIP temperature Figure  7e  shows the timing of the fast NGRIP temperature and CH 4 increases for all considered DO events, with the events showing a significant lag displayed in red. Our reconstruction for DO event 21 is consistent with  Vallelonga et al. (2012) , who also used the gas phase temperature proxy δ 15 N to compare with high-resolution CH 4 data on NGRIP ice and estimated a maximum lag for this event of 69 ± 5 yr with a most probable lag of only a few decades. The processes that could lead to a lag of the CH 4 increases compared to NGRIP temperature increases at the onset of DO events are not well understood. One can think of two extreme CH 4 source evolution scenarios leading to a lag of CH 4. In the first case, where the stadial CH 4 sources are maintained after the start of Greenland warming, all the important additional CH 4 sources causing the stadial-interstadial concentration increase must be delayed by at least the time of the corresponding lag.