dataesr/scientific-paragraphs-categorization huggingface dataset:
The ANTARES Neutrino Telescope and Data Sample The ANTARES neutrino telescope  [19]  is located in the Mediterranean Sea, about 40 km offshore from Toulon, France (42 • 48 N, 6 • 10 E). The detector consists of 885 photomultiplier tubes (PMTs) mounted on twelve vertical lines anchored to the seabed at a depth of 2475m, with a typical inter-line separation of ∼65 m. The operation principle is based on the detection of Cherenkov light induced by relativistic muons produced in the charged-current interactions of high-energy neutrinos with matter surrounding the detector. The knowledge of the time and amplitude of the light pulses recorded by the PMTs allows the reconstruction of the trajectory of the muon and to infer the arrival direction of the incident neutrino. To limit the background from down-going atmospheric muons, the design of ANTARES is optimised for the detection of up-going muons produced by neutrinos which have traversed the Earth.
Determination of the Magnification Factor The strategy presented here relies on an estimation of the magnification factor for each lensed system, as obtained from photon observations. To estimate the magnification of a given lensed image, a model is required for the mass distribution of the lens. Here, we utilise the simplest model able to account for the image morphology and magnification ratios in each lens system: the singular isothermal ellipsoid (SIE). SIE models are also a reasonable description of the mass distributions of elliptical galaxies (e. g. ,  [31] ). We adjust the parameters of SIEs with the "gravlens" modeling software  [32]  to fit image positions and flux ratios. We use image positions from infrared H-band HST observations from the CASTLES project 1  , which have uncertainties of 0.
Acknowledgments The authors would like to thank  D. Allard ,  O. Mena ,  J. A. Muñoz  and  G. E. Romero  for enlightening discussions during the preparation of this manuscript. They also acknowledge the financial support of the funding agencies:  Centre National de la Recherche Scientifique (CNRS) ,  Commissariat  à l'énergie atomique et aux énergies alternatives (CEA),  Commission Européenne  ( FEDER fund and Marie Curie Program ),  Région Alsace  (contrat CPER),  Région Provence-Alpes-Côte d'Azur, Département du Var and Ville de La Seyne-sur-Mer, France ;  Bundesministerium für Bildung und Forschung (BMBF) ,  Germany ;  Istituto Nazionale di Fisica Nucleare (INFN), Italy ;  Stichting voor Fundamenteel Onderzoek der Materie (FOM) ,  Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO) , the  Netherlands; Council of the President of the Russian Federation  for young scientists and leading scientific schools supporting grants,  Russia ;  National Authority for Scientific Research (UEFISCDI) ,  Romania ;  Servicio Público de Empleo Estatal (SEPE) ,  Ministerio de Ciencia e Innovación (MICINN) ,  Prometeo of Generalitat Valenciana and MultiDark, Spain ;  Agence de l'Oriental and CNRST, Morocco.
Metabolic analysis The extracellular acidification rate (ECAR) and the oxygen consumption rate (OCR) were measured with a Seahorse XF analyser (Seahorse Bioscience, MA, USA). A549 cells (8x10 4 ) and H1975 cells (1x10 5 ) were seeded on seahorse plates and allowed to grow for 24h in normoxia. Prior to measurement, Plates were incubated for 45min in a non-CO 2 incubator at 37°C with seahorse medium without glucose, pyruvate, serum or bicarbonate. 10mM of glucose (Sigma), 300nM of iMCT1/2 (AstraZeneca, UK), 50μM of phenformin (Sigma) and 1μM of oligomycin (Sigma) were injected. After each addition, three data points of 3min were undertaken to determine the oxygen and proton concentrations in the medium. The protein concentration was determined to normalize OCR and ECAR values.
AcknowledGeMents The JP team was funded from  Ligue Nationale Contre le Cancer (LNCC Equipe labellisée) ,  Fondation ARC ,  INCa ,  ANR , the  EU-FP7  " METOXIA ",  SERVIER-CNRS, and Centre Lacassagne. SG received a fellowship from  Fundação para a Ciência e Tecnologia  ( SFRH/ BD/33503/2010 ) and IM was supported by a fellowship from  LNCC. We thank  Dr Susan Critchlow  ( AstraZeneca ) for providing the iMCT1/2, the cytometry core facility (CYTOMED) for FACS analysis, and  Dr. Christiane Brahimi-Horn  for editorial correction of the manuscript.
Positive samples were subsequently screened with a previously described Rickettsia africae-specific qPCR method. Samples with fewer than 35 cycle thresholds (Ct) were considered positive  [18]. In order to generate sequence data allowing phylogenetic analyses of infecting Rickettsia, gltA and ompA were amplified and subsequently sequenced from a subset of randomly selected Rickettsia-positive tick samples. A fragment of gltA gene was amplified using the Rp CS. 409d and CS. 1258n primers, previously reported to amplify a 750-bp fragment from all known Rickettsia species  [6] , and ompA gene was targeted by using the primers 190. 70,190. 180, and 190. 701, amplifying a 629-632-bp fragment of SFG Rickettsia  [2, 6]. For each PCR reaction, one positive control (Rickettsia montanensis DNA) and 2 negative controls (sterile water containing DNA extracted from uninfected ticks maintained in laboratory colonies) were included, with the exception of the Rickettsia africae-specific qPCR reaction in which Rickettsia africae DNA was used as positive control.
Sequence editing and phylogenetic analyses Sequences were analyzed using Chromas Pro (version 1. 49 beta Technelysium Pty Ltd, Tewantin, Australia) and compared with sequences available in the GenBank database using NCBI BLAST. Multiple sequence alignments were noted at the nucleotide and amino acid levels using ClustalW implemented in BioEdit software. The sequences matched with sequences from other gltA and ompA rickettsiae retrieved from the GenBank database. Rickettsiaconorii and Rickettsia rickettsii sequences have been chosen as root sequences. Accession numbers of the GenBank sequences used for the genetic analyses are indicated in the phylogenetic trees. The selection of the DNA substitution model that best fit the data was performed with MEGA 5. 2 and was considered for phylogenetic analyses.
The sequence analysis of ompA genes obtained from Rhipicephalus spp. samples revealed 99. 0 to 99. 6% nucleotide identity with Rickettsia africae detected from Rhipicephalus evertsi evertsi in Senegal (GenBank accession numbers JN043509), while R. africae sequenced from Amblyomma variegatum showed 98 to 99. 7% average identity with R. africae detected in Ethiopia from the same tick species (GenBank accession numbers CP001612). The sequencing of gltA genes obtained from Amblyomma variegatum and Rhipicephalus spp. showed 99. 1 to 99. 42% average identity with the published sequences of Rhipicephalus africae that were amplified from Amblyomma variegatum collected in the West Indies (GenBank accession number HM050288).
Ticks collected from imported cattle Of the ticks collected from cattle imported from Tanzania, 77. 14% (27/35) were positive for Rickettsia spp. , with a Ct average of 27. 75 ± 4. 13. All of the samples detected positive for Rickettsia spp. were also positive for Rickettsia africae by qPCR (Figure  1 ), with Ct averages of 26. 7 ± 4. 67. The sequencing of ompA genes obtained from Amblyomma variegatum collected from imported cattle showed an average of 98% alignment with published sequences of Rickettsia africae from Amblyomma variegatum collected in Antigua (GenBank accession number EU622980). The sequence analysis of the gltA gene obtained from Amblyomma variegatum ticks revealed 98. 0 to 99. 0% nucleotide identity with the gltA gene from Rickettsia africae detected in Amblyomma variegatum from Ethiopia (GenBank accession numbers CP001612) and in Rhipicephalus evertsi evertsi from Senegal (GenBank accession numbers HM050288), respectively.
Methodology A literature search on the PubMed database was undertaken with no time limits. Single search terms included 'ATG', 'rATG', 'antithymocyte globulin', and 'Thymoglobulin', across all therapy areas. Only articles with an English abstract were reviewed. Abstracts from relevant congresses during 2013 and 2014 were also searched using the same search terms. While all relevant publications were reviewed, emphasis is placed on randomized trials where possible. 3 The Basis for Rabbit Antithymocyte Globulin (rATG) use in Solid Organ Transplantation rATG exerts its immunomodulatory and immunosuppressive effects via a wide range of immune and non-immune targets, adhesion molecules, and chemokine receptors  [11]. rATG administration induces a significant depletion of CD3 ? , CD4 ? and CD8 ? T-cells and NK cells, as well as other T-cell subsets  [11] , while leaving the B-cell count unaffected  [4].
Reducing Maintenance Immunosuppression In recent years, clinical investigation of rATG in kidney transplantation has centered on its ability to support either early steroid withdrawal or CNI-sparing regimens. The most robust data relating to early steroid withdrawal comes from a multicenter trial in which 151 living-donor kidney transplant patients were randomized to rATG (total dose 5-6 mg/kg) with steroids to day 7, or to an induction-free standard-steroids regimen, both with tacrolimus and MMF  [94]  (Table  2 ). At 12 months post-transplant, rates of BPAR and all efficacy endpoints were similar between the two groups, but total cholesterol was lower in the steroid-withdrawal group with trends towards a lower triglyceride level and less weight gain, although leukopenia was more frequent in the rATG cohort.
In the rATG group, tacrolimus exposure was reduced and steroids were selectively withdrawn at 3-6 months. At 1 year, the incidence of acute rejection was similar in both groups despite lower exposure to both CNI and steroids. Alternatively, rATG induction (up to 6 mg/kg in total) coupled with maintenance therapy using the costimulation blocker belatacept and a mammalian target of rapamycin inhibitor or MMF may enable avoidance of both CNIs and steroids with an acceptable rate of rejection  [126] ; further data are awaited.
Reducing Maintenance Immunosuppression Randomized trials of CNI reduction or avoidance in liver transplant patients using rATG induction are lacking, but retrospective, single-center data from a series of 391 recipients suggest that rATG induction with CNI initiation delayed to day 3 may reduce the risk of rejection versus a standard CNI therapy (14. 5 % vs. 31. 8 %; p = 0. 0008)  [71]. Other retrospective analyses have also indicated that rATG induction with reduced tacrolimus exposure and no steroids  [63] , or delayed tacrolimus  [141] , effectively maintains immunosuppressive efficacy. Such approaches may be particularly helpful in liver transplant patients with renal impairment at the time of transplantation, to minimize CNI-related nephrotoxicity and avoid acute renal failure to help preserve long-term kidney function  [142].
An analysis from 1995 to 2004, which was based on the Collaborative Transplant Study database, observed a marked increase in non-Hodgkin lymphoma with rATG induction versus noninduction  [200]. During that period, rATG doses were higher than at present, and this finding is consistent with other registry analyses based solely on data from the 1990s or early 2000s (Table  6 ). A somewhat more recent analysis of 2,151 adult heart transplant recipients  (1995) (1996) (1997) (1998) (1999) (2000) (2001) (2002) (2003) (2004) (2005) (2006) (2007) (2008)  receiving ATG in the UK (the preparation of ATG was not specified) found no evidence of increased death from lymphoma  [201]. An analysis of patients registered with the Australian and New Zealand Dialysis and Transplantation Registry (ANZDATA) registry during 1997 to 2009 indicated that acute rejection treated with lymphocytedepleting therapy (rATG was not specifically assessed) appears to be associated with an increased risk of cancer  [206].
Other registry analyses have described mixed findings, with some showing an increased risk for PTLD with rATG or ATG preparations of any type  [199, 203, 209, 210]  and others reporting no effect of rATG or polyclonal lymphocyte-depleting agents  [211] [212] [213]. In one of the most recent large-scale datasets, derived from the TAILOR registry, a non-comparative evaluation of PTLD in 2,322 patients receiving rATG (Thymoglobulin Ò ) after living-donor kidney transplantation during 2003-2008 showed the 5-year incidence of PTLD to be 0. 9 %  [68]. This is comparable with published incidence rates for the kidney transplant population as a whole  [198, 199]. Unlike most registries, TAILOR captures the rATG dose, and in this series the mean cumulative dose was *5. 3 mg/kg. It appears that the risk of PTLD and malignancy associated with modern rATG induction regimens may be less of a concern than during the high-dose era, but confirmatory data are required.
rATG as Pre-Emptive Treatment of Acute Graftversus-Host Disease Patients at high risk of GvHD and death can be identified on day 7 after HSCT based on laboratory data  [238]. In a prospective, randomized trial, all patients grafted from unrelated donors received rATG 7. 5 mg/kg pre-transplant  [238]. On day ?7, they were assigned to receive an additional rATG dose of 1. 25 mg/kg/day on days 7 and 9 posttransplant, or enter a control arm  [239]. One hundred and seventy patients were randomized and were evaluable for non-relapse-related mortality (the primary endpoint) or GvHD (a secondary endpoint). Non-relapse-related mortality was 29 % in the rATG-treated patients versus 35 % in the control arm (p = 0. 3). GvHD was significantly less frequent under rATG therapy; the incidence of acute GvHD III-IV was 5 % versus 15 % in controls (p = 0.
Despite the developments in the global modelling of chemistry and of the parameterization of the physical processes, carbon monoxide (CO) concentrations remain underestimated during Northern Hemisphere (NH) winter by most state-of-the-art chemistry transport models. The consequential model bias can in principle originate from either an underestimation of CO sources or an overestimation of its sinks. We address both the role of surface sources and sinks with a series of MOZART (Model for Ozone And Related Tracers) model sensitivity studies for the year 2008 and compare our results to observational data from ground-based stations, satellite observations, and vertical profiles from measurements on passenger aircraft. In our base case simulation using MACCity (Monitoring Atmospheric Composition and Climate project) anthropogenic emissions, the near-surface CO mixing ratios are underestimated in the Northern Hemisphere by more than 20 ppb from December to April, with the largest bias of up to 75 ppb over Europe in January.
, 2013). The second-most-important direct CO emission source is biomass burning. Observations of burnt areas, active fires and fire radiative power from various satellite instruments have been used to constrain these emissions on the global scale. Global and regional totals for the year 2005 from the most recent emission inventories -GFEDv2 (Global Fire Emissions Database, version 2; van der  Werf et al. , 2006 ), GFEDv3 (van der Werf et al. , 2010) , and GFASv1 (Global Fire Assimilation System;  Kaiser et al. , 2012)  -are displayed in Table  2. Note the large differences in continental-scale emissions between the inventories and the large interannual variability in the data sets. Biogenic emissions of CO generally contribute less than 10 % to the global total emissions. Estimates derived from MEGANv2  (Guenther et al.
Surface station data Long-term measurements of key atmospheric species from surface observation sites around the globe are collected at the World Data Centre for Greenhouse Gases (WDCGG) operated by the World Meteorological Organization (WMO) Global Atmospheric Watch (GAW) programme (http://ds. data. jma. go. jp/gmd/wdcgg/). We used monthly means of CO mixing ratios measured from 67 surface stations which provided data for all months in 2008; their positions on the globe are shown in Fig. 3  (red diamonds). The observation sites are operated by the NOAA Earth System Research Laboratory (USA), The Commonwealth Scientific and Industrial Research Organisation (CSIRO, Australia), Environment Canada, the Japan Meteorological Agency (JMA), the Czech Hydrometeorological Institute (CHMI), the German Federal Environmental Agency (UBA), the Swiss Federal Laboratories for Materials Science and Technology (EMPA), the Netherlands National Institute for Public Health and the Environment (RIVM), and the South African Weather Service (SAWS).
MOZAIC profiles The MOZAIC (Measurements of OZone and water vapour by Airbus In-service airCraft) programme collects ozone, CO, odd nitrogen (NO y ), and water vapour data, using automatic equipment installed onboard several longrange passenger airliners flying regularly all over the world  (Marenco et al. , 1998). MOZAIC products are available through the Ether French atmospheric database website: www. pole-ether. fr. Here we use CO data from vertical tropospheric transects taken in the vicinity of airports during ascent and descent. For more details of the data processing, see  Elguindi et al. (2010). In 2008, only three aircraft were operating with the MOZAIC instrumentation, and therefore only a limited number of airports were visited regularly (13 airports with a total of 935 profiles).
For the evaluation of the 2008 model simulations over Europe, we chose tropospheric data from the European airports of Frankfurt (Germany) and London (UK), where respectively 300 and 80 profiles were available. Furthermore we analysed an area average composed of the airports of Atlanta, Dallas, Philadelphia and Portland (OR) in the United States and Toronto and Vancouver in Canada, with 219 profiles altogether. This area average is meant to be representative of the North American area limited by the blue box in Fig. 3. There were no data over East Asia in 2008. We marked all airports used for evaluation with turquoise triangles in Fig. 3. The 3-hourly model results were interpolated to the times and locations of the MOZAIC observations; afterwards the profiles of each airport were combined to monthly means.
MOPITT atmospheric columns The MOPITT (Measurement Of Pollution In The Troposphere) instrument onboard the EOS (Earth Observing System) Terra spacecraft provides tropospheric CO measurements on a global scale  (Drummond and Mand, 1996; Deeter et al. , 2004). At nadir view, MOPITT offers a horizontal resolution of 22 km ×22km and achieves global coverage in 2-3 days. MOPITT data used in this study correspond to the daytime CO total columns from the version 5 (V5) level 2 (L2) product (http://www2. acd. ucar. edu/ mopitt/products), which is based on both near-infrared (NIR) and thermal-infrared (TIR) radiances  (Deeter et al. , 2013). Exploiting TIR and NIR radiances together increases the sensitivity for CO in the lowermost troposphere  (Worden et al. , 2010; Deeter et al. , 2011). The observations used here are area-averaged monthly means from the regions defined in Fig.
IASI atmospheric columns IASI (Infrared Atmospheric Sounding Interferometer) is a nadir-looking Fourier transform spectrometer (FTS), launched in 2006 on the polar orbiting MetOp-A satellite. Its spectral resolution of 0. 5 cm -1 (apodized), along with continuous spectral coverage from 645 to 2760 cm -1 allows the column and profile retrievals of several trace gases, twice daily at any location  (Clerbaux et al. , 2009). For carbon monoxide, profiles are retrieved using an optimal estimation approach, implemented in the Fast Optimal Retrievals on Layers for IASI (FORLI) software  (Hurtmans et al. , 2012). The spectra are processed in near-real time, and the CO profiles are distributed with error covariance, averaging kernels and quality flags information (www. pole-ether. fr). The IASI CO product was validated against ground-based observations  (Kerzenmacher et al.
It should be noted that 2008 was within the 3 years with lowest atmospheric CO concentrations out of the 13 years  (2000) (2001) (2002) (2003) (2004) (2005) (2006) (2007) (2008) (2009) (2010) (2011) (2012)  where satellite observations were available  (Worden et al. , 2013). Modelled tropospheric CO mixing ratios and total column densities are evaluated with the observational data introduced in Sect. 3. Impacts from uncertainties in the modelling of OH on the CO budget will be discussed in Sect. 6.
MACCity emissions First we compare our base case simulation (MI), using MAC-City anthropogenic and natural emissions, to GAW observations gathered from the WDCGG database. Figure  4  shows monthly means of surface station CO mixing ratios and of near-surface model mixing ratios. Modelled monthly means from 3-hourly values were interpolated to the station location for 67 stations ordered by latitude. The station data exhibits the highest values and also the largest variability at northern midlatitudes (30-60 • N) during wintertime, with mean January mixing ratios of more than 300 ppb for three stations, namely Hegyhatsal (Hungary), Payerne (Switzerland), and Black Sea (Romania). In addition, Payerne exceeded this threshold in February 2008, and the station Tae-ahn (South Korea) reached monthly mean mixing ratios of more than 300 ppb for March to May 2008 (not shown).
Optimized approach As indicated in Sect. 2, the MACCity inventory is based on the ACCMIP emissions for the year 2000. Lamarque et al. (2010)  pointed out that for USA, Europe, and East Asia published regional inventories have been given preference, notably EPA (Environmental Protection Agency) data for USA, EMEP (European Monitoring and Evaluation Programme) data for Europe, and REAS (Regional Emission inventory in ASia) data for East Asia. The EPA reported on air pollution trends of US cities between 1990 and 2008 and found maximal decadal decreases in CO pollution of 60 to 80 % for 1990 to 2008  (Riahi et al. , 2011). Consequently, in the RCP8. 5 scenario an exposure-driven spatial algorithm for the downscaling of the regional emission projection has been employed. This led to the highest emission reduction of up to 80 % per decade in those grid cells with the highest exposure for regions where emissions are reduced due to the implementation of air pollution control measures, e.
Global and regional CO anthropogenic emission totals from recent bottom-up inventories in teragrams per year. All data except from EPA and Environmental Canada are available online from the Emissions of atmospheric Compounds & Compilation of Ancillary Data (ECCAD) database (http://eccad. sedoo. fr/). ACCMIP a RETRO/REAS b MACCity c EDGARv4. 2 d EMEP e TNO-MACC f EPA + Env. Canada g REASv1 h.
Acknowledgements. This study was funded by the  European Commission  under the  Seventh Framework Programme  (contract number  218793 ). Data from the emission inventories used in this study are freely available on the GEIA emission data portal: http://eccad. sedoo. fr/. IASI has been developed and built under the responsibility of the  Centre National d'Etudes Spatiales (CNES, France). We are grateful to  Pierre Coheur  and  Daniel Hurtmans  ( ULB ) for developing the  FORLI-CO IASI  processing code and to  Juliette Hadji-Lazaro  ( LATMOS ) for establishing the IASI MACC near-real-time processing chain. The authors acknowledge the strong support of the  European Commission, Airbus , and the airlines (Lufthansa,  Air France ,  Austrian ,  Air Namibia ,  Cathay Pacific  and  China Airlines ), who carry the MOZAIC or IAGOS equipment and have performed the maintenance since 1994.
MOZAIC is presently funded by  INSU-CNRS (France) ,  Météo-France ,  CNES ,  Université Paul Sabatier (Toulouse, France)  and  Research Center Jülich (FZJ, Jülich, Germany ). IAGOS has been, and is additionally, funded by the  EU projects IAGOS-DS and IAGOS-ERI. The MOZAIC-IAGOS data are available via the CNES/CNRS-INSU Ether website: http://www. pole-ether. fr. ECMWF and  Forschungszentrum Jülich  are acknowledged for providing supercomputer time, and we thank  Claire Granier  and  Hugo Denier van der Gon  for helpful discussions. The service charges for this open access publication have been covered by a  Research Centre of the Helmholtz Association. Edited by:  V. -H. Peuch.