dataesr/scientific-paragraphs-categorization huggingface dataset:
Figures 1A-4A also show the spatial distribution of occurrence data, defined as one or more reports of leishmaniasis in a given calendar year, collated from a variety of sources. Overall, there is a relatively broad geographic spread and good correspondence with the evidence consensus maps for each disease. Tunisia, Morocco and Brazil report the highest number of unique CL occurrences in any given year, whilst India reported the largest proportion of the VL occurrence data. Table  1  reports the sources and types of data within the occurrence database. Whilst the majority of occurrence records contain accurate point data (62%), the remainder were recorded at a provincial or district level. Occurrence records for the two diseases were relatively similar in number with a total of 6426 records for CL and 6137 for VL.
The populations living in areas predicted to be subject to environmental risk of CL and VL are estimated to be 1. 71 billion and 1. 69 billion, respectively, approximately a quarter of the world's population. Figure  4 -figure supplement 4 compares these national estimates to the annual case incidence data from all countries for which at least one case per annum was estimated by  Alvar et al. (2012). There is a strong positive association between the two measures of disease occurrence. We provide estimates of the populations at risk in 90 countries for which no human cases of CL or VL were regularly reported  (Alvar et al. , 2012). A full table of this information is presented in the associated Dryad data set (doi: 10. 5061/dryad. 05f5h). For many of these countries,  Alvar et al. (2012)  reported a handful of  sporadic cases over the years indicating very rare occurrence of infection, whilst the remainder were countries with inconclusive evidence of disease presence or absence.
In some locations, cases have been reported as locally transmitted without the presence of proven vector species, which could indicate a false positive. However, the overall consensus score will reflect any uncertainty associated with the validity  of these reports; if multiple independent sources report autochthonous cases, this increased certainty will be reflected in a higher consensus score. Similarly, whilst the occurrence database contains data from across the globe, this data set is inevitably subject to spatial bias in reporting, with more data reported from more economically developed countries where we already have a good knowledge of the disease (e. g. , Spain, France, and Italy). The complexity and diversity of transmission cycles involving not just humans, but also a multitude of vectors and reservoirs, necessitated a modelling approach which can account for highly non-linear effects of covariates on probability of disease presence.
Similarly, reporting bias within the occurrence database is an issue with all presence-only species distribution models  (Peterson et al. , 2011). If bias is unaccounted for, there is the potential that the model merely reflects factors that correlate with the probability of reporting disease occurrence rather than the disease itself, such as healthcare expenditure  (Phillips et al. , 2009; Syfert et al. , 2013). The pseudo-data selection procedures (which included information from both the occurrence data set and the less-biased evidence consensus map) coupled with the model ensembling approach aimed to minimise this potential source of bias. The differences in the most important predictors of disease presence between the two forms of the disease and between the Old and New Worlds highlight the complex and spatially variable epidemiology of the leishmaniases.
Conclusions These maps represent evidence-based estimates of the current global distribution of the leishmaniases incorporating a comprehensive occurrence database and a rigorous statistical modelling framework with associated uncertainty statistics. We estimate that 1. 71 billion and 1. 69 billion individuals live in areas that are suitable for CL and VL transmission, respectively. These figures highlight the need for much greater awareness of this disease at a global scale. These maps provide an important baseline assessment and a strong foundation on which to base future burden estimates, target regions for control efforts and inform public health decisions.
Evidence consensus The methodology used for generating the definitive extents for the leishmaniases was adapted from work on dengue  (Brady et al. , 2012). Four primary evidence categories were used to determine a consensus on the presence or absence of the leishmaniases: (i) health reporting organisations; (ii) peerreviewed evidence of local autochthonous transmission; (iii) case data; (iv) supplementary information. Cutaneous and visceral leishmaniasis were the two symptomatologies investigated: other forms of the disease were subset within these two -whilst VL contained cases of post-kala-azar dermal leishmaniasis, CL included diffuse, disseminated, and mucosal forms of the disease. Although limited amounts of data were available for some of these forms, their epidemiology is similar, and consequently this categorisation was seen as appropriate.
Peer-reviewed evidence (scores between +2 and +6) A review of reported leishmaniases' cases was performed. Using PubMed and Web of Knowledge with '[admin1 province] leish*' as the search parameters, articles from January 1960 until September 2012 were abstracted. Each abstract was imported into Endnote X4 and assessed for relevance. Papers that included reported cases on either CL or VL were then obtained. Cases were included if there was sufficient evidence to suggest that local autochthonous transmission had occurred. Where individuals from a non-endemic country had travelled to an endemic country (e. g. , tourists and military personnel) and returned with an infection, this was included (as evidence for leishmaniasis in the foreign destination) since these typically represent immunologically naive individuals who have undergone more rigorous diagnostics in their home country, and thus represent a potentially more informed data source.
Each paper was assessed for contemporariness and diagnostic accuracy. Contemporariness was graded in 3 bands:  2005-2012 = 3, 1997-2004 = 2 and 1997  and earlier = 1, as was diagnostic accuracy where 1 was scored for data that reported 'confirmed' cases without detailing methodologies implemented; 2 was scored where evidence of microscopy, serology, or the Montenegro skin test had been used; 3 was awarded to those studies that had used PCR or other molecular techniques  (Reithinger and Dujardin, 2007). Contemporariness bins were based upon the potentially lengthy intrinsic incubation periods present with some Leishmania spp. as well as to accommodate the potential for epidemic cycles, where cases may only be detected in peak years and missed in the intervening baseline periods. The most contemporary and diagnostically accurate papers were then subset to maximise the consensus score for any given area.
Supplementary evidence Supplementary evidence was provided in cases where a consensus on presence or absence could not be reached using the aforementioned evidence types, typically with areas where the consensus value was close to 0%. For these regions, additional literature searches were undertaken to determine whether known vector species or infected reservoir hosts were reported in the region. The justification for each provincial scenario is outlined in the associated online databases (Dryad data set doi: 10. 5061/ dryad. 05f5h). In total, this assessment was required in 24 countries. An overall consensus score for each administrative region was calculated by the sum of the scores in each category, divided by the maximum possible score, then expressed as a percentage. Consensus was defined as either complete (±75% to ±100%), good (±50% to ±74%), moderate (±25% to ±49%), poor (±1% to ±24%), or indeterminate (0%).
Brazil and Peru The Brazilian Ministry of Health produces, via the Sistema de Informação de Agravos de Notificação (SINAN, 2013) reporting network, records of infections at the municipality level. This allowed for a more thorough evidence consensus to be performed at district level (termed Admin 2 FAO, 2008) within Brazil. As above, WHO and GIDEON status as well as peer-reviewed literature score were recorded, both aggregated to Admin 1 provincial level. Case data were then defined by the presence of a municipality reporting leishmaniasis between 2008 and 2011 inclusive, with positive reports scoring +6 and absence scoring -6. The overall consensus score was then calculated as above. In addition, provincial level case data for Peru was replaced by Ministry of Health information as it was more contemporary than that listed by  Alvar et al.
Occurrence records Two separate searches using PubMed and Web of Knowledge were undertaken using the search parameter "leish*," and including articles up to December 2012, and their respective abstracts, were filtered for relevance. From these searches, 4845 articles were collated, with data recorded at the resolution of either a point or Admin 1 or 2 polygon. These were then geo-positioned using Google Maps (https://maps. google. co. uk/). Each entry was evaluated to ensure that non-autochthonous cases and duplicate entries were eliminated. Each occurrence was assigned a start and end date based upon the content of the paper, used to define the time period over which occurrences were reported. In addition to this resource, reports were taken from the HealthMap database (http://healthmap. org/en/).
HealthMap is an online based infectious disease surveillance system that compiles data from informal data sources ranging from online news articles to ProMED reports  (Freifeld et al. , 2008). It parses information from these sources searching for relevant keywords, and then, using crowdsourcing and automated processes, geopositions those relating to the disease of interest. As of December 2012, a total of 690 leishmaniasis relevant articles were archived. Searches were also performed on GenBank accessions, searching for archived genetic information from Leishmania spp. known to infect humans (WHO, 2010). If the host was identified as human, geographic indicators were assigned either as point, Admin 1 or Admin 2, based upon the information in the location tag. Tags at the national level were filtered out of the data set.
In total, 563 accessions were associated with sub-national location details and added to the database. Finally, data were provided from the curated strain archives of the Centre National de Référence des Leishmanioses (CNR-L) in Montpellier, France. In total, information about 3465 strains isolated from humans was provided, collected from between 1954 and 2013. All data were geopositioned as precisely as possible, which resulted in both point-level data (referring to cities, towns or villages) as well as polygon-level data (provinces or districts) with area no greater than one square decimal degree. All data that had been manually geopositioned were checked to ensure coordinates were plausible and then occurrences were standardised annually to remove intra-annual duplicates, so that each individual record used in our model represented an occurrence of leishmaniasis infections in a given 5 km × 5 km location or administrative unit for one given year.
, 1999; Elnaiem et al. , 2003; Bhunia et al. , 2010; Chamaille et al. , 2010; Gonzalez et al. , 2010 Gonzalez et al. , , 2011;; Elnaiem, 2011; Hartemink et al. , 2011; Malaviya et al. , 2011). Estimates of precipitation were obtained from the WorldClim database (www. worldclim. org). This resource, which is freely available online, provides data spanning from 1950 to 2000, describing monthly averages over this time, at a 1 km × 1 km resolution  (Hijmans et al. , 2005). Using this baseline, interpolated global climate surfaces were produced using ANUSPLIN-SPLINA software  (Hutchinson, 1995). With the use of temporal Fourier analysis, seasonal and inter-annual variation in precipitation patterns, taken from the interpolated global surface, were used to calculate minimum and maximum monthly precipitation averages  (Rogers et al.
Poverty Neglected tropical diseases and poverty are often found to be linked and the use of a purely economic variable was chosen to act as a proxy for a variety of important global risk factors for disease, including malnutrition, housing quality, and living with domesticated animals  (Bern et al. , 2010; Boelaert et al. , 2009; Herrero et al. , 2009; Malafaia, 2009; Zeilhofer et al. , 2008). The G-Econ database (gecon. yale. edu) takes economic data, at the smallest administrative division available, and spatially rescales these data to create a 1 o × 1 o gridded surface of the globe  (Nordhaus, 2006 (Nordhaus, , 2008)). This rescaling estimates the gross cell product of each grid cell, conceptually similar to gross domestic product, referring to the total market value of all final goods and services produced within 1 year, and can be considered as an indicator of overall standard of living within that area.
Urbanisation Over the last few decades, there has been a tendency for the leishmaniases having a sylvatic/zoonotic transmission cycle to transition into the urban and peri-urban environment in response to increasing urbanisation trends  (Harhay et al. , 2011). The increasing overlap in habitat between suitable human and animal hosts and multiple available resting sites for adults can allow for transmission of disease to occur relatively easily  (Singh et al. , 2008; Poche et al. , 2011; Uranw et al. , 2013). The Gridded Population of the World version 3 (GPW3) population density database projected for 2010 was used. The core Global Rural-Urban Mapping Project Urban Extents surface used night-time light satellite imagery to differentiate urban areas  (Balk et al. , 2006) ; GPW3 is a revision which updates the criteria for urban areas to those areas where population density is greater than or equal to 1000 people per km 2.
Acknowledgements DMP is funded by a  Sir Richard Southwood Graduate Scholarship  from the  Department of Zoology at the University of Oxford. SIH is funded by a  Senior Research Fellowship  from the  Wellcome Trust  (# 095066 ) which also supports KAD and KEB. NG is funded by a grant from the  Bill & Melinda Gates Foundation  (# OPP1053338 ). PWG is a  Medical Research Council (UK)   Career Development Fellow  (# K00669X ) and receives support from the  Bill and Melinda Gates Foundation  (# OPP1068048 ) which also supports SB. OJB is funded by a  BBSRC  studentship. JPM is funded by, and SIH and OJB acknowledge the support of, the  International Research Consortium on Dengue Risk Assessment Management and Surveillance (IDAMS, European Commission 7 th Framework Programme  (# 21803 ) http://www.
Immunofluorescent Microscopy Organs were incubated in 30% sucrose in PBS (3-4 hr, +4 C), mounted in OCT medium (Tissue-Tek), frozen on dry ice, and stored at À80 C. Then 5 mm cryosections were cut with a CryostarNX70 cryostat (ThermoScientific). Dried sections were kept at À80 C until use and fixed with acetone (À20 C, 10 min). For details on the staining, see Supplemental Experimental Procedures. Microscopy was performed on an Axioskop 40FL fluorescence microscope using an AxioCamMRm camera and AxioVision Rel 4. 8 software (all from Zeiss). LM RFP infection in the T cell areas was quantified as the number of RFP pixels/number of total pixels in the T cell area using ImageJ software (NIH).
Flow Cytometry Calcium/magnesium-free PBS (GIBCO) containing 2 mM EDTA/0. 5% BSA was used during the entire staining procedure. For details on the antibodies used, see Supplemental Experimental Procedures. Serum cytokines were measured using a multiplex bead assay kit (mouse flowCytomix; eBioscience). Dead cells were excluded by DAPI (Sigma), the LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (Invitrogen), or ethidium bromide monoazide (Sigma) staining, and cellular aggregates were excluded by side-scatter pulse width. Cytometric acquisition/analysis was performed using LSRII (BD Bioscience) and FlowJo software (Treestar).
Statistical Analysis For survival curves, a log rank test was performed. All other statistical analyses were performed using one-way ANOVA with subsequent Newman-Keuls posttest, the Kruskal-Wallis test followed by Dunn's posttest, or Student's t test as indicated in the figure legends. Analysis was performed using GraphPad Prism software (*p < 0. 05, **p < 0. 01, ***p < 0. 001).
ACKNOWLEDGMENTS We thank  S. Dippel ,  E. Ermeling , and  C. Ja  ¨nke for expert technical support. We also thank  H. W. Mittru ¨cker ,  P. Dresing , and  S. Scheu  for initial support with the Listeria infection model and  J. Hu ¨hn ,  S. Halle ,  S. Cording , and  S. Amigorena  for helpful discussions. Finally, we acknowledge the assistance of the Cell Sorting Core Facility of the  Hannover Medical School , supported in part by  Braukmann-Wittenberg-Herz-Stiftung  and the  Deutsche Forschungsgemeinschaft (DFG). C. A. S. received a PhD stipend as well as personal support from the  Boehringer Ingelheim Fonds, Foundation for Basic Research in Medicine. M. D. received a PhD stipend from the  DFG  in the framework of the  International Research Training Group (IRTG)   1273. This project was financed by  SFB900.
We measured the frequency of live HIV-1 Gag + cells after 6 h of incubation with autologous NK cells, with or without HA-137. A basal level of killing activity was detected in the absence of Abs (data not shown) or with hIgGs (Fig. 2D ). Anti-HIV-1 or HA-137 Abs significantly increased NK cell-mediated killing of infected cells, with a mean killing of ∼33 and 36%, respectively, versus 10% (hIgGs) (Fig. 2D ). No difference between hIgGs and the absence of Ab was detected. To assess HA-137 specificity, we performed a dose-dependent assay and showed that HA-137 efficiency is decreased when its concentration is decreased, as well as in the presence of an excess of TM peptide (TMpep) (Fig. 2E ). HA-137 has low polyreactivity (Supplemental Fig. 1 ). There was variation in the killing efficiency for HA-137 and anti-HIV-1 Abs with respect to the strain used to infect cells (Fig.
Acknowledgments We thank  Dennis Burton ,  Pheroze Joshi ,  Neil Sheppard ,  Nancy Haigwood ,  Anne Hessell ,  Jeffrey Milush ,  Andre Raposo ,  R. Brad Jones , and  Mario Ostrowksi  for helpful discussions and  Pandey Suchitra  for help in providing clinical specimens and data. We gratefully acknowledge reagents supplied from the  National Institutes of Health AIDS Research and Reference Reagent Program.
Endogenous peroxidase activity was quenched with 3% (wt/vol) hydrogen peroxide, and the sections were blocked with 10% (vol/vol) normal goat serum. The von Willebrand factor (Dako) staining (12. 4 mg/ml) was carried out with a standard 3stage immunoperoxidase method using the Vectastain Elite ABC peroxidase kit (Vector Laboratories, Peterborough, UK). Diaminobenzidine was used as chromogen. Counterstaining was performed with hematoxylin. For each section, the surface of the bone marrow was measured with the 4x objective (Nikon Eclipse E800) and the number of positive vWF MKs was counted using the 20x objective. Morpho Expert software (Explora Nova, La Rochelle, France) was used for the quantification.
Experimental tail transection bleeding model Mice were anesthetized by intraperitoneal injection of xylazine (20 mg/kg) with ketamine (100 mg/kg). The bleeding time was determined according to Dejana et al. [20]  adapted for mice, by transection of the tail 2 mm from the tip. Blood was carefully blotted on a filter paper every 15 sec during the two first minutes and every 30 sec thereafter. The observation period was limited to 45 minutes. Hemostasis was considered to be achieved when no more bloodstaining was observed over 1 min. Raw data correspond to the bleeding time in minutes.
Mice lacking RGS18 present a mild thrombocytopenia Analysis of peripheral blood samples of RGS18-/-mice and normal littermates for their hematologic profile showed that RGS18-/-mice were moderately thrombocytopenic: a mean of ,15% reduction in platelet counts was observed in RGS18-/mice with respect to WT mice (Table  1 ). All other blood parameters analyzed, including red blood cells and total white blood cells, were normal in RGS18-/-mice. Interestingly, the mean platelet volume was significantly increased from an average of 4. 94 mm 3 in WT mice to 5. 05 mm 3 in RGS18-/-mice. These data suggested that RGS18 might be implicated in megakaryopoiesis/thrombopoiesis. One of the direct causes of thrombocytopenia is a reduction in the number of megakaryocytes (MK) in the bone marrow. We therefore examined MK counts in femora after staining of bone marrow sections for Von Willebrand Factor, a sensitive marker for identification of marrow MKs  [25].
Defective megakaryopoiesis in RGS18-/-mice To further characterize megakaryopoiesis in the absence of RGS18, MK progenitor cells from bone marrow of RGS18-/-and WT mice were first assayed in clonogenic culture. In vitro colony assays in presence of a cocktail of cytokines regulating megakaryopoiesis showed that the number of MK progenitors (CFU-Meg) was clearly higher in WT mice than in RGS18-/-mice (Figure  2A ), indicating that RGS18 deficiency in MK progenitors affects their in vitro maturation potential. To confirm these results, we next examined the in vivo maturation potential of bone marrow MKs. Bone marrow cells were stained for CD42b and MKs were identified by flow cytometry. We observed that the level of MKs from bone marrow of WT mice was in accordance with litterature data (,1%).
As shown in Figure  5C , murine TRAP (PAR-4 peptide activator) dose-dependently induced an activation-dependent conformational change in integrin aIIbb3 on platelets from WT littermates, and an enhanced response was observed in RGS18-/-mice as early as the concentration of 0. 25 mM of mTRAP. Similarly, the response to thrombin was found to be increased in RGS18-/-mice, as assessed using in vitro platelet aggregation assays (data not shown).
Each of these trained gene finders were then run on the target genomes and this annotation was combined in each case using Jigsaw  (50). The annotation was improved manually. Three further B. bigemina genomes (PR, BbiS3P and JG29), the B. bovis C9. 1 genome and the B. divergens Rouen1987 genome were sequenced using the Illumina GA platform. The libraries were prepared with the PCR-free protocol and sequenced to 76 read pairs with an insert size of around 350 bp. Illumina reads were assembled with velvet  (51). The genomes were improved using the Post Assembly Genome Improvement Toolkit (PAGIT) pipeline  (52) , applying the contig ordering against the BOND reference using the program ABACUS  (53)  and the gap-filling step  (54). For the B. bigemina genome a further gap-filling was performed, using gap-filler  (55).
Proteomic analysis Thermo RAW files were imported into Progenesis LC-MS (version 4. 1, Nonlinear Dynamics, UK). Runs were time aligned using default settings and using an auto selected run as reference. Peaks were picked by the software and filtered to include only peaks with a charge state of between +2 and +6. Peptide intensities were normalized against the reference run by Progenesis LC-MS and these intensities are used to highlight differences in protein expression between control and treated samples with supporting statistical analysis (ANOVA and q-values) calculated by the Progenesis LC-MS software. Spectral data were transformed to mgf files with Progenesis LC-MS and exported for peptide identification using the Mascot (version 2. 3. 02, Matrix Science) search engine. Tandem MS data were searched against the predicted protein set of the B.