dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We would like to thank  Kevin Tuck  (retired) and  Geoff Martin , both from the  Natural History Museum, London , for allowing the first author to examine the museum collection under their responsibility. We are also grateful to  David Adamski  ( Systematic Entomology Lab, US Department of Agriculture, Beltsville, Maryland ) for checking some type specimens of Philonome and  Atsushi Kawakita  for donating one specimen for analysis. We are indebted to  Young Sohn ,  Vichai Malikul ,  Donald Harvey , and  Karolyn Darrow  of the  Department of Entomology, Smithsonian Institution , for their assistance preparing the illustrations, graphics, and plates used in this publication. We also thank colleagues at the  Biodiversity Institute of Ontario, University of Guelph, Ontario, Canada  for their assistance in the production of DNA barcodes.
Jean-François Landry  of the  Department of Entomology, Agriculture and Agri-Food Canada/Agriculture, Ottawa , kindly provided specimen data and allowed us to use four unpublished barcodes of P. clemensella. We would like to thank the editor  Erik van Nieukerken  and two anonymous reviewers for their valuable comments on our manuscript. Field work in French Guiana was funded by the  CNRS program  'Amazonie', Nouragues research grants 2009 and 2010 to C. L. V. Funding for DNA barcoding was provided by the government of  Canada through Genome Canada  and the  Ontario Genomics Institute  in support of the  International Barcode of Life  project, and by  NSERC. The first author especially appreciates the financial support from the  Peter Buck Postdoctoral Fellowship  (2013Fellowship ( -2015)),  Smithsonian Institution.
Filters for chl-a were packed individually in aluminium foil bags and stored in a freezer at (188C. In the laboratory in Denmark, filters were kept in 5 ml 96% ethanol at 58C for a minimum of six and a maximum of 20 h for pigment extraction from the retained algae. Samples were centrifuged and the fluorescence of the supernatant was measured with a TD-700 fluorometer (Turner Design, Sunnyvale, CA, USA) and converted into chl-a concentrations by a calibration of the fluorometer. Under-ice video recordings were obtained by mounting a Lumix DMC FT5 underwater camera (Panasonic, Osaka, Japan) on an iron pole. The camera was lowered through an ice core hole to the bottom of the ice for inspection of under-ice conditions. Temperature data were obtained by lowering a conductivityÁtemperatureÁ depth (CTD) Plus 100 Sensor (SiS, Schwentinental, Germany) through the hole from where the ice core was retrieved with a vertical resolution of 0.
Optics An Li-190 PAR (400Á700 nm) sensor (LI-COR, Lincoln, NE, USA) was mounted at the bow of the ship to record surface downwelling PAR during the cruise. The sensor was connected to a CR-10 data logger (Campbell Scientific, Logan, UT, USA) with recording every 5 min. Sea-ice PAR transmittance t was determined as t 0(I i /(1 (a)*I d ), where I d and I i are irradiances at the surface and below the ice and a the albedo. The PAR attenuation coefficient of the ice K d (PAR)ice was determined as K d (PAR)ice 0 ln((I i /(1 (a)*I d ))/z, where z is the ice thickness (m). The albedo here is taken as a00. 55 based on a whole season of in situ measurements of albedo at 888N during a summer and late summer season  (Vihma et al. 2008) , where the areal extent and consistency of the albedo has been demonstrated by satellite reconnaissance  (Riihela ¨et al.
2010). PAR irradiances were measured with a recently calibrated LI-COR Li-192 sensor. The sensor was mounted on a thin dark-painted metal stick and lowered through a 9 cm diameter hole to the bottom of the ice. The hole was filled with small pieces of ice from the drilling to avoid any false surface light entering the hole. Care was taken to avoid any shadow effects from the stick in case of direct sun, and leaving the surface as undisturbed as possible, with no footprints. The first readings were immediately below the ice to determine the sea-ice PAR transmittance. This was followed by subsequent readings at 0. 1 m intervals covering a distance of 1. 5Á2. 0 m in the water below the ice. An average of 10 readings was obtained at each depth below the ice and data were used for determining the PAR attenuation coefficient K d (PAR) in the water below the ice.
3 nm resolution. A hole with a diameter of 25 cm was drilled through the ice and spectral sensor was lowered to a depth below the ice. Here a mechanical L-arm raised the sensor into a horizontal position and the sensor was lifted to measure immediately below the ice. The length of the arm was 75 cm and the hole was carefully filled with small chunks of ice and snow in order to avoid any false surface light interfering with measurements. Ten to 12 readings were obtained at measurement depths 0Á2 m below the ice with sensor integration time from several milliseconds to a few seconds. Surface spectral irradiance in air was measured immediately before and after completing under-ice measurements. All data were obtained within about 10 min. K d (l) was derived as K d (l)0ln(E z (l)/E z (1(l))/(z(z(1), with E z (l) as irradiance at a specific wavelength (l) and depth (z).
NLO simulations, parameters and uncertainties In this work, we employ the MadGraph5 aMC@NLO framework  [16] , which allows to compute both inclusive cross sections and differential distributions matched to parton-shower ACOT scheme  [11]. In this work we adopt a "pure" 5F scheme where m b = 0 throughout. programs, up to NLO accuracy in QCD, in a fully automatic way  [17] [18] [19] [20]  once the relevant Feynman rules and UV/R2 counterterms for a given theory are provided in the form of a UFO model  [21] [22] [23]. While these extra Feynman rules are available in MadGraph5 aMC@NLO by default for the SM, non-SM interactions that will be considered later in sect. 5 are encoded in the HC NLO X0 model  [24] [25] [26] , publicly available online in the FeynRules repository  [27]. In MadGraph5 aMC@NLO the code and events for tchannel tH production at hadron colliders in the 4F scheme can be automatically generated by issuing the following commands: (> import model loop_sm) > generate p p > h t b~j $$ w+ w-[QCD] > add process p p > h t~b j $$ w+ w-[QCD] > output > launch while the corresponding commands in the 5F scheme are: > import model loop_sm-no_b_mass > define p = p b b> define j = p > generate p p > h t j $$ w+ w-[QCD] > add process p p > h t~j $$ w+ w-[QCD] > output > launch Note that the $$ w+ w-syntax removes s-channel tH diagrams as well as real-correction diagrams where an on-shell W decays to two light quarks, which belong to W -associated production.
Acknowledgments We thank the  LHC HXSWG  and in particular the members of the ttH/tHj task force for giving us the motivation to pursue this study and for many stimulating discussions. We are grateful to  Rikkert Frederix  and  Stefano Frixione  for discussions and to  Paolo Torrielli  for his valuable help. This work has been performed in the framework of the  ERC  grant  291377  "LHCtheory: Theoretical predictions and analyses of LHC physics: advancing the precision frontier" and of the  FP7 Marie Curie Initial Training Network MCnetITN  ( PITN-GA-2012-315877 ). It is also supported in part by the  Belgian Federal Science Policy Office  through the  Interuniversity Attraction Pole   P7/37. The work of FD and FM is supported by the IISN " Mad-Graph " convention 4. 4511. 10and the IISN "Fundamental interactions" convention 4.
4517. 08. KM is supported in part by the  Strategic Research Program "High Energy Physics " and the  Research Council of the Vrije Universiteit Brussel. The work of MZ is supported by the  ERC  grant " Higgs@LHC " and partially by the  ILP LABEX  ( ANR-10-LABX-63 ), in turn supported by  French  state funds managed by the  ANR  within the  "Investissements d'Avenir" programme  under reference  ANR-11-IDEX-0004-02.
Acknowledgements. We thank  Pascal Hagenmuller , an anonymous reviewer and the associate editor  Eric Larour  for their valuable comments and remarks that helped us to improve our paper. J. Gaume was supported by a  Swiss Government Excellence Scholarship  and is grateful to the  State Secretariat for Education, Research and Innovation SERI of the Swiss Government. Benjamin Reuter ,  Eric Knoff  and  Mark Staples  assisted with field data collection. Edited by:  E. Larour.
Tuberculosis (TB) remains broadly present in the Americas despite intense global efforts for its control and elimination. Starting from a large dataset comprising spoligotyping (n = 21183 isolates) and 12-loci MIRU-VNTRs data (n = 4022 isolates) from a total of 31 countries of the Americas (data extracted from the SITVIT2 database), this study aimed to get an overview of lineages circulating in the Americas. A total of 17119 (80. 8%) strains belonged to the Euro-American lineage 4, among which the most predominant genotypic family belonged to the Latin American and Mediterranean (LAM) lineage (n = 6386, 30. 1% of strains). By combining classical phylogenetic analyses and Bayesian approaches, this study revealed for the first time a clear genetic structuration of LAM9 sublineage into two subpopulations named LAM9C1 and LAM9C2, with distinct genetic characteristics.
Among the large and heterogeneous lineage 4, the Latin American Mediterranean (LAM) family was first suggested based on the phylogenetic analysis of a large spoligotyping dataset and its name reflects the strains' origin  [11]. LAM lineage comprising several sublineages is the largest and most widespread within the Euro-American lineage 4; the phylogenetical inclusion of some sublineages within this group has been recently questioned  [12, 13] ; however, only few studies have been conducted on genotypic structure and phylogenetic history of this efficient genogroup. Consequently, this study aimed to get a first detailed overview of LAM lineage genetic specificities circulating in the Americas, and further provides novel evidence regarding LAM9 genetic structuration as two subpopulations categorized by distinct evolutionary histories and demographic characteristics.
Data collection This study made use of genotyping information of M. tuberculosis clinical isolates fully available without restriction. All data used in our study are either available at: http://www. pasteurguadeloupe. fr:8081/SITVIT_ONLINE, or in published studies  [8, 9, [13] [14] [15]. This database currently centralizes data on 120000 M. tuberculosis complex strains from 170 countries. Spoligotype International Type (SIT) and MIRU International Type (MIT) designates an identical pattern shared by two or more patient isolates by spoligotyping and MIRU-VNTRs, whereas "orphan" designates patterns reported for a single isolate not reported before in the database. Phylogenetic clade assignation follows rules of SITVITWEB in which the LSP-based Euro-American lineage (lineage 4)  [5]  is split in LAM, ill-defined T, Haarlem (H), X, and S lineages; the LSP-based "indo-Oceanic" lineage is named East-African Indian (EAI) by spoligotyping, while EAI by LSPs corresponds to Central-Asian (CAS) in the SITVIT2 database.
Phylogenetic inferences BioNumerics software 6. 6 (Applied Maths, Sint-Martens-Latem, Belgium) was used to compare spoligotypes and 12-loci MIRU-VNTR patterns of M. tuberculosis isolates from Americas, by drawing Minimum Spanning Trees (MSTs) in order to visualize evolutionary relationships between the clinical isolates in our study. MSTs are undirected graphs in which all samples are connected together with the fewest possible connections between nearest neighbors.
To estimate the number of population among LAM9 isolates, delta K was calculated by the Evanno method  [17]  implemented in the program STRUCTURE HARVESTER  [18]. Medians were then calculated from 10 replicates for K = 2 by using the FullSearch algorithm implemented in CLUMPP 1. 1. 2 software  [19]  to guarantee the optimum clustering. A cutoff of 0. 75 was fixed for clustering of LAM9 isolates to subpopulation 1 or 2. Finally, estimated membership coefficients were visualized using the software DISTRUCT 1. 1  [20]. A new MST analysis was then performed using BioNumerics software 6. 6 and identifying LAM9 strains belonging to subpopulation 1 or 2 defined by STRUCTURE analysis.
Allelic richness For analyses on allelic richness, M. tuberculosis strains were grouped according to their clades defined by the MST analysis, followed by structuration of LAM9 subpopulations as defined by STRUCTURE software. Mean allelic richness of each M. tuberculosis lineages was evaluated where 12-loci MIRU-VNTRs were available for at least 25 samples using the software HP-RARE 1. 0  [21]. This approach uses the statistical technique of rarefaction which compensates for sampling disparity.
The analyses were performed assuming exponential demographic change. The prior mutation rate value of each MIRU-VNTR locus ranged between 10 -8 and 10 -9 per locus and per generation, according to previous studies  [25, 27, 28]. The chain was run for 2 billion steps, recording parameter values every 100000 steps. The MCMC output was analyzed using the software Tracer  [29]  to obtain the posterior distribution and the effective sample size (ESS) of all parameters (which were all above 140) after a burn-in of 10%.
5%). LAM9 alone represented 10. 15% of all M. tuberculosis strains (n = 21183) from the Americas (for distribution of predominant SITs in the global database, readers may refer to S1 Table ). When focusing on geographical distribution of LAM sublineages in the Americas (Fig  1 ), contrasted patterns of sublineages proportions were observed; briefly: (i) Guadeloupe, Venezuela and Haiti presented quite similar distribution patterns with predominance of LAM9, LAM2, LAM5 and LAM1 sublineages, and two related patterns in respectively, (ii) Dominican Republic with absence of LAM1 and (iii) in French Guiana and Brazil with presence of LAM6; four other distribution patterns were characterized by (iv) large predominance of LAM9 isolates in Panama and Colombia, (v) predominance of LAM9 and LAM3 in USA, Cuba, Mexico, Peru, Chile and Argentina, (vi) large predominance of LAM3 in Honduras, and (vii) predominance of LAM9 and LAM4 in Paraguay.
Genetic structuration of LAM9 sublineage Evolutionary relationships between all LAM lineage isolates pooled together for which both the spoligotyping and 12-loci MIRU-VNTR data were available (n = 950) were investigated by MST analysis. Spoligotyping alone showed a closely-structured phylogenetic tree of this superfamily (Fig 2A ), with a huge central node made-up of the LAM9 sublineage; an observation also confirmed on global spoligotyping data on all LAM9 strains (n = 2151 strains, data not shown). However, it is common knowledge that mainly because of homoplasy, spoligotyping has limited resolution power when inferring M. tuberculosis phylogeny and that discrepancies can be obtained when comparing spoligotyping and other genotyping approaches as for example MIRU-VNTRs, IS6110 and LSPs  ).
These results suggest a phylogeographical specificity of these two subpopulations even if differences could be caused by differences in sample size. Allelic richness of 12-loci MIRU-VNTR markers was evaluated for LAM9C1 and C2 groups globally as well as at country level in Brazil, Colombia and USA, using a rarefaction procedure implemented in HP-RARE 1. 0 software  [21]  (Table  2 ). Both globally as well as for each of the countries studied, LAM9C2 was characterized by higher allelic richness than LAM9C1 isolates. Taking allelic richness as a surrogate marker of diversification time, our results tend to suggest that LAM9C2 isolates are older than LAM9C1 ones. Furthermore, it is interesting to note that, allelic richness was smaller for both LAM9 populations in Colombia as compared to Brazil and USA, probably reflecting respective immigration histories-an observation also seen through the preponderance of LAM9 representing 75% of all M.
"wild type" (WT) LAM isolates  [59] : 100% of LAM-RD Rio and just 2% of WT LAM patient strains had a single copy at MIRU40 while 98% of LAM-RD Rio had two copies at    MIRU2. Indeed, the authors of this study proposed to combine these markers to identify RD Rio strains within databases listing MIRU-VNTR typed LAM strains and more specifically to identify the theoretical "founding MIRU-VNTR type" for RD Rio M. tuberculosis (224226153321). Because LAM9C2 isolates in our study present typical signature of LAM-RD Rio strains, one may hypothesize that LAM9C2 could be constituted by significant number of LAM-RD Rio isolates, and more precisely by 27. 9% (n = 58/208) of the hypothetical ancestral RD Rio MIR-U-VNTR type (224226153321). This observation merits further investigation of LAM9C1 and C2 subpopulations using specific markers of RD Rio strains  [59, 60].
Conclusions By analyzing "classical" genotyping results extracted from an international database, we were able for the first time to reveal structuration of LAM9 sublineage into two distinct subpopulations LAM9C1 and LAM9C2 in the Americas. These clusters are characterized by contrasted geographical distribution, allelic richness, expansion ratios, and expansion dating estimates. Considering the combination of these characteristics, one may hypothesize that two distinct sublineages exist within the LAM9. Further studies based on WGS of LAM strains will allow one to have the needed resolution to decipher the biogeographical structure and evolutionary history of this successful family.
[8, 12, 13, 31, 57, 58]. It is therefore of prime importance to perform polyphasic analyses when exploring M. tuberculosis evolution for adequate discrimination. For this reason, we further looked in the genetic structuration of LAM lineage strains by constructing a MST based on combined spoligotyping and MIRU-VNTR data (Fig 2B), which globally conserved the overall structuration observed for all LAM sublineages with the exception of LAM9 (n = 450 strains in total) which was clearly split into two distinct subpopulations, an observation not yet reported in literature. To confirm this subdivision, a Bayesian model approach using STRUCTURE 2. 3 software [16]  was performed on same LAM9 dataset using 12-loci MIRU-VNTRs. The appropriate K value was selected by the Evanno method [17] (S4 Fig). STRUCTURE identified a total of K = 2 deeply divergent populations, named LAM9 clusters C1 and C2 (Fig 3A); individual strains in this figure are represented by vertical lines divided into two colored segments with the length of each segment being proportional to the estimated membership in each of the two populations (cutoff = 0.
Therefore, we decided to use this technology to search for the Hpn and Hpn-2 proteins in the proteomes of H. pylori and of non-pylori Helicobacter species. This study was performed with five selected representative strains belonging to the gastric Helicobacter group, namely H. pylori B128 (as a positive control), H. acinonychis (str. Sheeba), H. felis (ATCC 49179), H. bizzozeronii (CCUG35545) and H. mustelae (12198). In order to identify Hpn and/or Hpn-2 in total protein extracts from liquid cultures of these strains, we performed selective purification of the nickel-binding proteins, taking advantage of their property to strongly bind Ni-NTA agarose before their analysis by LC-MS/MS. Because the genomic regions containing the ORFs potentially encoding Hpn and Hpn-2 were misannotated, we manually implemented the sequences of these proteins in the corresponding databases before searching the proteomics data.
For this large study, we used the bacterial two-hybrid approach that tested pairwise interactions in E. coli  [54]. The hpn, hpn-2, hpnΔCter and hpn-2ΔCter genes were cloned in frame at their 5' or 3' extremities, with fragments encoding either the N-terminal (T25) or the C-terminal part (T18) of the Bordetella pertussis adenylate cyclase resulting into four different constructs for each protein. The ureA, ureB, ureI, ureE, ureF, ureG, ureH, hypA and hypB genes were cloned in frame at their 3' extremities with the T25 and T18 fragments. The different plasmids were transformed into E. coli in combination of pairs and the protein-protein interactions were evaluated by measuring the expression of the lacZ reporter gene. The results are illustrated in Fig  7  and the ß-galactosidase activity data are in S2 Table.
Measurement of metal sensitivity by disc diffusion and growth assays H. pylori strains were tested for their sensitivity to nickel by the disc agar diffusion method. Therefore, 2. 10 6 CFU of each strain were prepared from liquid culture and were spread on plates containing Brucella broth, 1. 5% bacto agar and 10% FCS. Sterile antibiotic assay discs (Whatman) were soaked in 4 μmol NiCl 2 (Sigma) and placed in the center of the plate. The data correspond to at least three independent experiments with two replicates per experiment. Growth inhibition diameters (zones of inhibition, ZOI) were measured after 5 days of culture. For tests of metal sensitivity during growth in liquid, H. pylori cells were inoculated at OD 600 0. 05 in 10 mL Brucella-Broth containing 10% FCS and increasing nickel concentrations (0, 5, 10, 30, 100 or 200 μM).
A 25 min (for targeted acquisitions) or 60 min (for data dependent analyses) gradient was used with the following conditions: from 1% to 50% solvent B in either 25 min or 60 min, then to 90% B in 1 min. Column compartment and analytical column were kept at 60°C. The "intact protein" mode was enabled on the Orbitrap Tribrid Fusion mass spectrometer. Tandem mass spectrometry experiments were performed with a resolution of 60,000 for MS 1 and 120,000 MS 2 , averaging 3-6 microscans for MS 1 and several microscans for MS 2 (20 microscans for H. mustelae and H. bizzozeronii and 5-8 for the other strains). Fragmentation was performed either with HCD (collision energy 25 eV) or with ETD (8 ms reaction time, 2. 0E5 reagent AGC target). The precursors were selected for fragmentation either in data-dependent mode (4 most intense ions, excluding charge states 1-5, 180 s dynamic exclusion) or in a targeted mode with an inclusion list of the theoretical mass-to-charge ratios of Hpn and Hpn-2 (with charge states between 7 and 13).
Data processing was accomplished using Thermo Scientific ProSightPC 3 software. Raw files were firstly deconvoluted with the Xtract algorithm. A three-stage database search was then performed for each strain against the corresponding Uniprot databases re-implemented with the sequences of Hpn and Hpn-2. The "absolute mass" mode was initially used with a precursor ion tolerance window of 4. 08 Da (to for potential S-S bonds) and 5 ppm for fragments. Then the "biomarker" mode was used with the same parameters to search for truncated proteoforms. Finally, an "absolute mass" search enlarging the precursor window to 10 kDa was used to search for all post-translationally modified proteoforms. Results are summarized in Table  2.
1. 7 [81] , a WAG + Γ4 model. A maximum likelihood tree of a subsample of 100 strains was inferred with PhYML version 3. 1  [82] , the LG  [83]  + Γ4 model (estimated α parameter), and the NNI + SPR tree topology exploration strategy. The robustness of the resulting ML trees was assessed using the non-parametric bootstrap method implemented in PhYML (100 replicates of the original dataset). Homologues of Hpn and Hpn-2 proteins and coding genes were searched in the 330 Helicobacter proteomes and genomes available using BLASTP and TBLASTN with default parameters, except the removal of the Low complexity regions filter and the matrix amino acid composition adjustment. There are a few H. pylori draft genomes i. e. strains Aklavik86 and PZ5086 in which hpn was not detected, and in strains Hp H5-b, E48, and PZ5024 in which hpn-2 was not detected likely because the genomes are not complete.