dataesr/scientific-paragraphs-categorization huggingface dataset:
Randomized photos were presented to three observers familiar with the model but not implicated in the design of this study. Observers noted yes (=1) if presence of white areas on the tumor or not (=0) and if tumors resembled to a normal tumor (=1) or not (=0). Data were only processed for tumors where two out of three observers concluded the same result. A contingency table was generated and analyzed using the Chi-square test (GraphPad Prism 5, GraphPad Software). (Reference n°DGOS/PF4/0013/105), the Fondation pour la Recherche Médicale (FRM; project n°DBI20131228566), the Ligue Nationale contre le Cancer (LNCC), the Agence Nationale de la Recherche in the frame of the "Investments for the future" Programme IdEx Bordeaux (Reference ANR-10-IDEX-03-02) and the following charity associations: Eva Pour La Vie, Aidons Marina, Fondation Flavien, E.
Notch, load ratio and load type effects Deguchi et al. [8] -  [10]  introduced a set of experimental data related to a ferrite-pearlitic nodular cast iron material with 10. 5% graphite, 45. 3% ferrite, and 44. 2% perlite content. The investigated material classifies as grade EN GJS 500-7 according to EN 1563:2012  [7]  with a yield strength of. 2 = 335 [MPa], an ultimate tensile strength of   = 552 [MPa]. Rotating bending and tension compression fatigue tests were conducted on circumferentially notched and unnotched polished specimens, and on specimens with a drilled hole. Fig. 1  shows the geometry of the test specimens. The fatigue limit was determined as the stress amplitude which the specimen has endured for 10 7 load cycles. Table  1. summarizes the test results, where D is the diameter of the proof section,   1 7 is the stress amplitude leading to the survival of 10 7 load cycles (fatigue limit), RB designates rotating-bending, T stands for pulsating tension, TC is for tension-compression, R is the load ratio,  is the notch depth,  is the diameter of the drilled hole and ℎ is the depth of the drilled hole.
The fracture surfaces were analyzed by means of optical and electron microscopy. The crack initiation sites were small subsurface defects not exceeding the 100  size measured in the √ parameter from Murakami  [1]. Specimen geometry is shown in Fig. 3 , results of the fatigue tests are summarized in Table  3. In order to obtain comparable data from the tests conducted at three different load ratios, the corresponding Crossland equivalent stress (  10 6 ) has been calculated for each data point. The choice of the Crossland equivalent definition is justified by the nature of the analysis; the aim is to analyze high cycle fatigue behavior under proportional loading conditions. The Crossland equivalent stress (  ) is defined: 𝜎𝜎 𝐶𝐶𝐶𝐶 = �𝐽𝐽2,𝑎𝑎 + 𝛼𝛼 𝐶𝐶𝐶𝐶 𝜎𝜎 ℎ,𝑚𝑚𝑎𝑎𝑚𝑚 , (1) where �2, is the square root of the amplitude of the second invariant of the deviatoric stress tensor,  ℎ, is the maximum of the hydrostatic stress in each load cycle and   is a model parameter.
Sanger sequencing verified the NRAS mutations (Supplementary Fig. 9 ). WES also revealed somatic mutations of TP53 in Xeno32 and NPC43 (Gly245Asp in Xeno32; Trp53* in NPC43), which were further verified by Sanger sequencing (Supplementary Fig. 10 ). Recurrent mutations of TP53 in NPC have been previously reported  19, 20. EP300 mutations were recurrently found in Xeno32 and NPC43. As one of the chromatin modifiers, inactivating mutations in EP300 have been implicated in many human cancer types  21. SMG1 gene was mutated in both Xeno23 and 47. Sanger sequencing in Xeno23 verified the mutation (Supplementary Fig. 11 ). According to a recent report, SMG1 can suppress CDK2 and, thereby, regulate tumor growth through cell cycle regulatory pathways of p53 and cdc25A  22. Whole-genome sequencing (WGS) analysis was performed in the established NPC PDXs and cell lines to further examine somatic mutations, including single-nucleotide variants (SNVs), INDELs, structural variants (SVs) and copy number variants (CNVs) (Supplementary Data 1-3).
After PD 22, the NPC43 cells could be passaged at a 1:4 splitting ratio. The mean doubling time of NPC43 cells was about 8, 4 and 2. 5 days at PD 22, 90 and 200, respectively. d NPC43 cells were stained for the expression of cytokeratin AE1/AE3 (green). The nuclei were revealed by Hoechst stain (blue). The epithelial nature of NPC43 was confirmed by the positive staining of pan-cytokeratin in cells using specific antibodies. Scale bar, 20 μm. e Images of EBV FISH revealing the presence of EBV in NPC43 as punctate red dots. Scale bar, 20 μm. f Expression of EBV genes was detected in NPC43 by real-time PCR. C666-1 was used as positive control. Data are shown as mean ± SD from three independent experiments. g Left panel: Representative image of NPC43 tumors subcutaneously grown in NOD/SCID mouse.
Phylogenetic study of EBV sequences in NPC PDXs/cell lines. The sequencing reads of WGS mapped to mouse genome (mm10) and human genome (hg19) were removed and then aligned to the reference EBV genome (NC_007605). The mapped reads were used for de novo assembly of EBV genome sequences. Detailed summaries of sequencing data mapping and assembly are included in Supplementary Tables  5  and 6. The phylogenetic trees of EBV whole-genome and genes were constructed accordingly. As shown in Fig. 9 , AG876, a type II EBV strain, clearly segregated from the other type I EBV strains, which is consistent with previous studies  28. The whole-genome sequences of EBV in the newly established NPC PDXs (Xeno23, 32, 47 and 76) and cell line (NPC43) clustered with the Asian EBV strains, especially those sequences from Chinese NPC (M81, C666-1, HKNPC1-9 and GD2).
Acknowledgements The authors acknowledge the funding supports from  Research Grant Council, Hong Kong: AoE NPC grant  ( AoE/M-06/08 ),  Theme-based Research Scheme grant  ( T12-401/ 13-R ) and  Collaborative Research Fund  ( C7027-16G ) and  General Research Fund  ( 17120814 ,  17161116 ,  17104617 ,  17114818 ,  17116416 ,  17111516 ,  17110315 ). The establishment and characterization of NPC xenografts were also supported by  HMRF  grant ( 04151726 ,  13142201 ). Imaging data were acquired using facilities in the  Faculty Core Facility ,  Li Ka Shing Faculty of Medicine, The University of Hong Kong.
, detection by enhanced-chemiluminescence) of LOX-PP. The purification process was followed by SDS-PAGE and Western blot with a primary anti-FLAG antibody (F3165, Sigma-Aldrich 51 ) and a secondary antibody conjugated to peroxidase (Bio-Rad, 172-1011). The gels were stained with EZBlue ™ Gel Staining Reagent and were scanned with the Canon LiDE 210 scanner. For Western blots immunocomplexes were detected with SuperSignal West Pico Chemiluminescence Substrate (34080, Thermo Scientific) and visualized using the Fusion FX camera (Vilber-Lourmat) for three minutes with default settings. Pre-stained molecular weight markers were also visualized with the Fusion FX camera (Vilber-Lourmat), and superimposed on the membrane imaged by chemiluminescence with the Fusion Capt Advance software. Full-length gel and blot are presented.
The molecular weight of LOX-PP calculated with the SAXS Molecular Weight package (SAXSMoW  28  , http://saxs. ifsc. usp. br/, s max value of 8/R g ) was found to be 29. 4 kDa. Size Exclusion Chromatography -Multi-Angle Light Scattering (SEC-MALS) analysis showed that glycosylated LOX-PP eluted as a single peak from a size-exclusion column with a molecular mass of 34. 1 kDa (mass fraction: 97%, Fig. 3b ). Both values are consistent with the apparent molecular weight calculated by SDS-PAGE (~ 30 kDa) and show that glycosylated LOX-PP is a monomer. The radius of gyration (R g ), determined with PRIMUS, was 3. 7 ± 0. 04 nm (Fig. 4b ), which is of the same order of magnitude than the theoretical Rg (3. 53 nm) calculated with Flory's equation, and the hydrodynamic radius (3. 05 nm). The experimental R g /R h ratio (1.
Heparin docking on LOX-PP and MD simulations. We have previously shown that LOX-PP interacts with 6-kDa HP with an affinity of 190 nM  26  but the localization of the binding site of HP on LOX-PP is unknown. We have thus performed docking experiments with the 3D models of LOX-PP and a HP oligosaccharide in order to localize putative binding site(s) in LOX-PP sequence, and to determine if the oligosaccharide binding was able to induce LOX-PP folding. Poisson-Boltzmann surface area (PBSA) electrostatic potential calculations carried out for each model showed that arginine residues crucial for the positive electrostatic potential of LOX-PP were concentrated either at the N-terminus (models 1-3) or at the C-terminus (models 4-5). According to the computational analysis of all protein-GAG structures available in the Protein Data Bank (PDB, https://www.
These data further indicate a high probability for HP multipose binding, which was previously computationally predicted and experimentally confirmed for other protein-GAG complexes  [33] [34] [35]. HP predicted binding sites appeared thus to be mostly localized in globular regions, at the N-terminus for models 1-3 and at the C-terminus for models 4-5. For each obtained cluster of docking solutions, we carried out all-atom MD simulations arbitrarily choosing three ligand poses from each cluster. In total, 30 different LOX-PP/HP complexes were analyzed. Again, our data suggest very heterogeneous nature of this interaction both for the free energy of binding and the radius of gyration changes upon GAG binding (Table  2 ). In most cases, the free energy of binding became more favorable during the simulation, suggesting that further contacts were established to tether LOX-PP/HP binding.
A single representative evidence of each interaction is displayed in Supplementary Figs  7  and 8. The interaction network of LOX-PP integrating partners curated from the literature and available in MatrixDB database  38  (http://matrixdb. univ-lyon1. fr/) is displayed in Fig. 9a. All the interactions identified in this study will be publicly and freely available in MatrixDB database. Most LOX-PP partners belong to the extracellular matrix (42. 5%) or are associated with it (21. 2%), whereas 30. 3% of them are intracellular and 6. 1% are membrane proteins (Fig. 9b ). Moreover, Table  2. MM-GBSA free energies of binding for LOX-PP/HP complexes after 10 and 20 ns of the simulation. Clusters were selected according to the procedure described in the Material and Methods section (n = 3). LOX-PP bound with very high affinity to tropoelastin and to plasminogen, and with high affinity to anastellin, a fragment of fibronectin (Table  3 , Supplementary Fig.
Prediction of intrinsic disorder in LOX-PP. Intrinsically disordered regions in the full-length sequence of LOX-PP were predicted with the metapredictor metaPrDOS combining DISOPRED2, DISPROT, IUPred, and PrDOS predictors  52  (http://prdos. hgc. jp/cgi-bin/meta/top. cgi). Molecular recognition features, short disordered regions able to undergo disorder-to-order transition upon binding to partners, were predicted in LOX-PP with ANCHOR  53  (http://anchor. enzim. hu/) and MoRFchibi SYSTEM  54  (http://www. chibi. ubc. ca/faculty/ joerg-gsponer/gsponer-lab/software/morf_chibi/).
Dynamic Light Scattering (DLS). DLS measurements were performed in a Zetasizer Nano ZS (Malvern, UMR 5223, Villeurbanne, France) using a disposable plastic cuvette (Eppendorf, 0030106300). Four series of fifteen spectra of LOX-PP diluted to 1. 1 mg/ml (35 µM) in HBS were acquired at a 173° angle, at 633 nm, at 20 °C. Data were analyzed with the Malvern software.
94 nm -1. Data quality was assessed with the autoprocessing framework EDNA 60 before analysis. Buffer spectra were subtracted from LOX-PP spectra and data were extrapolated to infinite concentration using ATSAS suite  61. Useful data range was defined by SHANUM  62  and PRIMUS  63  was used to calculate the radius of gyration of LOX-PP through Guinier's approach with a sR g limit <1. 06. Normalized Kratky plot was generated with scÅtter  64  to evaluate the flexibility of LOX-PP. The theoretical R g was calculated with Flory's equation, which associates the radius of gyration with the protein length (R g = R 0 N ν , N being the number of residues of the protein, R 0 being 2. 54 ± 0. 01 and ν 0. 522 ± 0. 01 for intrinsically disordered proteins  65  ). Ensemble modelling was performed with EOM (Ensemble Optimization Method 2.
5 M guanidinium chloride. Data were analyzed with Evaluation 9. 0 software. Building and analyzing the interaction network of LOX-PP. The interaction network of LOX-PP was built by integrating the new partners identified in this study by SPRi, SPR and BLI, and those curated from the literature available in the interaction database MatrixDB 38 (http://matrixdb. univ-lyon1. fr/) we have created. The network was visualized using Cytoscape 69 (http://www. cytoscape. org/). Coarse-grained simulations of the lysyl oxidase propeptide. 3D models of LOX-PP were generated using the UNRES coarse-grained model of proteins  70, 71  with the recently added function of including the distance distribution from SAXS as restraints  31. The full protocol is detailed in Supplementary material. The secondary structure of each model was determined from the coordinate (.
Acknowledgements This work was supported by a grant from the  Fondation pour la Recherche Médicale  (grant  n°DBI20141231336  to SRB),  Ligue Nationale contre le Cancer, Comité du Rhône  ( 2017-01CI: UCBL  to SRB) and the  National Science Center of Poland (Narodowe Centrum Nauki , grant  UMO-2016/21/P/ST4/03995  ( SAS, UU, AL ), the  European Union   Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie  grant agreement No  665778  to SAS). The SAXS experiments were performed on the beamline BM29 at the  European Synchrotron Radiation Facility (ESRF, Grenoble, France ,  MX-1841  and  MX-1920 ) and on the SWING (Small and Wide angle X-ray scattering) beamline ( French National Synchrotron Facility SOLEIL, Saint-Aubin, France ,  20170906 ). We are grateful to  Romain Salza  ( Villeurbanne, France ) for transfecting HEK293 cells with the LOX propeptide construct and for his help in performing SPRi experiments, to the local ESRF contact for providing assistance in using BM29 beamline, to  Nathalie Sintes  ( UMR 5223 ,  Villeurbanne, France ) for providing access to the DLS instrument, to  Laure Perrin-Cocon  and  Vincent Lotteau  ( International Center for Infectiology Research, Lyon, France ) for their generous gift of LTBP-1 domains and to  Laurent Terradot  ( UMR 5086 ,  Lyon, France ) for performing SEC-MALS experiment and analysis.
The same material was used to call OTUs from 16S rDNA v4 region amplicons. We mapped Illumina reads against all bacterial genomes in GenBank and against the A. thaliana reference genome, and determined the ratio of bacterial to plant reads. Microbial load varied substantially across the 176 plants (Figure  2A ), and we calculated its correlation with each of the 3,647 OTUs detected in at least one sample. Because OTUs were called on 16S rDNA amplicons, but microbial load was assessed on metagenomic reads, the two assays provided independent measurements of relative and absolute microbe abundance. Among all OTUs, a sequence that matched with OTU5 at 100% sequence identity over the v4 region was the most positively correlated with total microbial load (Figures  2B  and 2C ; Pearson correlation coefficient R = 0.
Six hundred and twenty-two genes are conserved (>90% of genomes) within OTU5, but are much more rarely found in other lineages, in fewer than 10% of non-OTU5 strains. A large percentage of the OTU5-specific genes, 25%, encode proteins without known function (''hypothetical proteins''). For successful colonization, microbes often deploy toxins, phytohormones, and effectors that they inject into host cells or the apoplast. To determine whether such compounds are likely to be associated with the abundance of OTU5, we generated a custom database of relevant genes known from Pseudomonas and used it to annotate each isolate (Figure  6C ; Table  S2 ). OTU5 strains lacked all known genes for coronatine and syringomycin/ syringopeptin synthesis, while genes for pectate lyase synthesis were broadly conserved both in and outside of OTU5 (Figure  S6 ).
Amplicons were quantified in duplicates with the PicoGreen system (Life Technologies, Carlsbad, CA, USA) and samples were combined in equimolar amounts into one library. The final libraries were cleaned with 0. 8x volume Ampure XP purification beads and eluted into 40 mL. Libraries were prepared with the MiSeq Reagent Kit v3 for 2x300 bp paired-end reads (Illumina, San Diego, CA, USA) with 3% PhiX control. All the samples were analyzed in 9 runs on the same Illumina MiSeq instrument. Samples failing to produce enough reads on one run were re-sequenced and data from both runs were merged.
ACKNOWLEDGMENTS We thank  Marek Kucka  for methodological help with Tn5 transpososome purification;  Julia Vorholt  for recommendations on infection methods;  Matthew Clark  for providing protocols for amended Nextera methodology;  Mathew Agler  for organizing and participating in several sampling trips;  Hernan Burbano  for discussions;  Joy Bergelson ,  Jeff Dangl , and  Michael Werner  for critical reading of the manuscript; and  Joffrey Fitz  for help with the panX visualization. Funding was provided by  HFSP  long-term fellowships (LT000348/2016-L, T. L. K. ; LT000565/2015-L, D. S. L. ), an  EMBO  long-term fellowship (LRTF 1483-2015, T. L. K. ),  ERC AdG IMMUNEMESIS  (D. W. ), and the  Max Planck Society  (D. W. and E. K. ).
In view of this,  Wang et al. (2011)  studied the source locations of over 1000 coronal CMEs, combining LASCO data taken during the period from 1997 to 1998 ─ near the start of Solar Cycle 23 ─ with extreme-UV (EUV) disc imaging. In attempting to identify the EUV source regions of the 1078 CMEs included in their LASCO event list during those years (extracted from the CDAW catalogue), the authors found that i) for 231 of the CMEs, the source regions could not be identified due to the poor quality of the data, ii) 288 of the CMEs could be associated with clearly identifiable front-side source regions, iii) 234 had identifiable signatures over the limb, and iv) for 325 CMES, there was no clear association with eruptive structures in the EUV data. The  Wang et al. (2011)  paper forms part of a long line of publications that, together, stress the lack of clarity of the CME onset process in terms of solar surface associations (see e.
, 2014; Rollett et al. , 2014; Temmer et al. , 2014; Wang et al. , 2014; Zhao et al. , 2016). By necessity, CME catalogues derived from single-spacecraft coronagraph imagery cite event speeds in the plane of the sky. In contrast, the availability of wide-angle imaging even from a single vantage point allows us to explore the 3D nature of CME propagation through the heliosphere; the extended elongation range of the data enables us to derive such 3D information through geometrical modelling. More specifically, fitting the timeelongation profiles of features of outward-propagating CMEs over large distances from the Sun (e. g. Davies et al. , 2009)  allows us, in principle, to determine the latitude and longitude (and radial speed) of propagation of each CME. Thus, we can determine whether or not a particular event might be directed towards Earth, Venus, Mars or indeed any other solar system "target" (see  Möstl et al.
, 2012 Möstl et al. , , 2017)). It is the purpose of this paper to focus on CMEs in the heliosphere by providing a benchmark for the cataloguing and statistical analysis of such events, which allows us to address uniquely a range of issues pertaining to CME propagation and evolution, and a number of concepts relating to CME onset models. It naturally sits alongside the established coronal CME catalogues that are mentioned in this paper, thereby setting the stage for a comprehensive analysis of the relationship between CMEs in the corona and heliosphere that should confirm or refute the findings of studies such as those mentioned above. This should pave the way for a far more complete view of CMEs, their sources, evolution and propagation, and by combining with "ground-truth" data from in situ measurement at specified locations, we are also much more able to assess the impacts of events that have been imaged in the corona and heliosphere.
There are 49 gaps longer than this in the nominal-cadence HI-1A dataset (from April 2007 to August 2017, outside the conjunction phase). Only four of these gaps lasted longer than 50 images (i. e. over 33 hours), the longest, at 121 hours occurring just prior to the onset of the conjunction phase. The HI-1B dataset manifests 31 gaps longer than 20 images in duration, again with only four longer than 50 images (these range from 39 to 45 hours in length). It is not straightforward to assess the required correction to account for these data-gaps but, making the relatively extreme assumption that a single CME was missed for each gap exceeding 20 images, this would lead to the loss of 49 HI-1A CMEs. This amounts to an average over the observation period of 0. 01 CMEs per day, making it insignificant in terms of Figure  2a  and 2b.
We consider time windows of +/-1, 2, 3, 6, 9, 12 and 48 hours in duration. We undertake this comparison, initially, by identifying HI-1B CMEs that are first detected within these pre-defined time limits of the times at which HI-1A CMEs are first observed, and then vice versa. The resultant percentages of so-called "coincident events" are presented in the upper and lower panels, respectively, of Figure  5 , as a function of time; data are binned using a bin size of three months. This figure includes events from April 2007 to August 2014; obviously no post-conjunction events are included due to the loss of contact with STEREO-B. The time axis covers a range of separation angles between the two spacecraft. As an illustration, in  January 2008 January , 2009 January , 2010 January , 2011 January , 2012 January , 2013 January , and 2014 , the STEREO-A/Sun/STEREO-B separation angle ─ centred approximately on the Sun-Earth line ─ was 44 o , 88 o , 132 o , 176 o , 218 o , 260 o and 302 o , respectively.
Thus, although potential CME-generating regions are likely to be more widely distributed in latitude when the Sun is more active, outward propagating CMEs appear to be deflected equatorward despite the more complex nature of the coronal structure at such times (this will be discussed in more detail below). Over the declining years of Solar Cycle 24 (after 2014), we are limited to data from HI-1A and LASCO only; during this time, the central PA distribution of CMEs identified in LASCO imagery remains broad, whereas the corresponding distribution for HI-1A becomes narrower. We note that the CDAW and COR-2 catalogues both list CME central PAs explicitly, as opposed to HI which just cites the northermost and southernmost extent from which the central PA is derived. The CDAW catalogue identifies full halos (i.
, 2004). Moreover, there is some evidence that CMEs tend to be "clearer" (brighter and more well-formed) at solar maximum. As expected, many of the conclusions of this work confirm the results of previous analyses of the statistical behaviour of CMEs in the corona, extending these conclusions to the case of the heliosphere. This includes results pertaining to CME rates, the variation of CME characteristics with solar cycle, and evidence supporting the continued deflection of CMEs towards the equator as they propagate outward, although, unlike some previous studies, the HI-1 data indicate such deflection predominantly occurs during solar maximum. The HICAT catalogue, on which this analysis is based, provides a benchmark for the analysis of heliospheric CMEs that sits alongside established coronal CME catalogues, enabling for a more complete view of CMEs from source/onset studies to impacts at Earth and elsewhere.