dataesr/scientific-paragraphs-categorization huggingface dataset:
vitripennis v1. 2 proteome database. Phylogenetic analysis of γ-GT amino acid sequences was performed using maximum likelihood (ML) with PhyML  [59]. ProtTest  [60]  was used to select the best-fit model of amino acid substitution for ML phylogeny. Leucinerich repeats (LRRs) were predicted using ScanProsite (http://au. expasy. org/prosite/). Toxin prediction was performed using ClanTox available at http://www. clantox. cs. huji. ac. il/  [61]. Knottin prediction was performed using Knoter1D available at the KNOTTIN database (http://knottin. cbs. cnrs. fr).
1% formic acid; buffer B: water/acetonitrile (20:80, v/v) and 0. 1% formic acid). MS/ MS data analysis was performed with the Mascot software (http://www. matrixscience. com) licensed in house, using the contig sequences of the Aphidius mixed library and non-redundant NR (NCBI). Peak lists generated for individual bands from the same gel lane were merged together into a single file before databank search submission. Data validation criteria were (i) one peptide with individual ion score above 50 (the mascot significant identity threshold corresponding to p < 0. 005 is 38 in our case) or (ii) at least two peptides of individual ion score above 20 (corresponding to 1% probability that a peptide spectrum match is a random event). The mascot score was calculated as -10Log(P). The calculated FDR (based on an automatic decoy database search) was lower than 1%: FDR = 0.
Quantitative real-time RT-PCR Total RNA was isolated either from dissected venom apparatus or from the rest of the female bodies (without venom-producing tissues) using the TRIzol reagent (Invitrogen), and reverse-transcribed using the iScript cDNA Synthesis Kit (BioRad). qPCR reactions were then carried out on an Opticon monitor 2 (BioRad) using the Absolute qPCR SYBR MasterMix Plus for SYBR Green I No ROX (Eurogentec). Primer pairs are listed in Additional file 14: Table  S5. PCR conditions were as follows: 50°C for 2 min, 95°C for 10 min, and 40 cycles of 95°C for 30 s, 60°C for 30 s and 68°C for 30 s. Each reaction was performed in triplicate and the mean of three independent biological replicates was calculated. All data were normalized using RPL19 and RPL23 as controls and results were analyzed using Qbase Software (Ghent University, Ghent, Belgium).
Acknowledgments We are highly grateful to  Christian Rebuf  for help in insect rearing. This work received support from the  Genoscope  ( Parasitoid venoms  project), the  Department of Plant Health and Environment (SPE)  from the  French National Institute for Agricultural Research (INRA)  and the  French National Research Agency  through the  PARATOXOSE  project ( ANR-09-BLAN-0243-01 ) and the  "Investments for the Future" LABEX SIGNALIFE: program  reference  ANR-11-LABX-0028. Caroline Anselme received post-doctoral support from the  INRA SPE department. The work carried out in Italy was supported by  PON   R&C 2007-2013 , financed by the  Ministry of University and Research (MiUR)  and  European Union (FESR) , project  GenopomPro , coordinated by the  Università di Napoli Federico II, Dipartimento di Agraria.
Availability of supporting data All trimmed ESTs for A. ervi FR and A. ervi IT are available in the NCBI dbEST repository with the following accession numbers: JZ569599 -JZ573851. The assembled transcripts corresponding to putative venom proteins have been deposited in GenBank under Transcriptome Shotgun Assembly accession number GBCU00000000. The version described in this paper is the first version, GBCU01000000.
The yielded milk was gently homogenized and a sample was taken in order to determine the contents of fat (FC), non fat dry matter (NFDM) and the density of milk (De) using a mid-infrared spectrophotometer equipment (Lactan 1-4 MINI © , Sibagropribor, Krasnoobsk, Russia). The total DM of milk was calculated by the sum of fat content and SNF and the fat yield corresponded to the multiplication of fat content and milk yield. An analysis of variance was performed to compare all determined variables using the MIXED procedure of SAS © (version 9. 3 2009, SAS Inst. , Inc. , Cary, NC) with the repeated time option. The model includes the fixed effects species (Bactrian, Dromedary, Iner-maya: F1 Dromedary female x Bactrian Male, Nar-maya: F1 Bactrian Female x Dromedary Male or F2-Kospak: Iner-maya female x Bactrian Male), parity (primiparous or multiparous), calving year (2012 or 2013), and the interaction between the species and the calving year.
In the context of the Linguistic Applications (LAPPS) Grid project, we have undertaken the definition of a Web Service Exchange Vocabulary (WS-EV) specifying a terminology for a core of linguistic objects and features exchanged among NLP tools that consume and produce linguistically annotated data. The goal is not to define a new set of terms, but rather to provide a single web location where terms relevant for exchange among NLP tools are defined and provide a "sameAs" link to all known web-based definitions that correspond to them. The WS-EV is intended to be used by a federation of six grids currently being formed but is usable by any web service platform. Ultimately, the WS-EV could be used for data exchange among tools in general, in addition to web services.
In the context of the Linguistic Applications (LAPPS) Grid project  (Ide et al. , 2014) , we have undertaken the definition of a Web Service Exchange Vocabulary (WS-EV) specifying a terminology for a core of linguistic objects and features exchanged among NLP tools that consume and produce linguistically annotated data. The work is being done in collaboration with ISO TC37 SC4 WG1 in order to ensure full community engagement and input. The goal is not to define a new set of terms, but rather to provide a single web location where terms relevant for exchange among NLP tools are defined and provide a "sameAs" link to all known web-based definitions that correspond to them. A second goal is to define relations among the terms that can be used when linguistic data are exchanged. The WS-EV is intended to be used by a federation of grids currently being formed, including the Kyoto Language Grid 10  , the Language Grid Jakarta Operation Center 11  , the Xinjiang Language Grid, the Language Grid Bangkok Operation Center 12  , LinguaGrid 13  , MetaNET/Panacea 14  , and LAPPS, but is usable by any web service platform.
Ultimately, the WS-EV could be used for data exchange among tools in general, in addition to web services. This paper describes the LAPPS WS-EV, which is currently under construction. We first describe the LAPPS project and then overview the motivations and principles for developing the WS-EV. Because our goal is to coordinate with as many similar projects and efforts as possible to avoid duplication, we also describe existing collaborations and invite other interested groups to provide input.
The Language Application Grid Project The Language Application (LAPPS) Grid project is in the process of establishing a framework that enables language service discovery, composition, and reuse, in order to promote sustainability, manageability, usability, and interoperability of natural language Processing (NLP) components. It is based on the service-oriented architecture (SOA), a more recent, web-oriented version of the pipeline architecture that has long been used in NLP for sequencing loosely-coupled linguistic analyses. The LAPPS Grid provides a critical missing layer of functionality for NLP: although existing frameworks such as UIMA and GATE provide the capability to wrap, integrate, and deploy language services, they do not provide general support for service discovery, composition, and reuse.
The LAPPS Grid is a collaborative effort among US partners Brandeis University, Vassar College, Carnegie-Mellon University, and the Linguistic Data Consortium at the University of Pennsylvania, and is funded by the US National Science Foundation (NSF). The project builds on the foundation laid in the NSF-funded project SILT  (Ide et al. , 2009) , which established a set of needs for interoperability and developed standards and best practice guidelines to implement them. LAPPS is similar in its scope and goals to ongoing projects such as The Language Grid 15  , PANACEA/MetaNET 16  , LinguaGrid 17  , and CLARIN 18  , which also provide web service access to basic NLP processing tools and resources and enable pipelining these tools to create custom NLP applications and composite services such as question answering and machine translation, as well as access to language resources such as mono-and multilingual corpora and lexicons that support NLP.
20 The LAPPS Grid also implements a dynamic licensing system for handling license agreements on the fly 21 , provides the option to run services locally with high-security technology to protect sensitive information where required, and enables access to grids other than those based on the Service Grid technology. We have adopted the JSON-based serialization for Linked Data (JSON-LD) to represent linguistically annotated data for the purposes of web service exchange. The JavaScript Object Notation (JSON) is a lightweight, text-based, language-independent data interchange format that defines a small set of formatting rules for the portable representation of structured data. Because it is based on the W3C Resource Definition Framework (RDF), JSON-LD is trivially mappable to and from other graph-based formats such as ISO LAF/GrAF and UIMA CAS, as well as a growing number of formats implementing the same data model.
Most importantly, JSON-LD enables services to reference categories and definitions in web-based repositories and ontologies or any suitably defined concept at a given URI. The LAPPS Grid currently supports SOAP services, with plans to support REST services in the near future. We provide two APIs: org. lappsgrid. api. DataSource, which provides data to other services, and org. lappsgrid. api. WebService, for tools that annotate, transform, or otherwise manipulate data from a datasource or another web service. All LAPPS services exchange org. lappsgrid. api. Data objects consisting of a discriminator (type) that indicates how to interpret the payload, and a payload (typically a utf-8 string) that consists of the JSON-LD representation. Data converters included in the LAPPS Grid Service Engines map from commonly used formats to the JSON-LD interchange format; converters are automatically invoked as needed to meet the I/O requirements of pipelined services.
22 This is what the WS-EV is intended to enable; effectively, it is a meta-type-system for mapping labels assigned to linguistically annotated data so that they are understood and treated consistently by tools that exchange them in the course of executing a pipeline or workflow. Since web services included in LAPPS and federated grids may use any i/o semantic conventions, the WS-EV allows for communication among any of them-including, for example, between GATE and UIMA services 23  The ability to pipeline components from diverse sources is critical to the implementation of the OA development approach described in the previous section, it must be possible for the developer to "plug and play" individual tools, modules, and resources in order to rapidly re-configure and evaluate new pipelines.
4. The WS-EV is not LAPPS-specific; it will not be governed by the processing requirements or preferences of particular tools, systems, or frameworks. 5. The WS-EV is intended to be used only for interchange among web services performing NLP tasks. As such it can serve as a "pivot" format to which user and tool-specific formats can be mapped. 6. The web service provider is responsible for providing wrappers that perform the mapping from internally-used formats to and/or from the WS-EV. 7. The WS-EV format should be compact to facilitate the transfer of large datasets. 22 Within UIMA, the output of tools conforming to different type systems may themselves require conversion in order to be used together. 23 Figure  5  shows a pipeline in which both GATE and UIMA services are called; GATE-to-GATE and UIMA-to-UIMA communication does not use the WS-EV, but it is used for communication between GATE and UIMA services, as well as other services.
Each service in the LAPPS Grid is required to provide metadata that specifies what kind of input is required and what kind of output is produced. For example, any service as depicted in the flow diagram in Figure  5  can require input of a particular format (gate, uima, json-ld) with specific content (tokens, sentences, etc. ). The LAPPS Grid uses the notion of discriminators to encode these requirements, and the pipeline composer can use these discriminators to determine if conversions are needed and/or input requirements are met. The discriminators refer to elements of the vocabulary.
Collaborations The LAPPS Grid project is collaborating with several other projects in an attempt to harmonize the development of web service platforms, and ultimately to participate in a federation of grids and service platforms throughout the world. Existing and potential projects across the globe are beginning to converge on common data models, best practices, and standards, and the vision of a comprehensive infrastructure supporting discovery and deployment of web services that deliver language resources and processing components is an increasingly achievable goal. Our vision is therefore not for a monolithic grid, but rather a heterogeneous configuration of federated grids that implement common strategies for managing and inter-changing linguistic information, so that services on all of these grids are mutually accessible.
To this end, the LAPPS Grid project has established a multi-way international collaboration among the US partners and institutions in Asia, Australia, and Europe. The basis is a formal federation among the LAPPS Grid, the Language Grid (Kyoto University, Japan), NECTEC (Thailand), grids operated by the University of Indonesia and Xinjiang University (China), and LinguaGrid 28  , scheduled for implementation in January 2015. The connection of these six grids into a single federated entity will enable access to all services and resources on any of these grids by users of any one of them and, perhaps most importantly, facilitate adding additional grids and service platforms to the federation. Currently, the European META-NET initiative is committed to joining the federation in the near future.
5 mM Tris-HCl, pH 6. 8, 2% SDS, 100 mM ␤-mercaptoethanol). Quantitative densitometric analysis of the immunoblots was performed by ChemiDoc software (Bio-Rad). Phosphatase Assay-Cells were lysed directly in Petri dishes with lysis buffer (50 mM Tris-HCl, pH 8. 0, 100 mM NaCl, 2 mM EDTA, and 1% (v/v) Igepal CA-630, PMSF, and a protease inhibitor mixture (Sigma). Whole cell lysates were incubated with anti-PP2Ac antibody (ON). After incubation with protein A beads the immunocomplexes were washed four times with lysis buffer. Beads were resuspended in phosphatase assay buffer (50 mM Tris-HCl, pH 7. 0, and 0. 1 mM CaCl 2 ), incubated for 30 min at 37 °C with or without okadaic acid 100 nM in presence of 1 mM NiCl 2 and 0. 125 mg/ml BSA, and then analyzed by fluorimetric assay using DiFMUP substrate as described  (20).
RNA Extraction and Quantitative Real-time-PCR-Cells were lysed using TRI-REAGENT (Molecular Research Center). 1. 0 g of total RNA was retro-transcribed by using 100 units of Moloney murine leukemia virus reverse transcriptase (Invitrogen). Quantitative real-time-PCRs were performed using the Bio-Rad CFX96 and SYBR Green technology. Data were analyzed by a comparative threshold cycle using hypoxanthineguanine phosphoribosyltransferase and ␤-actin as normalizer genes. All reactions were done in triplicate. Statistical Analysis-Results are expressed as the means Ϯ S. D. Student's t test was performed with Excel software. p values are represented as: *, p Ͻ 0. 05; **, p Ͻ 0. 01; ***, p Ͻ 0. 005. Data of the spreading area were analyzed using Non-parametric Mann-Whitney test (Prism GraphPad Software); ***, p Ͻ 0.
The appearance of cell death was scored by trypan blue staining. Data are presented as the mean Ϯ S. D. ; n ϭ 3. N, mRNA expression levels of RIP1, RIP3, and MLKL in HT29 and U87MG cell lines. Data were derived from public available microarray experiments (GSE48433, GSE23806, GSE14889, and GSE9171). Values are the average of two array chips for U87MG and three for HT29 cells. Errors bars represent S. D. O, mRNA expression level of RIP3 was measured in U87MG-and HT29-expressing cells using quantitative real-time-PCR. mRNA level was relative to U87MG cells. Values are shown in a logarithmic scale, Data are presented as the mean Ϯ S. D. ; n ϭ 3.
Cell proliferation assay The effect of NRG1β1 and pertuzumab on cell proliferation was evaluated using 3-[4,5-dimethylthiazol-2-yl]-5-[3-carboxymethoxyphenyl]-2-[4-sulfophenyl]-2H tetrazolium (MTS) and the electron coupling reagent phenazine methosulfate (PMS) as already described  [17]. www. impactjournals. com/oncotarget analyses of the TR-FRET and cell viability data were performed with the Prism GraphPad software (San Diego, CA) using one-way ANOVA followed by the Dunnett's test comparison with untreated cells).
ACKNOWLEDGMENTS We thank  G. Heintz ,  S. Bousquié ,  V. Garambois ,  I. Aït-Arsa  and  A. Ho -pun-cheung for excellent technical assistance. Flow cytometry analysis was performed thanks to  N. Vié  using equipment at the Montpellier IRO imaging facility. We thank  F. Bibeau  for providing pancreatic tumor samples, and  A. Cayre  and  F. Boissière  for pathology technical assistance. This work was supported by the program " Investissement d'avenir " grant agreement:  Labex MabImprove ,  ANR-10-LABX-53-01  and  INCa-DGOS-Inserm   6045. This paper has been accepted based in part on peerreview conducted by another journal and the authors' response and revisions as well as expedited peer-review in Oncotarget.
15418 nm. The diffraction patterns were obtained by scanning the detector from 2θ = 0° to 80°, while setting the incidence angle at 2°. The analysis of the spectra were carried out using the EVA software package from Bruker that contains a search and match option to identify various phases of the films. A MultiMode™ Scanning Probe Microscope (NanoScope III) from Digital Instruments was used to obtain AFM images of the surface morphology of the films. All measurements were performed under contact mode using a silicon nitride cantilever, integrated with a sharp tip that is approximated by a pyramid formed from intersected [111] silicon planes. The scan size ranged from 1 to 10 μm, and the surface topography of all films was quantified through the determination of the lateral grain size, and root-mean-square surface roughness.
The thickness and elemental composition of the films were determined by RBS; a Van de Graff tandem accelerator was used to accelerate a beam of 4 He 2+ ions to 2 MeV, which was focused to hit the surface with a 1 mm 2 spot size. The backscattered ions were detected at a scattering angle of 165°. The obtained RBS spectra were simulated using the SIMNRA software. The obtained values of film thickness were compared to those measured using an Ambios XP-1 high resolution surface profiler.
The RBS spectrum of Co 2 MnAl/GaAs film deposited at a substrate temperature of 500 o C and laser energy of 300 mJ is shown, with its simulated fit, in Fig. 2. The thickness of the film as deduced from the fitting of the spectrum was found to be 40. 5 nm compared to 38 nm as deduced from the profilometer measurement. The stoichiometric composition of this film was found to be 58%, 22% and 20% atomic for Co, Mn and Al, respectively. These values were obtained by simulating the RBS spectrum using the SIMNRA software. The effects of substrate temperature on film thickness, for the three values of the Laser energy are shown in Fig. 3. There is a clear trend that deposition at higher substrate temperature and laser energy leads to thicker films with the exception of the film deposited at 600°C and laser energy 400 mJ.
It is left as a fitting parameter, as well as the quality factor Q and the center frequency ω 0. Q and ω 0 are used to deduce the dissipation in the crystal and the value of the elastic coefficient c 44. Figure  2  shows a resonance example recorded at T = 25 mK, a temperature well below the stiffening temperature at which 3 He atoms start to pin the dislocation lines. It implies that dislocations are fully pinned by 3 He impurities. Q is consequently high (4124) since it is only limited by the acoustic coupling between the crystal and the body of the cell. Most of the time, the dissipation associated with dislocation motion is much larger than losses due to acoustic coupling. It is then reasonable to take Q -1 as a value for the dissipation. For every oriented crystal, a numerical model of the resonant cavity was produced with COMSOL software and used to predict the dependence of the resonance frequency on the value of c 44.
Scenario for genome erosion during Mollicutes evolution Overview: loss and gain of genes. Using our dataset of translation genes, we performed a reconstruction of gene gain and loss events in Mollicutes evolution. In this reconstruction, we hypothesized that the last ancestor common between the Mollicutes and B. subtilis was a virtual organism with 220 genes involved in translation (i. e. 208 B. subtilis query genes +12 genes found in Mollicutes but not in the modern B. subtilis). Ancestral gene content at each node of the phylogenetic tree was inferred using the posterior probabilities calculated from the birth-and death model implemented in the COUNT software package  [36]. Taking into account that the genome downsizing was probably a major component in Mollicutes evolution, the scenario was built allowing no gene gain in B.
S1 is important for translation initiation of Shine-Dalgano (SD)-containing mRNAs and becomes obsolete for Figure  1. Genes coding for proteins implicated in translation in Mollicutes. Using queries from E. coli (Ec) and from B. subtilis (Bs), the presence of homologous proteins was searched in 39 Mollicutes genomes (see list of selected species below part B of the figure). This figure corresponds to the raw data given in Table  S3. The results were grouped into three panels: conserved core of genes involved in translation (A), genes lost in some species only (B) and genes absent in all Mollicutes species (C). In panels A and C, only data concerning Ec and Bs are shown. In part B, the selected species clustered according to the 4 phylogenetic groups; Spiroplasma, Hominis, Pneumoniae and AAP  [25].
Mining genes encoding proteins of the translation apparatus in Mollicutes The whole set of proteins of the of Escherichia coli str. K-12 substr. MG1655 and of Bacillus subtilis subsp. subtilis str. 168 translational apparatus were obtained from the Modomics  [146] , Biocyc  [147] , SEED  [148] , SubtiList  [27]  databases, and Kyoto Encyclopedia of Genes and Genomes  [149] , plus an extensive review of literature (Table  S2 ). Homology between E. coli and B. subtilis proteins was inferred by sequence similarity using a reciprocal BLAST search approach (bidirectional best hit). All E. coli and B. subtilis proteins were used as queries for BLAST searches in 39 selected genomes from distinct Mollicutes species included in the MolliGen genome database (  [150] ; http://www. molligen. org) (Table  S3 ).
In this database, initial annotated genomes were obtained from GenBank files. These genomes were further curated by expert annotation that resulted in changes in the functional annotation of specific CDSs and in adding CDSs that were missing in the initial Genbank file. This step of data curation was performed in the frame of the present project for all the homologs involved in translation. Multiple genomes from the same species were excluded from our dataset because initial analyses indicated that no intra-species differences are evident in the gene sets encoding proteins involved in a central process such as translation and ribosome biogenesis. They were nevertheless useful for confirming the presence or absence of a given gene or solving some abnormalities due to occasional sequencing errors in the dataset.