dataesr/scientific-paragraphs-categorization huggingface dataset:
, or simply impractical to represent due to the et al combinatorial number of reactions implied by the rules(Hlavacek   et al, 2003). Storing rule definitions in SBML is now feasible with the "multi" package, allowing rule-based modeling tools such as the preferred format for model curation in BioModels Database (Malik-Sheriff et al , 2020), not only because of its popularity but also because of its provisions to precisely encode and annotate models to support reproducible modeling. SBML is also used to share models by more generic data management platforms such as SEEK (Wolstencroft et al , 2016) and comprehensive online simula- tion environments (e. g. , Moraru et al , 2008; Weidemann et al , 2008; Lee et al , 2009; Peters et al , 2017). Moreover, having an agreed-upon format has facilitated the introduction of better model management strategies.
SBML is used today as an import/export format by many databases of mathematical models (Misirli et al, 2014; Norsigian et al , 2019; Malik-Sheriff et al , 2020), as well as by pathway data- bases (Caspi et al , 2015; Mi et al , 2016; Fabregat et al , 2017) and reaction databases (Ganter et al , 2013; Wittig et al , 2017). SBML is.
3 An online database allows results to be uploaded and compared with results from other simulators Software can be added to the list upon request. Validation Facilities Conversion Facilities Validation software can check files for compliance to the definition of SBML, Converters (http://sbml. org/Software/Converters) can translate some good modeling practices, and consistency of units other formats to/from SBML 1 API libraries include built-in validation 1 Conversion tools support format conversions from MATLAB, BioPAX, 2 Online validator has simple user interface (http://sbml. org/Facilities/Val CellML, XPP, SBtab, and others idator) 2 Online services such as SBFC (Rodriguez , et al 2016 ) convert uploaded 3 Web services support software access files to a variety of formats Validation ensures compliance with: 3 API libraries provide converters between different SBML Levels/Versions • SBML syntax and different SBML constructs • SBML validation rules published as part of each accepted SBML speci-fication 10 of 21 Molecular Systems Biology 16: e9110 2020 | ª 2020 California Institute of Technology Published under the terms of the CC BY.
et al 2003 semanticSBML (Krause , et al 2010 ). Experimental kinetic information can be retrieved in SBML format from the SABIO-Reaction Kinetics database (Wittig et al , 2017 ). Tools such as COPASI (Hoops et al , ) and PyBioNetFit (Mitra 2006 et al , ) provide facilities to estimate parameters and to simulate the 2019 model with various algorithms. Other SBML-enabled tools such as Tellurium (Medley , et al 2018 ) and PySCeS (Olivier , et al 2005 ) provide capabilities such as identifiability and bifurcation analysis. - SBML LaTeX (Dräger 2 , et al 2009 ). Finally, the model can be exported from selected modeling tools, together with data and other information all bundled together in COMBINE Archive format (Bergmann , et al 2014 ) and published in model repositories such as BioModels Database (Malik-Sheriff , et al 2020 ).
Pipeline for automated model building Being able to describe model elements precisely using semantic annotations facilitates the creation of automated pipelines (Dräger , et al 2010 ). Such pipelines can combine existing models with databases of molecular phenotypes or reaction kinetics (Li , et al 2010 ). They can also generate models de novo from data resources, as has been demonstrated by the Path Models project (Büchel 2 et al , ). Path Models has produced 2013 2 , 143 000 SBML models -all fully annotated for over , -2 600 organisms, by using pathway data. Metabolic pathways were encoded in SBML Level Core while signaling path-3 ways were encoded with the SBML qual " " package (Chaouiya , et al 2013 ). Moreover, constraint-based models of genome-scale reconstruction were pro- vided for each organism.
The faces were all of adult women. There was no similarities between the four recurrent and the keeper that could have been perceived as cues by the horses (eg. eye or hair color or style). All the images were edited using ImageJ software. The images were cropped and the background was white. Brightness and contrast were automatically adjusted to control for differences in lighting conditions. Life-size images (photographs and black circle) displayed on the screen were: 25 cm high, 20 + 2 cm wide. Data collection and analysis. Data were analyzed with XLSTAT software. The data from the pre-training and training stages were analyzed to determine whether animal performance increased over the sessions. For the pre-training sessions, all the horses carried out four sessions, and we compared the percentage of success (number of correct responses out of the 32 trials) for all the sessions using a Friedman test.
Acknowledgements We would like to thank  Tiphaine Aguirre-Lavin ,  Fabrice Reigner  and their staff from the  UEPAO (Unité Expérimentale de Physiologie Animale de l'Orfrasière)  for technical help;  Sophie Nicod ,  Fabien Cornilleau ,  Emma Bertin ,  Alice Ruet  and  Ségolène Le Pivain  for their assistance during the experiment;  Marie-Claire Blache  for preparing the images and  Sue Edrich  from the translation agency Interconnect. IFCE ( French Horse and Riding Institute ) funded this experiment. This funding source had no role in the study design, data collection and analysis, or preparation and submission of the manuscript.
3c ). Brain (white arrowhead) and spinal column (grey arrowhead) defects were observed by CT-scan at stages E13 and E16. Altogether, these data   1. CAG, composite constitutive human cytomegalovirus enhancer and chicken beta-actin promoter; Neo, neomycin antibiotic resistance cassette; IRES, internal ribosome entry site; eYFP, enhanced yellow fluorescent protein; bGH polyA, bovine growth hormone polyadenylation signal. (b) PCR on genomic DNA prepared from [ FSF TGFβ CA ] murine primary ear skin fibroblasts transfected either with the pSICO-Flpo plasmid or an empty plasmid to detect the Flpo sequence, the unrecombined FSF TGFβ CA , and the recombined FSF TGFβ CA alleles. (c) Quantitative RT-PCR on total mRNA prepared from [ FSF TGFβ CA ] murine primary ear skin fibroblasts transfected either with the pSICO-Flpo plasmid or an empty plasmid to detect TGFβ CA (left panel) and eYFP (right panel) mRNA.
Acknowledgements This work was supported; by the  Institut National de la Santé et de la Recherche Médicale (INSERM) , by the  Centre National de la Recherche Scientifique (CNRS) , by the  Association pour la Recherche sur le Cancer for consumables and BK salary  (grant " ARC-2010-Subventions Libres "); by  Ligue Nationale Contre le Cancer, comité départemental de l' Ain  ( 01 ) for consumables; by fellowships from the  Ministère de l'Enseignement Supérieur et de la Recherche of France  (RMP and ABC), from the  Ligue Nationale Contre le Cancer (VCR) , from the  Ecole Normale Supérieure of Lyon (NC). For the generation of FSF TGFβ CA transgenesis vectors, and for [ FSF TGFβ CA ] mice, we acknowledge the contribution of  ICS (Institut Clinique de la Souris, Illkirch, France)  financially supported by  PHENOMIN grant  ( Infrastructure nationale en biologie et santé -Investissements d' Avenir ).
We specially thank  Marie-Christine Birling  for her precious help. For CT-Scan analyses, we acknowledge the contribution of Anican-Image ( CRCL, CLB, SFR Bioscience, Lyon ) facility financially supported by  Phenocan equipex  ( ANR -11-EQPX-0035   PHENOCAN-Investissements d' Avenir ). We specially thank  Thomas Barre  for his help. We also acknowledge the contribution of the  CELPHEDIA infrastructure (Anira, Lyon). We thank the staff of AniCan (CRCL, Lyon) and ALECs-SPF  for their technical assistance with animal care. We also thank the  AniPath platform (Université Lyon I)  and more specifically  Nicolas Gadot  for histological preparations. We thank  Brigitte Manship  for English language editing of the manuscript.
| HCP profiling by nanoLC-MS/MS Tryptic peptides were separated on an Acclaim Pepmap 75 µm × 50 cm 3-µm 100-Å reverse phase C 18 column installed on an Ultimate 3000 NanoLC system (Dionex) coupled to a Q-Exactive Plus MS (Thermo Fisher Scientific). MS and MS/MS data were acquired using a top 10 data-dependent acquisition mode with Xcalibur 4. 0 software. Data obtained were searched using the Mascot search engine against the Uniprot CHO database.
| AGA absolute quantitation Synthetic heavy-labeled peptides ( 15 N 13 C C-terminal lysine or arginine) SLHSEWASK and NC(CAM)QPNFWR were ordered as 1 mg lyophilized powder from Pepscan (Lelystad, The Netherlands). They were resuspended in water/acetonitrile/formic acid and spiked at a concentration of 100 ppm (=100 ng AGA/mg mAb1) in mAb digests. One microgram of digests was analyzed using the NanoLC-MS/MS system described in the previous paragraph. Data were acquired in triplicates using the parallel reaction monitoring (PRM) mode targeting charge 2+ ions of light-and heavy-labeled versions of SLHSEWASK and NC(CAM)QPNFWR peptides. Data were retreated using Skyline v4. 1. 0. 11796 open-source software (University of Washington) using the most intense transition of each peptide for quantitation.
| Immunogenicity in silico risk assessment Three publically available sequences of AGA (Cricetulus griseus: strain K1 Genbank ID EGV92246, strain 17A/GY Genbank ID ERE87799, and Homo sapiens: Genbank ID P20933) were aligned using NCBI COBALT alignment tool to evaluate homology and sequence identity. Using the EpiMatrix in silico major-histocompatibility complex (MHC)-peptide binding prediction algorithm, the amino acid sequence of the HCP was screened for the presence of putative T cell epitopes restricted by human leucocyte antigen (HLA) class II. By aggregating the EpiMatrix scores of the putative epitopes identified in the analysis, and relative risk as compared to the CHO proteome, an overall HCP specific EpiMatrix protein score was calculated  (Bailey-Kellogg et al. , 2014). Finally, using an orthogonal algorithm, immune epitope database (IEDB), an analysis of peptide binding to MHC class II alleles was performed.
| Homology modeling, structural evaluation, and hydrophobicity in silico characterization A homology model of AGA was built by means of Discovery Studio Suite 2017, using the human ortholog structure (Protein Data Bank ID: 1APZ  [Oinonen, Tikkanen, Rouvinen, & Peltonen, 1995] ). The sequence identity was 79. 3% and sequence similarity was 90. 7%. Surface hydrophobicity was calculated by means of spatial aggregation propensity algorithm  (Chennamsetty, Voynov, Kayser, Helk, & Trout, 2010).
| Recombinant protein production and characterization The coding sequence of AGA from Cricetulus griseus was retrieved from the UniProt database (accession number: G3HGM6_CRIGR). According to its annotation and the sequences alignments, the signal peptide was annotated from positions M1 to G24 and the proprotein from positions F25 to I346. Therefore, an expression cassette was designed in which a polyhistidine tag (His6) and a tobacco etch virus (TEV) protease site were introduced between the signal peptide and the proprotein sequence. The resulting construct sequence (SP-His6-TEV-AGA-F25-I346) was optimized for human codon usage and synthesized (GeneArt). This expression cassette was subcloned into a mammalian expression vector for transient transfection into the HEK293FS cell line (Thermo Fisher Scientific).
Five micrograms of only reduced recAGA and 5 µg of reduced N-deglycosylated recAGA were migrated on a 12% Tris-glycine SDS-PAGE and colored by GelCode Blue Stain for 1 hr. Intact N-deglycosylated LC-MS analysis was performed on an Exion ultra-performance liquid chromatography coupled to an X500-B quadrupole time-of-flight MS (Sciex). recAGA of 0. 2 µg were separated on a MAbPac Reverse Phase 4 µm 2. 1 × 50 mm column. Data were acquired and summed mass spectra were reconstructed with Sciex OS software. GPMAW 9. 51 was used to perform mass calculations and help manual assignment of masses observed.
| Establishing HCP profiles along with DSP steps To identify HCP(s) responsible for this increase, purification intermediates and DS for batches produced either before or after the HCP levels change were digested in denaturing conditions and analyzed by LC-MS/MS. HCP profiles were found to be very similar in all post capture step samples, consistent with HCP ELISA results, with up to nine HCP confidently identified (Table  1 ). For post first and second polishing steps, only one HCP, AGA, was systematically identified both before and after the HCP level increase. However, for DS samples, AGA was identified only from AGA was identified by matching with the UniProt/TrEMBL Cricetulus griseus database accession entry G3HGM6. This protein of 346 amino acids has a molecular weight of 37. 27 kDa.
As there is no literature available for this protein in CHO cells, information for human and mice homolog proteins was gathered. AGA enzyme is synthesized as a precursor polypeptide which is activated in the endoplasmic reticulum by a signal proteolytic cleavage step resulting in two subunits, an α and a β chains  (Ikonen, Julkunen, Tollersrud, Kalkkinen, & Peltonen, 1993). The two subunits associate into a dimeric enzyme molecule by noncovalent interactions and, upon entry into lysosomes, the α-subunit is further processed to eliminate an α-propeptide  (Ikonen et al. , 1991;  Figure  3 ). To determine the maturation state of AGA, tryptic peptide ions corresponding to the cleavage domain and α-chain propeptide were examined. TIGMVVIHK peptide corresponding to the N-terminal tryptic peptide of the β-chain was identified as well as YCG-PYKPSGSLEWAISAHK and QVDIHNHD peptides corresponding to the α-chain + propeptide (data not shown).
| HCP ELISA Kit ability to detect AGA Several known concentrations of recAGA were tested in the HCP ELISA assay. Results showed recoveries close to 100% for very low level of recAGA (<10 ng/ml; Figure  5a ). With the increase of recAGA amount, the recoveries tend to decrease with the observation of a plateau at about 10 ng/ml. These results were consistent with the observation of nonlinear behavior in samples containing AGA at >10 ng/ml per ELISA well and could also explain the satisfying linearity observed on samples with less AGA content before Batch O. In parallel, a commercial generic CHO-HCP ELISA assay was also tested with the same levels of recAGA (Figure  5b ). The results showed a twofold lower quantitation of this HCP with the generic assay in comparison with the in-house one. Moreover, two available commercial ELISA assays for specific AGA quantitation targeting hamster species were also tested but both showed an absence of response for all tested samples due to a significant matrix effect (data not shown).
Plasma Metabolomics Two-hundred microliters of plasma samples was mixed with 500 µL of phosphate buffer (pH 7. 0) prepared in deuterated water, and then centrifuged at 5500× g at 4 • C for 15 min, after which 600 µL of supernatant was transferred to 5 mm NMR tubes. All 1H NMR spectra were obtained on a Bruker DRX-600-Avance III HD NMR spectrometer operating at 600. 13 MHz for 1H resonance frequency using an inverse detection 5 mm 1H-13C-15N-31P cryoprobe attached to a Cryoplatform (the preamplifier unit). The 1H NMR spectra were acquired at 300 K using the Carr-Purcell-Meiboom-Gill (CPMG) spin-echo pulse sequence with presaturation, with a total spin-echo delay (2nτ) of 64 ms to attenuate broad signals from proteins and lipoproteins. A total of 256 transients were collected in 32 K data points using a spectral width of 20 ppm, a relaxation delay of 2 s, and an acquisition time of 1.
3 (Systat Software, San Jose, CA, USA). Data from each vessel were also analyzed to determine the exchanges during the whole postprandial period for each metabolite by calculating the AUC using the trapezoid method. Then, the exchange (% of induction) was calculated as above, using the AUC values. In order to determine if the exchange was significant during the postprandial period overall, the AUC values for the incoming and outgoing blood were compared using a paired-t-test. To determine if the exchange of a metabolite was affected by the meal intake, the AUC value was divided by postprandial period of time (510 min), and compared to the fasting value using a paired-t-test. Finally, the specific effect of the meal intake was evaluated by calculating the delta change between the maximum and fasting exchange values for a given metabolite.
, 2019). These stems were moved and left outdoor to transpire the solution for at least half a day. The stems were then transferred to the beamline stage and scanned twice in less than 5 minutes using two different energies of a high-flux (3 x 10 11 photons mm -2 ) monochromatic X-ray beam: 33. 1 keV and 33. 3 keV. The projections were recorded with a sCMOS camera equipped with a 250-mm-thick LuAG scintillator (Orca Flash, Hamamatsu, Japan). The complete tomographic scan included 1500 projections, and each projection lasted 50 ms. Tomographic reconstructions were performed using PyHST2 software  (Mirone et al. , 2014)  using the Paganin method  (Paganin et al. , 2002) , resulting in 32-bit volume reconstructions of 2048 x 2048 x 1024 voxels. The final spatial resolution was 2. 8769 µm 3 voxel -1.
Partially occluded vessels were considered as occluded, some examples are presented in Fig. S1. The equivalent-circle diameter of air-filled, occluded, and functional (iohexol-filled) vessels was measured on the cross sections from the central slice of the microCT scanned volume using ImageJ software  (Schneider et al. , 2012). In the high energy scans recorded at 33. 3 keV X-ray beam, iohexol appears bright white but its contrast can sometimes impede the clear limit of the vessel lumen. Therefore, all vessel diameters were recorded on the scan recorded at low energy (33. 1 keV X-ray beam), then the distinction of occluded from iohexol-filled vessels was done on the high energy scan (as done by  Bortolami et al. 2019). The theoretical hydraulic conductivity of each vessel (kvessel) [kg m MPa -1 s-1 ] was calculated using the Hagen-Poiseuille equation: 𝑘 "#$$#% = (𝜋 × Ø , × 𝜌) (128 × 𝜂) Where: Ø is the equivalent circle diameter [m], ρ the density of water [998.
If ks varies in unity with kth, differences in ks might result from anatomical differences (e. g. smaller ks are related to smaller vessels), otherwise ks variations are the consequence of hydraulic failure. Each method to measure ks, kth, and to observe tyloses is described below. Sampling started on June 19 th and finished on September 13 th 2019 for a total of 10 sampling dates, 39 stems of the current year from 23 control-asymptomatic plants, and 49 stems of the current year from 17 symptomatic plants. We randomly sampled control plants and esca symptomatic plants all along the season through the evolution of esca symptoms, obtaining measurements from 14 weeks before until 10 weeks after symptom appearance. To explore the contribution of the experimental design to data analysis, we tested the effect of the year of uprooting (2018 and 2019), the position of the analyzed internode, and the week of the measurement (i.
Statistical analysis All data management and statistical tests were done in SAS software (SAS 9. 4; SAS Institute). We used PROC GLIMMIX for generalized linear mixed models, PROC GLM for generalized linear models, PROC REG for regression analyses and PROC FREQ for frequency analyses (Chi-square test of independence). The normality of the response variables was tested using a Kolmogorov-Smirnov test (PROC UNIVARIATE) prior to analyses. Data were logtransformed (total density) or appropriate distributions (binomial, poisson) were fitted when appropriate.
ACKNOWLEDGMENTS We thank the experimental teams of UMR SAVE and  UMR EGFV (Bord'O platform, INRAE, Bordeaux, France)  and the SOLEIL synchrotron facility (beamline  PSICHE ) for providing the materials and logistics. Specifically, we thank  Jérôme Jolivet  and  Sebastien Gambier  ( UMR SAVE ) for providing technical knowledge and support for plant transplantation and maintenance. This work was supported by the  French Ministry of Agriculture, Agrifood, and Forestry (FranceAgriMer and CNIV)  within the  PHYSIOPATH project (program Plan National Dépérissement du Vignoble ,  22001150-1506 ) awarded to C. E. L. D. , and program Investments for the  Future  ( ANR-10-EQPX-16 , XYLOFOREST).
DATA AVAILABILITY STATEMENT Raw datasets are available in the INRAE dataverse: Bortolami, Giovanni; Farolfi, Elena; Badel, Eric; Burlett, Regis; Cochard, Herve; Ferrer, Nathalie; King, Andrew; Lamarque, Laurent J. ; Lecomte, pascal; Marchesseau-Marchal, Marie; Pouzoulet, Jerome; Torres-Ruiz, Jose M. ; Trueba, Santiago; Delzon, Sylvain; Gambetta, Gregory A. ; Delmas, Chloe E. L. , 2021, "Raw data for the paper "Seasonal and long-term consequences of esca on grapevine stem xylem integrity"", https://doi. org/10. 15454/U9KJEW, Portail Data INRAE, V1.
Double Fluorescent In-situ Hybridization (dblFISH) Sections were treated with 2% H 2 O 2 in PBS to inactivate endogenous peroxidase followed by incubation with anti-DIG antibodies POD fragments in combination with anti-DNP POD (Roche, Basel Switzerland; dilution 1:1000). Incubations with these antibodies were done separately at 4˚C, overnight, for each of the antibodies. Staining with tyramide Cy3 solution or Fluorescein in PBS/Tween (1:100) was carried for 10 min each (Perkin-Elmer, Woodbridge, Ontario). Images were acquired with a Nikon A1 confocal microscope and/or Zeiss AxioPhot Fluorescence Microscope and treated with NIS-Elements Advanced Research Software or ImageJ.
Synthesis of cDNA was accomplished by reverse transcription of total RNA. From control and lesion specimens 500ng of total RNA were reverse transcribed using the QuantiTect reverse transcription kit (Qiagen). Quality and purity of cDNAs was confirmed by Agarose gel Electrophoresis. In order to assay transcripts of genes of interests by qPCR, the following conditions were used: 95˚C for 30s, followed by 40 cycles of 95˚C for 5s and 59˚C for 5s, then a melt curve progressing from 65˚C to 95˚C, at 5s per 0. 5˚C increase. Two reference genes were used for each qPCR run either ef1a, ywhaz or rpl13a. Data were analyzed using CFXManager (Bio-Rad) and compiled using GraphPad PRISM.
Acknowledgments: The author would like to acknowledge  P. Jay ,  J. Pannequin  ( Institute of Functional Genomics, Montpellier ) and  M. Weber  ( Biotechnology and Cell Signaling, University of Strasbourg ) for the discussions on stem cell biology and DNA methylation from which this manuscript "stemmed",  F. Gerbe  ( Institute of Functional Genomics, Montpellier ) for his insights and support in figure editing, and  D. Castel  ( Gustave Roussy Cancer Institute, Villejuif ) for his important inputs to the manuscript. I apologize to all colleagues whose work could not be cited due to space limitations.
5 to the KEGG pathway database identified a number of enriched pathways (Fig. 1D  & 1E ), including those related to steroid hormone biosynthesis and ascorbate and aldarate metabolism, containing 18 and 7 genes respectively (Table  S1 ). There was extensive downregulation of the histone structural units H1, H2A/B, H3 and H4 and UDP-glucuronosyltransferases, which were enriched in multiple pathways. Specifically comparing transcriptomic data with the KEGG terms 'TCA Cycle' and 'Oxidative Phosphorylation' revealed extensive gene expression changes within these pathways (Fig. 1F  & 1G) including in the majority of genes encoding enzymes that catalyse metabolite interconversion (Table  S2 ). Analysis of the Oxidative Phosphorylation pathway revealed an overall downregulation of transcription of genes encoding components of respiratory complexes I (ND1, ND2, ND4L, NDUFS2, NDUFV1, NDUFA10, NDUFB2 NDUFA2, NDUFB10) and IV (COX1, COX4I1, COX8A, COX6B1), as well as ATP synthase (ATP6V1A, ATP5MF, ATP6V0D1, ATP6V1E1, ATP6, APT5MC2, ATP5MC1) (Table  S3 ).