dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements This work was supported by the  Centre National de la Recherche Scientifique (CNRS) , and the  University Paris Diderot-Paris7. We thank  Dr Olivier Bensaude  ( IBENS ) for the gift of alpha-amanitin,  Dr Jacques Moreau  ( Institut Jacques Monod ) for his help with oocyte injection experiments,  Dr Orestis Falkaris  and  France Lam  from the  ImagoSeine core facility  for their help with the Structured Illumination microscopy analyses. The ImagoSeine core facility is a member of the IBiSA and the  France-BioImaging  ( ANR-10-INBS-04 ) infrastructure. We thank  Ludovic Maingault  and  Daniel Quintas  at the animal housing facility of the  Jacques Monod Institute  for their care of the amphibians. We thank  Pr Michel Vervoort  ( Institut Jacques Monod ) for helpful discussions on the origin and evolution of vertebrates.
rT-qPcr analysis of chi3l1 Transcripts in Mammary Tissue From infected cows RNA was extracted from mammary gland tissue of German Holstein Friesian cows (n = 5) in mid-lactation, experimentally infected with E. coli strain 1303 as described previously  (32)  using Trizol (Invitrogen). Experimental infection of animals was conducted at the Clinic for Ruminants (Munich, Germany) with the approval of the ethics committee of the regional government of upper Bavaria, Germany (No. 55. 2-1-54-2531-108-05). Total RNA (1 µg) was reverse transcribed to cDNA using the iScript™ Reverse Transcription Supermix (Biorad). Quantitative PCR was then performed using the iQ SYBR Green Supermix (Biorad), using the primers listed in Table  1. Briefly, after normalization using the expression of three reference genes (ActB, PPIA, 18S RNA), expression of each gene was calculated using the Genex macro (Biorad) relative to the values obtained from uninfected cows arbitrarily set to 1.
statistical analysis Statistical analysis was performed using Prism (GraphPad) and SPSS (IBM Analytics). Data were checked for normality and an unpaired Student's t-test was used to determine whether differences between groups were statistically significant (P < 0. 05). resUlTs chi3l1 is Present in Whey From naturally coliform-infected Udder Quarters and expressed in experimentally E. coli-infected Udder Quarters Whey obtained from milk samples of dairy cows diagnosed with coliform mastitis (n = 7) were analyzed for the presence of CHI3L1. Rather than using an uncharacterized bovine ELISA, a previously characterized primary antibody against bovine CHI3L1 (31) was used for CHI3L1 detection in coliform-infected samples (n = 6). In five out of six coliform whey samples, it showed a strong signal by Western blotting while this 39-kDa protein band was absent in all whey samples obtained from bacteriologically negative quarter milk (n = 3) (Figure  1A ; Figure  S1  in Supplementary Material).
acKnOWleDgMenTs The authors gratefully acknowledge  L. Hulpio  and  A. De Visscher  ( Department of Obstetrics, Reproduction and Herd Health, Faculty of Veterinary Medicine, Ghent University ) for sampling milk of cows suffering from coliform mastitis. Furthermore, the authors thank  T. Wheeler  ( AgResearch ) for providing the anti-bovine CHI3L1 (which was produced by  Tanushree Gupta ,  Ric Broadhurst , and  Irina Boggs ),  L. De Bels  ( Department of Morphology, Faculty of Veterinary Medicine, Ghent University ) for the histological examination,  N. Van Herck  ( Department of Organic and Macromolecular Chemistry, Faculty of Science, Ghent University ) for the use of the ultrasone probe sonifier 450 and the technical assistance of  Men Choi  ( Department for Molecular Biomedical Research, VIB, Faculty of Sciences, Ghent University ) for the Procartaplex measurement.
2% complete, with 3,660 single-copy orthologs out of the 3,725 expected groups from the lineage Sordariomycetes data set. number SAMEA4778736 and BioProject accession number PRJEB27611). The PacBio reads are available in SRA under accession number ERP109716. The version described in this paper is the first version, UIHA01000000.
ACKNOWLEDGMENTS We thank  Philippe Lecomte  for preparing Fusarium graminearum DNA samples and the  GENTYANE INRA platform for the Sequel sequencing (Pacific Biosciences ). We also acknowledge  Antoine Mahul  and the  Mesocentre Clermont-Auvergne  for providing the computer calculation and storage facilities. This work is supported by the  Agence Nationale de la Recherche  ( NewMyco  project,  ANR-15-CE21-0010 ).
The ability of E. coli to grow in milk is highly correlated with the ability to cause mastitis  (13, 14) , and so to explore this hypothesis, we employed a proteomic approach to validate the production of FecA during growth in milk in vitro and a transcriptional approach to investigate the expression of fecA and fecB in vivo. In our in vitro experiment, we grew prototypical MPEC strain O32:H37 P4 in Dulbecco's modified Eagle's medium (DMEM) with and without the addition of citrate, and in ultra-heat-treated (UHT) milk, and investigated the proteins present in the outer membrane (OM) of the bacteria by mass spectrometry. These data show that the OM protein FecA could not be identified following growth in DMEM without the addition of citrate (0 peptides). With the addition of 0. 1 mM citrate, we could identify 10 peptides covering 20.
3% of the FecA protein sequence. With the addition of 10 mM citrate, we could identify 50 peptides, covering 67. 2% of FecA, and following growth in milk we could identify 63 peptides, covering 76% of the FecA protein sequence. These data are presented in Fig. 2A  as a function of the total number of peptides identified in the OM preparations. Remarkably, in UHT milk, peptides from FecA constituted almost 5% of the total number of identified OM peptides. The use of 10 mM citrate in this experiment reflects the concentration of citrate found in milk  (7). The list of all proteins identified is presented in Table  S2. In our in vivo experiment, we experimentally infected cows with MPEC strain P4 and measured the transcript level of the outer membrane receptor gene fecA and the inner membrane transport component gene fecB by reverse transcriptionquantitative PCR (RT-qPCR) in bacteria recovered from the milk at 6 h postinfection.
The numbers of data points per time point were 8 (P4 WT strain), 6 (strain P4 Δfec and strain K71 WT), and 4 (strain K71ϩfec). The stability of the Fec plasmid construct in transformed strain K71 was tested in vitro in a batch milk culture of this mutant grown up to 36 h. In this experiment, to check for any growth of K71 that was independent of the plasmid, bacterial counting was performed on agar with and without chloramphenicol. P4 WT and K71 WT were used as positive (high-growth) and negative (lower-growth) controls. Bovine intramammary challenge for RT-qPCR. Four Holstein-Frisian cows were challenged as previously described  (32). At 8 h postinoculation, 50 ml collected milk was mixed with 100 ml RNAProtect (Qiagen). The suspension was incubated at room temperature for 5 min and then centrifuged for 20 min at 5,000 ϫ g.
Due to the constraints imposed by the high cost of animal challenges, control data for strains P4 and wild-type K71 were taken from previous work  (15). We state explicitly that these strains were not used concurrently with their respective mutants; however, the experiments were conducted identically. Samples of milk from challenged glands were collected before milking and after 8, 16, 24, and 48 h. Teats were cleaned and disinfected, and foremilk was discarded. A sample of 3 ml of milk was collected aseptically into sterile tubes for bacteriologic culture. To detect contaminants, bacteriologic culture was performed by plating 100 l of milk on blood agar. E. coli counting was performed on MacConkey agar by CFU counting, following serial dilutions of milk with saline solution. Approximately 200 ml of milk was then collected for SCC determinations, and differentiation of leukocytes was evaluated as described previously  (3).
ACKNOWLEDGMENTS We acknowledge the support of  Shamai Jacoby  and the staff at the  Volcani Center experimental dairy  farm during animal experimentation. This work was funded by the  Biotechnology and Biological Sciences Research Council  (R. J. G. , D. G. E. S. , J. P. R. C. , and A. J. R. ) and the  Israeli Dairy Board  (S. E. B. , G. L. , and O. K. ).
To determine whether Kune loss of function affects the actin cable cell autonomously, we measured F-actin intensity in the plus wounds and compared en-Gal4-positive (Kune RNAi) with en-Gal4-negative (WT) regions of the cable. Interestingly, F-actin levels were not different between Kune RNAi and WT cells in the same wound (Fig. 6  G), suggesting that the effects of Kune loss of function on the actin cable are not cell autonomous. Altogether, these data indicate that SJs are not required for actomyosin cable function in a cell-autonomous manner, suggesting SJs do not directly target the cytoskeleton. This favors the hypothesis that the impact of SJs on cable contraction is a consequence of defects at the tissue level.
3% BSA + 0. 3% Triton X-100 in PBS), which was followed by primary antibody and probe incubation overnight at 4°C. The primary antibodies and probes used were mouse anti-Coracle C-terminal (1:500; Developmental Studies Hybridoma Bank), rabbit anti-GFP (1:2,000; Invitrogen), and Alexa Fluor 594-conjugated phalloidin (1:200; Invitrogen). Following incubation, embryos were washed in PBST, incubated in secondary antibodies conjugated to Alexa Fluor 488 or Alexa Fluor 568 (Invitrogen) for 2 h in blocking solution, washed in PBST, and mounted in 80% glycerol and 2% DAB CO (Sigma-Aldrich). Imaging was performed on an LSM 710 confocal microscope (Zeiss) with a 63× Plan Apochromat 1. 4 NA oil-immersion objective (Zeiss). Images were acquired using Zen software (Zeiss) and a step size of 0. 37 µm.
Neighboring cells and exchange events Maximum Z projections of E-cad::GFP-labeled embryos during the first 45 min after wound closure, acquired with a time interval of 2. 5 min, were used. An algorithm based on the invasion percolation of Ranked Surfaces  (Schrenk et al. , 2012)  was devised to segment cells using GNU Image Manipulation Program (GIMP) and MAT LAB (MathWorks), described as follows. First, a point inside the limits of every cell is marked manually. Each of these points is then uniquely identified as a cluster of pixels with a given label such that we have as many clusters as cells. All the nearest neighboring pixels of every cluster are added to a list of pixels and sorted according to their grayscale intensity. The first pixel of the list, the darkest one, is removed from the list and added to the same cluster of the neighboring pixel (meaning that it belongs to the same cell) identified with the proper label.
Acknowledgments We are indebted to  Nina Matova  for her insight and precious contributions; she will be remembered forever. We are grateful to  T. Pereira  for invaluable support on imaging and data analysis;  M. Behrndt  and  D. Siekhaus  for advice and technical help in laser-cutting experiments;  C. Crespo  and  F. Vasconcelos  for manuscript review; past and present members of the  Tissue Morphogenesis  and  Repair Lab  and  R. Teodoro  for helpful discussions and technical help;  C. Martins  for technical help; the microscopy facilities at  Chronic Diseases Research Center, Instituto de Medicina Molecular , and  Instituto Gulbenkian de Ciencia ; the  Bloomington Drosophila Stock Center  ( NIH P40OD018537 ), the  TRiP at Harvard Medical School  ( NIH/NIG MS R01-GM084947 ), the  Yale School of Medicine Flytrap project , and the  Kyoto Stock Center (Drosophila Genomics Resource Center)  for providing Drosophila lines.
This research was supported by  Fundação para a Ciência e a Tecnologia  ( SFRH/BPD/84569/2012  to  L. Carvalho ,  PD/ BD/106058/2015  to  S. Ponte ,  SFRH/BD/119240/2016  to  A. S. Nunes ,  UID/FIS/00618/2013 ,  PTDC/FIS-MAC/28146/2017 ,  PTDC/ BIA-BID/29709/2017  and  CON GEN TO ), the  European Research Council  ( 2007-StG-208631  and  ERC-2015-PoC-713735-EMO DI ), a  European Commission Marie Curie Intra-European Fellowship  ( PIEF-GA-2009-255573 ), the  Partenariat Hubert Curien Pessoa program  ( 30920XM ), the  European Science Foundation (Quantitative Models of Cellular and Developmental Biology Research Networking Program , grant  6839 ), and the iNOVA4Health Research Unit ( UID/Multi/04462/2013 ), cofunded by Fundação para a Ciência e Tecnologia, through national funds and by  FED ER  under the  PT2020 Partnership Agreement.
It has been nowadays accepted that sunflower stem canker is associated with a complex of Diaporthe species with different levels of pathogenicity. The main causal agent of the disease has been identified as D. gulyae sp. nov. in association with two less virulent species, D. kochmanii sp. nov. and D. kongii sp. nov. in Australia  [23] , whereas in the United States, D. gulyae and D. helianthi were both identified as causal agents of the disease having similar levels of aggressiveness  [24]. The highly virulent French isolate 7/96 can be referred as D. helianthi sensu stricto. A DNA region of 532 bp from this isolate, shared with all highly virulent strains but not with the Italian mildly virulent isolates, was identified and sequenced  [25]. This sequence, named lovB (accession number: AJ512137) showed a high similarity to genes encoding polyketide synthases (PKSs) from several species of filamentous fungi, including mlcA and mlcB of Penicillium citrinum, lovB of Aspergillus terreus, fum5 of Gibberella moniliformis, pks1 of Cochliobolus heterostrophus and pks1 of G.
helianthi 7/96 and annotated 40 genes coding for putative PKSs  [29]. By using the Pathogen-Host Interaction database (PHI-base) (http://www. phi-base. org) [30] , orthologs of genes known to be involved in biosynthesizing PKs, which are virulence factors in other fungal species, were identified. Furthermore, the role in virulence of the gene DhPHS1 (= D. helianthi polyketide synthase 1) was evaluated through a gene disruption approach.
Diaporthe helianthi strain 7/96 draft genome sequence v2 Based on raw data available from a previous project  [29] , we generated a new D. helianthi strain 7/96 genome assembly. Paired end reads of 90 bp (1. 80 Gbp) were assembled using SPAdes 3. 11. 0 [31]. The genome of D. helianthi consists of 7376 sequence scaffolds with a total assembly length of 63. 67 Mbp (N50 = 20,184 and L50 = 860), 43. 99% GC-content, and a maximum scaffold size of 151,286 bp. The completeness of the assembly was assessed using BUSCO v12  [32] , which estimated the genome sequence to be 99. 65% complete. The genome was annotated using the MAKER2 pipeline  [33]. Overall, 13,139 protein-coding gene models were predicted. The new genome assembly of D. helianthi strain 7/96 is present in GenBank with accession number: MAVT00000000.
Inoculated plants were kept in a moist chamber for 7 days at 24 °C. The bioassay was carried out on five plants for each fungal strain and was repeated twice. Data were analysed by ANOVA test with Welsch modification, because data were normally distributed but not homoscedastic. Different means were separated by T3 Dunnett test. Statistical analyses were performed by SPSS 20. 0 software.
PKS genes in Diaporthe helianthi genome By searching the draft nuclear genome of D. helianthi isolate 7/96  [29] , we found a large number of putative PKS homologues which have been deposited in GenBank (Additional file 1). Most PKS genes coded by D. helianthi were reducing PKSs, whereas only eight PKSs lacked reducing domains and clustered with nonreducing PKSs (Additional file 1). DhPKS8, DhPKS18, DhPKS27 proteins did not cluster into any of the clades indicated in Fig. 2. DhPKS1 was placed in nonribosomal peptide synthetase (NRPS)-PKS clade, with the closest sequence being ATEG_00325 protein from A. terreus involved in isoflavipucine biosynthesis.
and manually inspected for conserved domain (acyl transferase [AT] -InterPro domain IPR014043, acyl carrier protein or phosphopantetheine attachment site [ACP or PP] -IPR009081, beta-ketoacyl synthase N-terminal domain [KS-N] -IPR014030, beta-ketoacyl synthase C-terminal domain [KS-C] -IPR014031, Ketoreductase [KR] -IPR013968, polyketide synthase dehydratase [DH] -IPR020807, polyketide synthase, enoylreductase domain [ER] -IPR020843, methyltransferase [MT] -IPR013217, thioesterase [TE] -.
Discussion Bacterial vaginosis is a polymicrobial clinical syndrome in which Lactobacillus spp. , major constituents of "normal vaginal microbiota", are replaced by an overgrowth of non-beneficial anaerobic microbial species. This L. crispatus or GI (both 2 £ 10 7 /ml or 2 £ 10 8 /ml) were added to monolayer of A-431 or HeLa cells for 4 h at 37 C in anaerobic conditions. After incubation, cells were washed 2 times and microorganisms adhered were quantified as number of CFU/ml. Data are the mean § SEM from 2 independent experiments. Ã p < 0. 05, 2 £ 10 8 /ml (L. crispatus or GI) vs 2 £ 10 7 / ml (L. crispatus or GI). (B) Interference of L. crispatus or GI on G. vaginalis initial adhesion onto A-431 and HeLa cell lines. Two inocula (2 £ 10 7 /ml or 2 £ 10 8 /ml) of L. crispatus or GI were pre-adhered to epithelial cells, as above described, and subsequently G.
The genome sequence of T. peptonophilus OG-1 (GC%, core genome phylogeny) confirms previous reports that it may have been incorrectly placed in the Thermococcus genus and should instead be placed in the Pyrococcus genus. Strain P6 is most closely related to T. celer strain Vu 13 (1), as indicated by in silico DNA-DNA hybridization of their genomes (predicted value, 28. 90% using the genome-to-genome distance calculator GGDC version 2. 0  [14] ). This genomic distance suggests that strain P6 defines a novel species inside the Thermococcus genus. Accession number(s). This whole-genome shotgun project has been deposited in GenBank under the accession numbers CP014750, CP014751, CP014854, CP014855, CP014862, CP014863, CP015101 to CP015106, and CP015193.
ACKNOWLEDGMENTS This work was supported in part by the  Agence Nationale de la Recherche  ( ANR-10-BLAN-Living deep ) and by a grant from the  Fonds de Recherche of the ENS Lyon  to P. M. O. IonTorrent sequencing was performed in part at the sequencing platform of the  Institut de Génomique Fonctionelle de Lyon by Sandrine Hughes  and  Benjamin Gillet.
Statistical analysis Longitudinal analysis of tumor growth and bodyweight data was performed by linear mixed effect modeling on log pre-processed tumor sizes. Type II ANOVA (Wald tests) was used to compute p values by testing jointly that both tumor growth slopes and intercepts (on a log scale) were the same between treatment groups of interest https://kroe merlab. shinyapps. io/TumGrowth/. 40 For mice euthanized before the selected sampling point, the last measure was retained. Statistical significance of tumor vaccination experiment was assessed by means of the likelihood ratio test by means of TumGrowth software https://kroemerlab. shinyapps. io/TumGrowth/. 40 Analysis of mouse survival curves (log rank test) and of the effect of treatment on tumor size at a selected sampling point (unpaired t test) was performed by means of Graph Pad software.
Acknowledgments GK is supported by the  Ligue contre le Cancer  (équipe labellisée);  Agence National de la Recherche (ANR) -Projets blancs ;  ANR  under the frame of E-Rare-2, the  ERA-Net for Research on Rare Diseases; Association pour la recherche sur le cancer (ARC) ;  Cancéropôle Ile-de-France ;  Chancelerie des universités de Paris  ( Legs Poix ),  Fondation pour la Recherche Médicale (FRM) ; a donation by Elior; the  European Commission (ArtForce) ;  European Research Area Network on Cardiovascular Diseases  ( ERA-CVD, MINOTAUR ); the  European Research Council (ERC) ;  Fondation Carrefour; Institut National du Cancer (INCa) ;  Inserm (HTE) ;  Institut Universitaire de France ;  LeDucq Foundation ; the  LabEx Immuno-Oncology ; the  RHU Torino Lumière ; the  Seerave Foundation ; the  SIRIC Stratified Oncology Cell DNA Repair and Tumor Immune Elimination (SOCRATE) ; the  SIRIC Cancer Research and Personalized Medicine (CARPEM) ; and the  Paris Alliance of Cancer Research Institutes (PACRI).
Consequently, the GMO Panel considers that its previous conclusions on the safety of the single cotton events remain valid. The risk assessment of the three-event stack cotton included the molecular characterisation of the inserted DNA and analysis of protein expression. An evaluation of the comparative analysis of compositional and agronomic/phenotypic characteristics was undertaken, and the safety of the newly expressed proteins and the whole food/feed was evaluated with respect to nutritional characteristics and potential toxicity and allergenicity. An evaluation of environmental impacts and post-market environmental monitoring plans was also carried out. The molecular data establish that the events stacked in cotton GHB614 9 LLCotton25 9 MON 15985 have retained their integrity. Protein expression analyses showed that the levels of the newly expressed proteins are similar in the three-event stack and the single events.
3. 4. Comparative analysis 12 3. 4. 1. Choice of comparator and production of material for the comparative assessment 13 Application EFSA-GMO-NL-2011-94 includes data on agronomic and phenotypic characteristics of cotton and compositional data on ginned cottonseeds (fuzzy seeds). The data were collected from field trials performed in the USA. The field trials included the three-event stack cotton GHB614 9 LLCotton25 9 MON 15985, the non-GM comparator FiberMax958 (FM958) and the three single events GHB614, LLCotton25 and MON 15985. The non-GM comparator FM958 had a similar genetic background to the three-event stack and was considered an appropriate comparator by the GMO Panel. The field trials were conducted during the 2008 growing season in seven locations in the southerneastern USA 14 in typical cotton-growing regions.
events: GHB614 (untreated), GHB614 (treated with the target herbicides), LLCotton25 (untreated), LLCotton25 (treated with the target herbicides) and MON 15985 (untreated). The GMO Panel took into account the full data set provided, including the results for the three single events. In the following sections, only the results for the three-event stack and the non-GM comparator are discussed. 3. 4. 2. Agronomic and phenotypic analysis 17 3. 4. 2. 1. Agronomic and phenotypic characteristics tested under field conditions In total, 29 agronomic and phenotypic endpoints were measured, related to plant growth and morphology at different life stages, reproduction, agricultural productivity, fibre properties and disease susceptibility. 18  In order to test for differences between the three-event stack cotton and the non-GM comparator, an analysis of variance (ANOVA) was applied across the field trial sites.
Compositional analysis 21 Comparative compositional analysis was performed on fuzzy cottonseed samples obtained from cotton GHB614 9 LLCotton25 9 MON 15985 and the non-GM comparator FM958 grown in the USA field trials in 2008. Samples were analysed for 66 compositional parameters, selected in line with OECD recommendations  (OECD, 2009). Eighteen fatty acids had most of the sample values below the limit of quantification (LOQ) and were not analysed statistically. 22 The data for the remaining 48 compounds 23  were analysed with ANOVA, in order to test for differences between the three-event stack cotton and the non-GM comparator. 16  Significant differences in fuzzy cottonseed (with maintenance management treatment only; 'Untreated', Table  6 ) were identified for 10 endpoints. Significant differences in fuzzy cottonseed (treated with the target herbicides; 'Treated', Table  6 ) were identified for 14 endpoints.