dataesr/scientific-paragraphs-categorization huggingface dataset:
However, reduced odds of disease remained significantly associated with a history of vaccination for CPIV, CAV-2 or CDV with an independent effect of reduced odds of disease in shelter dogs and dogs from other sources compared with client-owned dogs (Table  2 ). Further examination of the vaccination effect indicated that the proportion of dogs with a history of vaccination against CPIV, CAV-2 and CDV reduced significantly as the severity of disease increased (Fig. 1 ). 3. 3. Significant variations in pathogen seroprevalence were associated with country, source, age, antibody status and clinical group, but varied by the pathogen studied Significant univariable variations in CRCoV seroprevalence were detected by country, age, source, disease status, clinical score, and CnPnV seropositivity (data not shown).
cynos or its relationship with clinical disease. However it is worth considering the limitations of the study which may have influenced this finding. Firstly, several mycoplasma species are carried by dogs, often as part of their normal respiratory flora  (Chalker, 2005) , however very limited data is available regarding their serological cross-reactivity  (Rosendal, 1975). The possibility exists therefore that the use of whole cell ELISA antigen in this study may have resulted in an overestimate in M. cynos seropositivity. Secondly, oropharyngeal swabs collected as part of a standard veterinary investigation of CIRD were analysed. Previously respiratory tissues were shown to yield a much higher recovery rate of M. cynos (99. 7-23. 9%) compared to oropharyngeal swabs (0-0. 9%) (Chalker et al.
Acknowledgements Sample collection and analysis for CRCoV, M. cynos and influenza A virus was funded by  Zoetis Animal Health. Screening for canine pneumovirus was supported by a grant awarded to  Judy A. Mitchell  and  Joe Brownlie  by the  Petplan Charitable Trust. The authors would also like to thank  C. Murrell  and  Y. Alver  for technical assistance, and  L. Harbour  for administrative support.
Immunofluorescence. For immunofluorescence experiments, cells were fixed by freezing methanol for 15 min at RT, permeabilized with Triton-X 100 (0, 4% in PBS) for 5 min at RT, treated with Glycin (100 nM) in PBS for 2 min at RT and blocked with 10% FCS in PBST for 1 h at 37 °C. Samples were incubated with C2IN antibody (rabbit) (1:1500 diluted in 10% FCS in PBST) for 1 h at 37 °C. After washing, fluorescence-labeled secondary antibody anti-rabbit 647 (donkey) (Thermo Fisher Scientific) was added (1:500 diluted in 10% FCS in PBST) for 1 h at 37 °C. Fluorescence imaging was performed using the iMic Digital Microscope (FEI Munich) using the Live Acquisition 2. 6 software (FEI Munich) and processed with ImageJ 1. 4. 3. 67 software (National Institutes of Health, Bethesda). The average cytosolic C2I labeling was determined from plot profile lines across individual cells in background-corrected images (Image J 1.
4. 3. 67, Fig. 5a  and b ). Plot profile data were exported into Matlab V9. 0 (The MathWorks) for the identification and exclusion of endosomal peaks (see Fig. 5c ). The area under the curve (AUC) of plot profile minima was taken as a measure of cytosolic labeling (see blue circles and area in Fig. 5c ). Minima were determined by the slope at the roots of the first derivative of spline filtered plot profiles. AUCs were corrected for the length of the plot profile line (AUC/length) to obtain the cytosolic C2I density (Fig. 5c ).
2% Triton X100 in PBS) and treated with antibodies against CDTa and E-cadherin over night at 4 °C. Fluorescence-labeled secondary antibodies in 5% goat serum and 0. 1% Triton X100 in PBS were added for 1 h at RT. Moreover, nuclei were stained with DAPI and F-actin with phalloidin-FITC. Confocal microscopy was performed. Quantitative analysis of the effect of CDT on E-cadherin organization was performed by determining four categories of degree of disorganization of E-cadherin structure. Examples for the different categories are given. Data were collected from two individual experiments (n = 2, at least 28 pictures per sample were analyzed) and blinded analysis of each experiment was performed by two individual persons.
Acknowledgements The work was supported by the  DFG  ( BA2087/2-2  to H. B. ) and the  Medical Faculty Ulm (Baustein 3. 2 to K. E. ). M. Beck  and  M. Hägele  are members of the  International Graduate School in Molecular Medicine Ulm (IGradU)  and thank  IGradU  for the support. We thank  Jonathan Häberle  for developing a software for quantifying PLA fluorescence signals,  Carsten Schwan  and  Alexander E. Lang  for providing CDTa, CDTb and HisTccC3hvr and  Stefan Liebau  for helping us with generation of iPS cells.
Acknowledgements We thank  Drs S. Viengchareun  for his help in performing luciferase assays and  J. Fagart  for discussion on GR structure. We thank  N. Ba  from  Plateau de morphologie at Institut Biomedical de Bicêtre  for preparing mouse pituitary slices and  Dr C. Adam  for the histological interpretations. We thank  C. Denoyelle  and  F. Petit  for their technical help as well as  J. A. Girault  who allowed us to use his ultracentrifuge (Beckman) at  Institut du Fer à Moulin (Paris). This work was supported by the  Institut National de la Santé et de la Recherche Médicale (INSERM)  and the  University Paris Sud  (Attractivity 2015 grant). M. A. is supported by a  doctoral fellowship  from the  Ministère de l'Enseignement Supérieur et de la Recherche (MESR).
Tertiary Models and Protein-Protein Docking The active A. phagocytophilum HSP70 and MSP4 proteins were modeled using I-TASSER  (Zhang, 2008) , and the unbound (apo)-HSP70 protein was modeled using Robetta  (Kim et al. , 2004). All tertiary models were optimized with the Schrödinger's Maestro Protein Preparation Wizard  (Li et al. , 2007). All steric clashes were resolved via minimization with the default settings in the Schrodinger's Maestro package. For the tertiary models, the Protein Preparation Wizard clusters at the highest degree of hydrogen bonding in equilibrium were used. Monte Carlo orientations were performed (100,000) for each cluster. The optimized structure is based on electrostatic and geometric scoring functions. The membrane positioning for MSP4 was calculated by the OPM database  (Lomize et al.
Three epitopes from HSP70 (FNDAQRQATKDAGTI, AGIKDNSKV and SNCSTDTLQQ) aligned without gaps to regions of MSP4 (FVAVGRDATLTPDNF, AGIPASNRV and AVCACSLLIS), with 26, 44, and 20% identity, respectively. These results suggested that antibodies against MSP4 epitopes (i. e. , DGATGYAI) could cross-react with a region of HSP70 (DGQTAVTI), thus explaining the anti-HSP70 response in MSP4-immunized lambs. Furthermore, these epitopes were highly conserved because A. phagocytophilum MSP4 and HSP70 protein sequences show a high homology between different strains (Supplementary Figures  2B-D ). In 56 of the MSP4 sequences available containing this region, the B-cell epitope was conserved (Supplementary Figure  2D ). This region was conserved in all HSP70 sequences available in GenBank (Supplementary Figure  2D ).
FUNDING This research was partially supported by the  Ministerio de Economia, Industria y Competitividad (Spain)  grants  AGL2014-56305  and  BFU2016-79892-P , the  European Union  ( EU) Seventh Framework Programme  ( FP7 )  ANTIGONE  project number  278976 , and the  CSIC  grant  201440E098  to  Jd. MV  and LM were supported by the  Research Plan of the University of Castilla-La Mancha  ( UCLM ),  Spain. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
In brief, 1. 5 μL of matrix solution containing diluted α-cyano-4-hydroxycinnamic acid in 500 μL acetonitrile, 250 μL 10% trifluoroacetic acid and 250 μL HPLC water was deposited on each spot for ionization and crystallization. All protein spectra obtained were compared with those of the MALDI-TOF database. If the score was greater than or equal to 1. 9, the strain was considered identified. Otherwise, the identification failed. When MALDI-TOF MS failed, bacterial identification was performed using 16S rRNA gene PCR amplification in combination with sequencing as previously described  [11]. Strain ND3 T exhibited 92. 4% of 16S rRNA gene sequence similarity with Sutterella wadsworthensis strain SW4, which is the phylogenetically closest species with a validly published name  [12]. As Stackebrant  [13]  suggested, if the 16S rRNA gene sequence similarity value was lower than 98.
7% or 95%, the strain was defined as a new species or genus respectively, without performing DNA-DNA hybridization  [14]. Phylogenetic analysis was performed by comparing the 16S rRNA gene sequences obtained from other Sutterellaceae family members. Sequences were aligned using CLUSTALW, and phylogenetic references were obtained using the maximum-likelihood method within the MEGA software (Fig. 1 ). The MALDI-TOF MS analysis of proteins was also performed, as previously described, to generate a reference spectrum. Spectra from 12 individual colonies of strain ND3 T were compared and a reference spectrum generated (Fig. 2 ). Different growth temperatures (25, 30, 37 and 45°C) were tested. Growth was observed after 24 hours of inoculation FIG. 1. Phylogenetic tree highlighting position of 'Dakarella massiliensis' strain ND3 T relative to other type strains within Sutterellaceae family.
Genome annotation Open reading frames (ORFs) were predicted using Prodigal  [22]  with default parameters. However, the predicted ORFs were excluded if they spanned a sequencing gap region. The predicted bacterial protein sequences were searched against the GenBank  [23]  and Clusters of Orthologous Groups (COGs) databases using BLASTP. The tRNAs and rRNAs were predicted using tRNAScan-SE  [24]  and RNAmmer  [25]  tools respectively. Signal peptides and numbers of transmembrane helices were predicted using SignalP  [26]  and TMHMM  [27]  respectively. Mobile genetic elements were predicted using PHAST  [27]  and RAST  [28]. ORFans were identified if their BLASTP E value was lower than 1e-03 for alignment length greater than 80 amino acids. If alignment length was smaller than 80 amino acids, we used an E value of 1e-05.
Such parameter thresholds have already been used in previous works to define ORFans. Artemis  [29]  and DNA Plotter  [30]  were used for data management and visualization of genomic features respectively. The Mauve alignment tool (version 2. 3. 1) was used for multiple genomic sequence alignment  [31]. The mean level of nucleotide sequence similarity at the genome level between 'Dakarella massiliensis' strain ND3 T and other bacteria was estimated using the average genomic identity of orthologous gene sequences (AGIOS) homemade software. This software can combine with others: Proteinortho (to detect orthologous proteins between genomes compared two by two, and then retrieve the corresponding genes) and the Needleman-Wunsch global alignment algorithm (to determine the mean percentage of nucleotide sequence identity among orthologous ORFs).
COGS, Clusters of Orthologous Groups database. Alicycliphilus denitrificans to 60. 00 between Comamonas badia and Alicycliphilus denitrificans. The genomic similarity of strain ND3T with species of Comamonadaceae family was also evaluated by two parameters: DNA-DNA hybridization (DDH) and AGIOS  [32] [33] [34]. The values found in DDH and AGIOS of 'Dakarella massiliensis' are in the range of those observed in the other genera of this family (Table  6 ).
9 μm. Positive for phosphatase alkaline, esterase (C4), esterase lipase (C8), lipase (C14), leucine arylamidase, valine arylamidase, trypsine, α-chymotrypsin, phosphatase acid, naphtol phosphohydrolase, α-galactosidase, α-galactosidase, β-glucosidase, α-mannosidase, D-galactose, D-glucose, esculin, salicin, D-cellobiose, D-maltose, D-lactose, D-saccharose, D- trehalose, D-raffinose, amidon, glycogen, D-turanose, D-tagatose, glycerol and arginine arylamidase. Strain ND3 T is susceptible to penicillin, amoxicillin, amoxicillin-clavulanate, ceftriaxone, imipenem, ciprofloxacin, clindamycin, doxycycline, erythromycin, gentamicin, metronidazole and rifampicin but resistant to trimethoprim-sulfamethoxazole and vancomycin. The 16S rRNA gene and genome sequences were deposited in GenBank under accession numbers LK054638 and CVTY00000000.
62 Nucleotide transport and metabolism H 77 3. 54 Coenzyme transport and metabolism I 58 2. 67 Lipid transport and metabolism P 113 5. 20 Inorganic ion transport and metabolism Q 27 1. 24 Secondary metabolites biosynthesis, transport and catabolism R 260 11. 96 General function prediction only S 118 5. 43 Function unknown - 171 7. 87 Not in COGs COGs, Clusters of Orthologous Groups database. a.
Analysis of interview data Interviews were audio-recorded, transcribed in the native language and cross-checked for accuracy by researchers against the recordings. Participants were able to request to comment on the transcript if they wished; none did so. All data were analysed using the same thematic analysis. 13 mmediately after individual interviews, interviewers summarised key themes to inform the analysis coding frame. Two researchers in each country identified and agreed initial and strong themes. England and France used QSR NVivo V. 10 software to organise data into themes; other countries used Excel spreadsheets. After the researchers in each country had undertaken at least several interviews and agreed initial themes, a high level thematic and coding framework was agreed by all researchers at a teleconference.
strenGths AnD lIMItAtIOns We included countries that varied in their chlamydia control programmes from little testing in primary care in France to an established NCSP in England. 1  We spoke to different GP staff, trainers and stakeholders, gaining a wide range of opinions about facilitators and barriers to delivering sexual health services and training in primary care across four countries. However, to facilitate implementation in other countries, further needs assessment may be needed to inform any further training modifications in that country. The study could have included more participants from each country to enrich the data and possibly find more facilitators or barriers to the Open Access intervention; however, the data was very consistent and we did reach data saturation in each country.
Acknowledgements We wish to thank the  National Chlamydia Screening Programme (NCSP)  and wider project group in England, especially  Kevin Dunbar ,  John Saunders ,  Anthony Nardone  and  Thomas Hartney , and all members of the 3Cs &  HIV  Project  Group  ( Deborah Shaw  and  Sharron Ainslie ). Also, the 3Cs & HIV Advisory Group in England ( Sebastian Kalwij ,  Farah Paruk ,  Farhana Lockhart ,  Jane Wilkinson ,  Jason Warriner ,  Richard Ma ,  Suzie Clements  and  Vicki Courage ). We wish to thank  Kaia Enni  and  Tatjana Meister  from Estonia. We thank  Anne Lennell ,  Timmy Leijen ,  Johan Hedlund  and  Johanna Haraldsson  for important contributions in the adaption of the Swedish model of CATTE. We wish to thank  Sanne Veringa  and  Soline Detanne  for their important work on the  CATTE  project in France.
We collected B. glabrata proteins from snail conditioned water (SCW) and following electrostimulation (ES), which induces rapid release of proteins. The detection by NanoHPLC-MS/MS of an orthologue of temptin, a pheromone of Aplysia 12 , among these proteins (Supplementary Note 5; Supplementary Data 10) suggests an operational pheromone sensory system in B. glabrata. To explore mechanisms for chemosensory perception, the B. glabrata genome was analysed for candidate chemosensory receptor genes of the G-protein-coupled receptor (GPCR) superfamily. We identified 241 seven transmembrane domain GPCR-like genes belonging to fourteen subfamilies, that cluster in the genome. RT-PCR and in situ hybridization confirmed expression of a GPCR-like gene within B. glabrata tentacles, known to be involved in chemosensation (Fig.
glabrata. The HSP70 gene family is the largest with six multi-exon genes, five single-exon genes, and over ten pseudogenes (Supplementary Figs 14-17; Supplementary Note 9; Supplementary Data 13). In general, it is anticipated that future genome assemblies and continued annotation efforts can identify additional B. glabrata genes and provide updated gene models to reveal that some current pseudogenes are in fact intact functional genes. The existence of a single-exon HSP70 gene, however, was independently confirmed by sequence obtained from B. glabrata BAC clone (BG_BBa-117G16, Genbank AC233578, basepair interval 49686-51425) and this supports the notion that prediction of single exon gene models for several HSP70 genes from the current genome assembly is accurate. Retention of HSP genes in B.
4 ). Highly conserved components of the molluscan shell forming toolkit include carbonic anhydrases and tyrosinases  33   51. Paired end reads from a 300 bp insert library (53. 42 Â coverage) were collected using Illumina instrumentation and assembled de novo using SOAP (v1. 0. 5)  52. The Newbler assembly was merged with the SOAP assembly using GAA  53  (see Supplementary Data 1 for accession numbers of sequence data sets). Redundant contigs in the merged assembly were collapsed and gaps between contigs were closed through iterative rounds of Illumina mate-pair read alignment and extension using custom scripts. We removed from the assembly all contaminating sequences, trimmed vectors (X), and ambiguous bases (N). Short contigs (r200 bp) were removed prior to public release. In the creation of the linkage group AGP files, we identified all scaffolds (145 Mb total) that were uniquely placed in a single linkage group (Supplementary Note 2; Supplementary Data 2).
Biomphalaria -snail; Crassostrea gigas-oyster; Haliotis iris-abalone;, Hirudo medicinalis -leech (all lophotrochozoans); Amphimedon queenslandica, sponge, Prebilateria, ophotrochozoans), Drosophila melanogaster-fruit fly, Ecdysozoa), and the deuterostomes Ciona intestinalis, sea squirt; Homo sapiens, human. See Supplementary Note 31 for accession numbers.
56kb. The assembly spans over 916 Mb (with a coverage of 98%, 899 Mb of sequence with B17 Mb of estimated gaps). The draft genome sequence of Biomphalaria glabrata was aligned with assemblies of Lottia and Aplysia (http://biology. unm. edu/biomphalariagenome/synteny. html) and deposited in the DDBJ/EMBL/GenBank database (Accession Number APKA00000000. 1). It includes the genomes of an unclassified mollicute (Supplementary Note 7; accession numbers CP013128). The genome assembly was also deposited in Vectorbase54(https://www. vectorbase. org/organisms/biomphalaria-glabrata). Computational annotation using Maker2 (ref. 9)yielded14,423predicted gene models, including 96. 5% of the 458 sequences from the CEGMA core set of eukaryotic genes55. Total RNA was extracted from 12 different tissues/organs dissected from several individual adult BB02 B.
glabrata snails (shell diameter 10-12 mm; between 2 and 10 snails per sample to obtain sufficient amounts of RNA). RNA was reverse transcribed using random priming, no size selection was done. Illumina RNAseq (paired ends) was used to generate tissue-specific transcriptomes for albumen gland (AG); buccal mass (BUC); central nervous system (CNS); digestive gland/hepatopancreas (DG/HP); muscular part of the headfoot (FOOT); heart including amebocyte producing organ (HAPO); kidney (KID); mantle edge (MAN); ovotestis (OVO); salivary gland (SAL); stomach (STO); terminal genitalia (TRG), see Supplementary Data 1 for accession numbers of sequence data sets. RNAseq data were mapped to the genome assembly (Supplementary Note 3). No formal effort was made to use the RNA-data to systematically enhance the structural annotation.
Acknowledgements We thank  S. Newfeld  for discussion of actin evolution;  N. El Sayed  and  H. Tettelin  for discussion of HSP annotation and expression. We acknowledge access to the Metafer microscopy system at the  I. Robinson Research Complex, Harwell, Rutherford Appleton Laboratory, Oxon, UK  ( BBSRC Professorial Fellowship , grant number  BB/H022597/1 ). Sequence characterization of the Biomphalaria glabrata genome was funded by  NIH-NHGRI  grant  HG003079  to  R. K. W. ,  McDonnell Genome Institute ,  Washington University School of Medicine. Biomphalaria glabrata and Schistosoma mansoni were provided to some participating labs by the  NIAID Schistosomiasis Resource Center (Biomedical Research Institute, Rockville, MD)  through  NIH-NIAID  Contract  HHSN272201000005I  for distribution through  BEI Resources.
K. F. H. and M. T. S. acknowledge  BBSRC  ( BB/K005448/1 ). B. G. acknowledges  ANR JCJC INVIMORY  ( ANR-13-JSV7-0009 ). S. E. acknowledges  NIAID  contract  HHSN272201400029C. J. M. K. acknowledges the  Research Council for Earth and Life Sciences  (A. L. W. ;  819. 01. 007 ) and the  Netherlands Organization for Scientific Research (NWO). R. M. C. acknowledges  NIH   GM061738  and support from the  American Heart Association ,  Southwest Affiliate  ( 14GRNT20490250 ). D. T. acknowledges  NIH   R25 GM075149. C. F. acknowledges  NIH   R01-GM077582. D. J. J. acknowledges D. F. G. JA2108/1-2. M. de S. G. acknowledges  CNPq 479890 /2013-7. K. M. B. and J. P. R. acknowledge  NSERC 312221  and  CIHR MOP74667. C. S. J. , L. R. N. , S. J. , E. J. R. , S. K. and A. E. L. acknowledge  NC3R GO900802/1.
K. K. B. and K. B. S. acknowledge  NSERC 315051  and  6793 , respectively. M. B. and C. J. B. acknowledge  NIH   RO1-AI109134. C. J. B. acknowledges  NIH   AI016137  and  AI111201. B. R. acknowledges  NHGRI 4U41HG002371. P. C. H. , M. A. G. and E. A. P. acknowledge  NSERC 418540. O. L. B. and Ch. C. acknowledge  ANR-12-EMMA-0007-01. S. F. C. acknowledges  Australian Research Council   FT110100990.
VectorBase did, however, make this RNAseq data available in WebApollo56such that the community could use these data to correct exon-intron junctions, UTRs, etc. through community annotation. All of these community-based updates have been incorporated and are available via the current VectorBase gene set. Repeat features were analyzed and masked (Supplementary Note 32; see Vectorbase Biomphalaria-glabrata-BB02_ REPEATS. lib, Biomphalaria-glabrata-BB02_REPEATFEATURES_BglaB1. gff3. gz). Further methods and results are described in the Supplementary Information. Data availability. The sequence data that support the findings of this study have been deposited in GenBank with the accession codes SRX005826, -27, -28; SRX008161, -2; SRX648260, -61, -62, -63, -64, -65, -66, -67, -68, -69, -70, -71; SRA480937; SRA480939; SRA480940; SRA480945; TI accessions2091872204-2092480271; 2104228958-2104243968; 2110153721-2118515136; 2181062043-2181066224; 2193113537-2193116528; 2204642410-2204763511; 2204820860-2204852286; 2213009530-2213057324; 2260448774-2260450167.
RON4 L1 is a new rhoptry neck protein. Transcriptomic and proteomic datasets in ToxoDB indicate that RON4 L1 is expressed in tachyzoite, bradyzoite and sporozoite stages, as well as in the cat enteroepithelial stage (www. Toxodb. org). Like RON8, RON4 L1 is a coccidian-specific protein. RON4 L1 shows 13% identity and 21% similarity with RON4 (Fig. S1 ): RON4 L1 is noticeably longer than RON4, and essentially homologous to its C-terminal region. RON4 L1 is a 1981 amino acids long protein, with a predicted molecular mass of 216 kDa. Besides a predicted signal peptide, no transmembrane domain or any other known recognized domains can be identified. To localize RON4 L1 , we first tagged the protein with a triple hemagglutinin tag (HA 3 ) at the C-terminal end, by single recombination at the endogenous locus, as described previously  24  and represented in Fig.