dataesr/scientific-paragraphs-categorization huggingface dataset:
Mitochondrial protein predictions A multipronged approach was used to predict mitochondrial proteins. (1) Each gene model and translated transcript was queried for N-terminal mitochondrial targeting sequences using Mitoprot and TargetP  [125, 126]. Sequences that returned a score greater than 0. 5 were further investigated as MRO candidates. (2) The top 10 BLAST hits retrieved from the nr database at NCBI were surveyed for any mitochondrial annotation and manually investigated. (3) All gene models and translated transcripts were queried against a local curated MitoMiner data set  [127]  and significant hits (e-value < 1e-10) were further investigated. (4) Finally, a local MRO protein data set from various anaerobic protists including Pygsuia biforma, T. vaginalis, and Mastigamoeba balamuthi was queried against the gene models and translated transcript data sets.
Cell cycle Homologs of proteins suspected to be involved in cytokinesis were identified by BLASTp against the Blastocystis ST1 predicted proteome (e-value cutoff: 10e-10), using as queries previously identified mammalian orthologs  [128]. Absence of homologs was verified by tBLASTn against the genomic scaffolds and transcriptome. Blastocystis hits were then used as queries to run reversed BLASTp searches against nr and results were manually inspected to confirm assignation to a given protein family. Identification of homologs of the APC/C complex and targets was carried out in a similar fashion, using as queries previously identified homologs in Blastocystis ST1 or, if these did not exist, various other eukaryotic homologs  [78]. For calcium-binding proteins, H. sapiens homologs of protein families identified in  [129]  were used as queries to carry out BLASTp searches against the Blastocystis ST1 predicted proteome but also against all eukaryotic protein data present in GenBank as of February 2016 ("Eukaryota[Organism]" option of the BLAST+ package).
DNA repair and meiosis A query database including 135 DNA repair genes, meiosis-specific genes, and meiosis-related genes from a wide range of eukaryotes was established using literature and key word searches of the NCBI database. Genes with functional experimental evidence were used as queries to retrieve similar proteins using PSI-blast. After retrieval, protein sequence alignments were created and used to build HMM profiles with HMMER3. 1b2 [130]  to enable gene searches in Blastocystis STs 1, 4, and 7. Retrieval of genes was restricted to e-values below 1e-04. Phylogenetic trees were constructed with FastTree  [131]  using closely related paralogs and/or reconstructing entire gene families for each gene of interest. Protein domains were mapped to the trees to facilitate gene recognition.
Kinome analysis 221 kinases were identified from the protein-coding gene set of Blastocystis ST1 using HMMER  [130]. The STYKc profile (SM00221) from the SMART database  [132]  was used, as was the Pfam Pkinase profile (PF00069)  [119]. Blastocystis kinases were classified by their positions in phylogenetic trees inferred from the alignments of the HMMER output (both neighbor joining and maximum likelihood trees were taken into consideration). Blastocystis gene models with 2 kinase domains were classified by the phylogenetic position of the domain with a better HMMER score. The kinase classification follows the webite www. kinase. com [33]. The 221 kinases identified from Blastocystis ST1 were used to query the protein-coding gene sets from STs 4 and 7. The annotations for STs 4 and 7 were also searched for the key word "kinase" and putative protein kinases were checked against the kinase database (www.
major CYP51E1, Monosiga brevicollis CYP51A1, T. pseudonana CYP51C1, and Chlamydomonas reinhardtii CYP51G. CYP searches for other organisms were done as above but using NCBI, CYPED (https:// cyped. biocatnet. de/), and the eukaryotic pathogen database EuPathDB (http://eupathdb. org/ eupathdb/)  [137] [138] [139].
Peroxisomal machinery To identify putative PEX genes in Blastocystis STs 1, 4, and 7, protein sequences from H. sapiens, S. cerevisiae, and/or Neurospora crassa were used as queries for BLASTp and tBLASTn searches against locally hosted Blastocystis protein sequences and scaffolds, respectively. Candidate homologs with e-values less than or equal to 0. 05 were subjected to reciprocal BLASTp searches against the locally hosted query genome as well as the locally hosted nr database. The retrieval of the original query as the top reciprocal BLASTp hit with an e-value less than or equal to 0. 05 was the criteria for identification of a putative homolog. To identify putative PEX genes in A. thaliana and the stramenopile genomes of P. ramorum, T. pseudonana, and P. tricornutum, H. sapiens, S. cerevisiae, and/or N.
crassa protein sequences were used as queries for pHMMer  [145]  searches against locally hosted query genomes. Candidate homologs with e-values less than or equal to 0. 05 were subjected to reciprocal pHMMer searches against the locally hosted genome and NR database. Thus, the retrieval of the original query as the top reciprocal pHMMer hit with an e-value less than or equal to 0. 05 was the criteria for identification of a putative homolog. Results were compared to previously listed PEX genes in A. thaliana  [146]  and P. tricornutum  [68]. Newly identified A. thaliana, P. ramorum, T. pseudonana, and P. tricornutum PEX genes were subsequently used as queries for BLASTp and tBLASTn searches against locally hosted Blastocystis protein sequences and scaffolds, respectively. Candidate homologs were subjected to reciprocal BLASTp searches according to the criteria described above.
Identification and analysis of CAZymes The CAZy annotation pipeline was used to analyze 5,966 predicted proteins from the Blastocystis ST1 genome using a 2-step procedure of identification and annotation  [147]. Sequences were subjected to BLASTp analysis against the CAZy database, composed of full-length proteins. Hits with an e-value <0. 1 were then subjected to a modular annotation procedure using BLASTp against libraries of catalytic and carbohydrate binding modules and profile HMMs  [148]. The results were complemented with signal peptide, transmembrane, and glycosylphosphatidylinisotol (GPI) anchor predictions  [149, 150]. Fragmentary gene models and all models suspected of containing errors were identified and flagged. A final functional annotation step involved performing BLASTp comparisons against a library of protein modules derived from biochemically characterized enzymes  [147].
Three other stramenopile species, the diatom T. pseudonana, and the oomycetes, Albugo laibachii Nc14 and P. infestans T30-4, are present in the CAZy database and were used for comparison. The predicted CAZymes encoded by the genome of the brown alga Ectocarpus siliculosus (http://bioinformatics. psb. ugent. be/orcae/ overview/Ectsi) were also annotated using the same procedures for comparison with other stramenopiles.
Flagellar-associated proteins A reciprocal best BLAST analysis was performed for the protein data sets from Blastocystis ST1 and C. reinhardtii using the program orthoparahomlist. pl with default settings (Stanke M. Orthoparahomlist. pl script. 2011. https://github. com/goshng/RNASeqAnalysis/blob/master/ pl/orthoparahomlist. pl). The resulting list of orthologs was compared against the 213 C. reinhardtii conserved ciliary proteins  [153]  to determine which of the orthologs found in Blastocystis ST1 had matches.
GTPases Members of the Ras superfamily were searched for in the 3 Blastocystis genomes using wellcharacterized representative sequences from other eukaryotes (H. sapiens, P. sojae, and others) as queries. Both the databases of predicted protein sequences (using BLASTp) and the genome sequence assemblies (using tBLASTn) were searched to ensure that no gene was missed because of the lack of a corresponding protein prediction. Indeed, a number of genes that were missing in the protein sequence databases were identified in all 3 STs. The missing or inaccurate gene models in ST1 were manually predicted or corrected using various lines of evidence (transcriptomic data and comparisons to homologs) and incorporated into the main genome annotation. Models missing for the ST4 and ST7 genomes were constructed only when the phylogenetic relationship to ST1 genes was unclear from the tBLASTn searches.
Inductive data structuring The interviews were then integrally transcribed and we structured the resulting scripts using the Nvivo qualitative analysis software. Taking one interview after the other, in random order, we coded the learning mechanisms in the inductive way characteristic of conventional coding  (Hsieh, H. E. and Shannon, S. E. 2005). Consequently, there was no previously defined list of nodes to be used. Each time the interviewee talked about how he learned something, we coded this excerpt of the text with a short expression describing "how the farmer learned". We used words that were as close as possible to the farmer's, while also trying to choose an expression not too specific to one particular excerpt, so that it could be re-used to code other parts of interviews dealing with the same mechanism.
| Species distribution data and climatic maps Data on the world-wide distribution of the 34 alien garden plants and their 173 native and naturalized congeners were taken from GBIF. All species lists were taxonomically harmonized using The Plant List (http://www. theplantlist. org). Multiple occurrences within 10′ × 10′ grid cells and clearly erroneous records, that is those in water bodies, were removed. We did not limit records to those from the native range because species are known to partly expand their realized climatic niches in the naturalization range  (Dellinger et al. , 2016; Early & Sax, 2014; Petitpierre et al. , 2012). Quarter, BIO18-Precipitation of Warmest Quarter. All these variables are known to potentially influence species distributions  (Root et al. , 2003). All climatic variables were provided by wORLdcLim at a spatial resolution of 10 min.
| Species distribution models We used the biOmOd2 pl atform (Thuil l er, Lafourcade, Engl er, & Araujo, 2009) in R (R Core Team, 2015) to quantify species' climatic niches and subsequently project current and future spatial distributions. The following modelling algorithms were used: generalized linear model (GLM), general additive model (GAM), boosted regression tree (BRT) and random forest (RF). For applying these species distribution models (SDMs) with presence-only data as provided by GBIF, we generated "pseudo-absences" following recommendations of Barbet-Massin, Jiguet, Albert, and Thuiller (2012): for regression technique models (GLM and GAM), we used 10,000 randomly distributed absences, and for machine-learning technique models (BRT and RF), we used a number of pseudo-absences equal to the number of occurrences found in GBIF and selected outside a radius of 200 km around these occurrences.
Finally, as a last caveat, we note that the models this study is based on were fitted using data taken from GBIF. This source combines the advantage of a global coverage, and hence the possibility to fit niches of species comprehensively, with the disadvantage of the errors and biases implicit to this database  (Meyer, Weigelt, & Kreft, 2016). Uncertainties in species distribution estimates and models resulting from these caveats have a clear geographical bias and are least pronounced in the well represented regions of Europe, North-and Central America, and Australia  (Meyer et al. , 2016). The majority of the ornamental plants and all congeners modelled here come from these areas, and we hence assume that data problems are of limited importance for them. Several of the ornamental plants are native to temperate Asia and Africa, however, and these regions have notoriously low data coverage.
EGF; Cullen et al. , 2011), the most comprehensive encyclopaedia of ornamental plants in Europe, with the Global Naturalised Alien Flora (GloNAF; van Kleunen et al. , 2015; https://glonaf. org/), a global database of naturalized alien plant species. They thereby identified nonnative ornamental plants cultivated in Europe which have naturalized somewhere outside of Europe, but not yet in Europe. For species distribution modelling (SDM) purposes, this list was then reduced to those 783 species with more than 50 occurrences found in a search of the Global Biodiversity Information Facility (GBIF, http://www. gbif. org/) database.
ACKNOWLEDGEMENTS This research was funded by the  ERA-Net BiodivERsA , with the national funders  FWF (Austrian Science Fund , project " Who Is Next "  I-1443-B25  to G. K. , I. D. , F. E. , D. M. , S. D. ),  DFG  ( German Research Foundation : O. B. , E. H. , M. vK. ) and  ANR (French National Research Agency : M. C. , W. T. ), part of the 2012-2013 BiodivERsA call for research proposals. P. P. and J. P. were supported by projects  504/11/1028  and  14-36079G   Centre of Excellence PLADIAS (Czech Science Foundation ), long-term research development project  RVO 67985939  and  Praemium Academiae  award (The  Czech Academy of Sciences ).
( EGF; Cullen et al. , 2011), the most comprehensive encyclopaedia of ornamental plants in Europe, with the Global Naturalised Alien Flora (GloNAF; van Kleunen et al. , 2015; https://glonaf. org/), a global database of naturalized alien plant species. They thereby identified nonnative ornamental plants cultivated in Europe which have naturalized somewhere outside of Europe, but not yet in Europe. For species distribution modelling (SDM) purposes, this list was then reduced to those 783 species with more than 50 occurrences found in a search of the Global Biodiversity Information Facility (GBIF, http://www. gbif. org/) database.
One explanation for this is that the presence of two branch points on Colour intensity in the heatmap is correlated to mean spot signals. The highest signal in each dataset was set to 100, and all other values were normalized accordingly as indicated by the colour scale bar. A low-end cut-off value of 5 was imposed. Homogalacturonan (HG), arabinogalactan protein (AGP), rhamnogalacturonan (RG). 6 1 , 6  5  -di-α-maltosyl-maltohexaose interferes with INCh1 binding to α-(1-4)-linked glucan more than the single branch point on 6  4  -α-maltosyl-maltohexaose. In addition to the oligosaccharides, INCh1 binding to starch derived from a variety of plant species was also assessed (Fig. 2a ). These data indicated that INCh1 bound to starch from diverse species, but not to floridean starch (a storage polysaccharide of red algae).
However, recombinant N. ulvanivorans ulvan lyase proved to be problematic to produce in useful quantities. The expressed protein could be detected by Western-blotting (Fig. S8a ) using an anti-His antibody, but not in SDS-PAGE gels (Fig. S8b ). We therefore identified a homologous ulvan lyase encoding gene (BN863_22190, Genbank: WP_038530530) in the genome of the marine bacterium Formosa agariphila  39  (F. agariphila). The corresponding protein is modular and includes an N-terminal signal peptide, a catalytic module, a putative carbohydrate module and a C-terminal type IX secretion module. This protein displays 52% identity with the entire sequence of the ulvan lyase from N. ulvanivorans and the catalytic modules of these two enzymes share 66% sequence identity. The recombinant expression in E.
The samples were finally mounted in CitiFluor (Agar Scientific) and scanned using laser scanning confocal microscope Leica SP5 using UV diode (405 nm), argon (488 nm) and helium-neon (543 nm) lasers. The pictures were processed with GIMP2 software. The algae used in this study were collected from young cultures and fixed for 1 hour on ice in a solution of 1% paraformaldehyde/0. 5% glutaraldehyde in natural seawater or 100 mM phosphate buffer with pH 7. 8. The algae were then washed three times at 10 min intervals in ice cold seawater or 100 mM phosphate buffer. The algae were then dehydrated over 6 hours in an increasing series of cold EtOH (e. g. 10-30-50-70-90-100% EtOH) and infiltrated in cold 1:2, 1:1 and 2:1 London Resin (LR)-EtOH solutions over 24 hours. The algae were then placed in the base of beem capsules or microcentrifuge tubes and covered with pure LR with added accelerator.
INCh1 was buffer-exchanged to 10 mM HEPES, 150 mM NaCl, pH 7. 5 using Amicon Ultra Centrifugal Filters (50 kDa molecular weight cut off, Millipore) and biotinylated with a 20-fold molar excess of EZ-link sulfo-NHS-LC-Biotin (Thermo Scientific) in the above buffer (30 min, RT). Excess reagent was removed (PD SpinTrap G-25 columns; GE Healthcare) while exchanging to running buffer (as above with 0. 005% P20 surfactant added). Sensorgrams (RU vs. time) for maltopentaose (34-625 μM) were recorded at 25 °C in running buffer at 30 μl min -1 , 60 s contact, 120 s dissociation and were baseline-corrected by subtracting data from a parallel flow cell with no INCh1 and normalized to the blank sensorgram. K D was calculated by steady state affinity equation (BIAcore T100 evaluation 2. 0. 3; GE Healthcare) (eq.
The same amount of cell wall material (alcohol insoluble residue) was used for each sample. Note that INCh2 bound to Ulva lactuca and Enteromorpha intestinalis containing ulvan, but that INCh2 binding was only abolished by pre-treatment of arrays with ulvan lyase on Ulva lactuca. (c) Diagram showing the cleavage sites of the ulvan degrading enzyme used in the major disaccharide units found in ulvan. Colour intensity in the heatmap is correlated to mean spot signals. The highest signal in each dataset was set to 100, and all other values were normalized accordingly as indicated by the colour scale bar. A low-end cut-off value of 5 was imposed.
Acknowledgements The authors wish to thank  Peter Ulvskov  for helpful discussions, and are grateful to the technicians  Valérie Echasserieau-Laporte  and  Louise Nancke. Furthermore we would like to thank:  Sachiko Nakamura-Tsuruta  ( Kobe University, Japan ) for the generous gift of the glycogen mAb ESG1A9;  Dr. Kurt Ingar Draget ,  Dr. J. Paul Knox ,  Dr. Vanja Tanackovic ,  Dr. Sanna Koutaniemi  and  Dr. Andreas Blennow  for providing the material for the study;  Dr. Agnès Groisillier ,  Ms. Bertille Massé  ( CNRS Roscoff ) and  Dr David Ropartz  ( BIBS platform, INRA Nantes ) for their help in the characterization of the ulvan lyases. This work was supported by the  Danish Strategic Research Council  and the  Danish Council for Independent Research, Technology and Production Sciences  under project GlycAct contract  10-093465  (M.
G. R. ); by the  FP7 Marie Curie action project CeWalDyn  under contract  329830  and  Danish National Advanced Technology Foundation  project  B21st  (J. M. ); by the  Danish Innovation Foundation (S. K. K. ) ; by the  Villum foundation  project  Planet  project nr. 00009283 (M. G. R. , J. M. , S. K. K. ); by the  US National Science Foundation (NSF) Molecular and Cellular Bioscience  ( 0919925  and  1517345 ) and  NSF Division of Biological Infrastructure  ( 0922805 ) (D. S. D. ); by the  Carlsberg Foundation  (J. U. F. , J. H. ); by the  French National Research Agency program  IDEALG No. ANR-10-BTBR-04.
Ex vivo results. Comparison with reference measurements. The comparison described in this section has been performed in the Department of Gynecologic Pathology at the Cancer Center Gustave Roussy in Villejuif. The MPC has been used to analyze several specimens of ex vivo cervices from total hysterectomies of women having shown a normal Pap smear. It should be important to note that the measurements were performed on fresh tissues prior to any kind of fixations. These samples were then also analyzed using another system, a Mueller Imaging Polarimeter (MIP) in backscattering configuration described in previous studies  11, 12  and routinely used for polarimetric imaging of ex vivo uterine cervix specimens. The MIP data are taken as reference measurements to determine the reliability of measurements obtained by the MPC.
The MIP measurements were used as a reference to confirm the accuracy of the data obtained with the MPC. Then, still using the ex vivo cervical specimens, a set of suitable operating conditions were determined for the MPC to achieve an acquisition time compatible with in vivo measurements. Finally the MPC was tested in vivo in real-world conditions on a number of healthy uterine cervices for patients with normal Pap smear. We have shown the ability of Mueller polarimetric imaging to clearly distinguish the two main types of epithelia (malpighian and glandular) that can be found on a healthy uterine cervix. Our results in vivo confirmed that the malpighian tissue is characterized by a strong anisotropy and so by high Retardance values as widely showed in previous studies ex vivo. On the opposite, we observed that glandular epithelium is characterized by a very low Retardance.
Acknowledgements The authors would like to pay the tribute to the seminal ideas of our group leader  Dr. Antonello De Martino  who passed away in August 2014. He pioneered the biomedical applications of Mueller polarimetry. The authors would like to thank the technical staff of the  Gynecologic Pathology Department of the Kremlin Bicêtre University hospital and Gynecologic Surgery Department of the Institut Gustave Roussy. The authors would also like to thank  Jean-Charles Vanel  for technical support.
In all cases, we obtained highly significant matches (Ͼ98% HHpred probability) to the Gag of retroviruses. The region of similarity encompasses the end of the CA NTD and extends throughout the CA CTD and NC domain (data not shown). To validate these matches, we aligned the retroviral CA-NC sequences with the corresponding protein sequences from the three other families of reverse-transcribing viruses. Inspection of the alignment showed that the sequence conservation among the aligned proteins encompasses not only the CA CTD and NC domain but also the CA NTD, with the exception of two short ␣-helixes (␣5 and ␣6) that have no equivalents in CPs of viruses other than retroviruses (Fig. 1  and 2 ). Importantly, nonpolar residues, which stabilize the hydrophobic core of the ␣-helical bundles of both the CA NTD and CA CTD  (10, 19) , are conserved in all CP/CA proteins.
As expected for viruses that possess small and constrained genomes, such neutral SNPs are extremely rare. Starting from a set of >1800 SNPs across the DENV genome, only three SNPs complied with the neutrality criteria and were enough represented in the sequence dataset for a precise Ne estimation. Using the method described by Monsion et al. [4] , Lequime et al. [2]  estimated Ne values ranging from 5 to 42 viral genomes (95% confidence intervals ranged from 2 to 161 founding viral genomes). Consequently, narrow bottlenecks occurred at the virus acquisition step, since the blood meal had allowed the ingestion of ca. 3000 infectious virus particles, on average. Interestingly, bottleneck sizes did not differ between mosquito genotypes. Monsion et al. 's  [4]  formula provides only an approximation of Ne.
A corrected formula has been recently published  [5]. We applied this exact Ne formula to the means and variances of the frequencies of the three neutral markers estimated before and after the bottlenecks (Table  1  in  [2] ), and nearly identical Ne estimates were obtained with both formulas. Selection intensity was estimated from the dN/dS ratio between the nonsynonymous and synonymous substitution rates using the HTS data on DENV populations. DENV genetic diversity increased following initial infection but was restricted by strong purifying selection during virus expansion in the midgut. Again, no differences were detected between mosquito genotypes. However and importantly, significant differences in DENV genetic diversity were detected among mosquito genotypes. As they could not be related to differences in initial genetic drift or to selection intensity, the authors raise interesting alternative hypotheses, including varying rates of de novo mutations due to differences in replicase fidelity or differences in the balancing selection regime.