dataesr/scientific-paragraphs-categorization huggingface dataset:
Reuse potential and limits While the previous section provides an example of the results that can be derived from the datasets, it is worth noting the limitations on providing similar results. The derived results should be presented pro rata with information presented above and in the metadata; i. e. , the resulting figures should be interpreted with respect to administrative restrictions and parameterisation of the simulation models applied in each country, for example as follows: Our PPFs are not optimised and should therefore not be interpreted as Pareto-optimal production frontiers achieved when the given resources and technology are optimally used, which is a common definition for a PPF. If optimisation was applied to enable a more efficient use of resources, it would shift the PPFs farther from the origin, which compares with a shift caused by technological improvements in typical analyses of Pareto-optimality.
g. Serbia and Slovenia). These factors or their combinations could have a great influence on the final predictions and the prediction uncertainties. However, these sources of variation are fundamentally related to the use of NFI data for projections and thus present also in projections based on NFI data such as those used in EFSOS-II. Also, while the definitions for FAWS and FNAWS are established  (Alberdi et al. 2016; Fischer et al. 2016; Lind et al. 2016) , FRAWS are not distinguished from these categories by NFIs of many countries and the related information may include many more sources of uncertainties (see below). The projection models were parameterised individually by national experts in relation to available data and countryspecific forestry practices and assumptions for the future.
With a small amount of data, the parameterisation of uneven-aged forestry dynamics can be deemed more uncertain than even-aged forestry dynamics. However, the future projections are inherently uncertain and their reliability depends on whether the assumptions on business-as-usual transitions and allocation of management activities still apply in the future  (Vauhkonen and Packalen 2018). Due to these limitations, our data should be considered as a pilot study or first example of deriving comparable information from European NFIs by harmonising definitions, assumptions, and modelling methodology. The dataset may readily be a useful source of data for analyses requiring comparable information: Due to the harmonised approach, the results can be easily compared with other projections either at the level of individual Member States, country groups such as those corresponding to UNECE/FAO (2011), or at the European level.
Acknowledgements We acknowledge  European Commission's Joint Research Centre (JRC)  for maintaining the EFDM source code repository; and the  National Forest Inventories  of the 23 participating countries for collecting the NFI data and enabling the use of these data for the present purpose. Funding Information Open access funding provided by  Natural Resources Institute Finland (LUKE). The research work has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under Grant No. 633464  to project " Distributed, Integrated  and  Harmonised Forest Information for Bioeconomy Outlooks (DIABOLO) ".
Results Literature-based invasion history. A search for "Mytilicola intestinalis" resulted in 72 hits on the Web of Science/Web of Knowledge (all databases) and 934 hits on Google Scholar (on 15 December 2017). A search for "Mytilicola orientalis" resulted in 15 hits on the Web of Science/Web of Knowledge (all databases), and 373 hits on Google Scholar (on 15 December 2017). More literature was found by snowballing (see Methods). Our literature survey led to the inclusion of 173 publications on occurrences of M. intestinalis (2187 data points including those of this study; reference list in Supplementary Information) and of 47 publications on occurrences of M. orientalis (416 data points including those of this study; reference list in Supplementary Information). The literature included peer-reviewed publications, fishery leaflets, reports, book sections and dissertations.
Mytilicola intestinalis discovery Latitude (DD) 1900-1909  1900-1939  1900-1949   1900-1959  1900-1979  1900-2017   Longitude (DD)    32, 33  ). Mytilicola intestinalis was detected in M. galloprovincialis and M. edulis. Mytilicola orientalis was also detected in these bivalves, but also in C. gigas and M. trossulus. Prevalences of M. intestinalis ranged from 0 to 82. 0% in the Mediterranean Sea Basins, the putative native region of M. intestinalis, and from 0 to 93. 8% in the invaded regions (Table  1 ). Prevalences of M. orientalis ranged from 0 to 10. 6% in Japan, the putative native region of M. orientalis, and from 0 to 73. 8% in the invaded regions (Table  1 ). invasion genetics of Mytilicola spp. A total of 424 M. intestinalis and 444 M. orientalis were successfully sequenced, which resulted in the detection of 18 and 26 haplotypes, respectively (Tables  S1  and S2 ) (Genbank accession No.
Materials and Methods Literature review. To describe the distribution of both invasive Mytilicola species through time in putative native and invaded regions, we searched the Web of Science/Web of Knowledge and Google Scholar with the keywords "Mytilicola intestinalis" and "Mytilicola orientalis". Further publications, including grey literature, were found by checking the references of each relevant publication (i. e. , "snowballing"). All publications were screened for recorded absence or presence of Mytilicola species per host species, and for coordinates of sampling sites. This resulted in data sets for Mytilicola intestinalis and for Mytilicola orientalis (available upon request) which were used for plotting occurrence maps with the R packages rworldmap  67  and ggplot  68. If latitude and longitude were not reported in a publication, we inferred approximate coordinates from maps so that the data could be plotted.
5. 1 (for M. orientalis) or BioEdit 7. 2. 5 77 (for M. intestinalis), after which forward and reverse reads were assembled. We screened all chromatograms for double peaks and at least one of the forward and reverse sequences had no double peaks at any base in the sequence. Some of the North American samples failed to amplify or sequence entirely and were not considered further. COI sequences were cropped to 483 base pairs (bp) for M. intestinalis and to 476 bp for M. orientalis. Unique haplotypes were determined using DnaSP 5 (M. orientalis)  78  or using a custom Python 3. 6 script (M. intestinalis) (GitHub: https://github. com/pluttik/collarl). Arlequin 3. 5. 1. 2  79 was used to calculate pairwise population comparisons (10,000 permutations), population differentiation based on the mitochondrial F-statistic Φ ST and conventional F-statistics F ST (10,000 permutations), Analyses of MOlecular VAriance (AMOVA), molecular diversity indices, Tajima's D statistic  80  and to perform Fu's F s tests  81, 82  for selective neutrality (10,000 simulated samples), mismatch distributions (10,000 permutations) and minimum spanning networks for both species.
Acknowledgements Financial support for this study was provided by the Special Program 1399 on host-parasite coevolution of the  Deutsche Forschungsgemeinschaft (DFG)  (grant number  We4641/1-2 ) to KMW. MEF is grateful for the MARS Travel Award 2016. MAG, DWT and PCL acknowledge support from  Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO)  and the  German Bundesministerium für Bildung und Forschung (BMBF)  (grant number  839. 11. 002 ). We thank  Baseclear B. V. in Leiden  for extraction, PCR and Sanger sequencing (M. intestinalis). We thank the  Institute of Clinical Molecular Biology in Kiel  for providing Sanger sequencing (M. orientalis) as supported in part by the  DFG Cluster of Excellence "Inflammation at Interfaces " and " Future Ocean ". We thank the technicians  S.
This N-terminal region of Mpe1 that is required for Ysh1 interaction contains a ubiquitin-like (UBL) domain. In the pull-down assays, Mpe1 interacted with full-length Ysh1 and the catalytic N-terminal domain (Ysh1-N), but not with the C-terminal domain (Ysh1-C) (Figure  1B ). Removal of the Ysh1 C-terminal domain and parts of Mpe1 both reduced the interaction with Cft2. Together, these data suggest that the N-terminal catalytic domain of Ysh1 interacts with the Mpe1 UBL domain. To further assess the stability of these interactions, complexes identified by pull-down were subjected to anion exchange chromatography. The interactions between Ysh1 and Mpe1 constructs were stable, whereas Cft2 dissociated during purification (Figure  1C ), consistent with Cft2 dissociation in earlier attempts to purify the Ysh1-Mpe1-Cft2 complex.
Analysis of a chemically cross-linked complex by negative-stain EM showed wellseparated particles (Figure  5B ). 2D class averages revealed a distinctive $21-nm particle with the Cft1-Pfs2-Yth1 scaffold of the polymerase module at one end and three globular densities extending from it (Figure  5C ). 2D class averages from cryo-EM micrographs revealed similar structures with one, two, or three globular densities next to the scaffold, with the same dimensions and spatial arrangement as the negative-stain particles (Figures  5D  and 5E , Table  2 ); however, these classes originated from only $0. 5% of particles. Instead, the cryo-EM dataset was dominated by smaller particles representing the Cft1-Pfs2-Yth1 scaffold. This suggests that the other globular densities corresponding to Cft2 and Pap1 are either highly flexible or dissociate during specimen preparation, despite chemical crosslinking.
Using the negative-stain dataset, we obtained a 3D reconstruction of CPF core at $20 A ˚resolution. We built a model for CPF core by docking known X-ray crystal structures and cryo-EM structures into the map (Figure  5F ). In our model, the Cft1-Pfs2-Yth1 scaffold with its four characteristic b propellers is located at one end of the complex with Pap1 in close proximity. Pap1 is known to be tethered to the complex through Fip1, which in turn binds zinc fingers 4 and 5 of Yth1 (disordered in the docked cryo-EM structure)  (Barabino et al. , 2000; Helmling et al. , 2001; Meinke et al. , 2008; Tacahashi et al. , 2003). We modeled the largest globular density proximal to the scaffold as the metallo-b-lactamase/b-CASP domain of the pseudonuclease Cft2. A disordered loop of 204 amino acids, absent from the crystal structure of Cft2, could act as a flexible tether.
Peptides were eluted with a gradient of acetonitrile. The analytical column outlet was directly interfaced via a nanoflow electrospray ionization source, with a hybrid dual pressure linear ion trap mass spectrometer (Orbitrap Velos, ThermoScientific, USA). MS data were acquired in data-dependent mode. High-resolution full scans (R = 30,000, m/z 300-2000) were recorded in the Orbitrap. For samples cross-linked with DSS, MS/MS scans of the 20 most intense MS peaks were recorded in the linear quadrupole ion trap (LTQ) after CID activation (collision energy 35). For samples cross-linked with the CID cleavable BuUrBu, the 3 most intense MS peaks were CID activated (collision energy 30) and high resolution MS 2 spectra were acquired (R = 30,000, m/z 300-2000). After in-source CID activation (collision energy 30), the three most intense ions recoded in MS 2 spectra were CID activated (collision energy 35) and the MS 3 spectra were recorded in the LTQ ion trap.
For data analysis, Xcalibur raw files were converted into the MGF format through MSConvert (Proteowizard;  (Kessner et al. , 2008) ) and used directly as input files for StavroX1  (Go ¨tze et al. , 2012)  and  MeroX (Go ¨tze et al. , 2015). Searches were performed against an ad hoc protein database containing the sequences of the complexes and a set of randomized decoy sequences generated by the software. The following parameters were set for the searches: maximum number of missed cleavages 3; targeted residues K, S, Y and T; minimum peptide length 5 amino acids; variable modifications: carbamidomethyl-Cys (mass shift 57. 02146 Da), Met-oxidation (mass shift 15. 99491 Da); DSS cross-links mass shift 138. 06808 Da (precision: 10 ppm MS 1 and 0. 8 Da MS 2 ), BuUrBu modification fragments: 85.
The mass spectrometer was operated at a source temperature of 80 C and a spray voltage of 2. 6 kV. Spectra were collected in positive ion mode. Peptide identification was performed by MS e  (Silva et al. , 2005)  using an identical gradient of increasing acetonitrile in 0. 1% v/v formic acid over 11 min. The resulting MS e data were analyzed using Protein Lynx Global Server software (Waters, UK) with an MS tolerance of 5 ppm. Mass analysis of the peptide centroids was performed using DynamX software (Waters, UK). Only peptides with a score > 6. 4 were considered. The first round of analysis and identification was performed automatically by the DynamX software, however, all peptides (deuterated and non-deuterated) were manually verified at every time point for the correct charge state, presence of overlapping peptides, and correct retention time.
X-ray data collection, structure determination, refinement and analysis Diffraction datasets (Table  1 ) of 900 images were recorded at Diamond Light Source, beamline I04-1 on a Pilatus 6M detector (Dectris), using an oscillation range of 0. 2 and an exposure time of 0. 2 s per image. Data were collected at a temperature of 100 K. Data were processed with the XIA2  (Winter, 2009 ) automated pipeline, using XDS  (Kabsch, 2010)  for indexing and integration, and AIMLESS  (Evans and Murshudov, 2013)  for scaling and merging. Resolution cut-off was decided by a CC 1/2 value > 0. 5 in the highest resolution shell. The structure was solved by two-component molecular replacement with  Phaser (McCoy et al. , 2007) , using the crystal structure of human CPSF73 (PDB: 2I7V;  (Mandel et al. , 2006) ) and the NMR structure of human RBBP6 (PDB: 2C7H;  (Pugh et al.
9, 150 mM NaCl. Cryo samples were then prepared on UltraAuFoil R1. 2/1. 3 gold supports  (Russo and Passmore, 2014). Grids were made hydrophilic by plasma treatment with 9:1 argon:oxygen for 30 s. Three microliters of sample was applied to grids, blotted for 10 s, and vitrified by plunging into liquid ethane using a Vitrobot MK IV (FEI) at 4 C, 100% relative humidity. Preliminary micrographs suggested that the complex was substantially smaller than expected ($8 nm). Thus, to enhance contrast we used a Volta phase plate with applied defocus and collected data only in holes with thin ice, on specimens prepared on all-gold supports. Micrographs were collected at IGBMC, Strasbourg on a C s -corrected FEI Titan Krios microscope (FEI) operating at 300 keV and equipped with a Volta phase plate, K2 camera (Gatan) and Gatan Image Filter (GIF) with a slit-width of 20 eV.
At 105,000 3 magnification, the calibrated pixel size was 1. 09 A ˚. Gain-normalized, LZW-compressed TIF movies with a total electron dose of $45 e -/A ˚2 were recorded in super-resolution mode over 9 s (42 frames) with applied defocus of À0. 5 mm. SerialEM software was used for automatic acquisition  (Mastronarde, 2005). After manual inspection, 994 micrographs were used in subsequent image processing. Movie frames were aligned and a dose-weighted average calculated with MotionCor2  (Zheng et al. , 2017). The contrast transfer function (CTF) and image phase shift was estimated using Gctf  (Zhang, 2016)  All subsequent image-processing steps were carried out in RELION2  (Scheres, 2012). Initially, auto-picking of 509,298 particles was carried out using a Gaussian blob as a reference. After several rounds of 2D and 3D classification (necessary to both clean dataset and enrich rare views), four classes that represented different views were low-pass filtered to 20 A ˚and used for template-based auto-picking.
CPF core Cross-linked CPF core was diluted to 250 nM in 10 mM HEPES, pH 7. 9, 150 mM NaCl. Cryo samples were prepared as above, but using a 6 s blot time. Test datasets were also acquired on Quantifoil R1. 2/1. 3 grids coated with graphene oxide or amorphous carbon, but this did not improve the specimen. Micrographs were collected at MRC-LMB on a Tecnai G2 Polara microscope (FEI) operating at 300 keV, using a Falcon III camera (FEI). At 59,000 3 magnification, the calibrated pixel size was 1. 78 A ˚. Uncompressed movies were acquired in integration mode with a total electron dose of $60 e -/A ˚2 over 2 s (62 frames) with applied defocus of À2. 5, À3. 0, À3. 5, À4. 0 and À4. 5 mm. After manual inspection, 704 micrographs were used in subsequent image processing. Movie frames were aligned and averaged with MotionCorr.
The contrast transfer function (CTF) was calculated using Gctf. All further image-processing steps were performed in RELION2. Initially, a subset of 20 micrographs with different defocus values were used to manually pick $5,000 particles for initial reference-free 2D classification. The resulting 2D classes were low-pass filtered to 20 A ˚and used as templates for automated particle-picking. From the initial 506,293 particles picked, iterative 2D classification was used to clean the dataset. In the cleaned data, 116,800 particles formed classes in which only density for polymerase module was visible; this was confirmed by a map at $8A ˚resolution following 3D refinement. The remaining 3973 particles formed classes in which additional globular subunits were visible.
ACKNOWLEDGMENTS We thank  Michael Webster ,  James Stowell ,  Juan Rodriguez-Molina ,  Gillian Dornan ,  Christos Savva ,  Giuseppe Cannone ,  Sjors Scheres ,  Chris Russo ,  Katerina Naydenova ,  Balaji Santhanam ,  Shabih Shakeel ,  Minmin Yu , the  LMB EM facility , and  LMB  scientific computation for assistance, advice, and helpful discussions. This work was supported by the  European Research Council  under the European Union's  Seventh Framework Programme  (FP7/ 2007-2013)/ ERC  starting grant  261151  (to L. A. P) and the  European Union 's  Horizon 2020 research and innovation programme (ERC Consolidator  grant agreement  725685 ) (to L. A. P),  Medical Research Council (MRC)  grant  MC_U105192715  (L. A. P. ),  EMBO Long-Term  Fellowship  ALTF66-2015  co-funded by the  European Commission  ( LTFCOFUND2013 ,  GA-2013-609409 ) through  Marie Curie Actions  (to A.
cerevisiae Rna14-Rna15 This work, based on Gordon et al. , 2011 N/A Recombinant protein complex: S. cerevisiae Pcf11-Clp1 This work, based on Gordon et al. , 2011 N/A Recombinant protein complex: S. cerevisiae '' CF IA '' Rna14-Rna15-Pcf11-Clp1 This work, based on Gordon et al. , 2011 N/A Critical Commercial Assays N/A Deposited Data Mendeley raw data (e. g. , uncropped gels, MS peptides) This work https://doi. org/10. 17632/rnsb352sx3. 1 Ysh1-Mpe1 crystal structure This work PDB:  6I1D Ysh1-Mpe1  cryo-EM map This work EMD: 0325 CPF core negative stain EM map This work EMD:  0324  NMR structure of Rna14-Rna15 monkeytail-hinge (used for Figure 6 Moreno-Morcillo et al. , 2011 PDB: 2L9B Crystal structure of Rna14-Rna15 complex (used for Figure 6) Paulson and Tong, 2012 PDB:  4EBA  NMR structure of C-terminal domain pf CstF-64 (used for Figure 6) Qu et al.
, 2007 PDB:  2J8P  NMR structure of  Hrp1-Rna15 RRMs  (used for Figure 6) Leeper et al. , 2010 PDB: 2KM8 Crystal structure of Rna15 RRM with bound GU (used for Figure 6) Pancevac et al. , 2010 PDB: 2X1F Crystal structure of Pcf11-Clp1 complex (used for Figure 6) Dupin and Fribourg, 2014 PDB: 4C0B Crystal structure of Pcf11-Clp1 complex (used for Figure 6) Noble et al. , 2007 PDB:  2NPI  Crystal structure of Pcf11-RNA pol II CTD complex (used for Figure 6) Meinhart and Cramer, 2004 PDB:  1SZA  Cryo-EM structure of Cft1-Pfs2-Yth1 (used for.
9% Millipore 1133660009 DiSuccinimidylSuberate (DSS) Creative Molecules 001S DiSuccinimidyl Dibutyric Urea (DSBU) Figures 5 and 6) Casan ˜al et al. , 2017 PDB: 6E0J Crystal structure of Cft2 (used for Figures 5 and 6) Mandel et al. , 2006 PDB: 2I7X Crystal structure of Pap1-Fip1 complex (used for Meinke et al. , 2008 PDB: 3C66 Figures 5 and 6) Crystal structure of CPSF-73 (used as molecular Mandel et al. , 2006 PDB: 2I7T replacement search model) NMR structure of Rbbp6 (used as molecular Pugh et al. , 2006 PDB: 2C7H replacement search model) Experimental Models: Cell Lines Sf9 Oxford Expression 600100-SF9 cells Technologies Ltd. Experimental Models: Organisms/Strains S. cerevisiae Ref2-TAPS (for purification of Casan ˜al et al. , 2017 kanMX6 MATalpha pra1-1 prb1-1 endogenous CPF): prc1-1 cps1-3 ura3delta5 leu2-3 his-Parent strain JWY104 Oligonucleotides RNA and DNA sequences, with details of end-labeling This work See Table S2 (Continued on next page) Molecular Cell 73, 1217-1231.
Gene expression analyses Gene expression analyses were performed using R software version 3. 2. 2 (https://www. R-project. org). Gene expressions were determined using high-quality reads. Expression data (Additional files 2 and 3) were first normalized with the Trimmed Mean of M-values (TMM) method  [27]  using the Bioconductor package edgeR  [28]. Normalized data were analyzed by Principal component analyses and hierarchical clustering. Genes were filtered using the data driven HTSfilter procedure using the Bioconductor package HTSFilter  [29]. Differentially expressed genes (DEG) between overfed and ad libitum fed ducks were determined in each genetic type using filtered genes set.
Functional annotation Functional annotation of differentially expressed genes with assigned GO terms for biological processes (GOBP) was conducted with the Database for Annotation, Visualization and Integrated Discovery (DAVID, http:// david. abcc. ncifcrf. gov/) bioinformatics resource, version 6. 82016  [30] [31] [32]. Enrichment of functional annotations in DEG was determined using the default medium classification stringency with an EASE enrichment threshold (a modified Fisher Exact P-Value) set to 0. 001. Enriched annotations were then clustered with the Wang method  [33]  using GO terms semantic similarity as metric. Expression profiles of down-and up-regulated DEG in the different clusters were also analyzed and visualized using clusterProfiler  [34]. Dot size in profiles corresponds to FC.
RNA sequencing and expression data To go further in the understanding of mechanisms involved in hepatic steatosis, gene expression analyses were conducted by high-throughput RNA sequencing. For this purpose, RNA were first extracted from the liver of Pekin, Muscovy, Mule and Hinny ducks fed ad libitum or overfed and were sequenced on a HiSeq2000 after cDNA library constructions (n = 79). Approximately 2215 million paired-ends sequences were produced, corresponding to 28 ± 8 million in each sample and to 27. 6 ± 7. 7 million (97. 4 to 99. 1%) high-quality paired-reads (Additional file 1). High-quality reads were assembled in 22,561 expressed genes and for each of these genes the number of mapped reads in each sample was counted (Additional files 2 and 3). These counts were considered raw expression data.
Acknowledgements The authors greatly acknowledge  Cécile Duby  for technical assistance in RNA preparation. The authors also thank the staff of the  INRA experimental Palmipèdes à Foie Gras (Palmipôle) unit  ( UE 0089 ,  Benquet, France ) for producing and rearing animals, the staff of  GeT core facility  ( US 1426 ,  GenoToul, Castanet-Tolosan, France ) for advices and sequencing, the  Bioinformatics core facilities  from  Genotoul (Toulouse, France) and GenOuest from Biogenouest (Rennes, France ) for data storage and access to clusters for analyses.