dataesr/scientific-paragraphs-categorization huggingface dataset:
X3440, 4 cores/CPU, 16GB RAM and a second phase on a machine with 2 CPUs Intel Xeon L5420, 4 cores/CPU, 16GB RAM. 4 http://wiki. dbpedia. org/ 5 https://github. com/ag-sc/matoll TEAM, COUNTRY, ORDER, DEATHPLACE, OCCUPATION, KINGDOM, NATIONALITY, BATTLE, HOMETOWN, AWARD, PREDECESSOR, PUBLISHER, DISTRIBUTOR, OWNER, RECORDEDIN, ALBUM, PRODUCT, PARENT, AFFILIATION, EDUCATION, ROUTEEND, ORIGIN, NEARESTCITY, ARCHITECT, COMPOSER, MOUNTAINRANGE, FOUNDEDBY, INFLUENCED, GARRISON, LEADER, PROGRAMMINGLANGUAGE.
Aims Critical appraisal of secondary data made available by the OECD for the time frame 2000-2011. Methods Comparison of trends and variation of amputations in people with diabetes across OECD countries. Generalized estimating equations to test the statistical significance of the annual change adjusting for major potential confounders. Results A total of 26 OECD countries contributed to the OECD data collection for at least 1 year in the reference time frame, showing a decline in rates of over 40 %, from a mean of 13. 2 (median 9. 4, range 5. 1-28. 1) to 7. 8 amputations per 100,000 in the general population (9. 9, 1. 0-18. 4). The multivariate model showed an average decrease equal to -0. 27 per 100,000 per year (p = 0. 015), adjusted by structural characteristics of health systems, showing lower amputation rates for health systems financed by public taxation (-4.
The main reason for not publishing the international trends of LEARD was a general disagreement among countries on how to cope with the observed variability in the results, how to consider the different coding mechanisms and data sources used to apply common definitions, and which methods would be required for statistical analysis. Consequently, the availability of these data has been substantially underexploited. Meanwhile, LEARD data collected by the OECD have been regularly uploaded to the official OECD online repository StatExtracts (http://stats. oecd. org/). In the present paper, we present the results of a critical appraisal of the LEARD data collected by the OECD for the years 2000-2011, with the aim of responding to the following main questions: • How was the trend over 12 years? • How did rates vary across OECD countries in each year? • Can amputation rates be used to evaluate quality of care and health systems performance? • How to enhance international comparability?.
Materials and methods Standardized LEARD for the time frame 2000-2011 were downloaded from StatExtracts in May 2015, with data referred to the HCQI data collection 2013. The entire time series was computed by the OECD, using numerators/denominators stratified by sex and age classes, delivered by countries on the basis of the following agreed criteria: • Numerators include all non-maternal/non-neonatal hospital admissions of subjects aged 15 or over with procedure code of lower extremity amputation (excluding toe) and diagnosis code of diabetes in any field in a specified year. Specific procedure codes (84. 10, 84. 12-19) were provided only for ICD-9-CM and ICD-10-WHO. In other cases, countries were asked to identify the most appropriate codes for their national classification systems. • Cases are excluded from the numerators if they are transferred from another institution or present a trauma diagnosis, or same day/day only admissions.
• Denominators refer to the total population aged 15 years or over. • All rates are expressed as the total number of amputations 9100,000 total general population, standardized (SR) using the total OECD population across 34 member states (MS) in year 2005. Additional data extracted from the OECD online repository included structural characteristics of data (use of registries and coding systems) and health systems of participating countries (tax-based systems vs insurance based)  [15]. Since the USA included amputation of toes in the numerator before 2010, all data reported prior to that date were excluded from the analysis. Descriptive measures included: measures of centrality (mean, median and range); dispersion (coefficient of variation x 100: CV), total general population aged 15 and over in all 34 MS; and projected total number of amputations per year (computed as a product between the total population and the relative standardized rate).
A graphical plot superimposing boxplots to turnip charts and a continuous line representing the average trend for the entire pool of OECD countries, was used to display results over time  [16]. Multivariate linear regression using generalized estimating equations (GEE) was used to estimate the average change of standardized LEARD over time, taking into account all structural characteristics identified above as potential confounders and including countries as clusters, with an exchangeable correlation matrix of rates over time. The adoption of GEE models was justified by the need of ensuring robust confidence intervals when the normality assumption is violated by correlated values within clusters (in this case, countries) and missing data are sparsely present  [17]. Sensitivity analysis was carried out to take into account the different composition of countries over time, testing the heterogeneity of results obtained for the whole period against those excluding observations prior to 2006, when a limited set of countries was included in the database.
Results An expanded version of the OECD data on LEARD for the time frame 2000-2011 is presented in Table  1  reporting standardized rates for each contributing country. Descriptive measures and the projected total number of amputations in the whole OECD area are presented in Table  2. A total of 26 OECD countries contributed to the HCQI data collection on LEARD with at least one year in the reference time frame. One half of MS presents only data from 2006 onwards. A total of 8 MS did not participate and were only considered for the total population used for standardization: Austria, Chile, Czech Republic, Estonia, Greece, Japan, Slovak Republic and Turkey. Overall, standardized LEARD experienced a 12-year decline of over 40 %, from a mean of 13. 2 amputations per 100,000 in 2000 (median, range: 9.
Although interesting, they should be also taken with extreme caution. In the OECD data collection, countries are fully in charge of ensuring accurate reporting of cases of diabetes. Therefore, we could not assess to what extent a systematic underreporting of diabetes diagnoses may have determined lower rates in specific cases. Until data quality issues such as this one are not fully resolved, the level of association found between insurance-based systems and higher rates should be only used to raise hypotheses for further investigation, but by no means can be intended as a cause-effect relationship. On the other hand, the significantly lower rates found for countries using non-ICD classification systems should not be interpreted in relation to data quality. In fact, systems, e. g. , NOMESCO, are prevalently used in countries (e.
Purpose: The optimal management of rare tumours (i. e. from accurate diagnosis to management in reference centres) is a public health challenge. In 2009, the French National Cancer Institute (INCa) identified and financially supported the two expert networks for pathological and clinical diagnosis and management of soft tissue tumours. Methods: The activities of both networks were prospectively collected using a nationwide database (rreps. org). Data describing the diagnosis management of 863 successive cases of desmoids tumours (DT) were prospectively collected from 2010 to 2013 and analysed. Results: The number of confirmed DT constantly improved from January 2010 to December 2013 (from 173 to 273 cases per year); the expected incidence ranged from 132 to 330 cases/ year. The rate of cases diagnosed with core-needle biopsies and CTNNB1 mutational status analysis increased from 30.
sarcomabcb. org/home. htm) is in charge of systematic reviewing diagnosed or suspected cases regardless of where the diagnosis was performed (i. e. general hospital and private clinic). This network is also responsible for conducting molecular diagnostic tests (e. g. exon 3 CTNNB1 mutation in DT cases). The clinical network, NetSarc Network for clinical management of Sarcoma", is a network of referral centres for the clinical management of adult sarcomas, GISTs, and DTs. The RRePS and NetSarc networks include 22 and 26 centres, respectively, covering the French territory and share an online database. This online database is prospectively annotated and enables the description of diagnoses in real-time. In parallel, the French patient advocacy group, SOS Desmoı ¨de, has supported the implementation of both networks, annual meetings with patients and caregivers, and updating of their website.
Shared database Both NetSarc and RRePs networks share an online database (https://rreps. sarcomabcb. org/home. htm), which provided some key indicators of activity All patients were anonymised. The main characteristics of the tumours and patients, course of disease, and nature of treatments were prospectively collected. The data were collected by pathologists, physicians, and clinical research assistants of the networks. Data quality was ensured by training all members, pre-testing, and performing consistency checks during data entry. Furthermore, the data were evaluated by the clinical research assistants of the three major expert networks during onsite audit and regular database queries.
Role of the French National Cancer Institute (INCa) The INCa has funded the setup and the operation of the networks for 4 years (2010, 2011, 2012 and 2013), including the development of the online database, costs related to second opinion and molecular biology confirmatory tests, and costs related to the management of the database. Nevertheless, this label provided by INCa was not associated with financial or regulatory constraints; therefore, physicians and pathologists outside the networks were free to refer (or not) the cases and patients to referral centres.
Results The results for the 10 Be concentrations (see Supplement) and fluxes of the four cores are shown in Fig. 1  as a function of their depth along with their stable isotope profiles. As previously noted  (Yiou et al. , 1997; Raisbeck et al. , 2007)  all cores show a highly structured peak of 10 Be centered on AIM-10 (EDC, EDML, Vostok) or DO-10 (NGRIP). It is this structure that allows us to make multiple synchronizations over the whole width of the peak, as shown in Fig. 2. This synchronization was done in two ways. Initially we selected five tie points (four peaks and one valley, Table  1  and Fig. 2 ) which appeared to us to be clearly common to all the profiles, and synchronized using the AnalySeries program of  Paillard et al. (1996). Subsequently, in an effort to avoid the subjectivity of choosing tie points, we did the synchronization using the MATCH protocol of  Lisiecki and Lisiecki (2002).
(2015). A stack (purple curve) is drawn using the 3 δ 18 O records from EDML, EDC and WDC, and the black lines correspond to its inflections identified by eye. ous at EDML since two other prominent peaks (but peaking at lower δ 18 O values) are also identified in the following centuries. The EDC, WDC and EDML δ 18 O profiles also display a δ 18 O decrease occurring about 200 years after the North-GRIP δ 18 O increase, as was extensively discussed in WAIS Divide Project Members (2015). For a proper comparison with the results displayed on WDC in WAIS Divide Project Members (2015), we have used the same statistical approaches, i. e. , the BREAKFIT software by  Mudelsee (2010)  and a similar automated routine (referred to as MATLAB routine in Table  2 ) using a second-order polynomial (rather than a linear for BREAK-FIT) fit to the data.
This stack clearly shows the δ 18 O decrease observed 200 years after the abrupt δ 18 O increase in Greenland, but it also depicts an inflection point ∼ 200 years (185-219 years according to the MATLAB routine) before the Greenland abrupt δ 18 O increase, so that on the stack, δ 18 O displays a ∼ 400-year-wide plateau at the time of the abrupt Greenland δ 18 O increase. Such a plateau is not unexpected and follows from our observation that in some ice cores (WDC, EDML) the maximum of the AIM was before the abrupt δ 18 O increase in Greenland, while in another (EDC) the maximum of the AIM occurs after the abrupt Greenland δ 18 O increase. This result seems at first sight to nuance the conclusions presented in WAIS Divide Project Members (2015) using the same approach for the determination of the breakpoint.
Acknowledgements. This project was initiated during discussions between the first author and  Sigfus Johnsen  at an EPICA meeting at San Feliu, Spain, in 2003. Sigfus was always a strong supporter of 10 Be measurements in ice cores, and enthusiastically responded positively to the idea of using high-resolution NGRIP samples to overcome limitations encountered with GRIP samples. We therefore dedicate this paper to Sigfus' memory. We thank  C. Buizert  and an anonymous reviewer for helpful comments. We would like to acknowledge the many people involved in logistics, drill development and implementation, ice core processing and analysis; without them this work would not have been possible. This includes NorthGRIP, directed and organized by the  Department of Geophysics at the Niels Bohr Institute for Astronomy, Physics and Geophysics, University of Copenhagen , and supported by funding agencies and institutions from participating countries, and EPICA, the  European Project for Ice Coring in Antarctica , a joint  European Science Foundation-European Commission scientific program , funded by the  EU  and by national contributions from  Belgium, Denmark, France ,  Germany, Italy , the  Netherlands, Norway, Sweden, Switzerland , and the  UK.
Data availability. The data in the Supplement are also available in the PANGAEA database: https://doi. pangaea. de/10. 1594/ PANGAEA. 872454 (NGRIP, EDML, Vostok) and https://doi. pangaea. de/10. 1594/PANGAEA. 872445 (EDC). The Supplement related to this article is available online at doi:10. 5194/cp-13-217-2017-supplement.
Furthermore, intra-field microbial community variation was strikingly reduced at Piccard while more variation was observed at Von Damm (Fig. 4 , Fig. S6 ). The archaeal community in a number of vents at  Von Damm, including Shrimp Hole, Ravelin #2 and Main Orifice, showed the most compositional variability compared with the other vents from the same vent field. Ravelin #2 has extremely low magnesium concentration (Table  1 ), indicating a higher proportion of end-member fluid (∼ 75%). ANOSIM analysis indicated that bacterial communities at orifices with a high fraction of end-member fluid (magnesium < 20 mM) were significantly different (P = 0. 008, R = 0. 658) from those with a low fraction of end-member fluid (magnesium > 20 mM). On the other hand, no significant grouping (in either the bacterial or the archaeal dataset) was found based on other chemical parameters, including temperature, pH, H2S and silica.
Chimneys from Lucky Strike and Rainbow group together, distinct from Lau Basin sulfide chimneys, which are more similar to the MCR and Axial post-eruption vents than the Mid-Atlantic Ridge chimneys. Guaymas and Lost City sites cluster separately from all other samples at a very low level of similarity. Within the archaea, Archaeoglobaceae were dominant at both MCR vents and the Lau Basin sulfide chimneys samples, while Methanothermococcus were present at high relative abundance in both the MCR and the Axial 'snowblower' vents (Fig. 5 ). Guaymas and Lost City vents were dominated by ANME. Sequences belonging to the genus Sulfurovum were detected in almost all datasets, although they were strikingly abundant at the MCR (up to 79% of total bacterial sequences), and to a lower extent in Axial 'snowblower' vents, as well as Rainbow and Lau Basin sulfide chimneys (Fig.
The relative abundance of best hits assigned to each major subsystem (orthologous gene classes) in the two samples indicated that both sites had a similar functional profile (Fig. S13 ), with 'amino acid transport and metabolism', 'translation, ribosomal structure and biogenesis', and 'Energy production and conversion' dominating the general functions in both metagenomic datasets. Consistent with the COG analysis, functional gene annotation based on KEGG annotation scheme showed that both samples were very similar (Fig. S14 ). When examining the 20 most abundant functions in each sample, 10 were shared between both (see Fig. S15A  and B ), and these are represented by constitutive genes involved in the replication, recombination and repair of DNA, or in post-translational modification. Among those genes differently abundant between the two samples, the amino acid metabolism function 5-methyltetrahydrofolatehomocysteine methyltransferase (metH, MTR) was specifically enriched at Von Damm, while the functions asparagine synthetase (glutamine-hydrolysing) (asnB, ASNS) and alanyl-tRNA synthetase (AARS, alaS) were more enriched at Piccard.
, 2006). The high relative abundance of putative sulfate-reducing bacteria at Shrimp Hole is consistent with sulfur isotope data from this site, indicating that microbial sulfate reduction is occurring in the shallow subseafloor  (Bennett et al. , 2015). Anaerobic methaneoxidizing archaea were also frequently detected at Von Damm, including Shrimp Hole, but very rarely at Piccard. This is consistent with geochemical modelling results, where the anaerobic oxidation of methane is predicted to be moderately exergonic in ultramafic systems, but not in mafic systems  (Amend et al. , 2011, this study). The ANME lineages at Von Damm are not the same as those seen at Lost City, where a single phylotype of archaea known as the Lost City Methanosarcinales dominates  (Schrenk et al. , 2004). The presence of ANME and sulfate-reducing bacteria in the venting fluids at Shrimp Hole suggests seep-like characteristics (i.
V6 Processing, data analysis and global taxonomic comparisons Sequence quality trimming and filtering were based on paired-end reads overlap analysis of Illumina sequence reads, as described in  Eren and colleagues (2013)  and the Supporting information. Oligotyping analysis is also described in the Supporting information. Quality-filtered V6 reads are publicly available through the VAMPS database (https://vamps. mbl. edu) under the projects JAH_MCR_Av6 and JAH_MCR_Bv6. Raw reads for V6 are available in the NCBI Short Read Archive under Accession Number PRJNA258374. Given the focus of this study on subseafloor organisms and the dramatic differences in depth between the two sites, we distinguished vent-specific microbial communities from background seawater communities that mix with venting fluids at the point of sampling or in the shallow seafloor by removing 16S rRNA gene operational taxonomic units (OTUs) that also occurred in seawater (Niskin samples at more than 0.
16S rRNA gene amplification, cloning and sequencing Full-length archaeal 16S rRNA genes were PCR amplified on an Eppendorf thermal cycler using the primers ARC-8F (5′-TCCGGTTGATCCTGCC-3′) and ARC-1492R (5′-GG CTACCTTGTTACGACTT-3′) on DNA from Hot Cracks #2 and Base of Lung Snack fluid samples collected at Von Damm and Piccard, respectively, as described in the Supporting information. Representative clone sequences are available at NCBI under accession numbers KJ622295-KJ622297.
Metagenomics Ginger Castle from Von Damm and Shrimp Gulley #2 from Piccard were analysed for shotgun sequencing of total community DNA. DNA was sheared to 175 bp using a Covaris S-series sonicator, and metagenomic library construction was completed using the Ovation Ultralow Library DR multiplex system (Nugen) following manufacturer's instructions. Metagenomic sequencing was performed on an Illumina HiSeq 1000 at the W. M. Keck sequencing facility at the Marine Biological Laboratory. All libraries were paired-end, with a 30 bp overlap, resulting in an average merged read length of 170 bp. Sequence quality trimming and filtering relied upon perfect identity of paired-end read overlaps using the Illumina-utils libraries, as described in  Eren and colleagues (2013). The two metagenomic datasets were assembled using CLC Genomics Workbench 4.
An expectation value threshold of 1e-10 was applied. Only hits with greater than 30% identity of aligned amino acid residues and alignment length of 30 amino acids (ca. a third of the average length of a prokaryote gene) were considered for the analysis. 16S RNA gene sequences were also extracted from metagenomes, as described in the Supporting information. Heat maps were created using R. In order to estimate and visualize alpha diversity in the metagenomic samples, the frequency of reads functional annotation was calculated as a function of their occurrence (including log scale) using in-house R scripts. We used the R library ggplot version 1. 0. 1 for visualization of the gene's taxonomic assignments. The metagenome raw reads are available in the European Nucleotide Archive under Study Accession Number PRJEB9204 (http://www.
Acknowledgements This work was supported through funding from the  National Aeronautics and Space Administration (NASA)   Astrobiology Science and Technology for Exploring Planets grant  ( NNX09AB756 ) to JAH,  CRG  and  JS , the  Deep Carbon Observatory 's  Deep Life I grant  to JAH, which is supported by the  Alfred P. Sloan Foundation. Ship  and vehicle time were supported via  NSF  Award  OCE106183  to CRG and JS. Chip Breier  and the crews of the  ROV Jason II  and  R/V Atlantis  provided critical support during cruise planning, at sea operations, and post-cruise analysis and interpretation. Caroline Fortunato  provided important feedback during manuscript preparation and data analysis. Hilary Morrison  provided assistance with data sequencing and archiving. Richard Fox ,  Loïs Maignien  and  A.
Structure-based lead optimization of the compounds. Structure-guided optimization was used to improve cyclophilin affinity and stability of the compounds. As ester functions are often associated with low biological stability, the first step was to replace the ester function of compound 22, which makes a key hydrogen bond with Arg55, without affecting the cyclophilin inhibitory potency. All designed compounds lacking the ester function lost their interaction with Arg55, resulting in a drastic decrease of cyclophilin inhibition (IC 50 4500 mM). This was the case of compound 23 (Table  1 ), although this compound retained all of the other key interactions of compound 22 (Supplementary Fig. 6    complex (PDB code 1YND) the side chain of Arg55 is pushed by an oxygen atom of SfA, a phenyl-pyrrolidine moiety was added to generate compound 24 (Table  1 ).
All NMR data were processed using Bruker software XwinNMR Version 3. 0, and the analyses and comparisons were made with in-house software Cindy for fragment screening. NMR experiments with compounds 22 and 27 were recorded at 25 °C on an Inova Agilent 600 MHz spectrometer equipped with a triple-resonance 1H, 13C and 15 N probe. 1 H-15 N-HSQC spectra were recorded with 50 mM protein, 200 mM compound 27 and 500 mM compound 22. Resonance assignment on ligand binding was checked using three-dimensional nuclear O ¨verhauser enhancement spectroscopy-15 N-HSQC spectra with 150 ms mixing time. 1 H and  13  C NMR spectra of compounds 22 and 25-31 are shown in Supplementary Figs  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25. Crystallization and structure determination of ligand-CypD. Crystals of apo CypD K133I suitable for ligand soaking were obtained by a procedure described by Schlatter et al.