dataesr/scientific-paragraphs-categorization huggingface dataset:
In fact, half of the 50 species present in the French national database were not considered in the gradient forest analysis. Since a minimal number of occurrences is required for the identification of meaningful thresholds (a limit of 7 occurrences was set here), species having a too sparse distribution among the sampled sites cannot contribute to the definition of community thresholds, although they might be ecologically relevant in a local or site-specific approach. In spite of the large number of explanatory variables considered, the performance of random forests was generally low to predict the biomasses of the 25 species (Fig. 2 ). Species biomass could be also better explained if descriptors of fish physical habitat were taken into account in the analysis. The inclusion of lake hydromorphological features such as the system size, substrate, macrophyte cover, ripisylve fragmentation or water level range, could improve the performance of the analysis.
The basic morphological variables used here (maximal depth, lake area and type of lake) had only a limited influence on fish biomass (Fig. 4 ). The knowledge of species manipulation in each lake would also allow a refined interpretation of the variations in biomass in particular for the species with angling and fishing interest. Unfortunately, such morphological and human impacted factors were difficult to obtain for the whole lake dataset. Hysteresis implies that a threshold in a gradient may change according to the direction in which an ecosystem evolves (degradation or restoration)  (Andersen et al. , 2009). It may be a source of uncertainty in the definition of a threshold which is not possible to evaluate with the analysis conducted here. As the number of lakes in our database which are currently getting restored is probably very low, the thresholds identified in this study rather represent protection limits that should not be exceeded.
DOC concentration naturally varies among lakes and is particularly high in lakes of the humic type. However, its concentration also depends on human activities via agriculture and waste water discharge. DOC may increase as a result of eutrophication as suggested by the correlation between TP and DOC in the dataset (r = 0. 66, S1). Thus, a limit of DOC between 1. 2 and 2 mg•L À1 might be used for the preservation of lakes presenting low natural DOC concentrations. Like DOC, water transparency (Secchi) is an integrative parameter related to the colored part of DOC but also to the suspended matter that depends on sediment input or resuspension and on lake productivity  (Carlson, 1977; Megard et al. , 1980). The gradient forest analysis revealed a Secchi depth limit of ca. 3 m separating whitefish which is associated to clear water, to common bream, white bream and pike-perch which accommodate well to turbid waters (Fig.
Acknowledgments. This research was funded by the  French National Agency for Water and Aquatic Environments (Onema). The authors are grateful (1) to the Onema agents who carried out fish sampling, (2) to the  French Water Basin Agencies  and their partners who contributed to lake data acquisition and (3) to the  AFB-Irstea consortium for Lake Hydroecology (Pôle AFB-Irstea  d'études et de recherche "hydroécologie des plans d'eau", Aix-en-Provence, France), who currently maintains the national biological and physico-chemical database for French lakes. Special thanks to  Georges Carrel ,  Samuel Westrelin ,  Nathalie Reynaud ,  Thierry Point  and to three anonymous reviewers who contributed to improve this article.
2 m distance from the source, behind a 150 mm-thick Be window acting as an interface between the under-vacuum part of the beamline and atmospheric pressure. With the beamline slits fully opened, the beam size at this location reaches 56 mm (H) Â 6. 2 mm (V). The beam intensity profiles, given by the bending magnet and electron beam properties, are flat and Gaussian in the horizontal and vertical dimensions, respectively. Fig. 2 (a) shows the experimental setup as implemented on the hard X-ray branch of the Metrology beamline. Fig. 2(b)  gives the calculated beam footprint using SpotX software  (Moreno & Idir, 2001) , together with the calculated spectrum at the sample position. The integrated photon flux over the beamline overall solid angle is about 2 Â 10 16 photons s À1 ; the integrated flux impinging on the solution over a 10 mm Â 1 mm area is about 6.
The resulting sample mix is then pushed in front of the beam by syringe B1. The exposure time is controlled by the speed at which the sample passes across the X-ray beam in the capillary. Syringe B2 is used to rinse the tubing before another sample is mixed and exposed. The sample collector rotates to collect either irradiated sample or the outflow from the washing step. For each  Experimental set-up implemented on the hard X-ray branch of the Metrology beamline. (a) Geometrical set-up for the biomolecules footprinting experiments on the hard X-ray branch of the Metrology beamline; (b) calculated pink beam footprint at the sample position for 430 mA current and considering the transmissions of a 150 mm-thick Be window, a 900 mm air path and a 10 mm-thick quartz capillary. Curves were calculated using the SpotX software, as described previously  (Moreno & Idir, 2001).
Complex formation was also confirmed by cross-linking studies (data not shown). The reaction mixture was delivered to the quartz capillary placed in front of the beam, and FH samples in the absence or presence of C3b were exposed to various radiation times ranging from 0 to 150 ms. All experiments were carried out at 21 C. Immediately after exposure, free hydroxyl radicals were quenched with 20 ml of 100 mM methionine (10 mM final concentration) and the samples were stored at À80 C.
S3 oleosin: solvent accessibility of a protein anchored in a half membrane. S3 oleosin (At4g25140, accession P29525 OLEO1_ARATH in UniProtKB data bank) is the major protein found in Arabidopsis thaliana lipid droplets. As described previously  (Vindigni et al. , 2013) , we have designed an expression system targeting S3 oleosin to Saccharomyces cerevisiae lipid droplets permitting to characterize the protein fold in native-like yeast lipid droplets environment using various biophysical methods. After purification, yeast lipid droplets harboring S3 oleosin were dialyzed against 10 mM sodium phosphate buffer at pH 7. 5. The emulsion of lipid droplets containing $5 mM of S3 oleosin was irradiated from 2. 5 to 100 ms. Subsequently, samples were collected and immediately mixed with methionine (10 mM final) and stored at À80 C.
SDS-PAGE was carried following the Laemmli protocol  (Laemmli, 1970)  and using 3-[N-morpholino]propane sulfonic acid (MOPS) running buffer. The gel was stained with Coomassie blue (Brilliant blue G-250, Sigma-Aldrich) according to  Neuhoff et al. (1988). We verified that protein backbone integrity was not affected during irradiation by scanning the gels using an EPSON Perfection 4990 PHOTO scanner, and the TIFF resulting files were analyzed using MultiGauge software from Fujifilm (St Quentin en Yvelines, France) (Fig. S1  of the supporting information). The protein bands were excised and destained using 50 mM NH 4 HCO 3 /CH 3 CN (1/1 v/v). In-gel digestion by trypsin or chymotrypsin (sequencing grade, Roche Diagnostics, Meylan, France) was carried out as previously reported  (Vermachova et al.
Bio-informatics data analysis Mass spectrometric raw data of the FH peptides were processed using ProtMapMS software  (Kaur et al. , 2009)  and manually validated using Xcalibur software (Thermo-Fisher Scientific) and the Mascot server. The proportion of unmodified peptide defined as the ratio of unmodified to the total amount of peptide (modified and unmodified) was calculated for each exposure time. The rate of oxidation of a given peptide was determined from the doseresponse plots of the proportion of unmodified peptide as a function of X-ray exposure time (ms). The dose-response plots were fit to y ¼ expðÀktÞ; ð1Þ where k is the first-order rate constant and t is the exposure time. The dose-response curves generated for each FH peptide were used to compare the oxidation extent of FH in both states (with and without C3b) and calculate the degree of protection.
The solvent accessible surface area of modified FH residues was calculated using GETAREA software (Fraczkiewicz & Braun, 1998) based on the available in-solution and crystal structural data of modules and whole FH. S3 oleosin Xcalibur raw data were transformed to mzXML open source format using ProteoWizard software version 3. 0. Subsequently, data were processed using PAPPSO's open source software: !Xtandem pipeline (available at http://pappso. inra. fr/bioinfo/) for peptide identification and detection of oxidized residues and MassChroQ  (Valot et al. , 2011). The latter was used to quantify oxidized and non-oxidized peptide by peak area integration under the extracted ion chromatogram.
Acknowledgements SOLEIL support is acknowledged under projects Nos. 20120893, 20130817 and 20140760. We also thank the general technical staff of SOLEIL for smooth running of the facility, and the SOLEIL mechanical engineering group for courteously providing the Metrology beamline layout. TC, YG and PJ were supported by a grant from  INRA CEPIA department :  OlSoleilMiox  project. We also warmly thank  B. Valot  and  M. Davanture  ( PAPPSO proteomic platform ) for precious help.
Computer simulations of the glycolysis and fermentation network in yeast We modeled the glycolysis and fermentation network in yeast using a simplified topology in which there was one input flux, the rate of glucose consumption, and two output fluxes, the rate of glycerol production and the rate of transformation of pyruvate into acetaldehyde (Fig  3 ). The system of ordinary differential equations we used was derived from Conant & Wolfe's model  [80]  obtained from the Biomodels database (http://www. ebi. ac. uk/biomodels-main/). This model is a slightly different version of a previously published model  [81]. We modified this model in order to increase the range of enzyme concentrations that can lead to a steady state. First, we excluded the reactions producing trehalose and glycogen because, due to their constant rates, they caused incompatibility when the entry of glucose decreased.
Second we suppressed mitochondrial shuttling, which is a composite reaction, because it is not associated with any enzyme. Thus our model included 17 reactions and 22 metabolites, including 6 cofactors (ATP, ADP, AMP, NAD, NADH and Fru-2,6-BP) (Fig  3 ). For all simulation conditions (see below), we solved the system of ordinary differential equations numerically using solvers (deSolve package) of the Runge-Kutta family  [82]  implemented within the R software tool (R Development Core Team 2010). We considered that the steady state was reached when metabolite concentrations varied less than 10 -4 between two successive time steps. Conant & Wolfe's model uses the maximal enzymatic rate V max , i. e. there is no explicit expression of enzyme concentration and catalytic constant k cat. To simulate variation in enzyme concentrations we needed to know the k cat values and molecular weights of the enzymes.
We found most k cat values in the Brenda database (http://www. brenda-enzymes. info/). When they were not known in yeast, we used data from other organisms. We found k cat values for 11 enzymes (S3 E ref = V max M r k cat , where M r is the molecular weight of the enzyme (S3 Table ). As expected, the flux response to variation in concentration of each enzyme, with the other 10 concentrations being maintained at their reference values, displayed saturation curves in most cases. However, for certain enzymes the reference concentration was far or very far along the plateau, so that varying the concentration was almost without effect on the fluxes. Therefore we tried to arbitrarily decrease the reference values of these enzymes, but as a consequence the rate of successful simulations decreased dramatically.
Acknowledgments We dedicate this work to  Pr. André Gallais , who brought us his impressive knowledge of heterosis. We thank  Dr. Catherine Damerval ,  Dr. Michel Zivy ,  Dr. Mélisande Blein-Nicolas ,  Dr. Warren Albertin ,  Dr. Philippe Marullo  and  Dr. François Vasseur  for exciting discussions on heterosis and for useful suggestions for improving the manuscript. We also thank  Marianyela Petrizzelli  for her help in checking the mathematical developments and  Dr. Hélène Citerne  for English corrections. This work was supported by the  ANR program  " ALIA " HeterosYeast  ANR-08-ALIA-9.
Quantitative RT-PCR. Total RNA extraction of mice renal cortex was performed by using Qiazol (Qiagen), according to manufacturer's recommendations. RNA was reverse transcripted by using the Quantitect Reverse Transcription kit (Qiagen) according to the manufacturer's protocol. The Maxima SYBR Green/Rox qPCR mix (Thermo Scientific Fermentas) was used to amplify cDNA for 40 cycles on an ABI PRISM thermocycler. The comparative method of relative quantification (2-DDCT) was used to calculate the expression level of each target gene, normalized to Ppia. The oligonucleotide sequences are available upon request. The data are presented as the fold change in gene expression. 2. 5. Histopathology and Immunohistochemistry. Kidneys were immersed in 10% formalin and embedded in paraffin. Sections (4 μm thick) were stained with hematoxylin/ eosin or Masson's trichrome and processed for histopathology or immunohistochemistry.
Acknowledgments The authors thank  Elizabeth Huc  and the ERI970 team for assistance in animal care and handling. The authors thank  Véronique Oberweiss ,  Annette De Rueda ,  Martine Autran ,  Bruno Pillard , and  Philippe Coudol  for administrative support. This study was supported by  INSERM  and the  Joint Transnational Call 2011 for "Integrated Research on Genomics and Pathophysiology of the Metabolic Syndrome and the Diseases arising from it" from l ' Agence Nationale de la Recherche, France  (to Pierre-Louis Tharaux).
(4) Examples of projects with EBV-relevant data products Due to the vast variability in spatial, temporal and taxonomic resolution and extent, as well as measurement units considered by different species distribution and abundance data sets, there is currently no comprehensive global database that fulfils all ideal requirements for EBV data products (see Table  2 ). As an alternative, different species distribution and abundance EBV data products could be built based on consistent global or regional data sets that are available for particular taxa. Herein, we selected as examples four projects that have compiled such data sets, covering both the terrestrial and marine realms (Table  3 ). We use these projects to identify how EBV-useable data sets, EBV-ready data sets and derived and modelled EBV data are produced from raw observations and how projects implement the data processing in a workflow environment.
Despite advantages, several problems exist with DNA-based surveys. Common marker sequences (e. g. 18S, 28S and 16S rRNA genes, or the ribosomal internal transcribed spacer) may not yield sufficient variation for species identification. Mitochondrial genes (e. g. cytochrome oxidase I) can identify species, but their use in large-scale and long-term projects is constrained by tremendous variation in primer use, amplification steps and sequencing platforms  (Bucklin et al. , 2016). Most species also have insufficient reference sequences in public archives such as GenBank, and a universal taxonomic system that allows combining the operational taxonomic units (OTUs) with the traditional Linnaean names is still lacking  (Kõljalg et al. , 2016). Nevertheless, DNA-based techniques have many advantages for assessing species distributions when compared to in situ field observations, including identification of cryptic organisms or incomplete individuals (Fig.
g. the matching of taxonomic names (step 5) and data quality-control procedures (step 6) -were implemented at different points in the workflow (Fig. 4 ). Moreover, workflow steps such as checking data-sharing agreements and licenses (step 2) or combining data sets from different sources (step 4) are often done by these projects before the EBV workflow starts. For instance, data-sharing agreements and licenses (step 2) were already arranged between data aggregators and key data providers before step 1. This allowed the raw data to enter the workflow, e. g. by agreeing to use data for all non-commercial purposes or by signing specific data-sharing agreements (Fig. 4 ). Of key importance is the publication of data products (Fig. 3 ). The eBird data (i. e. EBV-useable and EBV-ready data sets) can be requested from the eBird portal (http:// ebird.
org/ebird/data/download; this requires registration and login). Additional bar charts, maps, graphs, tables and visualization tools can also be explored (see http:// ebird. org/ebird/explore). For TEAM, the camera trap data (i. e. EBV-useable and EBV-ready data sets) are publicly available (http://www. teamnetwork. org/data/query) and the modelled occupancy time series for each population at each site (i. e. derived & modelled EBV data) can be downloaded (http://wpi. teamnetwork. org/wpi/dashboard). The LPI provides the individual records for each time series (i. e. the EBV-useable data set) -excluding about 3000 time series with confidential data -through its data portal (http://livingplanetindex. org/data_portal) as well as with the latest publication  (McRae et al. , 2017)  and as part of the Living Planet Report (http://www.
livingplanetindex. org). All data used in BALTIC were downloaded from the Swedish LifeWatch portal  (Gärdenfors et al. , 2014)  for marine monitoring data (EBV-useable data set), while processed data were stored in the data archives of Environment Climate Data Sweden (https://ecds. se/ under file identifier: ccc84507-49c1-43df-9887-97d2232bcb89), including the harmonized data (EBV-ready data set) and the statistically analysed data (derived & modelled EBV data). Despite these publishing efforts by all four projects, their data sets are published in different ways, and limited consistency and adoption of data and metadata standards is apparent.
(4) Legal interoperability in EBV workflows The above-mentioned workflow assumes legal interoperability, i. e. a condition where: (i) the legal use conditions can be clearly and readily determined for each data set; (ii) the legal use conditions for each data set allow for both creation and use of combined, or derivative products; and (iii) users can legally access and use each data set without seeking authorization from data rights holders on a case-by-case basis (RDA-CODATA Legal Interoperability Interest Group, 2016). Legal interoperability is therefore an important requirement for automated workflows and for the successful development of EBV data products. However, there are many cases where raw data and data sets might not   3  and Appendix S1. be 'findable, accessible, interoperable and reusable' (FAIR principles;  Wilkinson et al.
(a) Constraints on legal interoperability Key constraints on legal interoperability emerge from restrictions on data use, modification and sharing. For instance, legal interoperability is constrained when data sets are protected by different intellectual property rights (IPRs), e. g. U. S. copyright law or E. U. Database protection. Other restrictions on data access and re-use can come from national security regulations, protection of endangered species, other types of confidentiality, individual use agreements (e. g. contracts, licenses and disclaimers) as well as incompatible data policies of different data sets for the same species. In many situations, individual researchers and research teams act as if data were proprietary, and the use of data is not necessarily designated as open. When data sets are made accessible only on a case-by-case basis or if they are kept secret, legal interoperability is not achievable.
Restrictions on data access, use and sharing therefore have severe consequences for building EBV data products. For instance, including copyrighted or otherwise restricted raw data in EBV data products can impede quality control, limit data aggregation and restrict re-usability. Building EBV data products that involve proprietary data or sensitive data (e. g. because of threatened or endangered species) could lead to situations where different results are produced by different researchers. Moreover, legal interoperability becomes a key issue when combining data from multiple sources because the most restrictive access rights of an included data set will dictate the access rights of the whole EBV data product. Existing legal mechanisms therefore need to be promoted and enforced to ensure open access and legal interoperability (RDA-CODATA Legal Interoperability Interest Group, 2016).
e. placed in the public domain) is combined with data licensed as CC BY (i. e. attribution only) and also combined with data licensed as CC BY-NC (i. e. with attribution and only for non-commercial uses), then the resulting EBV data product will contain the most stringent license type (here, CC BY-NC). This is problematic because it limits the re-use of the EBV data product by imposing conditions of attribution and non-commercial use. Moreover, two of the six CC license types are incompatible with each other because they do not permit modification (Table  5 ). Hence, the ideal data sets for building EBV products are those in the public domain, with no restrictions on re-use and attribution (i. e. no need to specify source and license). If conditions for re-use are limited to attribution, the only legal requirement will be to include sufficient metadata to indicate the data source and the appropriate standardized license, if one is needed.
(5) Technical requirements for a workflow-oriented production There are multiple technical requirements related to a workflow-oriented production of global EBV data products. Interoperable computing infrastructure and promotion of the development, sharing and use of workflows is needed  (Hardisty et al. , 2013; Gärdenfors et al. , 2014; Kissling et al. , 2015; Enquist et al. , 2016). This includes agreeing and adopting appropriate structural formats for EBV data products, for means of data storage and for the execution and implementation of EBV workflows. data (e. g. raster and vector) from the Open Geospatial Consortium (OGC)  (Hugo et al. , 2017). GEO BON and the wider scientific community (e. g. data producers and product developers) should therefore develop recommendations and agreements on the most appropriate data models and file formats for EBV data products.
(b) Data storage EBV data products must be stored and managed on a long-term, semi-permanent basis. It is presently unclear who can take the burden of the storage commitment, and how this will be funded. The means of investment will depend on whether the semi-permanent storage of EBV data products will be done centrally (i. e. in a single repository, perhaps with duplicated mirror sites) or as a network of distributed, independent but interoperable storage services. The GEO BON Secretariat may host a selection of derived and modelled EBV data, but rely on partners such as GBIF nodes to host other EBV data products, including EBV-useable and EBV-ready data sets. Any large-scale trusted data repository for EBV data products must offer quality assurance as well as publishing and archival services so that different Biodiversity Observation Networks (BONs) and other actors can contribute to, manage and publish high-quality EBV data products.