dataesr/scientific-paragraphs-categorization huggingface dataset:
Data summary The primary discussion of the geochemical analysis was provided by  Fernandez et al. (2007a, b) , which described the results of four campaigns of data collection. Boreholes were drilled and rockcores were taken for geochemical and whole-rock analysis around the following dates (Table  1 ). Note that these are a subset of the boreholes drilled during these campaigns. The pore water analysis was conducted using two techniques. The majority of data were obtained through whole-rock analysis, whereby core samples were crushed and then leached using a solid to liquid ratio of 1:4, and the resulting fluid can be analysed. Some data were also obtained through squeezing and the extracted fluid analysed. In all cases, consistency in the squeezing results and the whole-rock analysis was good, sufficient to give confidence that the obtained results were representative.
Pore chemistry For the purposes of this simple model, the Opalinus clay is assumed to be composed of albite (71%), quartz (14%), calcite (13%) and pyrite (2%). As previously mentioned, albite and quartz are expected to be relatively inert. The initial pore water composition in the model was calculated in a separate PHREEQC calculation using the llnl. dat thermodynamic database assuming calcite and pyrite equilibrium, with Na and Cl concentrations reported by  Fernandez et al. (2007b, BVE-102)  with charge being balance on pH value. The composition is given in Table  3  and is consistent with the previous PHREEQC modelling reported  by Fernandez et al. (2007b) , which itself is consistent with the available groundwater composition data.
The fixed pore water composition was calculated in a separate PHREEQC calculation using the llnl. dat thermodynamic database  (Johnson et al. , 2000) , assuming calcite and pyrite equilibrium with Na and Cl concentrations reported by  Fernandez et al. (2007b, BVE-102)  and charge balance on pH value. The computed composition is shown in Table  3. This composition was also used as the initial pore water composition in the rock at the start of the calculations.
Reference parameterisation The model includes mineral reactions for pyrite, calcite, quartz and albite as shown in Table  4. The aqueous species included in the pore water chemistry model are listed in Table  5. log 10 K data for all aqueous and mineral species were taken from the database  (Johnson et al. , 2000). A temperature of 25 • C was assumed throughout to ensure availability of thermodynamic data, noting that this temperature is not very different from the 15 • C observed at the tunnel wall, and in the context of all the other uncertainties regarding the geochemical system, this is a relatively minor issue. The aqueous reaction subsystem was modelled assuming instantaneous equilibrium in the aqueous phase for all species. Mineral evolution was simulated with kinetics. For pyrite, the rate law of  Williamson and Rimstidt (1994)  was used: r pyrite = -A(t)k m 0.
Reaction SiO2(aq) Na + , NaSO4 -, NaHCO3(aq), NaCl(aq) Ca 2+ , CaHCO3 + , CaCO3(aq), CaSO4(aq), CaCl + HCO 3 -, CO3 2-, CO2(aq) SO4 2-, HS -, HSO4 -, H2S(aq) Mg 2+ , MgSO4(aq), MgHCO3 + , MgCO3(aq), MgCl + K + , KSO4 - Fe 2+ , Fe 3+ , FeCO3(aq), FeHCO3 + , Fe(OH)2 + , Fe(OH)3(aq), FeOH4 -, Fe(OH)2(aq), Fe(OH)3 -, Fe(SO)4(aq), FeCl + Al 3+ , Al(OH)4 -, Al(OH)3 O2(aq) Cl - H + , OH -, H2O Fig. 12. Pyrite oxidation model fit to measured data (top) and variation with pore water O2 and H + (bottom) (from  Williamson and Rimstidt, 1994). Selected model fit shown with the solid line. See Refs  (Mckibben, 1984; Moses and Herman, 1991; Nicholson et al. , 1988; Smith et al. , 1970). where the subscript i refers to the mineral (albite or quartz) with the values of the terms as given in Table  6. The rates are a fit to various experimental datasets, as shown in Fig.
Numerical implementation In this study, aqueous activities are represented using the Davies model, in which the activity coefficient i of species i is given by where A is the Debye-Hückel constant (see for example  Zhu and Anderson, 2002) , z i is the charge of species i, and the ionic strength I is defined as log 10 i = -Az i √ I 1 + √ I + 0. 2Az 2 i I (13) I = 1 2 i l i z 2 i (14) where l i is the molality (mol/kg) of species i. The activity a i of species i is then given by a i = i l i (15) Equilibrium conditions between the pore water species are represented by laws of mass action. These relate the equilibrium constant K j of the j-th species to the activities by K j = i a ˛ij i (16) where ˛ij is the stoichiometry of species i in the equation for species j. For this study, equilibrium constants have been taken from the thermodynamic database thermo.
com. V8. R6. 230  (Johnson et al. , 2000). The aqueous species are organised in the thermodynamic database so that reactions for all redox species can be expressed in terms of a collection of aqueous "basis" species, and reactions for all aqueous complex species and minerals can be expressed in terms of only basis and redox species. With sequences B 1 ,. , B N B , R 1 ,. , R N R and C 1 ,. , C N C used to index the basis, redox and complex species respectively, the mass action equations for the redox and complex species become K Rj = a -1 Rj N B i=1 a ˛BiRj Bi (17) K Cj = a -1 Cj N B i=1 a ˛BiCj Bi N R i=1 a ˛RiCj Ri (18) The activities of the redox and complex species appear with power (-1) in Eqs. (  17 ) and (  18 ) because the reactions are written so that the redox and complex species always have stoichiometry 1 in their defining reactions.
Acknowledgements The work described in this paper was conducted within the context of the international DECOVALEX Project (DEmonstration of COupled models and their VALidation against EXperiments). The authors are grateful to the funding organisations who supported the work. Quintessa Ltd. and  University of Edinburgh  were supported by the  Nuclear Decommissioning Authority  (NDA), UK; CEA was supported by  Institut de Radioprotection et de Sûreté Nucléaire (IRSN). The  Japan Atomic Energy Agency (JAEA)  and the  Institute of Rock and Soil Mechanics, Chinese Academy of Sciences (CAS)  funded DECOVALEX and participated in the work. The views expressed in the paper are, however, those of the authors and are not necessarily those of the funding organisations. The data used in this work were obtained in the framework of the  EC  project  NF-PRO  (Contract number  FI6W-CT-2003-02389 ) under the coordination of  ENRESA  ( Empresa Nacional de Residuos Radiactivos ).
Acknowledgments The authors would like to thank the  International Energy Agency team  who produced transportation analysis for the ETP 2012 including  Markus Wrake ,  Cecilia Tam ,  Alex Koerner ,  Tali Trigg ,  Hiroyuki Kaneko  and  John Dulac  (along with  Lew Fulton  and Franç ois Cuenot, authors on this paper). The publication of this paper has partly been financed by the project  METRASYS-Sustainable Mobility for Mega Cities  funded by the  German Federal Ministry of Education and Research  as part of the  program -Research for Sustainable Development of the Mega Cities of Tomorrow-Energy and Climate Efficient Structures in Urban Growth Centres‖.
The electrode was then  placed in an electrochemical cell and used as the working electrode with Ag/AgCl (1 M KCl) as reference and Pt wire as counter. All potentials are quoted vs the standard hydrogen electrode (SHE) using the conversion E SHE = E Ag/AgCl + 234 mV at 20 °C. The electrolyte was 0. 2 M MES at pH 6. 0, and all solutions were prepared using purified water (Millipore, 18 MΩ cm). Electrochemical measurements were made with an Autolab potentiostat (PGSTAT30) controlled by Nova software (EcoChemie). Impedance measurements were conducted using an Ivium Technologies COMPACTSTAT. e portable electrochemical interface and impedance analyzer, controlled by IviumSoft software. Cyclic voltammograms were recorded prior to and after impedance and chronoamperometric experiments with enzymemodified electrodes, in order to ensure that the catalytic activity of the enzyme had remained steady throughout the measurements.
The CK1-responsive phospho-proteome reveals potentially conserved clock-relevant CK1 targets Circadian effects of CK1 overexpression or inhibition must result from CK1 activity on as yet unknown clock-relevant targets in this minimal circadian model organism. To identify these CK1 targets, which might be conserved across species, the phospho-proteome of the parent line was compared to that in an overexpression line around the diurnal CK1 peak expression phase (ZT12). Following phospho-enrichment of trypsinised protein extracts of the parent line and CK1-OX8, all peptides for every identified unique phospho-site were quantified using label-free mass spectrometry. Out of all unique phospho-sites (Supplementary Dataset S1), 60 were found to be significantly differential in abundance (fold change > 1.
5, p < 0. 05, n = 5) between the parent and overexpression line (Figure  5A  Supplementary Dataset S1). The observation that the majority of significantly differential sites (52 out of 58) are up-regulated solidifies overexpression of functionally active  proteomic analysis of the phospho-proteome. A further 134 phosphorylation sites were identified as differential between mock-treated and inhibited cells (Figure  5B , 5C and Supplementary Dataset S2). The majority of differential phospho-sites in treated cells is down-regulated compared to the control, in line with inhibition of kinase function by these two compounds. Larger numbers of differentially abundant peptides were identified upon treatment with PF-670462 over IC261, in line with the stronger period lengthening effect observed for this inhibitor.
Additionally, it is now apparent that the kinome constitutes a complex network of intertwined pathways rather than a collection of numerous linear transduction cascades  [41]. It is even doubtful whether linear pathways exist in protein biochemistry  [42]. Modulation of a hugely important hub kinase like CK1 will have many, practically unforeseeable, results. Complex network effects are mirrored by our observation of down-regulated phosphorylation events upon overexpression of CK1, and by up-regulated sites upon kinase inhibition (Figure  5 ). These results imply that hypotheses based on a presumption of linear kinase signalling cascades are not fit to explain experimental results described here. When the phospho-proteome was analysed at the peak of clock activity for CK1 (ZT12), we note that among all CK1responsive phosphorylation events (Supplementary Dataset S1, S2), an observed phospho-site on O.
Phospho-proteomics Protein extract (300 µg) for LC-MSMS was prepared as described  [31]. After tryptic digestion, samples were cleaned (SupelClean C18 cartridge), dried by SpeedVac, and stored at -20°C. Phospho-peptide enrichment and LC-MSMS analysis was performed as described previously  [31]. Acetonitrile and water for LC-MSMS and sample preparation were HPLC quality (Fisher, UK). Formic acid was Suprapure 98-100% (Merck, Darmstadt, Germany) and trifluoroacetic acid was 99% purity sequencing grade. LC-MS label-free quantification was performed using Progenesis 4. 0 (Nonlinear Dynamics, UK) as described in  [31]. Multicharged ions (2+,3+,4+) were extracted from LC-MS files and MSMS data was searched using Mascot Version 2. 4 (Matrix Science Ltd, UK) against the Ostreococcus tauri subset of the NCBI protein database (12/01/2011; 8,726 sequences) using a maximum missed-cut value of 2, variable oxidation (M), N-terminal protein acetylation, phosphorylation (STY), and fixed carbamidomethylation (C); precursor mass tolerance was 7 ppm and MSMS tolerance 0.
4 amu. The significance threshold (p) was <0. 05 (MudPIT scoring). A minimum peptide cut off score of 20 was set, corresponding to <3% global false discovery rate (FDR) using a decoy database search. Data were converted and validated using the Pride converter 2  [53]  and are available on the public data repository PRIDE (http://www. ebi. ac. uk/pride/), accession numbers 27556-27585. Neutral losses of phosphoric acid typical of serine and threonine phosphorylated were validated manually in all significantly differential phospho-peptides. Ambiguous sites were confirmed by cross-referencing (by sequence, charge, and quantity of residue modifications) with most probable site predictions from MaxQuant  [54]  version 1. 0. 13. 8 in singlet mode, Mascot settings as above. Where multiple occurrences of residue phosphorylation events were quantified, abundances were summed, collating all charge states, missed cuts and further modifications.
Statistical analyses Graphs and statistical analyses were made using GraphPad Prism unless otherwise stated below. CK1 sequences were aligned using Mafft 6  [55] , and 3' and 5' non-conserved regions were removed in Jalview  [56]. Maximum Likelihood was employed to infer phylogeny (using RAxML 7. 2. 8-α [57] ). No evolutionary root was assumed a priori, and a gamma model of evolutionary rate heterogeneity was used (α = 0. 67). Amino acid replacement scoring was determined using the WAG matrix  [58]. Support for branches was evaluated using bootstrap analysis with 1000 starting trees. For statistical analyses on the phospho-proteomics results, data were tested at the phosphorylation site level (see Supplementary Datasets S1 and S2). Abundances were arcsinh transformed to generate normal distributions.
Phosphosites with a significantly differential mean-abundance, compared to the control, were identified with a two-tailed t-test for independent samples. Within group means on raw values were calculated to determine the fold changes. Peptides with p<0. 05 and fold change ratio >1. 5 between groups were defined as significantly differential. To predict CK1 target sites, GPS 2. 1  [59]  was used on the v2. 0 assembly of the Ostreococcus tauri genome  [27, 60]. Peptides were aligned to the reference assembly and CK1 targets were transferred. Highly conservative cut-off threshold was used for the CK1ε classifier. Permutation-tests were used to test if the mean fold-change of CK1ε targets was significantly different to the remaining peptides in the dataset. The significance of over-or under-representation of CK1 motifs was estimated using a Monte Carlo permutation test.
Criteria were p<0. 05 and fold changes >1. 5 or <0. 67, as indicated by black lines. Red datapoints represent significantly differential phospho-sites, black circles represent those that do not change significantly. The identities of these sites can be found in Supplementary Dataset S2 (D) Chord diagram showing the numbers of identified phospho-sites whose abundance significantly differs upon drug treatment with either IC261 or PF-670462 from their respective controls (>1. 5-fold change, p<0. 05, n=5), and the overlap between the indicated data sets. Up-regulated peptides are represented in dark red, downregulated peptides in lighter red. doi: 10. 1371/journal. pone. 0070021. g005.
Supported by  BBSRC  award  BB/J009423  and SynthSys; a  Centre for Integrative Systems Biology  supported by  BBSRC  and  EPSRC  award  BB/ D019621. GvO is supported by the  Royal Society  by a  University Research Fellowship  ( UF110173 ) and a  Research Grant  ( RG120372 ). JSO is supported by the  Wellcome Trust  ( 093734/Z/10/Z ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Methods Buchnera strains and GenBank sequence accession numbers Four B. aphidicola genomes (BAp, BSg, BBp, BCc) from the following four aphids: Acyrthosiphon pisum, BA000003  [1] ; Schizaphis graminum, AE013218  [3] ; Baizongia pistaciae, AE016826  [4] ; Cinara cedri, CP000263  [5] , were used in this work. A fifth genome sequence was published recently from the aphid Cinara tujafilina (CP001817  [6] ), very closely related to BCc. As BCt and BCc show very similar genomic repertoires and properties, BCt was not always included in the analyses of this study. The annotations of transcription units (operons) in BAp are those described in  [26]. In this work, the E. coli genome was used as the reference ancestral state of the Buchnera lineage, disregarding the evolution in the branch of E. coli.
Inventory of the transcription factors encoded in Buchnera genomes The inventory of the transcription factors encoded in the Buchnera genomes was primarily carried out using the close proximity of Buchnera to E. coli and the oneto-one orthology relationship for almost all of the genes of Buchnera, as referred to in BuchneraBase  [48]. We completed this inventory by searching in the Buchnera protein set for all Pfam domains annotated as regions with putative regulatory functions  [49]. As helix-turn-helix (HTH) domains are by far the most common protein DNA-binding domains in bacteria  [50, 51] , a systematic search for these structural domains was also carried out for the complete set of proteins in Buchnera, using the HTH software  [52, 53]. Non-HTH motif predictions such as zinc fingers, helix-loop-helix, beta-sheet antiparallel or RNA binding domains are available in the generalist DNA Binding Domain Database  [54].
Annotation of the cis-regulatory elements in Buchnera Promoters and transcription starts were predicted, in the four Buchnera strains, using the software BPROM © (http://linux1. softberry. com/berry. phtml) and MacVector (MacVector, Cary, NC, USA) for σ 70 and σ 32 promoters, respectively. BPROM was calibrated for E. coli with a specificity of about 80%. In this work, predictions were made using the E. coli parameters in the 500 bp regions located upstream from all the Buchnera coding DNA sequences (CDS). The motif detection function of MacVector was calibrated using the two consensus σ 32 -boxes (CTTGAAAA and CCCCTNT), separated by 11-15 bp  [55] , with a tolerance of 50% similarity, according to previous work performed in BSg  [12]. The transcription factor binding sites (TFBS), known in E.
Interaction-graph analysis and genome rearrangements The C3P software, developed by Boyer et al. [61] , is a graph-theoretical approach extracting common connected components between two or more graphs for exploring gene neighbourhoods in a genomic and functional context. If we consider two genes, x and y, located in close proximity on the genome, the main principle of this method is that if x and y are co-regulated (i. e. , neighbours in the transcription regulatory network), or if the proteins X and Y are interacting directly (i. e. , neighbours in the protein-protein interaction network), or are catalyzing successive steps in a metabolic pathway (i. e. , neighbours in the metabolic network), the relative positioning of the genes x and y should be preserved during genome evolution if selective pressures are acting on the transcriptional, protein-protein interaction or metabolic networks, respectively.
Physical properties of the DNA molecule of Buchnera Four physical sequence-dependent properties of the DNA molecule were computed using the GeneWiz software  [25]  for the four sequenced Buchnera strains: stress-induced duplex destabilization -SIDD  [42] , curvature  [62] , base stacking energy  [41]  and base-pair propeller-twisting  [63]. The calculation of these different parameters with GeneWiz leads to a single value for each base of the DNA sequence. Non-overlapping sliding windows of different sizes were then defined to calculate the smooth parameter-distributions at different scales (e. g. , 300 bp for the whole genome sequence analysis and 20 bp for the promoter region analysis). For the whole genome comparison between Buchnera and E. coli, two null models of base composition were constructed.
Transcriptomic analyses revealed that mutants deleted for NAPs, or overexpressing them, modify the gene expression regulation of numerous genes (e. g. , 819 and 610 for ΔFiS and ΔHNS mutants, respectively, in E. coli  [19] ). However, among these genes, subgroups of more specific targets are found in the RegulonDB database  [47]. We have analysed, in BAp, the distribution of the conserved specific target genes (using E. coli as the reference ancestral model) for the five NAPs (Additional file 3). Since a neutral model of random gene deletion would predict equivalent proportions of conserved target/non-target genes for all the NAPs, no specific selection for gene conservation was found in the Buchnera strains analysed (Additional file 3). Buchnera possess the minimal set of topoisomerases required to control chromosome supercoiling: one topoisomerase I, which removes negative supercoils without consuming ATP, and one gyrase (ATP-dependent) necessary for their introduction.
Acknowledgments We would like to thank  Sylvie Reverchon  for her critical reading of this paper and  Valerie James  for the English corrections. This work was partly funded by the  Agence National de la Recherche (ANR, France)  and the  Biotechnology and Biological Sciences Research Council (BBSRC, UK) , within the  MetNet4SyBio  project. LB was the recipient of a PhD fellowship from the  French Ministry of Research  ( 2007-2010 ).
Evaluation of the endocrine disruption effect The estrogenic test was performed by the WatchFrog Company using a ChgH-GFP transgenic medaka fry line. Transgenic medaka contain a green fluorescence protein (GFP) gene regulated by the regulatory sequence of the choriogenin H (ChgH) gene. In this genetically modified organism, estrogenic activity is indicated by fluorescence when exposed to estrogenic compounds. In a typical experiment, the estrogenic test is conducted in parallel in five vials and repeated four times. The exposure time in each vial is 48 h at 26 C. After 24 h, the medium is renewed and finally, after 48 h, the fluorescence of alevin is observed with a fluorescence microscope and quantified with Image J Software. The test in each vial has a specific objective. The first three vials are used as control test.
X-Ray Diffraction Analysis XRD measurements are performed on the ©Philips x'pert MPD diffractometer operating in the reflection mode with Cu-Kα1 radiation (1. 5406 Å, 40 kV, 55 mA) and diffracted beam monochromator, using a step scan mode with a step of 0. 1˚ (2θ) and 3 s per step. Diffraction pattern obtained from the TiO 2 nanopowder is compared with reference to the Join Committee on Powder Diffraction Standards (JCPDS) database.
Data analysis All statistical tests were performed with the Statgraphics Plus software (Manugistics, Rockville, MD, USA). General linear model (GLM) procedures, using the LSD method in post ANOVA multiple mean comparison tests, were employed to test effects of soil, treatment (irradiation, substrate and yeastextract amendment, exposure to high temperature, autoclaving and toxic compounds) and time factors on CO 2 emission and O 2 consumption. When model residuals did not follow a normal distribution, the variables were log-transformed. Nonlinear regressions were used to analyse kinetics of CO 2 , O 2 concentration and enzymatic activity.
Acknowledgements. We thank  D. Tourvieille  and the " Plant and Pathogen " team of the  UMR-INRA 1095  for their technical support. We thank  P. Ambus ,  L. da Silveira Pontes , and  L. Horváth  who sampled the soil in Denmark, Brazil and Hungary, respectively;  C. Mallet  for culture analysis;  S. Revaillot ,  O. Delfosse  and  J. -L. Ollier  for chemical and isotopic analyses;  L. Genestoux ,  C. Chabalier ,  F. -X. Sauvage ,  N. Duchatau  for respiratory enzyme activity analyses,  G. Borrel  for gas spectrometry;  A. Eller ,  S. Grootemaat ,  J. Bloor  for the revision of English; and  V. Allard ,  P. Barré ,  S. Barot ,  R. Pilon ,  J. Bloor ,  M. Bahn ,  M. Wallenstein ,  Å. Blagodatskaya  and the two other anonymous referees for their constructive comments on previous versions of the manuscript.