dataesr/scientific-paragraphs-categorization huggingface dataset:
Data collection and processing C. efficiens FAS I crystals were transferred to a cryoprotectant solution consisting of 20% ethylene glycol in the crystallization buffer, picked up in a nylon-fibre loop and plunged into liquid nitrogen. All crystals were exposed to single-wavelength X-radiation on beamline ID14-4 at the European Synchrotron Radiation Facility (ESRF) and maintained at 100 K while data were recorded on a CCD detector (ADSC Quantum Q315r). Individual diffraction images from C. efficiens FAS I crystals were initially indexed with iMosflm  (Battye et al. , 2011)  to determine the crystal form. Data were processed with the xia2 suite of programs  (Winter, 2010)  running the XDS package  (Kabsch, 2010)  and AIMLESS  (Evans, 2006). Crystals gave two different crystal forms in space groups R32 and C2 with differing unit-cell parameters (Table  3 ), designated crystal forms I and II.
Results and discussion We have recently established protocols for the recombinant overexpression of M. tuberculosis and C. ammoniagenes FAS I. C. efficiens, which is evolutionarily related to C. ammoniagenes, is reported to be moderately thermotolerant  (Nishio et al. , 2003) , and we expected a higher conformational stability of its protein inventory. Two FAS I-coding genes (FAS A, NP_737523. 1, and FAS B, NP_739002. 1) were identified in C. efficiens  (Stuible et al. , 1997). FAS B (UniProt accession code Q8FMV7) was picked as a target for our studies owing to its higher sequence identity to M. tuberculosis FAS I (44 and 52% for FAS A and FAS B, respectively). About 5 mg of protein per litre of E. coli expression culture was obtained after chromatographic purification (Fig. 2a ). The hexameric conformation was monitored by size-exclusion chromatography (Fig.
This indicated the presence of one molecule in the asymmetric unit and the absence of noncrystallographic symmetry. In case of crystal form II, up to six chains (a whole hexamer barrel) can be accommodated in the asymmetric unit, indicating clear noncrystallographic Data collection and processing. Values in parentheses are for the outer shell. symmetry. For crystal form II, search templates comprising the hexameric barrel, a trimeric dome, a dimer or a monomer individually did not yield unique solutions in the molecularreplacement analysis. In the case of crystal form I, the phase problem could be solved by molecular replacement (MR) using the structural model of M. smegmatis FAS I  (Boehringer et al. , 2013 ; PDB entry 3zen) as a model in MOLREP  (Vagin & Teplyakov, 2010)  with the help of the CCP4 suite.
The MR solution was confirmed with  Phaser (McCoy et al. , 2007) , which gave an LLG score of 424 and a TFZ score of 26. It should be noted that the overall sequence identity between C. efficiens FAS I and M. smegmatis FAS I is 53% (with 67% positives and 4% gaps; data from BLAST;  Altschul et al. , 1990). A pairwise alignment between the protein sequences of M. smegmatis FAS I and C. efficiens FAS I was used in phenix. sculptor (Bunkoczi & Read, 2011)  from the PHENIX package  (Adams et al. , 2010)  to mutate the MR solution (PDB) file to the C. efficiens FAS I sequence. An immediate rigid-body refinement with the different domains (sequence ranges:  AT, 10-367; ER, 368-879; SBS, 880-1002; DH, 1003 DH, -1289;; MAT, 1290 MAT, -1674;; DM, 1953 DM, -2065;; KR, 2073 KR, -2357;; KS, 2358-3022)  as independent rigid groups using PHENIX gave R and R free values of 0.
Acknowledgements We are grateful to  Dieter Oesterhelt , who supported this project in its early phase. We are also grateful to  Werner Ku  ¨hlbrandt for his continuous support of our research focus on the structural characterization of FAS megaenzymes. We thank  Jan Gajewski  for cloning C. efficiens  AcpS  and for collecting LC-MS data on the C. efficiens FAS I product spectrum. We also thank  Alexander Rittner  and  David Wirthensohn  for assistance when starting this project and for valuable discussions. Lastly, we thank  Andreas Bracher  for his assistance in synchrotron data-collection trips and the  EMBL-ESRF Joint Structural Biology Group  for help on the ESRF beamlines. This work was supported by the  German Research Foundation  ( DFG  Project  GR3854  to MG) and by the  Cluster of Excellence Frankfurt (CEF) 'Macromolecular Complexes' at the Goethe University Frankfurt (CEF   Adjunct Investigatorship Program ).
Nuclear Genomic and Transcriptomic Data Acquisition Raw or assembled nuclear genomic and/or transcriptomic data were retrieved from public databases or generated in our laboratory (table 1). Transcriptome assemblies for the sponge species Aphrocallistes vastus, Chondrilla nucula, Corticium candelabrum, Crella elegans, Ircinia fasciculata, Petrosia ficiformis, Spongilla lacustris, and Sycon coactum were downloaded from the Harvard Dataverse Network, doi:10. 7910/DVN/ 24737 and doi:10. 7910/DVN/24737 (Riesgo et al. 2012 (Riesgo et al. , 2014)). Transcriptome assemblies for Oscarella carmela and Ephydatia muelleri were obtained from the Compagen database  (Hemmrich and Bosch 2008) ; those for the octocoral Gorgonia ventalina  (Burge et al. 2013)  were acquired from FigShare  (Burge et al. 2012).
Transcriptome data for nine species of ctenophores  (Moroz et al. 2014)  were downloaded from the Pleurobrachia Neurobase Database (neurobase. rc. ufl. edu/pleurobrachia/browse, last accessed June 2014). Additional RNA-Seq libraries were obtained for the filisterean Ministeria vibrans, and the mesomycetozoan Creolimax fragrantissima (accessible on the NCBI [National Center for Biotechnology Information] Sequence Read Archive, SRR1029670 and SRR343051 respectively), with assemblies courtesy of In ˜aki Ruiz-Trillo at the Institut de Biologia Evolutiva (WP personal communication, April 2014). We downloaded predicted proteomes from the complete genomes of Amphimedon queenslandica  (Srivastava et al. 2010) , Mnemiopsis leidyi  (Ryan et al. 2013) , Pleurobrachia bachei  (Moroz et al. 2014) , Trichoplax adhaerens  (Srivastava et al.
2008) , Nematostella vectensis  (Putnam et al. 2007) , from their respective databases (table 1), and proteomes for Monosiga brevicolllis, Salpingoeca rosetta, Capsaspora owczarzaki, Sphaeroforma arctica from the Origins of Multicellularity Database  (Ruiz-Trillo et al. 2007 ). In addition, a whole-genome assembly from a Calcinean calcareous sponge Clathrina sp. was shared with us by Maja Adamska and Marcin Adamski at the Sars International Centre for Marine Biology  (DL personal communication, April 2014). Finally, we used Illumina DNAseq data for C. candelabrum generated in our lab. This data set was generated as described in  Haen et al. (2014)  from a specimen collected at the Endoume marine station in Marseille, France. A total of 59,853,912 paired-end reads were assembled using SOAPdenovo2  (Luo et al.
2012 ) with a k-mer size of 63, and the raw reads have been placed in the NCBI Sequence Read Archive under accession SRR2021567. The assembled data set has been placed on FigShare (doi: 10. 6084/ m9. figshare. 1412681). Complete mtDNA of P. ficiformis was amplified in two fragments by LA-Taq PCR (polymerase chain reaction) (Takara), which were pooled with other samples and submitted to the Iowa State University DNA Facility for library preparation and sequencing. The DNA library was prepared using the TruSeq kit and sequenced on the Illumina HiSeq 2500 platform. The mtDNA sequences were assembled with a modified PCAP package  (Huang et al. 2003; DL personal communication). Assembled mtDNA sequence was compared and found nearly identical with partial assemblies from P. ficiformis RNA-Seq data  (Riesgo et al.
2014 ). The complete mtDNA from Cr. elegans was also assembled using a modified PCAP packaged from RNA-Seq data obtained at the NCBI Sequence Read Archive, accessions SRR648558, SRR648671, FIG. n o i s s e c c A / e c n e r e f e R Y W V T S R Q P N M L K 2 I 1 I H G F E D C A s e i c 1. -Mitochondrial-encoded tRNA gene content in animals and unicellular relatives. For each group or species, filled squares indicate the presence of an mt-tRNA gene of the amino acid identity indicated at the top of each column. Gene content was determined using previously published annotated sequences or by surveying relevant literature (Reference/Accession column). The labels I1 and I2 indicate genes for mt-tRNA Ile (GAU) and mt-tRNA Ile (CAU), respectively. and SRR648683. The complete mtDNA sequences from Cr.
elegans and P. ficiformis have been deposited in GenBank under the accessions KR911862 and KR911863, respectively. Phylogenetic Profiling for Target Genes Eukaryotic sequences for each type of aaRS and the subunits of GatCAB were obtained from the Homologene database and multiple sequence alignments of these sequences were constructed using MAFFT 6 with the -globalpair option  (Katoh and Toh 2008). We constructed Hidden Markov Models (HMMs) using HMMER 3 for these alignments  (Finn et al. 2011) , which were then used to search the genome or transcriptome of each target organism with an e-value cutoff of 1e-5. BLASTP searches were conducted against the NCBI RefSeq database using the resulting hits to check for homology with the target gene. Regions from the resulting set of sequences that aligned with the eukaryotic HMMs were saved for phylogenetic analysis.
When no genomic sequences were available to refine transcriptomic data, HMM searches often produced a very large number of fragmentary hits, which aligned only partially to the query profile, or which showed high similarity with bacterial sequences. Thus, a phylogenetic profiling step was performed to identify homologous eukaryotic fragments and filter out prokaryotic contaminants. First, prokaryotic alignments were constructed based on reviewed amino acid sequences from reference proteome sets contained in the UniProt database. These alignments were combined with the previously constructed eukaryotic alignments and used to estimate phylogenetic trees with PhyML 3. 0 (see phylogenetic analysis)  (Guindon et al. 2010). The identities of partial transcripts obtained in the HMM profiling step were determined using pplacer  (Matsen et al.
2010) , by calculating the maximumlikelihood branching point for each fragment on the corresponding phylogenetic tree, conditioned on the alignment used to construct the tree and previous maximum-likelihood estimates of the branch lengths and other model parameters. Sequences that were placed inside of a eukaryotic lineage were retained for further analysis. Following this initial round of phylogenetic profiling, new HMM profiles were constructed from subalignments containing only eukaryotic sequences. These were then used to conduct a repeated round of phylogenetic profiling to verify the absence of some more poorly conserved genes that may have been represented only by short fragments that do not share a high degree of similarity with sequences in the Homologene database. Candidate homologs identified by this procedure were checked for structural homology with the target sequences using the Phyre 2 protein fold prediction server  (Kelley and Sternberg 2009).
To identify TilS homologs, fungal TilS sequences were obtained based on the accession numbers listed in  Xavier et al. (2012). These sequences were used to construct an HMM profile, which was then utilized to query each target genome and/or transcriptome. The HMM profiles, sequence alignments used to generate them and all sequence alignments, trees and PhyML statistics files used during the pplacer profiling step have been made available on FigShare (doi: 10. 6084/m9. figshare. 1412684).
2B ). Columns marked by amino acids shaded in gray indicate aaRS lineages that emerged through duplication of a single eukaryotic ancestor (fig. 2C  and D ). Dark gray boxes correspond to the choanoflagellate AsnRS that group with sequences from plants (supplementary fig. S4M , Supplementary Material online). The * by H. sapiens indicates results that were obtained from previously annotated sequences in the Homologene database (accession numbers can be found in supplementary material, Supplementary Material online). including species that do not encode corresponding mt-tRNAs, indicating that these enzymes may carry out functions distinct from the direct aminoacylation of mt-tRNAs (fig. 4  and 5 ). In particular we found homologs of each of these enzymes in A. queenslandica whose mt-DNA does not encode mt-tRNA Asp , as well as I.
More data from underrepresented animal lineages that have lost mt-tRNAs, including the bilaterian phylum Chaetognatha  (Faure and Casanova 2006) , and some additional groups of sponges will help to shed more light on the dynamic evolution of mitochondrial translation. FIG. 6. -Phylogenetic profiling for nuclear-encoded GatCAB, TilS, and MRPP3 homologs. For each species, filled squares indicate the successful identification of a mt-tRNA processing enzyme. Letters in H. sapiens indicate results that were obtained in previous studies (a,  Nagao et al. 2009; b, Reinhard et al. 2015). The absence of TilS in human was verified by our profiling procedure using version GRCh38 of the Ensembl human proteome assembly.
EnsemblMetazoa 25; f, Compagen Database; g, Sars International Center for Marine Molecular Biology (DL personal communication); h, Pleurobrachia Neurobase (neurobase. rc. ufl. edu/pleurobrachia/browse); i, NIH Mnemiopsis Genome Portal; j, Joint Genome Institute; k, FigShare, doi: 10. 6084/m9. figshare. 9432. Mitochondrial Sequence Data Acquisition mt-tRNA content was determined based on previously published/annotated mt-genomes (fig. 1). Individual mt-tRNA sequences were extracted from mitochondrial genomes of the protozoans Ca. owczarzaki KC573038, and Mo. brevicollis NC_020370; the homoscleromorph O. carmela NC_009090; demosponges Amphimedon compressa NC_010201, A. Axinella corrugata NC_006894, Chondrilla nucula NC_010208, E. muelleri NC_010202, Geodia neptuni NC_006990, Igernella notabilis NC_010216, Negombata magnifica NC_010171, Suberites domuncula NC_010496, Tethya actinia NC_006991, and Xestospongia muta NC_010211; the glass sponges Ap.
Acknowledgments The authors are grateful to  Dr Alexander Ereskovsy  and  Dr Manuel Maldonado  for providing specimens of C. candelabrum and P. ficiformis, respectively, and to  Dr Maja Adamska  and  Dr Marcin Adamski  for sharing unpublished genomic data of Clathrina sp. They also thank  Dr In ˜aki Ruiz-Trillo  for providing transcriptome assemblies for several species of protists. They thank  Dr Xiaoqiu Huang  for his help with the  PCAP program. They also thank the editor and an anonymous reviewer for helpful comments on an earlier version of this manuscript. This research was supported by a grant from.
vastus NC_010769, Hertwigia falcifera KM580071, Iphiteon panacea EF537576, Sympagella nux EF537577, Tabachnickia sp. KM580074, Vazella pourtalesi KM580075; the placozoan T. adhaerens NC_008151; the cnidarian Nematostella sp. NC_008164; and the bilaterians Anopheles gambiae NC_002084, Caenorhabditis elegans NC_009885, Strongylocentrotus purpuratus NC_001453, and Homo sapiens NC_012920. Species Data Type Source P T G Aurelia aurita x f Hydra magnapapillata x j NOTE. -P, predicted proteome; G, genome assembly; T, transcriptome assem- bly. a, NCBI Sequence Read Archive (SRR102967, SRR34305); b, Broad Institute origins of Multicellularity Database; c, Harvard Dataverse Network, doi:10. 7910/ DVN/25071, doi:10. 7910/DVN/24737; d, FigShare, doi: 10. 6084/m9. figshare. 141268; e,.
A. Magnetic field mapping The stray magnetic fields in an NMR or MRI laboratory depend on many parameters. During a dissolution-DNP experiment, the hyperpolarized fluid must travel through the space between two magnets. The fate of the hyperpolarization depends on the strength and orientation of the stray fields. We have mapped the field between our polarizer and an unshielded 300 MHz NMR spectrometer using a triple-axis Hall probe (Sentron Digital 3D Teslameter, Type: 3MS1-A2-D3) using custom-designed National Instrument Labview software. Rev. Sci. Instrum. 86, 024101 (2015) FIG. 1. Experimental arrangement in our laboratory consisting of a 6. 7 T DNP polarizer (middle) coupled to an unshielded 300 MHz spectrometer (left) and to an ultra-shielded 500 MHz magnet (right), either through a "vertical" magnetic tunnel, i.
The final TEMPOL concentration therefore usually ranges between 1 and 5 mM. In order to minimize relaxation during the relatively slow displacements of the shuttle, we decreased the TEMPOL concentration to 0. 25 mM (4-20 times below the usual concentrations in routine dissolution-DNP experiments) so that the paramagnetic contribution to the relaxation rate is R 1 para < 1 s -1. The relaxation rates R 1 ( 1 H) of bromothiophene carboxylate were measured in ten different magnetic fields B 0 = 7. 05, 1. 0, 0. 4, 0. 10, 0. 022, 0. 01, 0. 004, 0. 002, and 0. 001 T. A single acquisition of the 1 H spectrum at 7 T sufficed for each data point. Figure  2  shows the longitudinal relaxation rates R 1 ( 1 H) = 1/T 1 ( 1 H) in BTC. In sample 3, where the paramagnetic oxygen has been scavenged by sodium ascorbate, T 1 ( 1 H) is independent of the magnetic field down to 1 mT.
ACKNOWLEDGMENTS The authors thank  Martial Rey  and  Anto Barisic  for valuable assistance. This work was supported by the  Swiss National Science Foundation (SNSF) , the  Ecole Polytechnique Fédérale de Lausanne (EPFL) , the  Swiss Commission for Technology and Innovation (CTI) ,  Bruker BioSpin Switzerland AG , the  French CNRS , and the  European Research Council  ( ERC  Contract No. 339754  "Dilute para-water").
Using the United Nations COMTRADE database [1]  we construct the Google matrix G of multiproduct world trade between the UN countries and analyze the properties of trade flows on this network for years 1962 -2010. This construction, based on Markov chains, treats all countries on equal democratic grounds independently of their richness and at the same time it considers the contributions of trade products proportionally to their trade volume. We consider the trade with 61 products for up to 227 countries. The obtained results show that the trade contribution of products is asymmetric: some of them are export oriented while others are import oriented even if the ranking by their trade volume is symmetric in respect to export and import after averaging over all world countries. The construction of the Google matrix allows to investigate the sensitivity of trade balance in respect to price variations of products, e.
At present the COMTRADE database contains data for N c = 227 UN countries with up to N p ≈ 10 4 trade products. Thus the whole matrix of these directed trade flows has a rather large size N = N p N c ∼ 10 6. A usual approach is to consider the export and import volumes, expressed in US dollars (USD). An example of the world map of countries characterized by their import and export trade volume for year 2008 is shown in Fig. 1. However, such an approach gives only an approximate description of trade where hidden links and interactions between certain countries and products are not taken into account since only a country global import or export are considered. Thus the statistical analysis of these multiproduct trade data requires a utilization of more advanced mathematical and numerical methods.
The main problem of construction of such a matrix is not its size, which is rather modest compared to those studied in  [10] , but the necessity to treat all countries on democratic grounds and at the same time to treat trade products on the basis of their trade volume. Indeed, the products cannot be considered on democratic grounds since their con-tributions to economy are linked with their trade volume. Thus, according to Table  2 , in year 2008 the trade volume of Petroleum and petroleum products (code 33 in Table  1 ) is by a factor 300 larger than those of Hides, skins and fur skins (undress. ) (code 21 in Table  1 ). To incorporate these features in our mathematical analysis of multiproduct WTN we developed in this work the Google Personalized Vector Method (GPVM) which allows to keep a democratic treatment of countries and at the same time to consider products proportionally to their trade volume.
Google matrix construction for the WTN For a given year, we build N p money matrices M p c,c of the WTN from the COMTRADE database [1] (see  [11] ). M p c,c = product p transfer (in USD) from country c to c (1) Here the country indexes are c, c = 1,. , N c and a product index is p = 1,. , N p. According to the COMTRADE database the number of UN registered countries is N c = 227 (in recent years) and the number of products is N p = 10 and N p = 61 for 1 and 2 digits respectively from the Standard International Trade Classification (SITC) Rev. 1. For convenience of future notation we also define the volume of imports and exports for a given country and product respectively as V p c = c M p c,c , V * p c = c M p c ,c. (2) The import and export volumes V c = p V p c and V * c = p V * p c are shown for the world map of countries in Fig.
23 ). Even if the UN COMTRADE database contains a lot of information there are still open questions if all essential economic aspects are completely captured in this database. Indeed, the COMTRADE data for trade exchange are diagonal in products since there are no interactions (trade) between products. However, this feature may be a weak point of collected data since in a real economy there is a transformation of some products into some other products (e. g. metal and plastic are transferred to cars and machinery). It is possible that additional data should be collected to take into account the existing interactions between products. There are also some other aspects of services and various other activities which are not present in the COMTRADE database and which can affect the world economy.
One of the important missing element of COMTRADE are financial flows between countries. Indeed, the product 93 Special trans. (see Tables  1, 2 ) partially takes into account the financial flows but it is clear that the interbank flows are not completely reported in the database. In fact the Wold Bank Web (WBW) really exists (e. g. a private person can transfer money from his bank account to another person account using SWIFT code) but the flows on the WBW remain completely hidden and not available for scientific analysis. The size on interbank networks are relatively small (e. g. the whole Federal Reserve of USA has only N ≈ 6600 bank nodes  [27]  and there are only about N ≈ 2000 bank nodes in Germany  [28] ). Thus the WBW size of the whole world is about a few tens of thousands of nodes and the Google matrix analysis should be well adapted for WBW.
All data are obtained from the COMTRADE database[1]. We used products from COMTRADE SITC Rev. 1 classification with number of products N p = 10 and 61. We choose SITC Rev. 1 since it covers the longest time interval. The main results are presented for N p = 61 with up to N c = 227 countries. The names of products are given in Table1, their ImportRank index K and their fraction (in percent) of global trade volume in years 1998 and 2008 are given in Table2. The data are collected and presented for the years 1962 -2010. Our data and results are available at [25] , the data for the matrices M p c,c.
In this study, we explored mitochondrial haplogroups as potential modifiers of breast cancer risk in women carrying pathogenic BRCA1 or BRCA2 mutations. Our study includes females diagnosed with breast cancer and unaffected carriers belonging to CIMBA. We used an original analytic phylogenetics-based approach implemented in a homemade algorithm and in the program ALTree  [33, 34]  to infer haplogroups and to detect associations between haplogroups and breast cancer risk.