dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments The authors acknowledge  Douglas Micheau-Bonnier ,  Nicolas Gane , and  Bénédicte Votan  from the  GINECO study office , the  Délégation à la Recherche Clinique et à l'Innovation of the Hospices Civils de Lyon  and  Raymonde Maraval-Gaget. We also thank the following investigators and psychologists who participated in the trial:  Drs B Weber ,  MC Kaminsky , and  E Luporsi  ( Centre Alexis Vautrin-Brabois, Vandoeuvre-lès-Nancy ),  Prof H Curé ,  Drs AM Savoye  and  G Yazbek  ( Institut Jean Godinot, Reims ),  Drs I Ray-Coquard ,  JP Guastalla , and  O Tredan  ( Centre Léon Bérard, Lyon ),  Dr E Sevin  ( Centre François Baclesse, Caen ),  Drs L Stefani  and  J Provençal  ( Centre Hospitalier de la région d'Annecy, Pringy ),  Drs S Kalla ,  F Savinelli , and  G Deplanque  ( Groupe Hospitalier Saint-Joseph, Paris ),  Drs M Combe  and  M Atlassi  ( Centre Hospitalier du Mans, Le Mans ),  Dr J Salvat  ( Hôpitaux du Léman, Thonon-les-Bains ),  Profs E Pujade-Lauraine  and  J Alexandre , and  Drs L Chauvenet  and  JM Tigaud  ( Hôpital Hôtel-Dieu, Paris ),  Dr J Meunier  and  D Bosquet  ( Centre Hospitalier Régional d'Orléans, Orléans ),  Dr J Cretin  and  E Roux  ( Clinique Bonnefon , Alès),  Dr M Fabbro  and  P Champoiral  ( Institut du Cancer de Montpellier, Montpellier ),  Dr MN Certain  and  M Gillon  ( Centre Hospitalier d'Auxerre, Auxerre ),  Drs E Legouffe  and  M Armand  ( Clinique de Valdegour, Nîmes ),  Mrs I Gourmoud  ( Hôpital d'Instruction des Armées Sainte-Anne, Toulon ),  Drs C Ligeza-Poisson  and  P Deguiral ,  A Harel  ( Clinique Mutualiste de l'Estuaire, Saint-Nazaire ),  Dr C Tep  and  K Pietrain  ( Centre Hospitalier Départemental Les Oudairies, La Roche-sur-Yon ),  Dr F Rousseau  and  P Bensoussan  ( Institut Paoli Calmettes, Marseille ),  N Darchy  ( Hôpital Perpétuel Secours, Levallois-Perret ), and  G Marini  ( Centre Azuréen de Cancérologie, Mougins ).
-dihydro-2-methoxy-4-(4-methoxyphenyl)-2methylpyrano[3,2-c]chromen-5(2H)-one 3,829745 4 3,4-dihydro-2-methoxy-2-methyl-4-phenylpyrano[3,2c]chromen-5(2H)-one 3,943571 http://sciforum. net/conference/mol2netdihydro-2-methoxy-2-methyl-4-p-tolylpyrano[31-(4-(trifluoromethyl)phenyl)-3-oxobutyl)-4-hydroxy-2Hchromen-2-one 3,253213 11 4-hydroxy-3-(1-(4-nitrophenyl)-3-oxobutyl)-2H-chromen-2-one 3,281052 12 4-hydroxy-3-(3-oxo-1-p-tolylbutyl)-2H-chromen-2tert-butylphenyl)-3-oxobutyl)-4-hydroxy-2H-chromen-2Materials and Methods Data: Experimental results of the scavenging ability of the DPPH• radical (expressed as IC50) for 1329 molecules extracted over 170 scientific reports in the literature; thus yielding a comprehensive and diverse database of compounds for the mathematical analysis. All the structures were optimized using CORINA software.
Acknowledgments MENRT is gratefully acknowledged for the graduate fellowship awarded to  Anita Rayar. The authors gratefully acknowledge support for part of this work through the program  PYTHAGORAS II of EPEAEK II  (MIS:  97436/073 ). We would like to thank  Dr. C. Hansch  and  Biobyte Corp. 201 West 4th Street, Suite 204, Claremont, CA 91711,  USA  for free access to the  C-QSAR program. The authors also thank the " Service de Coopération et d'Action Culturelle " of  Embassy of France in Cuba  for the financial support. Author Contributions E. G. J. and S. J. B. are responsible for the model construction and evaluation. M. E. J. R. is responsible for the in vitro assay. The French team, A. M. R. and M. S. -I. V. , provide the coumarin derivatives structures from their chemical library. All authors contributed to the drafting and revision of the article and approved the final version.
1 5 3 , 4 - 3. 1 * 13431 -dihydro-2-methoxy-4-(4-methoxyphenyl)-2methylpyrano[3,2-c]chromen-5(2H)-one 3,829745 4 3,4-dihydro-2-methoxy-2-methyl-4-phenylpyrano[3,2c]chromen-5(2H)-one 3,943571 http://sciforum. net/conference/mol2netdihydro-2-methoxy-2-methyl-4-p-tolylpyrano[31-(4-(trifluoromethyl)phenyl)-3-oxobutyl)-4-hydroxy-2Hchromen-2-one 3,253213 11 4-hydroxy-3-(1-(4-nitrophenyl)-3-oxobutyl)-2H-chromen-2-one 3,281052 12 4-hydroxy-3-(3-oxo-1-p-tolylbutyl)-2H-chromen-2tert-butylphenyl)-3-oxobutyl)-4-hydroxy-2H-chromen-2Materials and Methods Data: Experimental results of the scavenging ability of the DPPH• radical (expressed as IC50) for 1329 molecules extracted over 170 scientific reports in the literature; thus yielding a comprehensive and diverse database of compounds for the mathematical analysis.
Gas Chromatography CCl4 was quantified using a CP 3800 gas chromatograph connected to a flame ionization detector (GC-FID; Varian, Palo Alto, CA, USA). Headspace aliquots (500 μL) were collected from sealed Hungate culture tubes with a gastight 1750 syringe (Hamilton, Franklin, MA, USA) and injected onto the GC column (CP-Sil 5 CB, length 15 m; Varian). Separation of volatile compounds was achieved by isothermal elution at 30 °C for 1 min, followed by a linear temperature gradient (20 °C min -1 ) up to 220 °C. Injector and detector were maintained at 220 °C (splitless mode) and 300 °C, respectively, with nitrogen (N2) as the make-up gas (Linde Gas). Peak areas were analyzed with Galaxie Workstation software (Varian) and expressed as percentage of CCl4 compared to an abiotic reference tube prepared under the same conditions.
T-RFLP Analysis PCR reaction mixtures, cycles and primers for bacterial T-RFLP were previously described  [20]. Primers 6-FAM-21f and 958r  [27]  were used for T-RFLP analysis of the archaeal 16S rRNA gene. Preparation of PCR-amplified 0. 9 kb 16S rRNA gene fragments and T-RFLP analysis were previously described  [20]. The T-RF database was constructed using the "Microbial community analysis III" interface (MiCA III;  [28] ), with the following parameters: primers 27f and 926r, restriction enzymes AluI and HhaI, RDP release 10 update 27 (700,829 good quality bacterial SSU 16S rRNA fragments), and 10 mismatches allowed within 15 bases from 5′ end of primers. Data obtained with different fluorochromes for internal marker and sample fragments permitted determination of the total number of T-RFs and their relative proportion.
Two types of degradation curves were observed after successive transfers (Figure  1 ). Initially, cultures C4 and C5 degraded CCl4 fastest in the first enrichment cultures, but eventually lost their capacity for CCl4 degradation upon successive inoculations under the same culture conditions (Table  S2 ; Figure  1 ). Evaluation of the diversity of Bacteria and Archaea in the five CCl4-degrading enrichment cultures by 16S rRNA gene T-RFLP analysis evidenced: (i) different fingerprints for each enrichment with exclusively bacterial content (no Archaea); (ii) shifts in community structure after successive transfers; and (iii) predominant phylotypes identified by database comparisons (  [28] , Table  1 ). a NCBI Blast and RDP database  [32]. When no sequence data were available, T-RFLP database analysis was performed using a size confidence interval of ±1 nt  [28] ; b n.
Acknowledgments We thank  Gwenaël Imfeld  and  Sophie Gangloff  from  Laboratoire d'Hydrologie et de Géochimie de Strasbourg (UMR 7517 UdS-CNRS, Strasbourg, France ) for chloride analysis. This work was supported by grants to CP from the  National Research Fund of Luxembourg  (Grants No. EXT-BFR-05-085  and  FNR-08-AM2c-21 ), by a  Programme Pluri-Formations  and the  Contrat-Plan Etat-Région  to REALISE, the  Network of Laboratories in Engineering and Science for the Environment in the Alsace Région , and by the  EC2CO INSU program  of the  Centre National de la Recherche Scientifique (CNRS).
Prior to assembly, short reads that are less than 500 bp were filtered off and minimum polymerase read quality used for mapping of subreads from a single zero-mode waveguides (ZMW) was set at 0. 75. The 112 228 filtered reads (N50 value was 13 159 bp and total bp number was 814 445 948) were assembled using RS_HGAP_Assembly (version 3. 0), which is an analysis pipeline module from Pacific Biosciences SMRT portal incorporating Celera Assembler, BLASR mapper and Quiver consensus caller algorithm. The cut-off length of seeding reads was set at 3 606 bp in order to serve as a reference for the recruitment of shorter reads for preassembly. The resulted consensus accuracy based on multiple sequence alignment of the subreads was at 99. 99 %.
Assembly, variants calling and genome sequence analysis Assembly of the sequences was performed using the CLC Genomics Workbench v7. 0. 0 software (CLC Inc, Aarhus, Denmark). After quality (quality score threshold 0. 05) and length (above 40 nucleotides) trimming of the sequences, contigs were generated by de novo assembly (CLC parameters: automatic determination of the word and bubble sizes with no scaffolding) for each strain. Paired end reads for each strain were mapped against the reference sequence of the strain D. solani 3337 at mild stringency threshold (0. 8 of identity on 0. 5 of read length) using CLC Genomics Workbench version 7. 0. 0 software. The unmapped reads for each strain were collected. The mappings were used for detection of variations (SNPs and InDels) using basic variant calling tool from CLC genomic workbench version 7.
Nucleotide sequence accession number Draft genome sequences of Dickeya solani strains 9109, 0512, 9134, 07-7 have been deposited at DDBJ/EMBL/ GenBank under the following accession numbers: (JWLS00000000) D. solani 9019, (JWMJ00000000) D. solani 0512, (JWLT00000000) D. solani 9134, (JWLR 00000000) D. solani 07-7. The versions described in this paper are versions (JWLS01000000) D. solani 9019, (JWMJ01000000) D. solani 0512, (JWLT01000000) D. solani 9134, (JWLR01000000) D. solani 07-7. Genomes of other Dickeya and Pectobacterium species were collected from public database (Table  S4 ).
Acknowledgements We thank  Robert Dees  ( Wageningen UR/Applied Plant Research ) for the gift of the ornamental strains D. solani  PPO9019  and  PPO9134 ,  Minna Pirhonen  ( Department of Applied Biology, University of Helsinki ) for providing PPL0433 ( =F8 ),  Leah Tsror  ( Gilat Research Center, Agricultural Research Organisation ) for providing GRC77 ( EU3296 ) and  Yves Dessaux  ( I2BC ,  CNRS ) for his help in the manuscript editing. This work was supported by a cooperative project between France and  Morocco  ( PRAD 14-02 , Campus France n°30229 ZK), the  University Paris-Saclay (Co-tutelle funding) , the excellence grant ( n°H011/007 ) awarded by the  Ministry of Higher education of Morocco , a collaborative project between.
Data quality was assessed using Pearson correlation coefficients (Table  S6 ) and principal component analysis (PCA) (Fig. S3 ), which demonstrated the degree of reproducibility between biological replicates. The total transcriptome data are recorded as an average of the clustered samples. A global view of relative expressed profiles of differentially expressed genes showed extensive variation in gene expression, both between early and late BCG daughter strains and with respect to virulent tubercle bacilli (Fig. S4 ). This supports the earlier genomic observation that the earlier strains are most closely related and cluster together. Quantitative RT-PCR analysis of 15 randomly selected target genes was conducted to confirm the validity of the data generated through global transcriptional profiles.
Raw reads were trimmed with Trimmomatic 80 to an average quality score of 20 within a window size of 4 bp. Initial contig assembly was performed with Velvet 81 , using VelvetOptimiser to choose kmer values ranging from 33 to 81 [http://www. vicbioinformatics. com/software. velvetoptimiser. shtml]. Contigs were orientated and ordered with M. bovis AF2122/97 (EMBL accession number BX248333. 1) as the reference genome and scaffolding and iterative gap filling were performed using PAGIT toolkit  82. Genome alignment and phylogenetics. The raw paired-end reads were also mapped against the reference M. bovis genome using BWA  83. SNPs were identified using Samtools  84  and filtered to ensure that they had a quality score more than 30 and were present in at least 75% of the mapped reads in each direction.
The reference genome was segmented into 5000 bp non-overlapping sliding windows per sample. The SNP density in each of these windows was represented by a colored circle in Fig. 1A , with different colours representing different samples. This Figure was composed using the Circos visualization package [http://circos. ca]. Filtered SNPs were also concatenated and used as alignments for the estimation of a maximum likelihood phylogeny using the default settings of RAxML v0. 7. 4. 100 initial trees were generated and the best tree identified, followed by the production of 100 bootstraps.
Illumina sequencing and Transcriptome (RNA-seq) data analysis. The bar-coded cDNA libraries were pooled together in equal concentrations in one pool before sequencing on Illumina HiSeq2000 using the TruSeq SR Cluster Generation Kit v3 and TruSeq SBS Kit v3. Data were processed with the Illumina Pipeline Software v1. 82. Sequence reads of the different conditions were mapped against the reference sequence of M. bovis AF2122/97 strain as paired end data using SMALT. The read counts were used in DESeq  86  to first generate a distance matrix and PCA plots (Fig. S3 , plotPCA function). Differential expression analysis (DESeq  86  ) was performed pairwise between individual BCG strain and M. bovis AF2122/97 strain, using the default parameter. For the up down regulated genes of each comparison, a GO enrichment was done, using the R package TopGO, default parameter (http://www.
bioconductor. org/packages/2. 11/bioc/html/ topGO. html). GO terms were obtained from EBI [ftp://ftp. ebi. ac. uk/pub/databases/GO/goa/proteomes/]. Quantitative RT-PCR. The reliability of the RNA-seq expression data was assessed using quantitative real-time reverse transcriptase PCR (qRT-PCR) analysis. Briefly, 200 ng of total RNA was used to generate cDNA using SuperScript III reverse transcriptase (Invitrogen). QPCR was performed using SYBR GreenER QPCR kit (Invitrogen) and the 7900HT Fast Real-Time PCR System (Applied Biosystems). Ct values of target genes were normalized to values obtained for the mycobacterial housekeeping gene sigA. In total, 15 genes involved in different pathways were randomly selected for verification of RNA-seq data (Table  S8 ). Whole cell lysate preparation and tandem mass tagging (TMT) quantification.
The LC-MS/MS analysis of the peptide fractions using an LTQ-Orbitrap Velos (Thermo Scientific) coupled with an Easy-nLC (Thermo Scientific) and the MS data processing were carried out following our published procedure  87. Briefly, the MS spectra were extracted using Proteome Discoverer software (http://www. thermoscientific. com/en/product/proteome-discoverer-software. html) and processed by an in-house script before Mascot search against the database for M. bovis sequence (EMBL accession number BX248333. 1). The resulting files were then processed by Scaffold (Proteome Software Inc. , USA) for validation of MS/MS based peptide and protein identifications. Peptide and protein identifications were reported if they could be established at greater than 95. 0% probability. Scaffold local false positive rates for peptide and protein were controlled within 1%.
Acknowledgements We acknowledge  Baoli Zhu  ( Chinese Academy of Sciences, Beijing, China ) for providing BCG China strain. We gratefully acknowledge the support of  Eveline Weerdenbrug ,  Jeroen Geurtsen  ( VU University Medical Centre, Amsterdam, The Netherlands ) and  Fiona Mcintosh  ( McGill University Health Centre, Montreal, Canada ). This work was supported by  faculty Baseline Research Funding (BRF)  to A. P. by the  King Abdullah University of Science and Technology (KAUST). TGC is supported by the  Medical Research Council, UK  (Grant number  MR/K000551/1 ).
Statistical Estimate on Final Structure Using Combinatorics. Assuming that a dislocation can propagate with the same probability into either NW as two NWs merge, each merging bilayer gives rise to two equally likely outcomes. For merging of two NWs with 10 bilayers each there will be 2  10  possible outcomes. If we involve a third 10 bilayer NW in the merging process, there will be (2 10 ) 2 outcomes. To estimate the amount of 3C, 2H, and 4H in each outcome, we define a 3C segment to be of at least six bilayers (two unit cells), 2H as six bilayers (three unit cells) and 4H as eight bilayers (two unit cells). If the 10 bilayer long segment does not include any of the above segments, it is considered to be a mixed structure. Using a simple MatLab script, we simulate the merging of two, three, and four 2H NWs with each 10 bilayers (where the 10 bilayer limit is chosen to limit computation time).
■ ACKNOWLEDGMENTS This work was performed within the  Nanometer Structure Consortium at Lund University  (nmC@LU) and with financial support from the  Swedish Research Council  (V. R. ), the  Swedish Foundation for Strategic Research (SSF) , the  Knut and Alice Wallenberg Foundation  (K. A. W. ) and VINNOVA. J. S. acknowledges the support by  FWF Vienna  (Project Number  P23706-N19 ). D. K. acknowledges the support by the  Austrian Academy of Sciences and Czech Science Foundation  (Project  14-08124S ).
Mechanisms of disease and clinical presentation APRT deficiency APRT deficiency (number 614723 in the Online Mendelian Inheritance of Man [OMIM] database), is a rare inherited disease caused by a complete deficiency of the APRT enzyme, produced by mutations in the APRT gene (Table  1 ). The disease is of autosomal recessive inheritance and individuals carrying only one mutant APRT allele (heterozygotes) are asymptomatic despite lower-thannormal levels of enzyme activity. Two types of APRT deficiency have been described, based on the level of APRT enzyme activity measured in vitro in cell lysates. Type 1 is characterized by complete deficiency in vitro, whereas APRT activity is low, but still detectable, in type 2. Type 2 has been reported almost exclusively in Japanese, whereas type 1 has been observed in other ethnic groups  [6] [7] [8].
Recombination analysis Identification of potential recombinant events in the MARV genomes were determined with the Recombination Detection Program (RDP) 4 Beta (version 4. 27) software suite  [15] , which incorporates several phylogeneticsubstitution and distance-based methods, including GENECONV  [16] , RDP  [17] , MaxChi  [18] , Chimaera  [19] , Bootscan  [20] , SiScan  [21] , 3Seq  [22] , and LARD  [23]. The P-value cut-off was set to 0. 05 in all analyses, and the Bonferroni correction was applied. The default settings were used for all analyses.
Codon adaptation index (CAI) analysis CAI analysis is a quantitative method that predicts the expression level of a gene based on its coding sequence. CAI values range from 0 to 1. The most frequent codons have the highest relative adaptiveness towards its host, and sequences with higher CAIs are suggested to be preferred over those with lower CAIs  [27]. The CAI analysis for MARV genes was performed using CAIcal server  [28]. The synonymous codon usage patterns of the viral hosts (H. sapiens and R. aegyptiacus) were used as references. Non-synonymous codons and termination codons were excluded from the calculation. The reference datasets for H. sapiens and R. aegyptiacus were obtained from the Codon Usage Database  [29]. The correlation analysis between CAI and ENC values was performed to determine the relative influence of mutation and selection.
Influence of overall host codon usage on that of MARV The RSCU values of MARVs and its two hosts, H. sapiens and R. aegyptiacus, were compared to determine influence of the host. The codon usage data of H. sapiens and R. aegyptiacus were obtained from the Codon Usage Database  [29]. Furthermore, the influence of the overall codon usage patterns of hosts on the formation of the overall codon usage of viruses, defined as the similarity index D(A,B)  [36] , was calculated as follows: R A; B ð Þ¼ X 59 i¼1 a i Â b i ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi X 59 i¼1 a 2 i Â b 2 i s D A; B ð Þ ¼ 1 ¼ R A; B ð Þ 2 ; where R(A,B) is defined as a cosine value of an included angle between A and B spatial vectors and represents the degree of similarity between MARV and host overall codon usage pattern.
Trends in codon usage variation To determine the trends in codon usage variation among coding sequences of different MARV isolates, we performed PCA on the RSCU values, which were examined as a single dataset (Fig. 1a ). The first principal axis (f' 1 ) accounted for 65. 55 % of the total variation, and the next three axes (f' 2 -f' 4 ) accounted for 14. 17, 10. 48, and 2. 36 % of the total variation in synonymous codon usage, respectively. Next, we plotted principal axes based on geographical locations of MARV isolates (Fig. 1b ). Three separate clusters were observed. Cluster A, which formed the largest cluster, consisted of isolates from the Demographic Republic of Congo (DRC), Uganda, and a single isolate from South Africa. The DRC isolates formed the majority of Cluster A. Cluster B was dominated by isolates from Uganda, Kenya, and a single isolate from DRC, whereas Cluster C consisted of all of the isolates from Angola and single isolates from Germany, the Netherlands, Uganda, and DRC.
Experimental 2. 1. Crystal data  Hydrogen-bond geometry (A ˚, ). (i) Àx þ 1; y þ 1 2 ; Àz þ 1 2 ; (ii) Àx þ 2; y À 1 2 ; Àz þ 3 2. Data collection: COLLECT (Nonius, 2002); cell refinement: DENZO-SMN  (Otwinowski & Minor, 1997) ; data reduction: EVALCCD  (Duisenberg et al. , 2003) ; program(s) used to solve structure: SIR97  (Altomare et al. , 1999) ; program(s) used to refine structure: OLEX2. refine (Dolomanov et al. , 2009) ; molecular graphics: ORTEP-3 for Windows  (Farrugia, 2012)  and Mercury  (Macrae et al. , 2006) ; software used to prepare material for publication: WinGX  (Farrugia, 2012)  and PARST  (Nardelli, 1995).
, 2008; Coelho et al. , 2011; Le Bail et al. , 2011). Meiosis generates male and female mutant or WT gametophytes. Dashed lines stand for meiospore release from unilocular sporangia, plain lines for spore or gamete release from plurilocular sporangia and gametangia respectively. Prostrate filaments and erect filaments characteristic of the general morphology of Ectocarpus siliculosus sporophyte are also displayed (left part). 2010 ) or designed de novo from the E. siliculosus genomic sequence  (Cock et al. , 2010)  using the WebSat software  (Martins et al. , 2009). Forward oligonucleotide sequences were 5 -extended with the M13 oligonucleotide sequence (5 -TGTAAAACGACGGCCAGT-3 ) to allow 5 labeling of PCR product as described in  Schuelke (2000). Final concentrations of 0. 1 μM forward, 0.
In silico analyses Short reads were trimmed using sickle version 1. 33  (Joshi, 2011) , leaving a total number of ∼ 85 millions reads per strain. SNPs were directly inferred from the Ec568 and Ec32 trimmed short reads using the DiscoSNP software  (Peterlongo et al. , 2010)  with kmers of size k = 31 and a minimal coverage c = 4. Then, each SNP was mapped onto the E. siliculosus genome by searching the optimal match of its surrounding sequence (the 61-mer centered on the SNP), using BLASTN 2. 2. 28+ from the ncbi-blast+ package  (Altschul et al. , 1990; Camacho et al. , 2009) , in ungapped mode, with a minimum identity of 96. 7 (at most 2 unmatched nucleotides, including the SNP, among 61). Only unique matches were retained. By comparing the two parental sets of reads, 291274 SNPs could be identified, among which 83150 were purine-purine replacements, while 83048 were pyrimidinepyrimidine replacements.