dataesr/scientific-paragraphs-categorization huggingface dataset:
After every 10th passage and the last one, DNA from a bacterial sweep was extracted and the total DNA was subjected to the MLVA assay. PFGE. Each isolate was typed by PFGE according to PulseNet standardized procedures with the AscI and ApaI restriction enzymes  (18). Data analysis was performed with BioNumerics version 6. 5. ApaI and AscI PFGE types were defined as differing from other types by at least two bands for each individual enzyme. Data analysis. PCR products obtained with fluorescently labeled primers (Table  2 ) were subjected to capillary electrophoresis on an ABI 3730XL DNA sequencer. The sizes of PCR fragments were determined with the Applied Biosystems GeneMapper v4. 0 software. The number of tandem repeats was then calculated according to the PCR fragment size and the known length of the repeat unit of each VNTR locus.
The number of tandem repeats was rounded to the closest whole integer. In accordance with this procedure, an allele number corresponding directly to the number of tandem repeats was assigned to each PCR fragment. Allele strings were then imported into a BioNumerics database. Because no data were available at locus Lm11 for most isolates of CC7 and CC8, we chose to exclude this VNTR locus from subsequent polymorphism calculations and from the determination of the overall number of MLVA types. Each unique combination of the 10 remaining allelic numbers was converted into a distinct MLVA type. PFGE patterns were compared with a tolerance parameter of 1% and an optimization parameter of 1%. Dendrogram analysis by the unweighted-pair group method using average linkages (UPGMA) and minimum spanning tree (MStree) construction were performed with BioNumerics.
MLST analysis of the 255 study isolates. To determine their diversity and whether they belong to major MLST clones, we analyzed the 255 isolates by MLST. Data for 155 isolates were derived from our previous studies  (12, 36) , and we performed MLST analysis of 100 additional isolates for the purposes of the present study. These 100 isolates included 38 strains from the reference ILSI collection, 24 isolates collected during the large 1992 outbreak in France  (37) , and 38 isolates representing CC3, CC4, CC5, and CC8 (see Materials and Methods). The seven MLST genes of the 100 isolates could be amplified, and their sequence types (STs) were determined. The 20 STs that were not previously described (ST326 or above in Table  S1  in the supplemental material) were incorporated into the Institut Pasteur MLST database at www.
Values inside or just above circles indicate the ST numbers of the central STs of numerically important CCs. Left panel, lineage I; right panel, lineage II. All data are publicly available at http://www. pasteur. fr/mlst. preliminary screening were distributed into two distinct groups (Table  2 ), and two separate multiplexed PCR assays called M1 (six VNTR loci) and M2 (five VNTR loci) were developed. To test for the stability of the VNTR loci during laboratory subculture, strain EGDe was subcultured 65 times and no repeat number variation was observed during these passages at any of the 11 VNTR loci. Typeability of the 11 VNTR loci of lineage 1 and 2 isolates. The two multiplexed PCR tests were applied to the analysis of an expanded panel of 255 L. monocytogenes isolates. These isolates represented multiple isolates of major L.
We showed that MLVA loci are stable during laboratory subculture and found complete repeatability of allele coding by capillary electrophoresis separation. Elimination of loci with nonspecific amplification also facilitated the sizing of fragments and the determination of tandem repeat numbers. We also showed that the L. monocytogenes VNTR loci selected have a very strong tendency to evolve by the stepwise addition or removal of single repeat units. This observation indicates that the quantitative difference in the number of repeats, rather than simple allelic mismatch, can be taken into account to estimate strain relationships. We compared MLVA-11 with the three widely used methods serotyping, PFGE, and MLST. While several MLST schemes have been published  (9, 12, 47) , only the Institut Pasteur scheme  (12)  provides a standardized nomenclature through a publicly accessible database and is used in a coordinated manner by multiple laboratories (www.
In our study, we used mostly independent isolates collected over wide temporal and geographic scales. Nevertheless, we found several groups of epidemiologically unrelated isolates with the same MLVA pattern and sometimes also the same PFGE pattern (see Table  S1  in the supplemental material; PFGE16/54 and MLVA0010 [n ϭ 9], PFGE27/11 and MLVA0055 [n ϭ 6], PFGE53/14 and MLVA0048 [n ϭ 7], and PFGE42/41 and MLVA0022 [n ϭ 5]). These results show that identity of MLVA and PFGE profiles does not necessarily imply a direct epidemiological link. This is especially true for MLVA, and in our retrospective study of isolates from the French pork jelly outbreak, some of the isolates defined as unrelated by PFGE were not distinguished by MLVA. MLVA has strong potential for interlaboratory standardization, as this method is highly reproducible and as data scoring into integer numerals provides unambiguous results.
The variation disclosed at these loci proved highly consistent with MLST data and was phylogenetically informative. These results show that MLVA could be used as a rapid identification method for MLST-defined clonal groups, including those corresponding to so-called ECI to ECIV. Because it has lower discriminatory power, MLVA cannot replace PFGE in outbreak investigations. However, given its simplicity, low cost, high throughput, and rapid time to results (around 8 h), MLVA could represent a useful screening method to alleviate the PFGE workload. Within the context of an outbreak, MLVA could advantageously fill the gap between the throughput needed to characterize a high number of isolates in a short period of time and the high discrimination level needed for informed epidemiological decisions.
ACKNOWLEDGMENTS We thank  Martin Wiedmann  for providing strains from the ILSI collection and  Marie Ragon  and  Alban Le Monnier  for contributing to the initiation of this work. We acknowledge  Nathalie Tessaud-Rita  and  Arnaud Bertel  for technical help. This work was supported financially by the  Institut Pasteur ,  INSERM , and the  Institut de Veille Sanitaire (Saint Maurice, France ).
SUBJECTS AND METHODS Participants The data were derived from a longitudinal study of neuropsychiatric disorders in community-dwelling French elderly, the Esprit study. 25 Eligible participants, who were at least 65 years of age and non-institutionalized, were recruited by random selection from the electoral rolls between 1999 and 2001. Ethics approval for the study was given by the national ethics committee. After obtaining written informed consent from all participants, interviews were administered by trained staff at baseline and 2, 4, 7 and 10 years of follow-up. Of the 2199 non-demented elderly recruited, participants were excluded from this analysis if they were not assessed for current psychiatric symptomatology (n ¼ 29) and had missing covariate data (n ¼ 256). Of the remaining participants, 1005 provided buccal samples for genotyping.
The amplified PCR products were analyzed by fluorescence scanning in a BMG labtech Pherastar scanner and the results were interpreted with KlusterCaller 1. 1 software. The error rate for the KASP assay system is less than 0. 3%. Data concerning an additional ACE polymorphism (rs4291), as well as replicate data for rs4343 were also available, as these had been genotyped previously by the Lille Genopole (http://www. genopole-lille. fr/spip/) using DNA extracted from blood samples collected at baseline. The data concerning rs4343 was identical when we compared the results of genotyping from buccal-and blood-cellderived DNA, which helped verify the accuracy of the data.
AUC were standardized and calculated between 0800 hours and 2200 hours for each subject (extrapolating values from the equation of the regression line), as published previously. 5, 35 The associations between ACE SNPs and cortisol AUC were evaluated using analysis of covariance and adjusting for age, gender and DEP. SAS (v9. 1, SAS Institute, NC, USA) was used for the statistical analyses with a significance level of Po0. 05. Given that seven SNPs were investigated, the Bonferroni-corrected P-value was 0. 0071.
Supplementary Figure  S1B ). 40 The strongest associations were observed with rs4291, located in the promoter region, and the closely linked rs4295 in intron 2. The importance of variation in or around the promoter regions has been suggested in a number of common diseases  41  and functional consequences for ACE gene transcription regulation has been proposed for rs4291. 12 urthermore, this SNP does appear to be functionally significant as it has been associated with ACE level in two studies. 42, 43 While no prior study has examined the functionality of the other variants examined in this study, we used a specific program RESCUE-ESE (http://genes. mit. edu/burgelab/rescue-ese/)  44 to help predict the effects of single-base changes on exonic splicing enhancer activity and thus their potential functionality.
DEP was assessed by trained staff using two distinct measures validated in the general population, including a structured diagnostic interview  26, 27  according to DSM-IV criteria. We controlled for a large number of covariates, thus minimizing any confounding, which contrasts with previous studies that have predominantly presented minimally adjusted analyses in clinical samples. Finally, in addition to using a genotyping system with a low error rate, we also controlled for the accuracy of ACE genotyping by comparing the genotyping data obtained from blood and cheek DNA extracts for one SNP. Several experimental and human studies have demonstrated a strong interrelationship between angiotensin II and the secretion of pituitary hormones, which may influence the susceptibility to develop late-life depression.
ACKNOWLEDGMENTS The  ESPRIT  project is financed by the  regional government of Languedoc-Roussillon , the  Agence Nationale de la Recherche (ANR)  Project  07 LVIE 004  and an unconditional grant from  Novartis. Joanne Ryan  is the holder of an  NHMRC Training (Postdoctoral)  Fellowship (Overseas Public Health, APP1012735). This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3. 0 Unported License. To view a copy of this license, visit http://creativecommons. org/licenses/by-nc-nd/3. 0/.
plus function. Colors were generated in a standardized manner using the rank of miRNA expression values across samples. The non-parametric Wilcoxon's rank sum was used to measure the significance of association of miRNA expression to the various selected sample classes. P-values were corrected for multiple comparisons using the Bonferroni method. Potential targeting of differentially expressed miRNA and diametrically, differentially expressed mRNA was examined by assessing the number of predicted targets present. The significance of this value was calculated by comparing this with that expected by chance using Chi-squared statistic. This analysis was carried out using an algorithm implemented Java v1. 5 and the TargetScan version 5. 1 database.
Statistical analysis Means of total P, Fe and N contents in the EC and non EC dust used in DUNE-1-P, -Q and DUNE-2-R were compared using a one-way ANOVA and a Fisher LSD means comparison test (α = 0. 05) (Table  1 ). Means of N 2 fixation rate in Dust-and Controlmeso were compared using a repeated measure ANOVA and a Fisher LSD means comparison test. When assumptions for ANOVA were not respected, means were compared using a Kruskal-Wallis test and a post hoc Dunn's test in XLstat software.
This work is a contribution of the DUNE experiment (a DUst experiment in a low Nutrient, low chlorophyll Ecosystem, http://www. obs-vlfr. fr/LOV/DUNE/index. html) and was funded by the LEFE, UPMC and ANR-DUNE under the contract "ANR-07-BLAN-0126-01". We would like to sincerely thank the "R éserve naturelle de Scandola, Parc naturel r égional de Corse", in particular J. M. Dominici, Jo Albertini and collaborators, for professionalism and cooperation in the implementation of the field work in the bay of Elbo. We are grateful to Eric Thiebaut for his help on the statistical tests. E. Pulido-Villena, T. Wagener, K. Desboeufs, F. Louis, J. M. Grisoni, D. Luquet, M. Deschatres, J. Caparros, F. Dulac, C. Brunet, I. Biegala, M. Bressac, S. Blain, N. Leblond, K. Wuttig, C. Rouvi ères, V. Giovagnetti and L.
Acknowledgements. This work is a contribution of the DUNE experiment (a DUst experiment in a low Nutrient, low chlorophyll Ecosystem, http://www. obs-vlfr. fr/LOV/DUNE/index. html) and was funded by the LEFE, UPMC and ANR-DUNE under the contract "ANR-07-BLAN-0126-01". We would like to sincerely thank the "R éserve naturelle de Scandola, Parc naturel r égional de Corse", in particular J. M. Dominici, Jo Albertini and collaborators, for professionalism and cooperation in the implementation of the field work in the bay of Elbo. We are grateful to Eric Thiebaut for his help on the statistical tests. E. Pulido-Villena, T. Wagener, K. Desboeufs, F. Louis, J. M. Grisoni, D. Luquet, M. Deschatres, J. Caparros, F. Dulac, C. Brunet, I. Biegala, M. Bressac, S. Blain, N. Leblond, K. Wuttig, C. Rouvi ères, V.
Data mining pointed to a regulatory network in which Sfl1p and Sfl2p act as both transcriptional activators and repressors. Sfl1p directly represses the expression of positive regulators of hyphal growth (BRG1, UME6, TEC1, SFL2), while upregulating both yeast form-associated genes (RME1, RHD1, YWP1) and repressors of morphogenesis (SSN6, NRG1). On the other hand, Sfl2p directly upregulates HSGs and activators of hyphal growth (UME6, TEC1), while downregulating yeast form-associated genes and repressors of morphogenesis (NRG1, RFG1, SFL1). Using genetic interaction analyses, we provide further evidences that Sfl1p and Sfl2p antagonistically control C. albicans morphogenesis through direct modulation of the expression of important regulators of hyphal growth. Bioinformatic analyses suggest that binding of Sfl1p and Sfl2p to their targets occurs with the co-binding of Efg1p and/or Ndt80p.
The resulting reads were mapped to the C. albicans Assembly 21 genome and alignments were visualized using the Integrative Genomics Viewer (IGV) software  [44, 45]  (see Materials and Methods for details). Using the Model-Based Analysis for ChIP-Seq (MACS) peak-finding algorithm  [46] , we identified 163 and 213 binding peaks for Sfl1p and    [42]. A triple HA tag (dark grey box) was inserted in frame with the SFL1 or SFL2 coding sequences (SFL1 or SFL2; black arrowed rectangle) in plasmid pCaEXP  [42]. The tagged alleles are placed under the control of the MET3 promoter (MET3p; ligh grey rectangle), which is induced in the absence of methionine and cysteine, and are followed by the C. albicans URA3 marker (open rectangle). (B) Western blot analysis of homozygous sfl1 or sfl2 mutants (sfl1D/sfl1D or sfl2D/sfl2D) expressing HA 3tagged versions of the SFL1 or SFL2 genes, respectively (SFL1-HA 3 or SFL2-HA 3 ) together with the corresponding empty vector controls (Vector).
Ndt80p is a transcription factor that controls the expression of genes involved in many cellular processes, including drug resistance, cell separation, morphogenesis and virulence through the recognition of mid-sporulation elements on the promoter of its targets  [57, 58]. This suggests the presence of functional interactions between Sfl1p, Efg1p and Ndt80p and proposes that Sfl1p binds to two different motifs or that an additional factor binds either 59-TCGAACCC-39 or 59-TtCtaGaA-39. We searched the YeT-FaSCo and the JASPAR databases for similarity with known transcription factor binding sites  [59, 60]. Interestingly, the 59-TtCtaGaA-39 sequence was strongly similar to the S. cerevisiae Hsf1p motif (P = 3. 856610 204 , using YeTFaSco), while database searches did not identify any known motif that closely resembled the 59-TCGAACCC-39 sequence (data not shown).
On the other hand, we found 3 high-scoring motifs in Sfl2p-enriched sequences, including the Efg1p and Ndt80p binding motifs as well as the GAA-containing sequence, 59-aaNAATAGAA-39 (where N represents any nucleotide; shown are motifs found using the positionanalysis program, significance index score. 5) (Figure  8B ). To confirm that the 59-aaNAATAGAA-39 motif was specific to Sfl2p, we performed motif discovery analyses using DNA sequences encompassing 6250 bp around peak summits of the regions specifically bound by Sfl2p and found the similar high-scoring motif 59-aANAATAGAA-39 (Figure  8C ). The 59-aANAATA-GAA-39 motif shows moderate similarity with the S. cerevisiae Sfl1p and Mga1p motifs (scores = 17. 75 and 17. 36, respectively using the JASPAR database). All these identified motifs were distributed preferentially around the center of the sequences corresponding to peak locations (Figures 8A, 8B and 8C), suggesting that Sfl1p, Sfl2p, Efg1p and Ndt80p binding sites were very close to each other.
4Orc2 of the Model-Based Analysis for ChIP-Seq (MACS) peakfinding algorithm  [46]  for peak finding with the following parameters: bandwidth = 250; mfold = 10,30; shiftsize = 100; Pvalue cutoff for Sfl1p peaks = 1e-14 and P-value cutoff for Sfl2p peaks = 1e-100. Replicates 1 and 2 from the two independently performed ChIP-Seq experiments were processed separately. Overlapping peak intervals (intersection) from replicates 1 and 2 of Sfl1p or Sfl2p binding data were generated using the Galaxy tool Intercept version 1. 0. 0 (https://main. g2. bx. psu. edu/). The complete Sfl1p and Sfl2p binding and expression datasets are provided in Tables S1-S8 in Text S1. The command line version of the PeakAnnotator (v 1. 4) sub-package from the PeakAnalyzer suite of algorithms  [80]  was used to annotate the Sfl1p and Sfl2p binding peaks in Tables S1, S2, S4 and S5 in Text S1.
The Cy3-and Cy5-labeled cDNA lyophilized pellets were resuspended in 10 ml of DNase-free water then 2. 5 ml and 12. 5 ml of 10X blocking agent and 2X hybridization buffer (Agilent Technologies), respectively, were added. The resulting samples were mixed, incubated at 95uC during 3 min and snap cooled on ice during 1 min then hybridized to a Candida albicans expression array (Agilent Technologies) designed such that two nonoverlapping probe sets are targeting each of 6,105 C. albicans ORFs for a total of 15,744 probes, thereby allowing two independent measurements of the mRNA level for a given gene (The EMBL-European Bioinformatics Institute ArrayExpress platform accession number: A-MEXP-2142, http://www. ebi. ac. uk/arrayexpress/arrays/A-MEXP-2142).
Gene expression microarray data analysis Images of Cy5 and Cy3 fluorescence intensities were generated by scanning the expression arrays using an Axon Autoloader 4200AL scanner (Molecular Devices, Downington, PA). Images were subsequently analyzed with the GenePix Pro 6. 1. 0. 2 software (Molecular Devices, Downington, PA). GenePix Results (GPR) files were imported into the Arraypipe 2. 0  [82]  or the GeneSpring (Agilent Technologies) softwares. Following spot filtering and bad spot flagging, global signal intensities were normalized using Loess normalization and replicate slides (n = 3) were combined and the P-values calculated using a standard Student's t-test.
Acknowledgments We are grateful to members of the  UniteBiologie et Pathogenicite Fongiques  for their constant support and numerous insights during the course of this project. We are indebted to  Caroline Proux  and  Jean-Yves Coppe  ´e from the  Institut Pasteur Transcriptomics and Epigenomics Platform (Genopole Institut Pasteur)  for their assistance with the ChIP-Seq experiments;  Dr Martine Raymond  from the  Institute for Research in Immunology and Cancer (IRIC) ,  Montreal, Canada  for the SGY243-strain derivatives and the pCaMPY-36HA plasmid and  Dr Joachim Ernst  from the  Heinrich-Heine-Universita ¨t, Dusseldorf, Germany  for strains AVL12 and  HLCEEFG1. We also thank the  Candida Genome Database  for.
This work was supported by research grants from the  European Commission  ( FinSysB PITN-GA-2008-214004 ) and  Agence Nationale de la Recherche  ( KANJI ,  ANR-08-MIE-033-01 ) to CdE. SZ was supported by postdoctoral fellowships from the  European Commission  ( FinSysB PITN-GA-2008-214004 ) and the  Agence Nationale de la Recherche  ( KANJI ,  ANR-08-MIE-033-01 ). AN was supported by a doctoral studentship from the  DIM-Malinf Region Ile-de-France. This study has received funding from the  French Government 's  Investissement d'Avenir program ,  Laboratoire d'Excellence ''Integrative Biology of Emerging Infectious Diseases''  ( ANR-10-LABX-62-IBEID ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The end effector is also a printed component and is attached to the frame by six tie rods. The tie rods are constructed from carbon fiber rods and miniature tie rod ends used in remote controlled models. The plastic end effector is protected from the heat of welding by a 1. 5" thick piece of calcium silicate. The stepper motors, power supply and limit switches are wired to corresponding terminals on the microcontroller board as shown in Fig. 2 , which is connected to a computer running Linux with a USB cable. Control is provided by an Arduino-based microcontroller board designed for RepRap 3-D printers and requires a host computer to operate. The welder is setup for the wire to be used for printing by manually running beads and assuring that it is functioning correctly. Shielding gas (75% Ar/25% CO 2 ) is employed at a rate of 20 CFH.
The stage is placed under a fixture designed to hold the welding gun perpendicular to the build surface. After leveling the stage, the distance between the build surface and nozzle is set to about 6mm by adjusting the welding gun fixture. The entire software tool chain is freely available open-source software. (http://www. appropedia. org/Open-sour ce_metal_3-D_printer). The open-source firmware (Repetierfirmware) translates G-code commands into pulses to the stepper motors, controlling the motion of the stage. Host software (Repetier-Host) running on a host computer provides an interface for loading G-code which it then sends to the controller. Models based upon the stereolithography (STL) standard are converted to G-code by software colloquially known as a ''slicer'', which creates patterns from uniformly thick slices of the model through the z-axis.
The final result was expressed as: Screen ratio = screen CT of the plasma to be tested / screen CT of the reference pool. The result was accepted as abnormal if the screen ratio was higher than 1. 2 and the presence of lupus anticoagulant was suspected. In suspected cases, a second CT determination (confirmatory CT) was done. Confirmation ratio was calculated (=confirm CT plasma to be tested / confirm CT of reference pool). Thereafter, the normalized ratio was computed using the following formula: Normalized ratio = screen ratio / confirm ratio. A normalized ratio of equal to or higher than 1. 2 confirmed the presence of lupus anticoagulant. Recording and statistical analysis of the data was done using version 3. 5. 1 (2008) of the Epi Info software. Fischer's test was used to compare the data.
The GϩC contents are 58. 8%, 58. 6%, and 56. 7% for the circular chromosome, linear chromosome, and At plasmid, respectively. A total of 5,379 putative coding sequences were predicted using the Rapid Annotations using Subsystems Technology (RAST) version 4. 0 automated pipeline  (4). A survey of the P4 genome revealed the presence of a luxI homolog on the At plasmid, the function of which remains to be investigated. Nucleotide sequence accession numbers. The A. tumefaciens P4 genome sequence has been deposited at DDBJ/EMBL/ GenBank under the accession no. APJV00000000. The version described in this paper is the first version, APJV01000000.