dataesr/scientific-paragraphs-categorization huggingface dataset:
As previously described, the median fold change of the six ISGs, when compared to the median of the combined 29 healthy controls, was used to create an interferon score for each patient  9. RQ (relative quantification) is equal to 2 -ΔΔCt i. e. the normalized fold change relative to a control. When a patient was assayed on more than one occasion, the data for repeat measurements were combined to calculate a mean value (using Applied Biosystems DataAssist software v. 3. 01).
Microsatellite genotyping To confirm maternity and paternity, informative polymorphic microsatellite markers on chromosomes 3 (D3S3640, D3S3560), 11 (D11S4205, D11S913, D11S987, D11S1889), and 20 (D20S847, D20S896, D20S843) were genotyped using DNA from F102, F524_2, F647, F626, F237, F163 and respective parents, as well as an unrelated control sample. DNA samples were amplified by standard PCR (primer sequences available on request). Each amplicon was mixed with HiDi™Formamide (AppliedBiosystems) and 500ROX™SizeStandard (AppliedBiosystems) and run on the GeneticAnalyzer3010 capillary electrophoresis system. Results were analyzed with the GeneMapper v4. 1 (AppliedBiosystems) software.
Electrophoretic Mobility Shift Assay (EMSA) and ATP hydrolysis assay Assays were performed as previously reported  12. Briefly, 3′-fluorescein labeled 112 bp (20 nM)  14  was incubated with protein (40 -160 nM) in buffer B (20 mM Hepes, pH 7. 5, 150 mM NaCl, 1. 5 mM MgCl2 and 2 mM DTT) in the presence and absence of 2 mM ATP, and the complex was analyzed on Bis-Tris native PAGE (Life). Fluorescent gel images were recorded using the scanner FLA9000 and analyzed with Multigauge (GE Healthcare). Curve fitting was performed using the program KaleidaGraph (Synergy). For ATP hydrolysis assays, IFIH1 (0. 3 μM) was incubated with ATP (2 mM) and 112 bp dsRNA (0. 6 μM) in buffer B at 37°C. Use of an excess amount of 112 bp dsRNA (0. 6 μM corresponds to 4. 8 μM IFIH1-binding sites as each 112 bp dsRNA can accommodate 8 IFIH1 molecules) simplifies the comparison between wild-type and mutant IFIH1 by focusing on the intrinsic ATP hydrolysis activities, independent of dsRNA binding  12.
Acknowledgements We sincerely thank the participating families for the use of genetic samples and clinical information, and all clinicians who contributed samples and data not included in this manuscript. We thank  Diana Chase  for proofreading the manuscript. We thank  Gigi Notarangelo  for helpful discussion. Y. d. T. D. holds a Novartis Foundation post-doctoral fellowship. S. H. holds a  Pew scholarship and Career Development award  from  Boston Children's Hospital. Y. J. C. acknowledges the  Manchester Biomedical Research Centre, Manchester Academic Health Sciences Centre , the  Greater Manchester Comprehensive Local Research Network , the  Great Ormond Street Hospital Children's Charity , the  European Union 's  Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement  241779 , and the  European Research Council  ( GA 309449 ).
The ChIP-Seq GsFLX libraries were analyzed on a Bio analyzer 2100 using Agilent RNA 6000 Pico methods and quantified using Quant-iT TM RiboGreen (Invitrogen). Equimolar amounts of the libraries were mixed, fixed on beads, and amplified using the GS FLX Titanium emPCR Kit (454 Life Sciences, Roche Diagnostics). The beads were purified, enriched, counted using Beckman Coulter Z1, and deposited on the GS FLX Titanium Pico Titer Plate (454 Life Sciences, Roche Diagnostics). The pyro sequencing reaction was performed using a GS FLX Titanium Sequencing Kit and Genome Sequencer FLX Instrument (454 Life Sciences, Roche Diagnostics). For bioinformatics analyses, the GSMapper software v 2. 3 (Roche) was used to align reads for each sample using the updated T. gondii ME49 genome databases downloaded from http://www.
toxodb. org. Only sequences of a minimum overlapping length of 40 nucleotides with at least 90% identity were considered for further analyses. The ChIP-Seq data specific to TgENO2 or TgENO2-HA were subtracted from non-specific sequences obtained with the pre-immune sera used as negative control and data collected for specific sequences immunoprecipitated by anti-ENO2 and anti-HA antibodies were grouped into four sub-groups of associated contigs. Signal Map software was used to schematically represent the number of reads per contig and their corresponding positions, which allowed visualization of putative gene promoter occupancy by ENO2 for all chromosomes of T. gondii.
40 Oil DIC M27, Zeiss) as previously described  [31]. Quantification of TgENO2 signal in the nucleus and cytoplasm of the intracellular parasites was performed using 8-bit images (256 grey levels) that were acquired sequentially and averaged four times. Size was adapted to the optimal resolution that could be obtained by the confocal setup (0. 13 mm per pixel). UV excitation (laser diode 405 nm) enabled imaging of the DAPI signal of parasite nuclei (blue image corresponding to spectral range 410-495 nm) and excitation at 561 nm allowed imaging of the TgENO2 signal (red fluorescence corresponding to spectral ranges 565-700 nm). Image analysis was performed using ImageJ (NIH) software. A short macro enabled us to automatically determine the relative proportion of TgENO2 signal in the nucleus versus the cytoplasmic signal.
Genome-wide TgENO2 occupancy of gene promoters defined by ChIP-Seq We next investigated the interactions of TgENO2 with 59-UTR gene sequences that might correspond to putative gene promoters in vivo using chromatin immunoprecipitation followed by highthroughput sequencing (ChIP-Seq). Intracellular actively dividing tachyzoites of wild-type T. gondii 76K strain or transgenic TgENO2-HA parasites were fixed by formaldehyde and released from host cells. After chromosome fragmentation by sonication, the chromatin was immunoprecipitated using specific anti-TgENO2 or anti-HA antibodies, or with pre-immune or nonrelevant anti-ROP1 sera as negative controls. The immunoprecipitates were subjected to high-throughput sequencing and bioinformatics analyses using genome data from http://www. toxodb. org.
Funding: This work was supported by grants from the  Centre National de la Recherche Scientifique (CNRS) ,  Institut Medicale de la Recherche Scientifique (INSERM)  and the  Institut Pasteur de Lille (IPL) and Laboratoire d'Excellence (LabEx) ParaFrap  from the  National Agency for Research [PIA ,  ANR-11-LABX-0024 ] to ST. The funding organizations had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Acknowledgements This work was supported by grants from the  University of Franche-Comté (UFC)  and the  Ré gion Franche-Comté  ( RECH-FON12-000013 ) to  Georges Herbein. Amit Kumar  is a recipient of a postdoctoral fellowship of the  Region Franche-Comté  and  Wasim Abbas  is a recipient of a doctoral scholarship from the  Higher Education Commission, Pakistan.
Study Population We used pooled data from the CASCADE September 2011 data release in EuroCoord (www. EuroCoord. net), which consists of 25,629 seroconverters from 28 cohorts across Europe, Canada, Australia and sub-Saharan Africa. [24]  Date of seroconversion is estimated by various methods, most commonly as the midpoint between the last documented HIV negative and the first positive HIV antibody test dates with an interval of ,3 years between the two test dates (85%). For the remainder, date of seroconversion was estimated through laboratory evidence of seroconversion (PCR positivity in the absence of HIV antibodies or antigen positivity with fewer than four bands on Western blot) (13%), or as the date of a seroconversion illness (2%) with both an earlier documented negative and a later positive HIV test not more than 3 years apart.
Results Data from 28 cohorts of 25,692 individuals formed the base from which sub-populations of EC and non-EC were drawn according to each definition. Median (IQR) year of HIV seroconversion was 1999  (1992, 2005)  and median age at seroconversion 31 years  (25, 37). HIV risk groups were MSM (55%), MSW (26%) or IDU (14%), and the majority were male (78%).
doi:10. 1371/journal. pone. 0086719. t003 Table  4. Estimated hazard ratios comparing non-elite controllers (EC) and unknown to EC for time from estimated HIV seroconversion to a composite endpoint of AIDS, Death, ART, or CD4,350 cells/mm 3 restricting entry to the risk set at 10 years post seroconversion using the CASCADE dataset applied to 10 definitions of EC found in the literature. Of note, however, CD4 slopes during total ART-naı ¨ve followup were significantly negative (a = 0. 05) for all but one definition. HIV-RNA and CD4 values and CD4 slopes showed consistent results when CD4 values within 6 months of seroconversion were excluded (data not shown).
Discussion Using the large size of the CASCADE dataset we were able to provide reliable estimates of the proportion likely to be elite controllers in an HIV-positive population. Our findings confirm that, by whichever definition, elite control is a rare phenotype likely to comprise around 1% of individuals. This is in line with estimates reported by others  [7, 8, 23]  although it should be noted that the choice of denominator may distort the proportion (for example, considering all individuals regardless of their length of follow-up or HIV infection duration will tend to under-estimate this proportion of ECs). Interestingly, we also find evidence that ECs may eventually lose control of viraemia. Definitions A, E, F and J which require low consecutive or a high proportion of low HIV-RNA measurements are best at capturing individuals with the slowest disease progression.
When restricting the dataset to those with 10 years of follow-up, definitions A, E and F and J demonstrated the lowest hazard of AIDS, Death, ART or CD4,350 cells/mm 3 compared to definitions with single measurements or higher levels of viremia. Definition J, with the longest follow-up of 10 years was not significantly different from all other definitions, although this is likely due to low numbers of individuals classified by this definition. The proportion classified as EC varied according to each definition, with definition D, requiring an HIV-RNA threshold of ,2000 copies/ml, classifying the greatest proportion as EC. This definition performed particularly poorly overall with the highest median HIV-RNA and fastest CD4 cell loss while classified as EC and during ART naı ¨ve follow-up. Given that the lower limit for available assays has been less than 1000 copies/ml for at least 10 years, inclusion of 2000 copies/ml limit is justifiably termed ''viral controllers'' rather than EC.
The requirement of only one HIV-RNA measurement below a certain threshold (B and C) also resulted in relatively high proportions of EC (2. 47% and 4. 12%, respectively), agreeing with studies previously reporting proportions of individuals with $1 HIV-RNA undetectable  [27, 28] , and suggesting that one undetectable measurement is insufficient in defining EC status. HIV-RNA values were relatively high during EC period for both definitions with the upper quartile experiencing HIV-RNA values. 8000 copies/ml. Similarly, even while classified as EC, CD4 cell counts were significantly declining. Thus, the use of at least two HIV-RNA counts results in more   E , c ) F ,and d) J using the CSCADE dataset. A: HIV-positive $6 months, with $2 consecutive HIV-RNA ,75 copies/ml; E: HIV-positive $1 year, with $3 consecutive HIV-RNA ,75 copies/ml spanning $12 months F: HIV-positive $1 year, with $3 consecutive HIV-RNA ,75 copies/ml spanning $12 months with no previous blips $1000 copies/ml, J: HIV-positive $10 years, with $90% of HIV-RNA ($2 HIV-RNA ever) ,400 copies/ml.
This is most evident in definition J, requiring. 2 HIV-RNA measurements and at least 10 years of follow-up with. 19,000 individuals Table  5. HIV-RNA and CD4 values and estimated CD4 slope during elite control (EC), and throughout ART-naı ¨ve follow-up using the CASCADE dataset applied to 10 definitions of EC found in the literature. with either insufficient follow-up or number of HIV-RNA measurements. To examine the impact of missing data on this, for each definition we classified individuals with inadequate information (insufficient number of HIV-RNA measurements or follow-up requirements specified by the definition) as EC and then as non-EC. The proportion of EC; however, may theoretically range from 0. 04, if all unknowns are classified as non-EC, to 74%, if all unknowns are classified as EC (data not shown) indicating the difficulties with estimating the true proportion of this group in the presence of missing data.
Supporting Information Table  S1  Number of HIV-RNA and CD4 measurements during elite control and ART naı ¨ve follow-up, time from SC to first HIV-RNA and number of HIV-RNA measurements within 6 months of HIV positive test date using the CASCADE dataset from 10 definitions found in the literature. Note-all values unless otherwise stated are median (IQR) {CD4 slope modelled on the square root scale with linear mixed models A: HIV-positive $6 months, with $2 consecutive HIV-RNA ,75 copies/ml; B: HIV-positive $1 year, with $1 HIV-RNA ,50 copies/ml, C: HIV-positive $1 year, with $1 HIV-RNA ,75 copies/ml, D: HIV-positive $1 year, with $3 HIV-RNA ,2000 copies/ml, E: HIV-positive $1 year, with $3 consecutive HIV-RNA ,75 copies/ml spanning $12 months F: HIV-positive $1 year, with $3 consecutive HIV-RNA ,75 copies/ml spanning $12 months with no previous blips $1000 copies/ml, G:HIV-positive $2 years, with $2 HIV-RNA ,75 copies/ml, H: HIV-positive $5 years, with $5 consecutive HIV-RNA ,500 copies/ml, I: HIV-positive $10 years, with all measured HIV-RNA ,50 copies/ml, J: HIV-positive $10 years, with $90% of HIV-RNA ($2 HIV-RNA ever) ,400 copies/ml.
Acknowledgments CASCADE Steering Committee:  Julia Del Amo  (Chair),  Laurence Meyer  ( Vice Chair ),  Heiner C. Bucher , Genevieve Chene,  Osamah Hamouda ,  Deenan Pillay ,  Maria Prins ,  Magda Rosinska ,  Caroline Sabin ,  Giota Touloumi. CASCADE Co-ordinating Centre:  Kholoud Porter  ( Project Leader ),  Ashley Olson ,  Kate Coughlin ,  Sarah Walker ,  Abdel Babiker. CASCADE Clinical Advisory Board :  Heiner C. Bucher ,  Andrea De Luca ,  Martin Fisher ,  Roberto Muga  CASCADE Collaborators: Australia PHAEDRA cohort ( Tony Kelleher ,  David Cooper ,  Pat Grey ,  Robert Finlayson ,  Mark Bloch )  Sydney AIDS Prospective Study and Sydney Primary HIV Infection cohort  ( Tony Kelleher ,  Tim Ramacciotti ,  Linda Gelgor ,  David Cooper ,  Don Smith );  Austria Austrian HIV Cohort Study  ( Robert Zangerle ); Canada South Alberta clinic ( John Gill );  Estonia Tartu U ¨likool (Irja Lutsar) ;  France ANRS CO3 Aquitaine cohort (Genevieve Chene ,  Francois Dabis ,  Rodolphe Thiebaut ,  Bernard Masquelier ),  ANRS   CO4  French Hospital Database ( Dominique Costagliola ,  Marguerite Guiguet ),  Lyon Primary Infection cohort (Philippe Vanhems) ,  French ANRS   CO6  PRIMO cohort ( Marie-Laure Chaix ,  Jade Ghosn ),  ANRS   CO2  SEROCO cohort ( Laurence Meyer ,  Faroudy Boufassa );  Germany German HIV-1 seroconverter cohort  ( Osamah Hamouda ,  Claudia Ku ¨cherer ,  Barbara Bartmeyer );  Greece AMACS (Paparizos V, Gargalianos-Kakolyris P, Lazanas M) ;  Greek Haemophilia cohort  ( Giota Touloumi ,  Nikos Pantazis ,  Olga Katsarou );  Italy Italian Seroconversion Study  ( Giovanni Rezza ,  Maria Dorrucci ), ICONA cohort ( Antonella d'Arminio Monforte ,  Andrea De Luca.
ACKNOWLEDGMENTS Sponsorship for this study and article processing charges were funded by  Galderma International S. A. S France. All named authors meet the ICMJE criteria for authorship for this manuscript, take responsibility for the integrity of the work as a whole, and have given final approval to the version to be published. Editorial assistance in the preparation of this manuscript was provided by  Dr. Lisa Swanson  of  Havas Life Medicom. Support  for this assistance was funded by  Galderma International S. A. S France.
, 2009; Shahzad et al. , 2013). Overall, these datasets indicate that PDF1s have a pivotal role in the plant response to both biotic (response to pathogens) and abiotic stress (here zinc excess). PDF1 transcripts are constitutively accumulated at a much higher level in A. halleri than in A. thaliana, which is the main feature that differentiates the two species. In metal extremophile species, the evolution of hyperaccumulation is associated with drastic transcriptomic changes, which so far have been mainly shown by high constitutive transcript accumulation of metal homeostasis related genes  (Talke et al. , 2006; Van De Mortel et al. , 2006). This high constitutive transcript accumulation of metal homeostasis related genes was noted in comparison to A. lyrata and A. thaliana, which are close phylogenetic relatives  (Koch and Matschinger, 2007; Schranz et al.
The specificity of primer pairs was assessed by sequencing the PCR product from the genomic DNA template (data not shown). The PCR efficiency (E) of each AtPDF1 primer pair was determined after the analysis of 5 serial 1:10 dilutions of plasmid DNA (Supplementary Table  1 ). Actin was used as internal control  (Shahzad et al. , 2010 (Shahzad et al. , , 2013)). PCRs were performed on cDNA samples in triplicate. The qRT-PCR results were considered when the threshold cycle (C t ) was below 35, as recommended in  (Bustin et al. , 2009). Above this value, transcripts were considered as non-detected. The C t value obtained for all experiments are listed in Supplementary Table  2. Actin relative expression levels (REL) with efficiency correction were determined as previously described  (Shahzad et al.
Note that since FFP does not rely on sequence alignment, bootstrap resampling was not done on alignment sites but rather on distance matrix columns, as detailed in  Sims et al. (2009). Searches for cis-regulatory motifs were performed by considering either the promoter region corresponding to the full set of studied PDF1s or the one corresponding to the subset of four PDF1s responding positively to MeJA treatment. The subset of negatively responding PDF1s was not considered as it just involved a single sequence. Searches for cis-regulatory motifs were conducted using the TOUCAN workbench  (Aerts et al. , 2005). With the TOUCAN graphical interface, motifScanner software  (Aerts et al. , 2003)  was used to search for known regulatory elements stored in PlantCare  (Lescot et al. , 2002). Motifs having a P-value < 0.
thaliana and A. halleri with respect to their response to JA signaling pathway activation, i. e. , their main responsive feature. Indeed, responsiveness to JA signaling pathway activation has not been systematically conserved during paralogous duplication events (AtPDF1. 2b and AtPDF1. 3), nor has it been systematically conserved in syntenic orthologues (see PDF1 present at locus 2). This is indicative of evolutionary differences that exist in PDF1 expression amongst A. thaliana and A. halleri species, which could potentially be due to micro-divergences in promoter regions amongst members of this multigenic family. Indeed, this study highlighted four punctual nucleotide motifs, which so far have not been described as being associated with or involved in the JA-response. They are annotated in the PlantCare database as related also to light-responsive elements.
ACKNOWLEDGMENTS Thi Ngoc Nga Nguyen  is supported by a Ph. D. scholarship from the  University of Science and Technology of Hanoi. We are thankful to  Dr. Pierre Saumitou-Laprade  for kindly providing us with A. halleri seeds collected at the site of Auby, France. We are greatly indebted to  Dr. Christian Dubos  for critical advice regarding in silico promoter analysis. We are grateful to  Drs. Hatem Rouached  and  Zaigham Shahzad  for helpful comments on the manuscript.
Method The primary objective of our study was to evaluate the risk factors of SIEs in RTX treated patients. This is a case-control study. Cases for analysis were defined as "RTX courses with occurrence of SIEs" and controls as "RTX courses without SIEs". Data were collected in a single centre of internal medicine (National Centre for Rare Systemic Auto-immune Diseases, Lille, France). All patients who received off-label RTX for SAID between 2005 and 2011 were included in the study. Due to the individual and nominative dispensation of this drug, the central pharmaceutical department was able to forward an exhaustive list of all the patients treated in our department. There were no exclusion criteria; all patients were taken into account. A course of RTX was defined as IV infusions of either 2×1,000 mg given 2 weeks apart or 4×375 mg/m 2 given 4 weeks apart.
Statistics SIEs were right censored at 12 months after the first perfusion of RTX for each treatment course. The influence of patient's characteristics at the start of an RTX course was estimated by logistic regression models. Some patients underwent several courses of RTX, and, as analysis had focus on each RTX course and not on each patient, these RTX courses for a same patient could not be assumed to be independent. Therefore, the analysis was adjusted for clustered data (procedure SURVEYLOGISTIC). Results are expressed as odds ratios with their two-sided 95 % confidence intervals. Analyses were conducted using the SAS 9. 1. 3 statistical software (SAS Institute, Cary, NC, USA).
Laboratory monitoring Ig levels, CD4 lymphocyte count and CD19 lymphocyte count were monitored. Due to the observational nature of the study, data were not collected at regular intervals. Before the first RTX infusion for each cure, the mean IgG level was 9. 9±6. 9 g/l (n=51), and lymphocyte counts were 1,267±976/mm 3 with 627±474 CD4/mm 3 and 3. 4±6. 4 CD19/mm 3. During the 6 following months, the mean IgG level decreased to a nadir of 8. 7±4. 8 g/mm 3 (n= 56) compared to IgA or IgM which both remained virtually unchanged. Sixteen out of 42 patients with documented IgG values experienced an IgG level below 6 g/l, and ten had a nadir below 5 g/l. Post course CD19 counts were documented in 59 patients, and 31 (52. 5 %) had no CD19 (i. e. a count equal to 0/mm 3 ) after the RTX course. CD4 count decreased from 627±474/mm 3 to a nadir of 469± 384/mm 3.
The leishmaniases are vector-borne diseases that have a broad global distribution throughout much of the Americas, Africa, and Asia. Despite representing a significant public health burden, our understanding of the global distribution of the leishmaniases remains vague, reliant upon expert opinion and limited to poor spatial resolution. A global assessment of the consensus of evidence for leishmaniasis was performed at a sub-national level by aggregating information from a variety of sources. A database of records of cutaneous and visceral leishmaniasis occurrence was compiled from published literature, online reports, strain archives, and GenBank accessions. These, with a suite of biologically relevant environmental covariates, were used in a boosted regression tree modelling framework to generate global environmental risk maps for the leishmaniases.
Evidence of leishmaniasis For each province or state across the globe (classed as Admin 1 by the Food and Agriculture Organization's Global Administrative Unit Layers  (FAO, 2008) , totalling some 3450) evidence was collected regarding CL and VL presence or absence. An assessment of the consensus of this evidence ranging from comprehensive agreement on disease presence (+100%) to consensus of disease absence (-100%) was made. Figures 1A-4A present these evidence consensus maps, with full reasoning for each administrative unit's score outlined in the associated data set (Dryad data set doi: 10. 5061/ dryad. 05f5h). For Brazil, it was possible to perform this analysis at the district level (classed as Admin 2) totalling some 5510 units. In total, 950 Admin 1 units from 84 countries reported a consensus on CL presence greater than indeterminate (a score of 0), with 310 Admin 1 units from 42 countries reporting a complete consensus on the presence of CL.