dataesr/scientific-paragraphs-categorization huggingface dataset:
2 g L 21 salmon sperm DNA) and denatured for 5 min at 95uC before cooling for 5 min at room temperature. Labelled cDNA was then applied to the microarray slide, covered with Hybri-Slip cover slips (Molecular Probes), placed in hybridization chambers (Corning) and hybridized overnight at 42uC. Following hybridization, the slides were washed twice in 0. 16 SSC, 0. 1% SDS (42uC, 10 min) and twice in 0. 16 SSC (room temperature, 10 min). After drying by centrifugation (5 min at 8006g), the hybridized slides were scanned with a SYS-SN-ARRAY Agilent Microarray Scanner (Agilent, Santa Clara, CA, USA) at 10 mm resolution. 3) Data analysis. The signal and background intensity values in both channels for each printed spot were obtained using GenePix Pro 6. 0 software (Axon Instruments, USA). Spots with a reference signal lower than background plus two standard deviations were excluded.
A total of four arrays were performed using biological replicates (RNA samples were collected from four cultures in BSIC and M9-Glc respectively on separate days). Two microarrays were hybridized with cDNA from BSIC and M9-Glc labelled with cy3 and cy5 respectively and other two hybridizations with cDNA samples conversely labelled. Empty and flagged spots were excluded, and intensities were transformed using a base-2 logarithm. Data normalisation and differential analyses were done using R software. A background correction based on a convolution model which was found to stabilize the variance of the log-ratios (normexp + offset) was processed using limma R package (http://www. bioconductor. org/packages/2. 6/bioc/html/limma. html)  [24]. The mean spot intensity-dependent dye effect was corrected by performing a global Lowess normalization.
In silico analysis The list of genes was submitted to Database for Annotation, Visualization and Integrated Discovery (DAVID) (resource v6. 7) (http://david. abcc. ncifcrf. gov/summary. jsp) to access a relational database of functional annotation  [29, 30]. The genes were categorized in Gene Ontology (GO) categories (''Biological Process'' or ''Compartment cellular'') using the chart feature offered by DAVID (http://www. geneontology. org/GO. nodes. html). The Gene Functional Classification tool in DAVID builds clusters of genes with significantly similar ontologies as tested against whole E. coli genomes. For each gene list clustered in the different GO terms, DAVID calculated an ''Expression Analysis Systematic Explorer'' (EASE) score (also called enrichment score) corresponding to a modified Fisher Exact P-value (ranged from 0 to 1).
Expression of genes involved in the metabolism of carbon sources A high enrichment score was obtained for the genes categorized in the tricarboxylic acid (TCA) cycle GO category when E. coli EDL933 was incubated in BSIC in comparison with M9-Glc (Table  1 ). The genes associated with the TCA cycle are listed in Table  2. The Embden-Meyerof-Parnas (EMP), Entner-Doudoroff (ED) and Pentose-phosphate (PP) pathways are essential for E. coli central metabolism and provide the main routes of carbon flux. However, transcription of genes encoding enzymes required for the different steps of the EMP, ED and PP pathways was not significantly altered in EDL933 incubated in BSIC (GEO database: accession number GSE49468). The TCA cycle that can be activated by both glycolytic and gluconeogenic substrates,  is essential for respiration-mediated ATP synthesis and the generation of precursors for many other biosynthetic pathways.
In this study, the genes classified in the gluconeogenesis (GNG) GO category were significantly up-regulated by EHEC EDL933 in BISC (Table  1 ). GNG is essentially a reversal of glycolysis but certain GNG steps are irreversible and thus performed by specific enzymes. During incubation in BSIC, EDL933 up-regulated genes involved in irreversible GNG reactions. As shown in Table  2  and Fig. 2 , transcription of the genes encoding the irreversible key GNG enzymes, phosphoenolpyruvate (PEP) synthase (ppsA), fructose-1,6-bisphosphatase (fbp) and PEP carboxykinase (pckA) was induced. In contrast, transcription of the genes coding for the enzymes catalyzing irreversible glycolysis steps (pfkA, pfkB and pykF) was not significantly altered (GEO database: accession number GSE49468). In addition to the observed GNG gene up-regulation, EHEC EDL933 induced pathways involved in assimilation of GNG substrates such as glycerol, glycerol-3P, L-lactate and C4dicarboxylate.
Simulation data was obtained based on 1,000,000 reintroductions of the first strain into a fully susceptible population (increased to 10,000,000 reintroductions for N p 50,000 and Nm p 0. 001). We looked at the case where the initial R 0 is low, ranging between 1 and 1. 2, and can mutate into a more adapted strain with F 0 equal to 1. 2, 1. 5, 1. 8, or 2. 5. For simplicity (unless stated otherwise), the removal rates for both strains (by this we mean the recovery rate) was set to 1, therefore the transmission rate was equal to the reproductive ratio. Since the long-term probability of extinction for both strains is 1 with SIR dynamics, we say that the second strain has "emerged" if it reaches its outbreak threshold, here set to 5/log(F 0 ) infected hosts. This threshold means that it subsequently has less than a 0.
5% probability of becoming extinct by stochastic drift  (Hartfield and Alizon 2013b). Note that the analytical solution (eq. [5c]) gives the emergence probability of a second strain given that the first strain has emerged. Therefore, we scale down our analytical solution by 1 Ϫ 1/R 0 , the emergence probability of the first strain in a fully susceptible population  (Allen 2008) , in order to account for the first strain emerging in the simulations. Simulations were written in C, and source code was deposited in the Dryad Digital Repository: http://dx. doi. org/10. 5061/dryad. kj238 (Hartfield and Alizon 2013a ). 1.
Acknowledgments We would like to thank  D. Fontenille  for advising us on the epidemiology of the Chikungunya outbreak on La Reunion,  L. Wahl  for discussions on the mathematical analysis, and two anonymous reviewers for helpful comments on the manuscript. M. H. is funded by an  ATIP-Avenir  grant from  CNRS  and  Institut national de la santeet de la recherche medicale (INSERM)  to S. A. ; S. A. and M. H. acknowledge additional support from the  CNRS  and the  Institut de Recherche pour le Developpement (IRD).
For the amplification of nine nuclear markers (rag, gapdhs, s7, bmp4, ednrb1, mitfa, tyr, hag and csfr1), we used the primer sets published in ref. 36. The sequences of M. zebra, O. niloticus and N. brichardi were extracted from the respective genome assemblies (http://www. broadinstitute. org/models/tilapia). The data for Astatoreochromis alluaudi, Thoracochromis brauschi and Serranochromis macrocephalus were collected with Sanger sequencing following the method described in ref. 36, all other data were generated by amplicon sequencing with 454 GS FLX system at Microsynth, Switzerland, following the manufacturer's protocols  37, 38. Sequences were quality filtered using PRINSEQ (length: 150 bp minimum; low quality: mean Z15; read duplicates)  39  and assembled with Burrows-Wheeler Aligner, Smith-Waterman alignment (BWA-SW) followed by visual inspection and consensus sequence generation in Geneious 6.
1. 6 (ref. 40). As a tenth marker, we included mitochondrial NADH dehydrogenase subunit 2 (ND2) sequences available on GenBank (see Supplementary Table  1  for accession numbers). Since the ednrb1 gene sequence is not available in the N. brichardi genome assembly, we used the gene sequence from its sister species, N. pulcher, instead. Sequences were aligned with MAFFT  41  and the most appropriate substitution model of molecular evolution for each marker was determined with JMODELTEST v2. 1. 3 (ref. 42) and BIC  43. The partitioned data set (5,051 bp) was then subjected to phylogenetic analyses in MRBAYES v3. 2. 1 (ref. 44) and GARLI v2. 0 (ref. 45). MRBAYES was run for 10,000,000 generations with two runs and four chains in parallel and a burn-in of 25%, GARLI was run 50 times followed by a bootstrap analysis with 500 replicates.
SUMTREES v3. 3. 1 of the DENDROPY package v3. 12. 0 (ref. 46) was used to summarize over the replicates and to map bootstrap values to the ML topology. Differential gene expression analysis using RNAseq. We used a transcriptomic approach (RNAseq) to identify genes differentially expressed between male and female anal fins of A. burtoni. Library construction and sequencing of RNA extracted from three male and three female anal fins (at the developmental stage of 30 mm; Fig. 2 ) was performed at the Department of Biosystems Science and Engineering, University of Basel and ETH Zurich. The samples were sequenced on an Illumina Genome Analyzer IIx. Each sample was sequenced in one lane and with a read length of 76 bp. The reads were then aligned to an embryonic A. burtoni reference transcriptome assembled by Broad Institute (http://www.
broadinstitute. org/ models/tilapia). This transcriptome is not annotated and each transcript has a nomenclature where the first term codes for the parent contig and the third term codes for alternatively spliced transcripts (CompX_cX_seqX). The reference transcriptome was indexed using NOVOINDEX (www. novocraft. com) with default parameters. Using NOVOALIGN (www. novocraft. com), the RNAseq reads were mapped against the reference transcriptome with a maximum alignment (t) score of 30, a minimum of good-quality base pair per read (l) of 25 and a successive trimming factor (s) of 5. Reads that did not match these criteria were discarded. Since the reference transcriptome has multiple transcripts/isoforms belonging to the same gene, all read alignment locations were reported (rALL). The mapping results were reported (o) in SAM format.
The output SAM file was then transformed into BAM format, sorted, indexed and converted to count files (number of reads per transcript) using SAMTOOLS version 0. 1. 18 (ref. 47). The count files were subsequently concatenated into a single data set-count table-and analysed with the R package EDGER  48  in order to test for significant differences in gene expression between male and female anal fins. The 10 most differentially expressed transcripts were identified by BLASTx 49 against GenBank's nonredundant database (Supplementary Table  2 ). We selected two genes out of this list for in-depth analyses-fhl2a and fhl2b-for the following three reasons: (i) fhl2b was the gene showing the highest difference in expression between male and female anal fins; (ii) the difference in gene expression in its paralog, fhl2a, was also significantly high; and (iii) the functional repertoire of the Fhl2 protein family indicates that these might be strong candidates for the morphogenesis of a secondary male colour trait.
The insertion and direction of the fragments was confirmed by Sanger sequencing using M13 primers (available with the cloning kit) and BigDye terminator reaction chemistry (Applied Biosystems) on an AB3130xl Genetic Analyzer (Applied Biosystems). In situ hybridization was performed in 12 fins from A. burtoni males, six for fhl2a and six for fhl2b. The protocol was executed as described in ref. 16, except for an intermediate proteinase K treatment (20 min at a final concentration of 15 mg ml À 1 ) and for the hybridization temperature (65 °C). Synteny analysis of teleost fhl2 paralogs. The Synteny Database (http://syntenydb. uoregon. edu  54 ) was used to generate dotplots of the human FHL2 gene (ENSG00000115641) region on chromosome Hsa2 and the genomes of medaka (Supplementary Fig. 2a ) and zebrafish (Supplementary Fig.
Acknowledgements We thank  A. Theis ,  T. Bosia ,  B. Egger ,  G. Banyankimbona ,  E. Schraml ,  M. Muschick  and  H. Gante  for their assistance with the photographs;  P. Beldade ,  J. Ganz ,  H. Hoekstra ,  J. H. Postlethwait ,  G. Wagner  and the members of the  Salzburger Laboratory  for their discussions;  J. Bessa  for sending us the ZED vector;  V. Laudet  for providing medaka and zebrafish;  J. Ganz ,  University of Oregon  and the  Imaging Core Facility of the Biozentrum, University of Basel  for their support with confocal microscopy; the  University of Oregon zebrafish facility ,  A. Indermaur  and  A. Ru  ¨egg (Basel) for fishkeeping; and the  BROAD Institute  and the  Cichlid Genome Consortium  for the cichlid genomes. This study was supported by grants from the  Fundac¸a ˜o para a Ciencia e Tecnologia (FCT, Portugal)  to M.
Background. Contemporary antiretroviral treatment regimens are simpler than in the past, with lower pill burden and once-daily dosing frequency common. We performed a meta-analysis of randomized controlled trials (RCTs) to investigate the impact of pill burden and once-daily vs twice-daily dosing on ART adherence and virological outcomes. Methods. A literature search of 4 electronic databases through 31 March 2013 was used. RCTs comparing oncedaily vs twice-daily ART regimens that also reported on adherence and virological suppression were included. Study design, study population characteristics, intervention, outcome measures, and study quality were extracted. Study quality was rated using the Cochrane risk-of-bias tool. Results. Nineteen studies met our inclusion criteria (N = 6312 adult patients).
Search Strategy We systematically searched the following databases from their inception until 31 March 2013 (including those years searched by the Parienti meta-analysis): Cochrane CENTRAL, PubMed, Google scholar, and Web of Science. Our search terms included the following: "HIV," "treatment simplification," "coformulation," "fixed-dose combination," "QD," "twice-daily," "once-daily," "adherence," "HAART," "ART," "cART," and "patient preference. " We also searched abstracts from major HIV/ AIDS and infectious diseases conferences (from 2008 onward) including Conference on Retrovirus and Opportunistic Infections, International AIDS Conference, International AIDS Society Conference on HIV Treatment, Pathogenesis and Prevention, International Conference on Antimicrobial Agents and Chemotherapy, and Infectious Diseases Society of America Conference.
This review was performed according to the PRISMA recommendations for meta-analyses of RCTs  [40]. Stata 12 (Stata Corporation, College Station, TX) and Review Manager 5. 2 software (http://ims. cochrane. org/revman) were used for meta-analysis; Trial Sequential Analysis Software, version 0. 9 beta (www. ctu. dk/tsa), was used for the trial sequential analyses.
Our results suggest that these savings may be counterbalanced, in part, by worse virological outcomes if an increase in pill burden is required. However, no study, including ours, was specifically designed to directly investigate the impact of desimplification involving switching patients from once-daily STR to once-daily ART regimens containing multiple tablets. Further research is urgently needed to address this question. Our study has several strengths. We performed a comprehensive search of several databases and sources to identify eligible RCTs that provide the highest quality of evidence. Three authors independently evaluated each study for inclusion and data extraction. Furthermore, we performed a trial sequential analysis; this is an efficient decision-making tool that is used to establish whether firm evidence of effect has been obtained  [70].
Acknowledgments. We thank  Dr Catherine Orrell, MBChB ,  University of Cape Town , and  Dr Calvin Cohen, MD ,  Harvard Medical School, Boston, MA , for critical reading of this manuscript. Financial support. There was no funding source for this study. Research grant support. The  US National Institutes for Allergy and Infectious Disease-National Institutes of Health (NIAID-NIH) ,  AIDS Clinical Trial Group (ACTG) ,  Stellenbosch University (SU)-Clinical Trial Unit (CTU)  Award:  2UM1AI069521-08  (J. B. N. ); the  US NIH-Fogarty International Center (FIC)/Health Resources and Services Administration  ( HRSA)/ US President Emergency Plan for AIDS Relief (PEPFAR) Grant Award ,  T84HA21652-01-00  for  Medical Education Partnership Initiative (MEPI).
Patient samples and gene expression data 206 patients with newly-diagnosed MM were enrolled in the current study after written informed consent at the University hospitals of Heidelberg (Germany) or Montpellier (France) (HM cohort). These patients underwent frontline induction treatment with Dexamethasone and various drugs, high-dose chemotherapy with 200 mg/m2 Melphalan and autologous stem cell transplantation according or in analogy to the GMMG-HD3-trial  [66]. At relapse, various treatments regimens were applied including Bortezomib and immunomodulatory drugs (Thalidomide, Lenalidomide, Pomalidomide). Bone marrow was harvested at diagnosis, MMCs were purified, gene expression profiling (GEP) assayed using Affymetrix U133 2. 0 plus microarrays, and data normalized using the MAS5 Affymetrix algorithm with a scaling factor of 500 as described previously  [67].
The. CEL and MAS5 files are deposited in the Array Express public database (http://www. ebi. ac. uk/arrayexpress/) under accession number E-MTAB-362. Publicly available MAS5 normalized GEP data (GEO, http://www. ncbi. nlm. nih. gov/geo/, accession number GSE2658) from purified MMCs of a cohort of 345 patients were also used. These patients were treated with total therapy 2 protocol (UAMS-TT2 cohort) at the University of Arkansas for Medical Sciences (UAMS, Little Rock, USA)  [68].
Identification of prognostic Drug Metabolism and Clearance genes (DMC genes) and DMC score building Based on the review of literature and databases  [69] , a consensus list of 350 human genes coding for xenobiotic receptors and co-regulators (29 genes), phase I DMEs (107 genes), phase II DMEs (90 genes) and uptake and efflux transporters (124 genes) was selected. The corresponding Affymetrix probe sets and gene ontology description are listed in the Supplemental Table  S1. When several probe sets were available for a same gene, the probe set with the highest variance was chosen. Genes whose expression in MMCs could predict for patients' Event Free Survival (EFS) were identified using a univariate Cox Model. A prognostic Drug Metabolism and Clearance score (termed DMC score) was built by computing the mean of the standardized Affymetrix signals of the prognostic genes weighted by their Cox Beta Coefficient.
Data Analysis The analyses were done with R (http://www. rproject. org/) and Bioconductor (http://www. bioconductor. org/) softwares. Survival curves were plotted using the Kaplan-Meier method. Gene expression data were visualized using Cluster (v2. 11) and Tree View (v1. 6, Eisen laboratory, Berkeley, USA). Ingenuity Pathway Analysis (IPA) software was carried out using a false discovery rate (FDR < 0. 05) with at least 5 genes for one pathway. Gene set enrichment analysis was performed using the GSEA Software (http://www. broadinstitute. org/ gsea/index. jsp, Broad Institute, Cambridge, USA), and the collections for canonical pathways (c2. cp. kegg) or transcription factor targets (C3. tft).
ACKNOWLGEMENTS This work was supported by grants from the  French INCA (Institut National du Cancer) Institute  ( 2012-109/087437 ), the  European Community  ( FP7-OVERMYR) ,  FEDER  ( 141786 & 42667 ) and the  University Hospital of Montpellier  ( CEP-IRB ). We thank  Mrs Pantesco  from the  Microarray Core Facility of IRB  (http://irb. montp. inserm. fr/en/index. php?page=Plateau&IdEquipe=6).
Analyses Interviews were tape-recorded and transcribed. The "MaxQDA 07" software (Maxqda 2007, http://www. maxqda. com) was used to manage and analyse the qualitative data collected. We conducted a thematic content analysis of the interviews  [24]. The qualitative analysis started with individual readings by three researchers (two midwives and one psychologist [MJG, NJ, CC]). The analysis continued during data collection and the encoding process using the constant comparative method, which consists of analysing the interviews by comparing one response to earlier reported responses  [25]. This analysis was subsequently used to establish analytical categories that were used as a basis for the final grid used by the three researchers to analyze the transcripts in order to maximize the theoretical sensitivity and rigour  [26].
Using participant-generated data via the interviews and verifying their interpretation using triangulation between the three researchers allowed to assess their reliability  [27]. Research methods to determine the credibility, conformability, and transferability were derived from previous comparable studies  [28]. In accordance with the stated objectives, the analyses focused on the identification of key delivery experience elements and similarities and differences, depending on the mode of delivery. Emergent data were corroborated with existing theories and compared to previous research data to assess their degree of conformity. Finally, background data were provided to ascertain the study context and allow comparisons.
The morphological properties of genealogical and marriage alliance networks constitute a key to the understanding of matrimonial behavior and social norms, in particular where these norms have not been explicitly formalized. Their analysis, however, faces a major difficulty: the actual datasets which allow researchers to reconstruct kinship and alliance networks are generally subject to a marked observer bias, if only due to limitations of observer mobility and/or informant memory. This paper presents an agent based simulation method destined to evaluate the impact of this bias on some key indicators of kinship and alliance networks (such as matrimonial circuit frequencies). The method consists in explicitly simulating the exploration of a given network by a virtual observer, the bias being introduced by the observer's inclination for choosing informants who are more or less closely related to each other.
1. 5 We will start by introducing the basic notions of kinship and alliance networks and present the problem of interpreting matrimonial circuit censuses, drawing on an empirical example. We shall then present the virtual fieldwork model, which we apply both to genealogical and to alliance networks. We will show that observer behavior, even if as neutral and objective as possible but subject to constraints related to the examined kinship system (such as residence rules), may lead to a bias which not only distorts the "brute" data but also the more subtle indicators we may hope to construct from them, such as potential or expected circuits. In the conclusions, we will address the questions how, in spite of these difficulties, we may still use genealogical datasets to study matrimonial practices.
2. 4 To illustrate these concepts, let us consider a dataset collected by Michael Gasperoni ( 2011, 2013), drawing on the matrimonial practices of Jewish families in early modern central Italy ("Ebrei", downloadable at www. kinsources. net/  [3] ). The genealogical network (figure  1a ) contains 2597 marriages (edges) for 7331 individuals (nodes), distributed over 15 generations. From this network we can derive the alliance network of patrilineal components (figure  1b ), where the same marriages (arcs) are distributed between 1740 patrilineal groups (nodes). The circuit census.
2. 20 Since the models for genealogical and for alliance networks are very similar (though not identical), we shall present their general characteristics in the section concerned with genealogical networks, while the section on alliance networks will focus on the differences. 2. 21 Both models have been implemented in the free software Puck 2. 0. (download at http://www. kintip. net/). The source code is available at http://sourceforge. net/projects/tip-puck/  [5].