dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical analysis Continuous data are described as means and standard deviations (mean ± SD) or as medians and ranges (median (range)). For all analyses, since serum IL-33 is not systematically detectable, we presented qualitative results as detectable serum IL-33 or undetectable serum IL-33. Among patients of the SMART cohort, we compared patients who were assessed for serum IL-33 level and those who were not due to the availability of the serum samples. Student and Wilcoxon tests were used to compare quantitative values and the Chi-squared test was used for qualitative values. We analyzed by logistic regression the relationship between EULAR response at 24 weeks and the following four explanatory variables: 1) high disease activity defined as DAS28-CRP >5. 1; 2) high serum IgG level; 3) auto-antibody status (i.
e. , the presence or absence of RF and/or anti-CCP antibodies), since all of them have been found previously as associated with subsequent RTX response  [25, 26] ; and 4) detectable serum IL-33. All these explanatory variables were entered in a stepwise multivariate model systematically adjusted on RF or anti-CCP positivy (entry level, p = 0. 15; level for staying in the model, p = 0. 10). Results are expressed as odds ratios (ORs) with 95% confidence intervals (CIs). A p value <0. 05 was considered as significant. Statistical analysis was performed with SAS 9. 4 software.
Acknowledgements We thank the other members of the scientific committee of the SMART study:  Pr. J. Sibilia  ( Strasbourg, France ),  Pr. J. Tebib  ( Lyon, France ),  Pr. B. Combe (Montpellier, France) , and  Pr. X. Le Loët (Rouen, France). We thank all the SMART investigators:  Dr. I. Azais , Poitiers;  Dr. J. C. Balblanc , Belfort;  Dr. F. Berenbaum , Paris;  Dr. P. Bertin , Limoges;  Dr. M. -C. Boissier , Bobigny;  Dr. P. Bourgeois , Paris;  Dr. A. Cantagrel , Toulouse;  Dr. P. Carli , Toulon;  Dr. P. -Y. Chouc ,  Marseille; Dr. M. Couret , Valence;  Dr. L. Euller-Ziegler , Nice;  Dr. P. Fardellone , Amiens;  Dr. P. Fauquert ,  Berck/Mer ;  Dr. R. -M. Flipo , Lille;  Dr. P. Gaudin , Echirolles;  Dr. J. -L. Grauer , Aix en Provences;  Dr. A. Heraud , Libourne;  Dr. P. Hilliquin , Corbeil;  Dr.
[55]  3. 4 % in a paediatric ICU. Serious consequences have been described due to drug incompatibility, such as obstruction of catheter, therapeutic failure, or the occurrence of embolism  [56, 57]  of fatalities  [58, 59]. A number of practical measures can reduce the risks. Contact time between incompatible drugs can be limited by using multilumen catheters  [60]. Some hospitals have implemented strategies to avoid mixing incompatible drugs. For example, in Switzerland, a colour coding system according to drug pH was adopted over five years, resulting in a reduction in incompatibilities between acid and alkaline drugs  [61]. Double-entry tables, or lists of drugs commonly used, can be drawn up  [62]. Although a number of publications and databases deal with the subject  [63] [64] [65] , discrepancies exist among available references, data is often non-existent or incomplete, and usually describe only one mixture.
Conclusion IV infusions are extensively used in clinical wards, exposing patients to the risk of particulate contamination as well as drug incompatibility when several drugs have to be administered simultaneously through a limited number of venous accesses. Preventing both contamination and drug incompatibility are therefore essential to the safe administration of injectable drugs to polymedicated patients. Clinical pharmacists have an important role to play here: they must inform and educate the nursing staff on choices to be made and ways of preventing drug incompatibilities in ICUs (research in literature and databases, double-entry tables, use of multi-lumen infusion devices, in-line IV filters, identification of drugs by colour-code according to pH, etc). Medical devices (e. g. plastic materials, silicon oil, sterilisation process) or drug handling (e.
Background: The bacteria of the Borrelia burgdorferi (s. l. ) (BBG) complex constitute a group of tick-transmitted pathogens that are linked to many vertebrate and tick species. The ecological relationships between the pathogens, the ticks and the vertebrate carriers have not been analysed. The aim of this study was to quantitatively analyse these interactions by creating a network based on a large dataset of associations. Specifically, we examined the relative positions of partners in the network, the phylogenetic diversity of the tick's hosts and its impact on BBG circulation. The secondary aim was to evaluate the segregation of BBG strains in different vectors and reservoirs. Results: BBG circulates through a nested recursive network of ticks and vertebrates that delineate closed clusters.
Literature search Data on the pair-wise systematic associations of ticks in vertebrates, BBG in vertebrates and BBG in ticks were compiled from a literature review of journals that are searchable in the Thomson Reuters, Scopus and PubMed databases. A "record" was a pair-wise BBG-tick-vertebrate combination at a single geographical site. If the same pairwise combination was observed at the same site several times (for example, in seasonal collections), it was included only once. However, the same combination of partners at different sites was included once for each site in order to estimate how common that association was, and then the number of reports was used for weighting (see below). The literature search extended from January 1990 to December 2014. It was evident in the initial stages of the bibliographical search that the use of a long series of keywords (i.
e. a series based on the names of tick species and vertebrate hosts) would miss relevant studies. We therefore decided to perform a deliberately less stringent query that only included the generic names "Ixodes" OR "Borrelia" and then to critically evaluate the abstracts in order to manually select the papers that dealt only with ecological information. Papers addressing the clinical presentation, treatment or diagnosis of infections in humans were only included in the dataset if adequate information about the association of a species of tick and BBG was reported. We removed records involving livestock because they are considered accidental hosts, and those records would generate spurious information that would distort the relationships of the community of tick-borne pathogens  [23]. There are no compilations of records of BBG detected on ticks while feeding because the bacterial DNA cannot be reliably attributed to either the vertebrate or the vector.
It is important to stress that the network structure requires bivalent interactions (i. e. the pathogen must be associated with either the tick or the vertebrate). These associations ignore the effects of the vertebrate, which may transmit the pathogen to co-feeding ticks  [29, 30]. We also removed records involving species in the recurrent fever group, with some exceptions that were used as controls for the computations (see below), as well as records involving the ticks and vertebrates associated with this group. We updated the scientific names of BBG species to include the most recent and accepted ones  [1] [2] [3] [4] [5] [6] [7] [8]. Because of the lack of availability of the original publication at the time of the compilation, data on Borrelia chilensis and Ixodes stilesi  [2]  were not included in the analysis; we included only the records for I.
Multilocus sequence typing and ecological relationships Multilocus sequence typing (MLST) is a powerful molecular biology technique that is based on using the sequences of 8 chromosomal housekeeping genes to obtain information on population structure and the evolutionary relationships of BBG  [9]. We used MLST to evaluate the significance of the associations among strains of BBG and species of ticks or genera of vertebrates. For the MLST analysis, we used the sequences in the Borrelia MLST databases (http://pubmlst. org/ borrelia; accessed 19 Sept 2016). The data were updated with 613 additional sequences that were obtained from a variety of sources in Europe  [42]. The sequences of individual housekeeping genes were concatenated, and those that differed by one or more nucleotides were assigned allele numbers.
Some species of BBG linked a few otherwise isolated clusters, suggesting invasion events and further spread; these have been described previously  [10]. However, undetermined BBG genospecies were included in the network in order to use data obtained before modern molecular techniques became available, and this could result in bias in terms of the structure of the clusters. A combination of centrality indices was used to quantify the relative importance of each tick in the network, with centrality being positively correlated with the phylogenetic diversity of the species of ticks but not with its host richness. Vertebrates that had the highest centrality with ticks also contributed more to the circulation of the pathogens. Circulation of the pathogens is thus supported by a wide range of vertebrates and by the generalist ticks that they share.
If the environmental dimensions of the interacting species expanded, or if new species converged towards such niches due to interactions, then other species became part of the evolving network, leading to the observed sub-networks. We hypothesise that sub-networks are the result of secondary niches between ticks and hosts that led to subdivisions of the central core of the network. We updated the publicly available MLST dataset and produced 704 unique sequences with the aim of checking the links to ticks and/or vertebrates. These results are preliminary due to bias stemming from the reporting of the pathogens in only a few species of ticks and the scarcity of data from vertebrates. However, it is important to notice that (i) I. ricinus (western Palaearctic) and I. scapularis (eastern Nearctic) do not share any BBG strains; (ii) I.
The latter and all of the studies analyzed in this pooled analysis; however, were retrospective in nature. Prospective studies have not yet been completed to unequivocally show the clinical relevance of minority HIV-1 drug-resistance mutations. Furthermore, clinical cut-offs for the significance of such minority HIV-1 drug-resistance mutations have yet to be defined. More sensitive assays and studies are required to answer these questions. Here, we describe an assay with the potential to help answer these questions. All other authors declare no competing interest. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials. We previously described a multicenter study demonstrating high inter-laboratory correlation of UDS-detected minority HIV-1 drug-resistance mutations exclusively in HIV-1 subtype B samples.
Primer design The overlapping amplicons span PR codons 10-99, RT codons 1-251 and the entire V3 region. The amplicons were designed to provide dual coverage for Stanford Database (version 6. 0. 9) Drug Resistance PR and RT mutations with a score 5 (any drug) and tropism determinants in V3 (Fig A  and Table  A in S1 File). All primers were designed using the principles previously described, with the exception of allowing for 98% conservations instead of 99% as described in the referenced paper  [11]. The longer read length chemistry employed in this study reduced the required number of overlapping RTP amplicons from six to four and also allowed for placement of primers in sufficiently conserved areas outside the V3 region.
Sample characteristics The RTP samples used in this study were cultured recombinant virus diluted in plasma from HIV-1 negative individuals. The cloned inserts included the coding regions for the complete protease and the 5' 302 amino acids (aa) of the reverse transcriptase (nucleotide positions 2,002 to 3,457 based on the reference sequence HIV-1 HXB2 , GenBank accession number K03455). The V3 samples were cultured samples from patient isolates, diluted in HIV-1 negative plasma. Two control samples were generated for inter-and intra-laboratory comparison purposes (control sample A) and for amplification control (control sample B). Control sample A is a mixture of two plasmid samples obtained through the AIDS Research and Reference Reagent Program, Division of AIDS, NIAID, NIH: pM46I/L63P/V82T/I84V and pL10R/M46I/ L63P/V82T/I84V from Dr.
Ultra deep sequencing Each of the 4 amplicon pools was separately subjected to clonal emulsion PCR amplification on beads using reagents that enabled sequencing in both the forward and reverse directions (Lib-A kit, 454 Life Sciences-A Roche Company, Branford). DNA-containing beads were counted on a Multisizer3 instrument (Beckman Coulter Inc. ) and prepared for sequencing. Approximately 790,000 beads from each of the four pools were loaded in the four regions of a PTP fitted with a 4-lane gasket. Sequencing was performed on a GS FLX Titanium System (454 Life Sciences -A Roche Company, Branford). Resulting sequence reads were aligned to HIV-1 HXB2 by the GS Amplicon Variant Analyzer (AVA) v2. 3 software included with the 454 Life Sciences instrument. The AVA software demultiplexed barcoded reads and aligned them to the HIV-1 HXB2 reference while simultaneously eliminating primer-derived sequences.
Data analyses Data was analyzed for intra-and inter-laboratory concordance using the R statistical package  [13]  or GraphPad Prism software (GraphPad Software, San Diego, CA). The correlation of variant prevalence for sample replicates within sites and common samples across sites was also computed. In addition, the minimum, maximum and median variant levels, as reported by each site, were calculated to assess concordance with population sequencing results for all samples. For minority variant calling, 1% was chosen as cut off based on previous reports showing combined PCR and pyrosequencing error rates of 0. 1-0. 3% using HIV-derived clonal sequences  [14] [15] [16]. Tropism analysis was performed with the geno2pheno co-receptor algorithm for each V3 sample at a false positive rate setting of 3.
Overall performance Ten out of eleven sites delivered a complete data set. Sequencing information was obtained for 2,986 of 3,520 (85%) expected amplicons. One site was unable to deliver information for the second of their four plates (Table  1 ) and other sites encountered sporadic amplification failures. Table C in S1 File describes the details for each amplicon drop-out. The higher rate of drop-outs in plate 4 are due to the lower viral titers associated with the dilution series samples. Fig B I in S1 File shows the uniform distribution of the total number of high quality (HQ) reads (those reads that passed the amplicon data processing pipeline) per sequencing region for each site. Furthermore, almost all of the HQ reads could be aligned to HIV-1 HXB2 with the exception of those from site 27 (region 2) and sites 26 and 28 which delivered a reduced total number of HQ reads.
Inter-laboratory concordance To determine inter-laboratory variability of the current workflow for end users, each site was given a questionnaire to identify and report variant percentages using the AVA software. Ten preselected drug resistance mutations were chosen for this analysis, two were expected negatives (V179D, F227L), three were <5% prevalence (V75A, V82I, G73S) and the remaining five were >10% prevalence (Table  1 ). All readings reported in this table required a minimum of 15 reads in addition to successful amplicon generation as indicated by the amplification control on the relevant plate. A read coverage of <15 was defined as sequencing failure. Of those amplicons reported with sufficient read coverage, all but one was accurately detected and reported. The single highly inconstant variant was the I54V protease mutation on plate #2 of site 27.
Concordance with population sequencing The ViroSeq assay was performed on the sample set by a single laboratory to determine concordance with UDS. 99%-100% of drug resistance mutations detected by the population sequencing-based assay were also found by UDS by all sites (Table  3 ). Three categories of mutations were analyzed: i) major, defined as having a Stanford drug resistance database score >5, ii) polymorphic, defined as having a Stanford drug resistance database score <5 and iii) bulk, defined as any other difference from HIV-1 HXB2 at the amino acid level. The single discrepancy between UDS and population sequencing for the polymorphic mutation may be due to low sequencing coverage. Of clear clinical interest, we found that several population sequencing-called mutations were incorrect due to the inability of population sequencing to phase adjacent nucleotides.
Discussion The data presented here demonstrate that ultra deep sequencing can provide highly consistent results together with excellent cross-site correlation. For all drug resistance mutations identified by the Stanford Drug Resistance Database in the sequenced region, we demonstrate near perfect concordance with population sequencing results. In addition, 41 mutations were found by UDS in the reverse transcriptase and protease regions at frequencies below 20%. These low frequency mutations could not be detected by population sequencing due to its inherently lower sensitivity  [2]. Several studies have previously reported high concordance of UDS and standard population sequencing for mutations present at levels greater than 20-25% (reviewed in  [6, 17] ). One such study reported similar reproducibility of the UDS results with a correlation value of r 2 = 0.
969  [18]. Additionally, some variants called by population sequencing were incorrect due to the inability of population sequencing to phase individual nucleotides. In the example shown in Fig C in S1 File, population sequencing analysis indicated four possible mutations at codon 215, i. e. , T215 (ACT), T215Y (TAT), T215S (TCT), and T215N (AAT). In this particular case, the Serine and Asparagine codons were listed as a combinatorial possibility by the ViroSeq data analysis software, but UDS shows that both are not present among the actual quasispecies. Since T215Y is detected with both methods, it makes no clinical difference in this case, but it is easy to see how in certain instances this could cause interpretation of resistance where none is present, leading to unnecessary avoidance of a potentially useful drug regimen.
Looking at the technical performance of the assay, it was that certain amplicons performed more robustly than others, both in PCR and sequencing. In general, shorter amplicons can be expected to amplify with higher efficiency than longer ones  [19]. This phenomenon negatively affected the number of HQ reads for amplicons RTP4 and RTP5, the two longest amplicons in the set, across all sites. It was also noted that the sequencing run at site 29 yielded a disproportionally large number of HQ reads. This difference was found to be due to a custom change in their software pipeline settings allowing more HQ reads to be reported; however, this can lead to reduced accuracy and is generally not recommended. The AVA software automatically discarded the majority of the additional low accuracy reads and the variant percentages reported from site 29 were similar to those reported by other sites.
Conversely, sites 26 and 28 had average read counts but produced a significantly reduced number of aligned reads. This was likely due to the presence of increased amounts of primer dimers that were introduced, along with the amplicons of interest, into the emPCR step prior to the sequencing run. The presence of primer dimers in emPCR is deleterious to the amplification of target amplicons as these shorter fragments are preferentially amplified on the beads  [20]. This phenomenon results in a decreased of amplified target amplicons available for sequencing. Assay performance at low viral titers was investigated with two dilution series. Data gathered across all sites demonstrated that, even at low titers, mutations present at >20% of the viral population were generally detected. Minority HIV-1 drug resistance mutations in the range of 2-10% were detected at the majority of sites, and minority HIV-1 drug resistance mutations in the range of 1-2% were still detected by some sites.
The current assay does not contain a step to normalize the transferred cDNA molecules and may therefore not be suitable to link certain drug resistance mutations at low levels, especially in very high viral load samples. Finally, we must consider errors introduced during the process of pyrosequencing. The 1% cut-off for minority HIV-1 drug-resistance mutations is approximately a magnitude higher than the reported substitution rates introduced by pyrosequencing  [29, 30]. In addition, mutations must be detected in both forward and reverse reads at the approximate same frequency to be deemed real. Insertions and deletions (indels) occur predominantly in homopolymer regions  [29, 30]  and artifactual variant calling can be mitigated by using appropriate platform specific analysis software such as AVA to appropriately align reads and by manually inspecting the alignments in regions with homopolymer runs.
The viral titer for each is shown. Table  Primers. Table  C : Details of amplicon drop out across sites per amplicon. Lack of amplicon production was reported by each site as any amplicon measuring less than 1 ng/μL or that was comprised of primer dimer alone. All amplicon concentration measurements were taken following PCR and purification. Table D: Drug resistance mutations found only by UDS. Details on reports of each site. The summary of the data are given in table 4. Hits, number of reads reporting the variant; denom, number of total reads at this position. (DOC).
Acknowledgments The HIV-1 Alphastudy Group: Austria:  C. Gabriel ,  M. Danzer ,  S. Stabentheiner ,  J. Pröll ,  K. Hofer  ( Blood Center Linz ); Belgium:  J. Aerssens ,  W. Mostmans ,  K. Thys ,  H. Van Marck  ( Janssen Infectious Diseases-Diagnostics bvba, Beerse ); France:  J. Izopet ,  M. Dubois ,  F. Nicot  ( INSERM U563, Toulouse ); O. Bouchez ,  D. Milan  ( INRA, Laboratoire de Génétique Cellulaire, Plateforme Genomique Toulouse ); Germany:  M. Däumer ,  B. Thiele  ( Institute of Immunology and Genetics, Kaiserslautern );  C. Kuecherer ,  K. Meixenberger ,  A. Nitsche ,  A. Radonic ,  P. W. Dabrowski  ( Robert-Koch-Institute, Berlin );  T. Lengauer ,  A. Thielen  ( Max-Planck-Institute for Informatics, Saarbrücken );  G. Schmitz-Agheguian ,  M. Victor  ( Roche Applied Science, Penzberg ); Italy:  M.
Primer design and testing We focused on species of parasites common in archeological samples for which modern reference DNA sequences were available. We designed primer pairs to target tapeworms (Taenia saginata, T. solium, T. asiatica, Echinococcus granulosus, E. multilocularis, Diphyllobothrium latum, D. dendriticum, D. nihonkaiense), roundworms (Ascaris lumbricoides, A. suum), a whipworm (Trichuris trichiura), a pinworm (Enterobius vermicularis), and flukes (Fasciola hepatica, F. gigantica, Dicrocoelium dendriticum, D. chinensis). To select for amplicons containing single nucleotide polymorphisms (SNPs) that would allow the identification of human gastro-intestinal helminths in a species-specific manner, we designed primers based on the analysis of 3,352 mitochondrial and nuclear DNA sequences present in GenBank 1 at the end of 2013.
Aligned sequences were used to design primers hybridizing to conserved sequences and flanking one or several diagnostic SNPs for each genus with the exception of Ascaris lumbricoides and A. suum, the distinction of which cannot be achieved using short DNA fragments based on currently available DNA sequences  [18, 19]. Primer design was performed using the program primer3 within the software Geneious 6. 1  [20]. For primer optimization, the software Oligo 6 (Molecular Biology Insights, Inc) was used to select primers with a Td of 65°to 67°C (nearest neighbor method) and for which there was no predicted 3'-dimer having a ΔG below -1. 6 kcal/mol. In this way, we designed 82 primer pairs amplifying fragments between 52 and 121 bp and tested them for efficiency and dimer formation using qPCR in a LightCycler 480 1 (Roche Applied Science, Penzberg, Germany).