dataesr/scientific-paragraphs-categorization huggingface dataset:
Principal Findings Our study exploring a large dataset from social networks highlights the attractiveness of NPIs for patients with breast cancer. The results from conversations in 2 forums and 4 Facebook discussion groups and pages recommended by the French National Cancer Institute indicated that 27,279 words were related to NPIs in the 264,249 posts analyzed. NPIs are clearly a topic of concern for patients with a generally similar interest in the categories between forums and Facebook sources. Patients seek information about the best use of NPIs and use these NPIs. The study supports the results of a survey conducted in 2005 on CAM by using a structured questionnaire with an average of 35. 9% of a sample of 956 European patients  [7]. The European study had identified 33 CAM  [7] , whereas this study identified 101 CAM.
Relatives of a sick person can also register to search for information. Impostors could also be spreading false medical information. Although voluminous and proportional to the attractiveness of CAM, the declarative data did not distinguish interest from real use. Posting can reflect as much a request for information or a doubt as the sharing of actual use of an NPI. Qualitative approaches should complete these mass data analyses to better identify the real choices (eg, medical prescription vs autoprescription) and context-specific uses. It is essential to know whether these practices are used in a complementary or alternative way to approved and prescribed cancer treatments  [46]. Analyses were performed on data compiled between 2006 and 2015. With more data and a longer period of time, it would be interesting to study the chronology of the vocabularies used by patients about NPIs to identify potential fashion effects.
Background: Although antimicrobial resistance is increasingly common in equine medicine, molecular and epidemiological data remains scarce. Objectives: We estimated the prevalence of, and risk factors for, shedding of multidrug resistant (MDR), extended spectrum β-lactamase (ESBL)-producing, and AmpC β-lactamase-producing, or some combination of these in Escherichia coli in horses in France. We characterized ESBL/AmpC isolates for antimicrobial susceptibility and the presence of virulence and ESBL/AmpCassociated resistance genes. Animals: Fecal samples from healthy adult horses at 41 premises were collected. A questionnaire was completed by each premises manager. A subset of these samples was tested to build 2 bacterial collections. Methods: Indicator (without enrichment) and specific (enrichment with ceftriaxone) E.
20  data is available on the presence of MDR or ESBL/AmpCproducing isolates and ExPEC in the healthy equine population in France. Our objective was to determine the prevalence of, and risk factors for, shedding MDR or ESBL/AmpC-producing E. coli isolates in horses. We characterized potential ESBL/AmpC isolates for antimicrobial susceptibility and the presence of virulence and ESBL/AmpCassociated resistance genes.
| Sampling This work was part of a larger study on resistance to anthelmintics and antimicrobials in horses in France. Sampling details were described elsewhere. 21 Briefly, premises housing more than 40 horses, as mentioned in the French Horse and Riding Institute (IFCE) database, were contacted by telephone and selected on a voluntary basis. For each breeding premises, a riding school within a radius of 50 km was recruited when available. At time of the study, we estimated the number of riding schools in the source population as 1600 and the number of breeding premises as 249 in the study area (only riding schools located in French departments including selected breeding premises were considered). To be included in the study, horses had to be >2 years old and considered healthy by the premises manager.
We used the primer sequences described previoulsy. 26 The ESBL/AmpC resistance genes were detected by PCR performed on DNA extracted by heat lysis, as previously described. 27 The protocol was provided by the National Microbiology Laboratory of the Public Health Agency of Canada  28  with control strains ECL3482, PMON38, and CTX-M15. When bla CTX-M was detected, the CTX-M group was determined by PCR. 29 The amplicon was purified using the QIAquick PCR Purification Kit, according to manufacturer instructions. The variant was identified by Sanger sequencing and compared using the Comprehensive Antibiotic Resistance Database (CARD) (https://card. mcmaster. ca/). We estimated the prevalence of horses shedding resistant or nonsusceptible (resistant and intermediate) isolates for each antimicrobial and of premises housing these horses.
Although we detected nonsusceptibility to third-generation cephalosporins in the indicator collection, none of the isolates carried tested ESBL/AmpC genes, suggesting that other ESBL/AmpC genes may be present in the population, (eg, bla OXA , bla PER , bla GES-1 , and bla VER-1 ) or other mechanisms of resistant to cephalosporins may be present (eg, an efflux pump). These other mechanisms would less likely be transmissible by mobile elements but also could account for treatment failure when using cephalosporins and therefore could still have an impact on the health of horses. In the indicator collection, we detected viable E. coli in only 68% of the fecal samples. This viability rate is low compared to other published studies in healthy horses,  4  and compared to internal data available in our laboratory.
3a. The estimated distance between the float and the eddy center, inferred as described in the Data and Methods section, increased suddenly whenever a float crossed the radial distance threshold of about 30 km, despite relatively strong velocities of about 0. 3 m s -1 at that distance, see Fig. 2b. It is worth noting that three additional RAFOS floats deployed at 40 km from the eddy center at 250, 550 and 800 m, and not otherwise described here, were ejected rapidly after only a couple of revolutions. The eddy vorticity was roughly constant Blue dots are estimates of MLD from CTD profiles (blue line from optimally interpolated sections). White triangles in the upper panels show the position of cruise CTD/L-ADCP or glider profiles. Note that glider sections, due to their spiraling trajectories, did not capture the strain rate at the eddy periphery as accurately as synoptic shipborne sections.
Data and Methods Cruise data. Observations in the LBE were made during the three PROVOLO cruises from RV Håkon Mosby in June 2016 and from RV Kristine Bonnevie in March 2017 and September 2017. Conductivity-Temperature-Depth (CTD) profiles were acquired using a Sea-Bird Scientific SBE 911plus system, with pressure, temperature, and salinity data accurate to respectively ±0. 5 dbar, ±0. 002 °C, and ±0. 003 g kg -1. The CTD data were processed using the SBE software following the recommended procedures. Salinity samples were analyzed in order to correct, when necessary, CTD-derived values. Conservative Temperature Θ, Absolute Salinity S A and potential density anomaly σ Θ were calculated using the TEOS-10 Gibbs Seawater Oceanographic toolbox  66. Profiles of horizontal currents were acquired by a pair of 300-kHz lowered acoustic Doppler current profilers (L-ADCP) attached to the CTD rosette, operated in master-slave mode with 8-m vertical bins.
The L-ADCP data were processed using the velocity inversion method  67  implemented in the LDEO software version IX-12  68  , with typical horizontal velocity uncertainties of 2-3 cm s -1. All current measurements were corrected for the magnetic declination. In the field, the LBE was identified using a vessel-mounted ADCP. Several CTD/L-ADCP sections from the LBE center to about 80-100 km radius were carried out. A total of 15, 30, and 13 CTD/L-ADCP profiles were taken respectively in the vicinity of the LBE during the June 2016, March, September 2017 cruises. One radial section was performed during both the June 2016 and September 2017 cruises, while two radial sections were performed during the March 2017 cruise.
Data Availability Data collected during the PROVOLO project are available at the Norwegian Marine Data Center (Cruise data: https://doi. org/10. 21335/NMDC-1093031037, Seaglider data: https://doi. org/10. 21335/NMDC-980686647). Seaglider data were processed using a toolbox developed by Bastien Queste at the University of East Anglia (https:// bitbucket. org/bastienqueste/uea-seaglider-toolbox. git). ERA-Interim reanalysis can be freely downloaded for research purposes from the ECMWF's website (https://www. ecmwf. int). Level-2 satellite data from MODIS-Aqua are made freely-available by NASA Goddard Space Flight Center (Ocean Color, https://doi. org/10. 5067/AQUA/ MODIS/L2/OC/2018; Sea Surface Temperature, https://doi. org/10. 5067/AQUA/MODIS/L2/SST/2014). Lagrangian analysis tools developed by Jonathan Lilly are contained in a freely-available Matlab toolbox (jlab: A data analysis package for Matlab, v.
S1b ), HRM analysis (Fig. 3 ), and was further diluted as template for cycle sequencing. The produced sequences and sample information are available at BOLD (the Barcode of Life Data Systems http://www. boldsystems. org/) with accession numbers MG191372-MG191375, MG191658-MG191703 and MH034113. Some coralline algal specimens presented more than one distinct morphology. To reveal the possible presence of several species, separate aliquots were sampled from these. Six specimens were suspected of being composed of several taxa (five from d8-Krøttøya & one from d19-Sørøya). All six specimens revealed the occurrence of two different species as shown in Fig. 4. The taxonomic results are presented in Table  2  in a matrix format showing all eight taxa and their occurrence either as a single maerl species or co-occurrence with another species.
Methods Sampling and DNA preparation. A total of 47 free-living coralline specimens (maerl and rhodoliths) were collected and analysed from five areas along the Norwegian coast in 2016 and 2017 (Supplementary Table  S1 ). Each sample was labelled -NCCA-with a unique 4-digit identifier. When a sample appeared to be composed of several species, an additional letter ("a", "b", etc. ), was added to the corresponding NCCA number. Pictures of all samples and aliquots used for DNA preparation can be found on Barcode of Life Data Systems (BOLD)  40  Dataset -DS-NOCCAMET Corallines DNA preparation & psbA HRM, associated to the produced sequences (Supplementary Table  S2 ). The samples were conserved by drying in heating cabinets at 60 °C, overnight. We developed a simple DNA preparation protocol without any purification steps.
PCR optimal annealing temperature was determined by running a PCR with a temperature gradient. Optimized amplification for the newly designed primer pair psbA21-350F & psbA22-350R was carried out under the following conditions: a denaturing step for 2 min at 98 °C, followed by 40 cycles of 98 °C for 10 s, 57 °C for 20 s and 72 °C for 20 s. Melt curve analysis was performed between 65 °C and 95 °C using 0. 2 °C increments with readings after 5 s. HRM analysis was performed using Precision Melt analysis software (Bio-Rad) by setting the difference curve analysis between 76. 4 and 82. 6 °C. SsoFast ™ EvaGreen ® mastermix was used for HRM analysis as well as for product input for sequencing. PCR product electrophoresis was done on a 1. 7% agarose gel (Agarose I biotechnology grade, VWR) in 2X TAE buffer (VWR), run for 110 min at 70 V and visualized with GelRed (Biotium; www.
The PCR plate was then sealed and vortexed for 30 min prior to being processed by an ABI3730XL DNA analyzer (Life Technologies, Applied Biosystems). Trace files analyses were performed using CodonCode Aligner v7 (CodonCode Corporation), sequence alignments were performed using MultAlin  42  and the species delimitation was inferred using the UPGMA method (unweighted pair group means analysis) using MEGA version 7. 0. 21  43. The genetic distances were computed using the Kimura 2-parameter method  44  and are in the units of the number of base substitutions per site. The analysis involved 49 nucleotide sequences, including two reference sequences from GenBank. All positions containing gaps and missing data were eliminated. There were 307 positions in the final dataset.
Anatomical studies of sequenced corallines. Consistent diagnostic features described for North Atlantic coralline genera (such as, type of intercellular connections between contiguous cell filaments, shape of epithallial, size of subepithallial initial cells, type of sporangial conceptacle -uniporate/multiporate-, thallus organization and construction; see Adey and Adey  45  and Irvine and Chamberlain 7 ) were observed using a scanning electron microscope (SEM, model JEOL JSM 6400, Universidade da Coruña, Spain). Before SEM examination, representative fragments for each sample sequenced were removed under a stereomicroscope and they were positioned on a stub and gold-coated to show surface view, transverse view and reproductive structures (if present). All data generated or analysed during this study are included in this article (and its Supplementary Information files).
Figure5. Species delimitation among sequenced specimens. Tree inferred by unweighted pair group means analysis tree for the psbA sequences using Kimura 2-parameter substitution model. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (10,000 replicates) is shown next to the branches. In addition to the 47 coralline specimens sequenced for this study, 2 sequences, DQ167995 & KM369059, were used to serve as outgroup. GenBank accession numbers for the sequences generated for this study are indicated in Additional Table2.
Acknowledgements This work, part of  NIVA 's project " Norway 's hidden marine biodiversity: The hunt for cryptic species within the coralline algae", was funded by the  Norwegian Biodiversity Information Center  (Project no. 70184235 ). Viviana Peña  acknowledges support by  Universidade da Coruña (Contrato programa-Campus Industrial de Ferrol). We also acknowledge  Torbjørn Brekke from Slettaa dive club  for providing the Karmøy (d21) samples.
Bioanalyzer and High Sensitivity DNA Kit (Agilent) were used to check the fragment size distribution of each library. Libraries were sequenced on an Illumina Miseq sequencer based at the Environmental Microbial Genomics group in Laboratoire Ampère (Ecole Centrale de Lyon) with 2 × 250 bp chemistry (MiSeq Reagent Kit v2). Bioinformatic analyses. Raw sequencing data were filtered using the base quality upon read length with the fastX toolkit  54. Due to high variability in sequenced fragment size, forward and reverse reads were not paired and used as technical duplicates (marked with 0. 1 or 0. 2 at the end of sample name) to verify the congruity of annotation between the forward and reverse reads pools. Metagenome coverage was checked using NonPareil3  55  based on k-mer redundancy in the datasets and varied from 12% for seawater and up to 35% in surface snow.
Quality-checked reads were aligned against the non-redundant (nr) protein reference database using Diamond BlastX algorithm  56  and alignment outputs were filtered to an e-value threshold of 10e -5. Taxonomic composition and functional annotations were analyzed with MEGAN 5  57. Specifically, taxonomic assignment of each metagenomic read was based on last common ancestor (LCA) of all hits matching NCBI genome database as referenced in MEGAN GI accession number data release from March 2015. Reads with identified protein function (representing on average 35% of all QC-passed reads) were assigned to hierarchical subsystems based on SEED  58  , KEGG  59  , and COG 60 databases. For specific functions, such as melanin, scytonemin, mycosporine-like amino acids (MAAs) and mannitol biosynthesis, metagenomes were aligned against specific databases created from the NCBI protein database and retrieved using GERMLAB scripts.
Microbial attributes were obtained from organisms with described features in NCBI database and referenced in MEGAN5. Trophic life styles were investigated using the ratio of COG functions characteristic of oligotrophy or copiotrophy determined by marine genomes and metagenomes in 2009 by Lauro et al. 61. Statistical analyses were performed using STAMP  62  and R-packages: ade4tkGui  63  , pvclust  64  , and vegan  65.
Genomic features of osmotic and photochemical stress responses. The relative abundance of genes related to photochemical and oxidative stress responses was variable, but generally higher in surface snow layers than in deeper sampling horizons of saline snow, sea ice brine and seawater (Fig. 6 ). Enzymatic antioxidative mechanisms were significantly more abundant in surface snow layers especially in SL0 and SL1 where they represented up to 2% of total annotated reads. The same trend was observed for non-enzymatic responses. DNA repair mechanisms were present in all sample datasets with similar abundance (between 2 and 3% of the total annotated reads), although at a finer scale, base excision repair was more predominant in surface snow than in other samples (data not shown). The functional group for osmotic stress response mechanisms had a higher relative abundance in saline horizons (SL3, BR and SW at about 0.
5%, which is more than twice the amount than in the surface snow; Fig. 7A ). Relative abundance of genes associated with choline and bioconversion to glycine betaine was higher in saline snow as compared to brine and seawater. Sarcosine oxidase genes were predominant in brine and seawater and low in snow. Ectoine biosynthesis genes, which were observed less frequently than other compatible solutes (representing less than 0. 01% of total annotated reads), had a higher relative abundance in brine and saline snow than in seawater (Fig. 7B ). Figure  6. Photochemical stress response. Relative abundance of functions associated with photochemical stress response (UV-radiation and oxidative stress) (normalized to total abundance of annotated reads against SEED database, as percentage). Enzymatic antioxidants include genes coding catalase, superoxide dismutase, rubredoxin, glutaredoxin.
Non-enzymatic antioxidant biosynthesis (1) includes genes involved in the biosynthesis of antioxidants and the sunscreens carotenoids, glutathione, mycothiol and tocopherol from SEED subsystems. Non-enzymatic antioxidant biosynthesis (2) refers to scytonemin, melanin, mycosporine like amino-acid (MAA) and mannitol that were identified using a home-made specific database as indicated by the red asterisk. No genes coding for polyol mannitol (mdpa) were detected in any dataset. DNA repair includes genes coding exo-and endonuclease, base excision repair and UVrABC system.
Sequences annotated as viruses were detected in high abundance in seawater and sea ice brine, representing up to 2. 5 and 5% of the reads, respectively, while less than 0. 1% in saline snow. Genes involved in DNA metabolism (including DNA polymerase, recycling of host nucleotides, and de novo synthesis via ribonucleotide reductase) were the most virally enriched auxiliary metabolic genes (acquired from host genomes) in sea ice brine and seawater datasets, as previously observed in temperate ocean metagenomes  77, 78. A parallel study carried out at our study site using epifluorescence microscopy confirmed elevated densities of viruses and high virus-to-bacteria ratios in both sea ice brine and seawater  52. Virus-host interactions are thought to be a key feature of sea ice ecosystems, with a major role of viruses in the control of bacterial populations and nutrient turnover  [79] [80] [81].
Acknowledgements We thank the staff from the  Greenland Climate Research Center in Nuuk (Greenland) ,  Ivali Lennert  and  Carl Isaksen , as well as  Heidi Sørensen. We are grateful to  Soren Rysgaard  and  Malene Simon  for sharing equipment and facilitating opportunities and logistical support in the field and at the  Center in Nuuk. We also thank  Eric Collins ,  Evan Firth  and  Sebastien Cecillon  for feedback on sampling procedures and data analyses, and  Julien Prabel  for his contribution to illustration. L. M. was supported by the  Région Rhone-Alpes  ( Cible 2012-12-010748-01 ). J. W. D. and S. D. C. were supported by  NSF  award  ARC-1203267. We would like to acknowledge the support of  IPEV (ALCHEMI).
The PCIN63-UCA Does Not Bind to Env Proteins from Time Points Preceding Initiation of the Lineage To better define the affinity maturation pathway for the PCIN63 lineage, we next determined the PCIN63 unmutated common ancestor (UCA). For the HC, an unmutated common ancestor (PCIN63-UCA-HC) was identified from the 40 mpi time point. However, for the light chain, lineage assignment based solely on V K +J K gene usage and 5-residue LCDR3 criteria identified 18 unmutated putative precursor light chain sequences from the NGS dataset. The most frequent putative unmutated light chain sequence had an LCDR3 with amino-acid sequence QQSEA and was named PCIN63-UCA-KC1 (Figure  3A ). The second most frequent unmutated light chain sequence with matching V K +J K genes had an LCDR3 with amino-acid sequence QLYET, similar to the LCDR3 of the least mutated PCIN63-light chain sequences found at 40 mpi and was named PCIN63-UCA-KC2 (Figure  3A ).
Residues varying from VH1-2 and VL putative germlines are indicated by a single letter code. (C and D) Longitudinal frequency of PCIN63 Ab lineage NGS sequences containing 1-5 residues mutated from germline motif to any of the amino-acid found in the isolated mature PCIN63 Abs. (C) Left panel shows motifs containing the same number of SHMs but varying in amino-acid sequence are separated by white lines within each shade of the motif-coded color. Motifs are arranged from top to bottom in chronological order of selection, i. e. , time first mutation is detected for this motif. Right panel shows logogram representing the distribution of amino-acids at each position of the motif for the isolated mature PCIN63 Abs, the entire PCIN63 lineage NGS sequences and random Ab sequences from the same NGS dataset.
DISCUSSION The exceptional breadth of VRC01-class bnAbs and their commonly shared features have long made them favored targets for rational vaccine design  (Wu et al. , 2010; Zhou et al. , 2015). Despite major progress in the isolation and characterization of VRC01-class antibodies and the design of immunogens to prime VRC01-class precursors by immunization, the field has yet to elicit VRC01-class antibodies by immunization  (Jardine et al. , 2013; McGuire et al. , 2013; Dosenovic et al. , 2015; Jardine et al. , 2015; Briney et al. , 2016b; McGuire et al. , 2016; Sok et al. , 2016; Tian et al. , 2016). Among other challenges, antibodies of this class can be up to 40% mutated from germline suggesting that during infection, VRC01-class antibodies require putative PCIN63-UCA-KCs, the number of sequences (# seq) found in the NGS dataset and the corresponding LCDR3 amino-acid sequences (right) are also indicated.
Residues previously described as important for binding to the HIV Env CD4bs are colored in red. (B) Binding affinity of PCIN63 mature and putative UCA Abs and VRC01-class inferred germline (VRC01, VRC03, VRC07, 12A12, 12A21, 3BNC60, 3BNC117, VRC-PG04, VRC-CH31) and mature Abs (minVRC01, VRC01, VRC03, VRC07, VRC23, VRC27, 12A12, min12A21, 12A21, 3BNC117, VRC-PG19, VRC-CH31, VRC-N6) for the indicated previously described VH1-2 germline targeting immunogens, as measured by SPR. Data are representative of at least two experiments.