dataesr/scientific-paragraphs-categorization huggingface dataset:
Research in context Evidence before this study Raynaud's phenomenon can be secondary to connective tissue diseases, especially systemic sclerosis (SSc), where it represents the most frequent and earliest sign of vasculopathy. The updated European League against Rheumatism (EULAR) guidelines recommend oral calcium channel blockers (CCBs) or phosphodiesterase type 5 inhibitors (PDE5i) as first-line therapy for systemic sclerosis (SSc)-related RP. Yet, whether one treatment is superior over the other is unknown, owing to the lack of direct/indirect comparisons. Moreover, other drugs have been proposed, such as endothelin receptor antagonists, prostacyclin analogs, or non-prostanoid IP-receptor agonists, but the place of these options within the treatment strategy remains unclear. We searched Pubmed for metaanalyses on the treatment of secondary RP published between database inception and August 8, 2019.
Methods This systematic review complies with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) statement guidelines. 10, 11 The protocol and systematic search strategy are available online (PROSPERO registry, CRD42017057518, http://www. crd. york. ac. uk/PROSPERO/display_record. asp?ID=CRD42017057518). On publication of this article, the full dataset will be made freely available online through the Open Science Framework.
Literature Searches We searched for narrative or expert reviews, systematic reviews, and meta-analyses indexed in MEDLINE and/or the Cochrane Database of Systematic Reviews on treatments for secondary RP or for SSc-related digital ulcers, published from inception to January 2017. We screened all trials included in the reviews we had found. In addition, we searched for RCTs published from inception to September 2019 in MEDLINE, Embase, the clinicaltrials. gov registry, and the AdisInsight database. Finally, we asked key opinion leaders in the field. No language restriction was applied. Details of the search strategy are available as supplementary material (appendix p3). into account disability and impact on quality of life. 12, 13 If RCS was not reported, other severity scores were extracted and converted into the 10-point scale used for the RCS.
Data synthesis All pharmacological treatments were grouped into 15 therapeutic classes: αadrenoceptor antagonists; anti-oxidants; anti-interleukin-6 (IL6); angiotensin-converting enzyme inhibitor (ACEi) and angiotensin receptor blockers (ARB); Botulinum Toxin type A (BTA); CCBs; endothelin receptor antagonist (ERA); PDE5i; phosphodiesterase-3 inhibitors (PDE3i); intravenous prostacyclin analogs (IV PGI2); oral prostacyclin analogs/nonprostanoid IP-receptor agonists (Oral IP agonists); selective serotonin reuptake inhibitor (SSRI); soluble Guanylate Cyclase stimulators (SGCs); topical nitric oxide donor (Topical NO); and thromboxane synthase inhibitors (TSI). When a study reported several arms with different doses of the same drug, these groups were merged. We measured treatment effect using the mean difference (MD) for efficacy outcomes and incidence rate ratios (IRR) for safety outcomes.
Acknowledgments We thank  Pfizer  for giving us access to the individual data of the trial NCT01090492 testing the efficacy of a PDE5i ( PF-00489791 ) in Raynaud's phenomenon. We also thank  Pr Michel Cucherat  for relevant and helpful advice;  Dr Florian Naudet  and  Dr Clement Palpacuer  for the base code of the quality figure;  Theophile Tiffet  for his help; and  Dr Alison Foote  for correction of English language usage. This work was supported by the  NIHR Manchester Biomedical Research Centre.
The limit of detection (LOD) of the IFNα and IFNβ assays were 0. 5 fg/mL and 0. 2 pg/mL, respectively. Functional activities of type I IFN were measured using an in vitro cytopathic assay that has been previously described  (Lebon et al. , 1979). Briefly IFN activity was determined by addition of patient plasma to Madin-Darby bovine kidney (MDBK) cells which were challenged with vesicular stomatitis virus to measure the viral cytopathic effect as compared with an IFN standard  (Lebon et al. , 1979). Blood ISGs were measured by an 11-gene blood signature score (ACS TB risk signature) by qRT-PCR from RNA isolated from PAXgene collected whole blood, as previously described (  7 ). The raw data (Dataset_1) from the paper is available at Figshare, doi: 10. 6084/m9. figshare. 8799131.
FUNDING This work was supported by the  Strategic Health Innovation Partnerships (SHIP)  Unit of the  South African Medical Research Council  with funds received from the  South African Department of Science and Technology ; the  European Commission -funded TBVAC2020 consortium ( H2020-PHC-643381 ), the  Agence Nationale de la Recherche  ( ANR  grant number  CE17001002 ) and the  Fondation Recherche Medical  (FRM grant number  SPF201170938617 ). The authors thank  ImmunoQure AG  for sharing the antibodies to assess IFNα protein levels in the Simoa assay.
Patients and Healthy Donors Metastatic colorectal cancer patients were enrolled from March 2013 to August 2016 in the "Epitopes-CRC02" trial (NCT02817178), a French multicentric prospective study assessing the impact of treatment on the CD4 T cell response. All patients were enrolled after signing an informed consent, in accordance with French regulation, and after approval by local and national ethics committees. All data were anonymized. Overall population characteristics are summarized in Table  S1. For each patient, blood samples were collected before any metastatic cancer specific treatment (baseline) and after 3 months of a chemotherapy-based regimen. The materials used and analysis plan are illustrated in Figure  1. Briefly, we monitored ILCs by flow cytometry in 86 patients at baseline and 76 matched patients after chemotherapy.
From the samples collected after treatment, we retained data for patients receiving the following chemotherapy-based regimens: (A) 5FU and Irinotecan (Folfiri) (n = 19), (B) 5FU and Oxaliplatin (Folfox) (n = 40), and (C) 5FU, Oxaliplatin and Irinotecan (Folfoxiri) (n = 17). Patients treated with 5FU only, patients without treatment data available or patients without available data at baseline were removed from the analysis. Of note, we chose to include five patients who received Oxaliplatin and Raltitrexed, a folic acid analog that inhibits thymidylate synthetase similar to 5FU, in the Folfox branch. A total of 86% of patients received a bevacizumab regimen as well, regardless of the chemotherapy protocol. For healthy donor controls, blood cells were collected from anonymous donors at the Etablissement Français du Sang (Besançon, France) and the Transfusion Interregionale CRS (Lausanne, Switzerland) using an apheresis kit preparation, after obtaining signed informed consent.
Assessment of Spontaneous hTERT-Specific CD4 T Cell Responses in Cancer Patients An IFN-γ ELISpot was conducted for 74 patients of the cohort at baseline, as previously described by Godet et al. (42). Briefly, spontaneous responses were assessed by IFN-γ ELISpot after an in vitro stimulation of PBMCs with a mixture of eight peptides derived from hTERT (TERT 44-58 , TERT 578-592 , TERT 921-935 , TERT 1055-1069 , TERT 541-555 , TERT 573-587 , TERT 613-627 , and TERT 911-925 ) at 5 µg/ml for 10 days. Another peptide mixture, referred to as CEF (PANATecs), derived from influenza virus (Flu), Epstein Barr virus (EBV), and cytomegalovirus (CMV) was used to evaluate antiviral recall responses in the same patients. CEF IFN-γ ELISpot data were available for 69 of the 74 patients. After the 10-day incubation with the peptide mixtures, the cells (10 5 per well) were cultured in triplicate in the ELISpot plate with restricted peptides mixture or individual peptides at 5 µg/mL in X-vivo 15 medium (Ozyme, BE04-418) for 15 h.
Statistical Analysis Numerical data are expressed as the mean ± SEM (Standard Error Mean). Student's t-tests, ANOVAs and Chi-square tests were used for the evaluation of statistical significance, calculated with GraphPad Prism 8. 0 or R Studio. P-values lower than 0. 05 were considered significant with * p < 0. 05, * * p < 0. 005, * * * p < 0. 001, and * * * * p < 0. 0001. Progression free survival (PFS) was calculated from the date of study enrolment to the date of tumor progression. Kaplan-Meier survival curves were generated using R Studio R software (median with 95% confidence interval).
Of note, ILC counts were not influenced by microsatellite status, RAS and BRAF mutations, carcinoembryonic antigen (CEA) value or lymphocyte count. Interestingly, only 13% of MSI tumors had an ILCtot high phenotype and the BRAF mutation prognostic biomarker was not enriched in the ILCtot high patients. Tumor response rate was also not different based on the profile of ILC distribution. Next, some hypotheses were formulated regarding the different subsets of ILCs and were subsequently tested with our data. (i) We first hypothesized that MSI CRC patients harbor a higher mutational load and an interferon gamma (IFN-γ) signature. However, we observed that ILC subsets were distributed equally in the nine MSI tumors (data not shown), with the ILC1 subset count higher in only two patients. (ii) Next, inflammatory contextures, such as mucosal immunity or hepatic metastatic localization, were specifically assessed for ILC subsets.
SUPPLEMENTARY MATERIAL The Supplementary Material for this article can be found online at: https://www. frontiersin. org/articles/10. 3389/fimmu. 2019. 02121/full#supplementary-material Table  S1  | Clinicobiological characteristics of CRC patients. The table summarizes the clinicobiological characteristics of CRC patients enrolled in the "Epitopes-CRC02" trial (NCT02817178) before (baseline) and after chemotherapy treatment (n = 96).
20 articipants in each study were followed up at 3. 5 y of age and 4. 5 y of age to assess antibody persistence (UTNs: U1111-1111-5789 and NCT01105559 [South Africa] and U1111-1122-2457 and NCT01983540 [Colombia and Costa Rica]). These antibody persistence data are reported in this article. For the study in Colombia and Costa Rica (Study 2) only participants in Colombia were followed up at 3. 5 y of age and 4. 5 y of age due to the closure of the study site in Costa Rica (due to a lack of proposed clinical studies), so only data from Colombian participants are presented at these time points for Study 2. All study protocols and amendments were approved by independent ethics committees and studies were performed according to local regulations, Good Clinical Practice, and the ethical principles of Declaration of Helsinki (Edinburgh revision, October 2000).
16, 20, 24 All data are presented with their 95% confidence intervals (CIs) calculated using the exact binomial distribution (Clopper-Pearson)  32  for proportions and the normal approximation method for GMCs and GMTs. No calculation for sample size was performed since these were descriptive studies. The sample size in each study was based on the available participants who had completed the prior primary series and booster vaccinations, i. e. a maximum of 567 participants for Study 1 and a maximum of 699 participants in Study 2 (see Figure  1 ). All statistical analyses were performed under the responsibility of the Sponsor's Biostatistics Platform using SAS® software, Version 9. 1 or 9. 2 (SAS Institute, Cary, North Carolina, USA).
Acknowledgments The authors acknowledge all enrolled infants and parents/legal guardian-(s) for their participation. The authors would also like to thank the co-investigators for the primary series and booster studies in South Africa ( Ismail Mitha MD ,  Anthonet Koen MD ,  Clare Cutland MD , and  Michelle Groome MD ) and  Costa Rica  ( Adriano Arguedas Mohs MD ,  Arturo Abdelnour Vásquez MD ) and all study personnel for the conduct of the studies. At  Sanofi Pasteur , the authors thank  Fabrice Bailleux ,  Xavier DaCosta ,  Séverine Paulhac ,  Eduardo Santos-Lima ,  Maria Consuelo Miranda , and the  Hexaxim clinical team  for their valuable input into the conception, execution, and analysis of the clinical trials described in this manuscript. This manuscript was prepared with the assistance of a professional medical writer,  Dr Andrew Lane  (Lane Medical Writing) funded by  Sanofi Pasteur , in accordance with the European Medical Writers Association guidelines and Good Publication Practice.
By the end of 2018, nearly 8000 complete tailed phage genomes were published online and a further 22,000 partial genomes were stored in databases gathered under the umbrella of the International Nucleotide Sequence Database Collaboration  (Karsch-Mizrachi et al. 2012; O'Leary et al. 2016). The classification of this massive group is the formal responsibility of the Bacterial and Archaeal Viruses Subcommittee of the International Committee on the Taxonomy of Viruses (ICTV). In recent years, we (the Subcommittee) have focused on classifying newly described phages into species and genera  (Lavigne et al. 2008 (Lavigne et al. , 2009;; Adriaenssens et al. 2015; Krupovic et al. 2016; Adriaenssens et al. 2017 ). However, once our attention shifted toward higher order relationships, we found that the ranks currently used in phage taxonomy (species, genus, subfamily, family, and order) are no longer sufficient for the description of phage 2 SYSTEMATIC BIOLOGY diversity.
Creation of the "Herelleviridae" Data Set Genome sequences of known spounaviruses were retrieved from the GenBank or (preferably) RefSeq databases based on literature data, and taxonomic classifications provided by the ICTV and the National Center for Biotechnology Information (NCBI). Records representing genomes of candidate spouna-related viruses were retrieved by searching the same databases with the tBLASTn algorithm  (Altschul et al. 1990 ) using as queries terminase and major capsid proteins of type isolates of the original subfamily  (Brister et al. 2015). After manual curation, the search yielded a set of 93 virus genomes (Supplementary Table  S1. 1 available on Dryad), which were reannotated using PROKKA  (Seemann 2014)  and used in the following analyses. To conduct interfamilial comparisons, we compiled an additional genome set including well-described viruses from the ICTV 2016 Master Species List 31V1.
Definition of the New Herelleviridae Family Within the dsDNA Virosphere We examined whether or not the family, Herelleviridae, is a clearly distinct group of viruses within the dsDNA phages, by using two cutting-edge virus clustering tools capable of discerning relations even between divergent taxa. Using vConTACT v2. 0, we constructed a monopartite network of viral genomes by clustering gene families based on BLAST hits between their protein products as previously described  (Bolduc et al. 2017a; Jang et al. 2019). In this framework, similarities between pairs of genomes were calculated as a function of the shared protein families. The network was visualized with Cytoscape (version 3. 5. 1; http://cytoscape. org/) with genomes sharing more proteins clustered more closely together (detailed information in Supplementary File 1 available on Dryad).
The second method used is 'Genome Relationships Applied to Virus Taxonomy' or GRAViTy [GitHub: Paiewsakun/GRAViTy  (Aiewsakun et al. 2018; Aiewsakun and Simmonds 2018) ]. This framework created a dendrogram of viruses, based on protein profile hidden Markov models of the predicted gene products and genome organization models calculated into a composite generalized Jaccard (CGJ) score representing the difference between two viruses on a scale from 1 to 0 (detailed information in Supplementary File 1 available on Dryad). We also investigated the clustering of the family within the Caudovirales order on the VIPtree server  (Nishimura et al. 2017b) , which uses the Phage Proteomic Tree approach described below and detailed in in Supplementary File 1 available on Dryad.
Genome-Based Analyses Nucleotide sequence-based grouping of phages was conducted using VICTOR (Virus Classification and Tree Building Online Resource), a Genome-BLAST Distance Phylogeny (GBDP) method  (Meier-Kolthoff et al. 2014; Meier-Kolthoff and Göker 2017). The program calculates intergenomic distances from BLAST+ hits using GBDP (including 100 pseudobootstrap replicates) and used them to infer a balanced minimum evolution tree with branch support via FASTME including subtree pruning and regrafting postprocessing (for details of the algorithm design, see  Meier-Kolthoff et al. 2014; Meier-Kolthoff and Göker 2017). The analysis was conducted under settings recommended for prokaryotic viruses. To reevaluate and interpret results of the VICTOR clustering, we compared the genome sequences using the Gegenees tool with default parameters  (Camacho et al.
2009; Ågren et al. 2012). The program calculated symmetrical identity (SI) scores for each pairwise comparison based on BLASTn hits and a genome length. To check if the translated local alignment of the whole genomes will be more sensitive to a phylogenetic signal at higher taxonomic ranks, we followed the Dice methodology proposed previously  (Mizuno et al. 2013 ). The Dice score was calculated based on all reciprocal tBLASTx hits between pairs of genomes with ≥30% identity, alignment length ≥30 amino acids, and Evalue ≤0. 01. Pairs of scores were used to construct a distance matrix, which in turn was converted to the final tree using the BioNJ algorithm  (Gascuel 1997). Again, to evaluate and interpret this result, we calculated SI scores between all translated genome sequences using Gegenees.
Proteome-Based Analyses The Phage Proteomic Tree was constructed as described previously  (Rohwer and Edwards 2002). In brief, the protein sequences were extracted and clustered using BLASTp. These clusters were refined by Smith-Waterman alignment using CLUSTALW version 2  (Larkin et al. 2007). Alignments were scored using open-source PROTDIST from the phylogeny inference package (PHYLIP)  (Felsenstein 1989). Alignment scores were converted to distances as described in  Rohwer and Edwards (2002) , and the distances thus obtained were used to generate the final tree using the neighbor joining algorithm.
Identification of Protein Clusters In order to comprehensively define the gene content in herellevirus genomes, we applied two independent, yet complementary methods of identifying orthologous clusters. An initial set of orthologous protein clusters (OPCs) was constructed using the GET_HOMOLOGUES software suite, which utilizes several independent clustering methods (Contreras-Moreira and Vinuesa 2013). To capture as many evolutionary relationships as possible, a greedy COGtriangles algorithm  (Kristensen et al. 2010 ) was applied with a 50% sequence identity threshold, 50% coverage threshold, and an E-value cutoff equal to 1e-10. The results were converted into an orthologue matrix with the "compare_clusters" script (part of the GET_HOMOLOGUES suite)  (Felsenstein 1989). A second method was based on assignment of the genes to a predefined pVOG (prokaryotic Virus Orthologous Group) set described previously  (Grazziotin et al.
2017 ) and available at http://dmkbrain. ecn. uiowa. edu/pVOGs/. In brief, protein-coding genes in the 93 analyzed genomes were identified using Prodigal V2. 6. 3 in anonymous mode  (Hyatt et al. 2010). Then, the gene products were assigned to the respective orthologue group by HMMsearch (E-value <10 -2 ) against the database of Hidden Markov Models (HMMs) created for every of 9518 pVOG alignments using HMMbuild of HMMer v3. 1b2  (Finn et al. 2011).
Analysis of Gene Synteny To investigate a genomic synteny-based classification signal, we implemented a method developed at the University of Utrecht, a gene order-based metric built on dynamic programming, the Gene Order Alignment Tool (GOAT, Schuller et al. : Python scripts are available on request, manuscript in preparation). The tool used the pVOG assignments described above to generate a synteny profile of every genome (in fact, this pVOGs methodology is integral part of the GOAT pipeline). The algorithm accounted for gene replacements and low similarity between genes by using an allvs-all similarity matrix between pVOG pairs based on HMM-HMM similarity (HH-suite 2. 0. 16) (Söding et al. 2005). Distant HHsearch similarity scores between protein families were calculated as the average of reciprocal hits and used as substitution scores in the gene order alignment.
Marker Protein Phylogenies Based on the OPC and pVOG clusters defined above, which respectively identified 14 and 38 core protein clusters (Supplementary Table  S2  available on Dryad), we chose 10 consistently-predicted protein groups (encoded by genes with well-defined boundaries and without introns) for inclusion as phylogenetic marker. The selected clusters included: DNA helicase cluster, tail sheath protein, two different groups of virion proteins (including the major capsid protein cluster), and six clusters with no known function. The members of these clusters were aligned using Clustal Omega with default parameters  (Sievers et al. 2011). The resulting alignments were analyzed with the IQ-TREE pipeline, which includes the ModelFinder tool that determines the most suitable model of sequence evolution for the alignment, the main algorithm that constructs a maximum-likelihood tree and ultrafast bootstrap (UFBOOT)-an UFBOOT subroutine that calculates the support of the branches  (Nguyen et al.
2015; Chernomor et al. 2016; Kalyaanamoorthy et al. 2017; Hoang et al. 2018 ). The same program was used to generate the approximation of the "species tree" based on the concatenated alignments of all markers. In this case, the partitioned model of the alignment was also calculated using the ModelFinder module of IQ-TREE and the analysis was run in 100 replicates to select the final tree with best log-likelihood score.
Genome-Based Analyses The genome-based analyses used to identify close relationships between phage genomes provide powerful information for species and genus demarcation. We performed an all-against-all BLASTn analysis with Gegenees  (Ågren et al. 2012) , revealing that the genomes of several viruses were similar enough to consider them strains of the same species (they shared >95% nucleotide identity, Table  1 , Supplementary Table  S1 , Fig. S2  available on Dryad). We could delineate clear groups with significant nucleotide similarity, proposed as genus-rank taxa, at similarities greater than 50%. Using the BLAST-based phylogenetics framework VICTOR (Meier-Kolthoff and Göker 2017), we were able to confirm that the existing genera form well-supported clades (Fig. 2a ). Similar patterns emerged at the translated nucleotide level when the genomes were analyzed using the tBLASTx-based Dice method (Fig.
2b )  (Mizuno et al. 2013 ). An all-against-all comparison at the translated nucleotide level (tBLASTx) with Gegenees showed an overall low level of similarity (15%) within the newly proposed family and allowed us to start delineating the subfamily level at approximately 25% translated genome similarity (Supplementary Fig. S2  available on Dryad). However, the subfamily boundaries were not always clear using these methods. For example, the members of the Brockvirinae subfamily shared 20-25% similarity at the translated nucleotide level with the twortviruses and jasinkaviruses.