dataesr/scientific-paragraphs-categorization huggingface dataset:
We identified 76 ortholog groups with ≥3 genes in both S. pistillata and A. digitifera (Dataset S6). Both coral species expanded genes related to innate immunity receptors. For instance, we discovered 3 cases where a gene encoding for a NOD-like receptor family member (NLRC3) was independently expanded in both corals (Fig. 3B , Dataset S6). Further, we found 1 case where a gene encoding for a TLR (Toll-like receptor 1) and another case where a gene encoding for a TNFR (Tumor necrosis factor receptor superfamily member 19) showed independent duplication in both corals (Fig. 3B , Dataset S6). Importantly, the ortholog groups showed different degrees of expansions in both corals. In three of the above cases, we found more duplicated genes in A. digitifera than in S. pistillata. In contrast, in only one of the above cases we found more genes in S.
pistillata than A. digitifera (Fig. 3B , Dataset S6). We found an extreme case of expansion for one of the NOD-like receptor family members, where A. digitifera harbored 52 proteins in comparison to S. pistillata that harbored only 5 proteins (Fig. 4A , Dataset S6). Overall, A. digitifera had a stronger tendency to show 'extreme' expansions (10 ortholog groups with more than 10 proteins) than S. pistillata (3 ortholog groups with more than 10 proteins) (Dataset S6). Besides innate immunity receptors, we also found 2 ortholog groups related to biomineralization, i. e. homologs of Carbonic Anhydrase (CA) and Bone Morphogenetic Protein 1 (BMP-1)  40  , to be expanded in both species, but at very similar levels (3 vs. 4 proteins for CA and 3 proteins each for BMP-1 for A. digitifera and S. pistillata, respectively) (Fig.
3B , Dataset S6). Orthologs that harbored gene duplications in only of the coral species were present at a similar number in S. pistillata and A. digitifera (Dataset S7). We identified 191 genes in A. digitifera that mapped to ortholog groups with ≥3 genes in S. pistillata. Among these, we found homologs of innate immunity related proteins, namely TRAF3 (TNF receptor-associated factor 3) (Fig. 4B ) and TLRs (Toll-like receptor 2), to be present with 3 copies in S. pistillata mapping to 1 counterpart in A. digitifera. Also, a homolog of peroxidasin, important for oxidation-reduction, was present with 5 copies in S. pistillata that mapped to 1 corresponding counterpart in A. digitifera (Dataset S7). Looking at genes that were specifically expanded in A. digitifera, we identified 167 genes from S.
This number closely resembles the number of one-to-one orthologs identified by Bhattacharya et al. 23  in a large meta-analysis of available coral genomes and transcriptomes (4,751 ortholog pairs). Within the set of conserved orthologs across corals, the authors characterized sets of proteins responsible for biomineralization, environmental sensing, and response to temperature, light, and pH. Our analysis of enriched GO terms largely supports the results of the study by Bhattacharya et al. 23  and further highlights the overarching emphasis on processes related to the cnidarian-dinoflagellate symbiosis in the coral host core set of conserved proteins. In line with functional conservation, the set of one-to-one orthologs revealed a comparatively high degree of sequence conservation of 62% at the protein level (Dataset S4).
This analysis revealed several striking features. First, among the shared enriched processes for this category of orthologs, we found many processes directly related to the cnidarian-dinoflagellate symbiosis (Fig. 3A , Dataset S5). This partially resembles the results from the one-to-one ortholog analysis with the important difference that independent expansions of genes that map to common processes indicate that cnidarian-dinoflagellate Figure  2. Classification of genomic protein sets of S. pistillata and A. digitifera according to evolutionary relationship. 25,769 S. pistillata proteins were compared to 23,523 A. digitifera proteins and assigned to four categories: (i) one-to-one orthologs (black), (ii) many-to-one and many-to-many orthologs (dark grey), (iii) species-specific proteins without homologs in other species (intermediate gray), and (iv) proteins without easily discernible orthologous relationships (light grey).
Second, within these processes, homologs of the same or similar genes are repeatedly being expanded across species, as highlighted by the example of three cases of expansion of NLRC3 (Fig. 3B , Dataset S6). This suggests that the same genes are potentially subjected to adaptation within and between coral species, arguing that convergent evolution might not only happen on the process level, but also at the protein level. Further evolutionary analysis incorporating more species might provide an avenue to identify genes important to coral adaptation. Last, even though we find expansions of the same genes between species, the extent of duplication is in some cases extremely uneven (Fig. 4A , Dataset S6). Again, incorporation of genomic data from additional species in the near future should help to answer whether this pattern is restricted to the species compared here or whether it is a general feature of coral (clade) evolution.
digitifera (Dataset S5). (B) Ortholog groups with independently expanded genes in both coral species show different degrees of expansions in both corals and featured many immunity-related genes (Dataset S6). Notably, the NLRC3 examples belong to three distinct ortholog groups (Dataset S6). BMP-1 = Bone Morphogenetic Protein 1; CA = Carbonic Anhyrdase; TNFR19 = Tumor necrosis factor receptor superfamily member 19; TLR1 = Toll-like receptor 1; NLRC3 = NOD-like receptor C3. a more complex innate immunity network may partially reflect adaptations associated with the endosymbiosis with Symbiodinium and the ability to counter environmental insult by pathogens  24, 27, 39. Our results from the analysis of independently expanded ortholog groups belonging to TLRs, TNFRs, and NLRs echoes the analysis of Shinzato et al.
pistillata (3 genes) and one corresponding counterpart in A. digitifera. (C) Ortholog expansion displaying a many-to-one relationship of a member of the NOD-like receptor family member (NLRC3) with a particularly pronounced expansion in A. digitifera (55 genes) and only one corresponding counterpart in S. pistillata. Baumgarten et al. 27  and Poole and Weis 51 who found that the TLR/ILR protein repertoires of the symbiotic sea anemone Aiptasia show close similarity to N. vectensis with apparently lineage-specific expansion in A. digitifera. From the admittedly limited analysis of two coral genomes, it appears, however, that A. digitifera shows a more pronounced tendency to duplicate genes in the ortholog groups that are expanded in both corals (many-to-many) (Dataset S6). This pattern was also apparent when considering innate immunity-related ortholog groups that are expanded in only one of both corals (many-to-one) (although expansions were similar when considering all ortholog groups) (Dataset S7).
A check for potential co-isolation of Symbiodinium DNA was assessed via PCR targeting the multicopy gene RuBisCO (Genbank accession number AY996050) and did not yield any amplification. The primers used were 5′-GGCGATGCCTCAGACAAGA-3′ (forward) and 5′-TGGGAGTGGTCTGCTTCATG-3′ (reverse), detailed in Moya, et al. 56.
A total of 5 paired-end and 8 mate-pair libraries were generated and sequenced on the Illumina HiSeq platform at the KAUST Bioscience Core Facility with exception of the library "miseq", which was sequenced on the Illumina MiSeq platform (Table  S4 ). An additional mate-pair library (mp05) was generated and sequenced at GATC Biotech (Konstanz, Germany) (Table  S4 ). All data were uploaded to NCBI and are available under Bioproject ID PRJNA281535 (https://www. ncbi. nlm. nih. gov/bioproject/PRJNA281535/). All sequencing libraries (435x coverage) were trimmed using Trimmomatic version 0. 32  57  to remove adaptors, primers, and low quality bases at the ends of sequence reads. Putative PCR duplicates were removed using FastUniq version 1. 1  58  to compact the dataset for higher assembly performance.
Three-pass digital normalization was performed on all paired-end libraries to reduce data redundancy with khmer 59 version 0. 7. 1 (k = 20 C = 20, then k = 20 C = 10). Four paired-end libraries (221x coverage) and four mate-pair libraries (96x coverage) were de novo assembled with ALLPATHS-LG release 48961  60  using parameter HAPLOIDIFY = True, and transcriptome data was used to scaffold the assembly with L_RNA_Scaffolder 61. All Illumina sequencing libraries were used for scaffolding and gap filling using SSPACE version 1. 2  62  and GapFiller version 1. 11  63  iteratively for 3 rounds. The above-described procedure yielded an assembly of 358,078,850 bp total contig size and 400,108,361 bp total scaffold size with respective N50s of 24,388 bp and 457,453 bp. Basic genome statistics for contigs and scaffolds were generated using the perl script (http://korflab.
ucdavis. edu/datasets/Assemblathon/Assemblathon2/Basic_metrics/assemblathon_stats. pl) used to validate assemblies in the "Assemblathon 2 Contest"  64. The estimated genome size as per ALLPATHS-LG was reported at 433 Mb, and the assembled contig and scaffold lengths provide a genome coverage of ~83% and 92%, respectively. Further information regarding genome statistics are provided in Tables  1  and S1. Identification and removal of contaminating sequences. To identify and remove sequences likely to have originated from dinoflagellate, bacterial, or viral contaminants, a custom script was written employing the following strategy. BLASTN searches were conducted against six databases: the genomes of S. minutum  65  and S. microadriaticum  48  ; complete bacterial genomes (ftp://ftp. ncbi. nih.
gov/genomes/Bacteria/all. fna. tar. gz), draft bacterial genomes (ftp://ftp. ncbi. nih. gov/genomes/Bacteria_DRAFT/), and complete viral genomes (ftp://ftp. ncbi. nih. gov/genomes/Viruses/all. fna. tar. gz) databases from NCBI; and the viral database PhAnToMe (http:// phantome. org). All databases were retrieved in July 2014. As the lengths of the query and hit sequences were up to hundreds of kilobases, a combination of cutoffs (total bit score >1,000, e-value ≤ 10 -20 ) was used to identify scaffolds with significant sequence similarities to non-coral sequences representing potential contaminants. This procedure yielded 41 scaffolds that displayed significant similarity in over 50% of their non-N sequences, and thus were considered to have originated from bacterial contaminants and removed from the final assembly.
Annotation of repetitive elements. De novo identification of species-specific repeat regions in the genome assembly of S. pistillata was performed using RepeatScout (version 1. 0. 5)  66 with an l-mer size of 16 bp. Using the default settings, 10,224 distinct repeat motifs were identified that occurred ≥ 10 times. Annotation of these repeats was performed as described previously  27  using three different methods: (i) RepeatMasker (version 4. 0. 2)  67  using RepBase version 19. 07, (ii) TBLASTX against RepBase version 19. 07, and (iii) BLASTX against a custom-made non-redundant database of proteins encoded by transposable elements (TEs; NCBI keywords: retrotransposon, transposase, reverse transcriptase, gypsy, copia). The best annotation among the three methods was chosen based on alignment coverage and score.
Gene model prediction. All 89,208 transcripts from the reference transcriptome (see above) were mapped to the genome assembly and filtered by PASA release 20140417  71  to create a training set for AUGUSTUS version 3. 0. 2  73, 74. The training set was filtered using the following steps: (1) incomplete transcripts were removed, (2) transcripts with less than 3 exons were removed, (3) transcripts with ambiguous 5′ or 3′ untranslated regions (UTRs) were removed, (4) redundant transcripts were removed as indicated by BLASTP, (5) transcripts harboring repeat sequences were removed based on BLASTN against the repeat library generated by RepeatScout (see above). This yielded 2,844 transcripts and corresponding mapping information that were used to train AUGUSTUS. To improve prediction accuracy, a 'hints' file indicating the locations of matching transcripts was generated by mapping all 89,208 transcripts from the reference transcriptome to the genome assembly using BLAT and the AUGUSTUS script blat2hints.
Coral genomic protein set composition. BLASTP searches of gene models from S. pistillata and A. digitifera were performed against two different databases. Using S. pistillata to illustrate the procedure, two databases were created: a 'non-coral' database, and a 'with-coral' database. The former consisted of Aiptasia gene models  27  and the NCBI 'nr' database (Nov. 2015 release); the latter included gene models from A. digitifera, in addition to the sequences from the 'non-coral' database. Species names contained within annotations for the best hits (e-value ≤ 10 -5 ) were parsed and fed into a python script that obtained the full taxonomic hierarchy for the respective organisms via an API hosted by Encyclopedia of Life (http://eol. org/api)  76. Based on the resulting hierarchies, best hits were grouped based on their respective genus.
Protein set annotation. The final set of predicted proteins derived their annotations from UniProt (i. e. , SwissProt and TrEMBL) or the NCBI 'nr' databases (Table  S1 , Dataset S8), similar to the pipeline described previously  27, 68. Briefly, genomic protein models were subjected to a BLASTP search against SwissProt and TrEMBL databases (June 2014 release). GO terms associated with SwissProt and TrEMBL hits were obtained from UniProt-GOA (July 2014 release)  78. If the best-scoring hit of the BLASTP search did not yield any GO annotation, further hits (up to 20 hits, e-value ≤ 10 -5 ) were considered and the best-scoring hit with available GO annotation was used. If none of the SwissProt hits had GO terms associated with them, the TrEMBL hits were processed similarly. Using this procedure, 21,446 genes (83.
2% of the 25,769 gene models) were annotated and had at least one GO term associated with them (17,506 proteins had GO annotations via Swiss-Prot, while the remaining 3,940 were from TrEMBL) (Table  S1 ). A majority of the annotations were based on strong alignments to existing sequences within the SwissProt and TrEMBL databases: 19,060 genes had e-values ≤ 10 -10 , 15,637 of these had e-values ≤ 10 -20. Proteins that had no matches to either database were subjected to an additional search against the NCBI 'nr' database (e-value ≤ 10 -5 ). An additional 1,466 proteins were annotated this way. A small fraction of proteins (2,857, 11. 1%) had no hits to any of the three databases. A similar procedure was performed for the A. digitifera gene models to eliminate potential biases stemming from the use of different annotation pipelines and databases (Dataset S9).
Accession codes. The genome assembly, gene models, and protein models described in this study are available for download at http://spis. reefgenomics. org/download. A JBrowse genome browser is available at http://spis. reefgenomics. org/jbrowse. A BLAST server for the Stylophora pistillata genome is available at http:// spis. reefgenomics. org/blast/. Raw sequence data reported are deposited at  NCBI  under the accession number  PRJNA281535  (https://www. ncbi. nlm. nih. gov/bioproject/PRJNA281535/).
All events were acquired by a BD LSR-II cytometer equipped with BD FACSDiva software (BD Biosciences) and data were analysed using FlowJo software (Tree Star, Ashland, OR, USA). Cell lysis. RIPA lysis for western blot (WB): purified naive T cells were differentiated into T H 2, T H 9 and Treg cells. Cell pellets were incubated in five volumes of RIPA buffer (50 mM Tris-HCl (pH 7. 5), 150 mM NaCl, 1% NP-40, 0. 5% Nadeoxycholate, 0. 1% sodium dodecyl sulfate, 1 mM EDTA, protease inhibitors) for 45 min on ice. After centrifugation at 16,000×g for 15 min at 4 °C, the supernatant was recovered for WB analysis. Low salt (LS) lysis for immunoprecipitation: purified naive T cells were differentiated for 24 h into T H 9 cells in the presence or in the absence of chloroquine. Cell pellets were incubated in two volumes of LS buffer (10% glycerol, 20 mM Tris-HCl (pH 8), 0.
Acknowledgements The authors are supported by grants from the  Ligue Nationale contre le Cancer  (to F. G. ), the  Fondation de France  (to L. A. and T. R. V. ), the  Institut National du Cancer  (to F. G. ), the  Fondation ARC pour la recherche sur le cancer  (to L. A. ), the  Institut Mérieux  (to L. A. ), the  Conseil Régional de Bourgogne  (to F. G. and L. A. ), the  FEDER , the  Agence Nationale de la Recherche  ( ANR-13-JSV3-0001 ) (to L. A. ) and ( ANR-11-LABX-0021 ), the  ARSEP  (to L. A. and M. D. ), the  Ligue Régionale contre le cancer Comité Grand-Est  (to L. A. ) and the  European Commission  ( Marie Curie Fellowship   PCIG10-GA-2011-303719 ) and  ERC   starting grant  ( 677251 ) (to L. A. ).
Primers with degenerate nucleotides as less as possible were selected. These primers delineated an amplicon with a consensus sequence shared by DENV strains of the 4 types. We designed within the amplified region a 14 nucleotide probe with LNA™ modifications to fit thermal requirement of a TaqMan® probe. DENV genomic sequences were available from Virus Pathogen Database and Analysis Resource  [19]. Sequence alignment was performed with MUSCLE tool provided by VIPR. Sequence annotation was done using BioEdit Sequence Alignment Editor v7. 1. 3 [20]. Melting temperature and complementarity of primers were checked with Oligocalc calculator  [21]. LNA™ probes were designed with LNA™ oligo tools from Exiqon and synthesized by Eurogentec®. Due to perfect match with at least 13 nucleotides between sequences template and DRa primer, DRa likely accounts for DENV1, DENV2, DENV3 RT-PCR amplification in combination with forward primer.
Tests for primers cross-reactivity Cross-reactivity of primers used in our triplex assay was checked with a panel of pathogens comprising Alphavirus (Sindbis Virus, Ross River Virus, Semliki Forrest Virus, Onyong Onyong Virus), Flavivirus (West Nile Virus, Yellow Fever Virus, Zika Virus, Hepatitis C Virus), fungi (Candida albicans) and bacteria including Branhamella catarrhalis, Citrobacter diversus, Haemophilus parainfluenzae, Klebsiella oxytoca, Mycobacterium tuberculosis, Neisseria sp. , Pseudomonas aeruginosa, Salmonella typhi, Staphylococcus aureus, Streptococcus pneumonia. We found no evidence of cross-reaction targeting these pathogens (data not shown).
Multiplex assay accuracy for CHIKV and DENV Accuracy of our multiplex assay was checked using external quality assessment standards (EQA) from Integrated Quality Laboratory Services (IQLS) in charge of implementing the SEGA network (epidemiological surveillance and response in the Indian Ocean). Bias was calculated against data produced by the reference laboratory or against the averaged data of all laboratories enrolled in the SEGA network. A negative bias against other laboratories accounts for better sensitivity of our test compared to others. Our CHIKV results have shown similar performance with the reference laboratory and an increased sensitivity of 7. 91% compared to all laboratories. For DENV detection, our assay was characterized by an increased sensitivity of 8. 05% compared to the reference laboratory and produced similar results when compared to other laboratories (Table  5 ).
9 For instance, data from the NOR-DMARD registry indicated that switching from one TNF inhibitor to another restored clinical response in patients with AS. 10  Conversely, a systematic switch when low disease activity was observed was not suitable. For instance, in Crohn's disease, there was a loss of tolerance and a high rate of discontinuation of adalimumab when infliximab was replaced with adalimumab in patients with stable disease as compared with patients who remained on infliximab. 11 munogenIcIty One major concern with interchangeability of bDMARDs is immunogenicity. 4 9 12 Indeed, it is well known that bDMARDs, especially monoclonal antibodies, may induce antidrug antibodies (ADAb). Immunogenicity to bDMARDs in inflammatory diseases is a complex phenomenon that is influenced by several factors including patient characteristics (body mass index, for instance), the disease itself and its pathophysiological-associated mechanisms, the administered drug dosage and circulating through levels, the associated drugs and especially concomitant use of conventional synthetic DMARDs such as methotrexate.
The results of the phase III study are not currently published, and this bsDMARD is not currently approved by medical agencies. After the 24-week, randomised, double-blind phase, patients entered into a transition period from week 24 to week 52. After the double-blind phase, 254 patients continued to receive SB5, 125 switched from adalimumab to SB5, while 129 kept adalimumab. The clinical response as evaluated by the ACR20 response was sustained and did not differ between the three groups. Safety and immunogenicity were also comparable in the different treatment arms (table  1 ). 21 itches in routine practice Data about switching TNF inhibitors in real practice are now available. NOR-SWITCH ( ClinicalTrials. gov NCT02148640) is the first trial that investigated the effect of switching originator infliximab to CT-P13 at country level, in Norway.
According to national guidelines, all the patients with inflammatory rheumatic diseases treated in routine care by originator infliximab were switched to CT-P13. 23 Data on efficacy, safety and immunogenicity were then monitored. Disease activity was recorded and compared at different time points, including before switching, at the time of the switch and 3 months later, allowing disease flares to be evaluated in 768 patients. Infliximab originator was given for a mean period of 6. 6 years. Disease activity and disease flare remained unchanged 3 months prior to Treatments the switch versus 3 months after the switch. At the last visit at 12 months, disease activity was stable. Treatment adherence was similar between the different inflammatory rheumatic diseases. CT-P13 was stopped in 15% of patients between the switch and the end of follow-up due to loss of efficacy in half of them.
Immunogenicity assessed by the rate of ADAb positivity was comparable between inclusion visits and at 6 months. Similar results were reported in this registry when switching etanercept originator to its bs SB4  24  (table  1 ). What are the issues when switching a bodmArd to a bsdmArd? Overall, data on the effects of switch in the field of biologics are accumulating and provided valuable insights on efficacy, safety and immunogenicity with bsDMARDs. Extension studies evaluating the transition from originators (infliximab, etanercept or adalimumab) to their respective bsDMARDs (CT-P13 or SB2, SB4 and SB5, respectively) are reassuring as are data from switch studies in patients receiving infliximab or etanercept in routine care. The follow-up in the long-term extension/transition studies, in the NOR-SWITCH trial and in the Danish registry, was sufficient to detect an effect on efficacy, safety and immunogenicity of the bsDMARDs.
Mortality monitoring and DNA quantification in oyster mantle and haemocytes Oyster mortality was first observed at 48hpi and increased gradually from 48hpi to 96hpi for the two batches, regardless of the animal age (Fig  1 ). However, the final mortality rate was significantly different between the NSI 01/15 (74%; 17/23) and J6 (100%; 9/9) (Fig  1 ). No mortality was recorded in control tanks containing oysters injected with ASW. No significant difference was observed between the two infected oyster batches at 2hpi (p = 0. 128), 24hpi (p = 0. 100), and 48hpi (p = 0. 100) for the OsHV-1 DNA amounts (Fig 2 ). No viral DNA was present in the mantle of NSI 01/15 oysters injected with ASW whereas OsHV-1 DNA was detected below the quantification limit of the real time PCR in the mantle and the haemolymph of J6 oysters injected with artificial seawater (data not shown).