dataesr/scientific-paragraphs-categorization huggingface dataset:
Cytoplasmic localization of RAP1 has also been reported, as well as its involvement in NF-B signalling  (35, 36). A recent study shows that RAP1 can affect TRF2 interaction properties toward duplex DNA  (37). In TeloPIN database  (5) , RAP1 and TRF2 interact respectively with 131 and 247 partners, among which 32 are common partners between RAP1, TRF2 and other shelterin proteins and 12 are common partners exclusively between RAP1 and TRF2. Therefore, whether or not RAP1/TRF2 interaction may affect/reinforce their respective properties and how DNA/TRF2 complex recruits its numerous protein partners compared to RAP1/TRF2/DNA complex remain to be fully characterized. In order to address this central question, we initiated a comprehensive study of the parameters that describe the assembly of RAP1 and TRF2.
HJ protection A total of 5 nM of telomeric HJ (tHJ) labelled on one strand was incubated with different concentrations of proteins in 10 l of binding buffer containing 10 mM MgAc 2 and digested for 60 min using 2 nM of T7 Endonuclease I, MBP-CceI and MBP-RusA or 50 nM of GEN1 1 -527. Reactions were performed at 4 • C for Endo I or 37 • C for MBP-CceI, MBP-RusA and GEN1 1 -527. The reaction was stopped by addition of 6 g of proteinase K followed by 20 min incubation at 4 • C or 15 min at 37 • C. Formamide was added to a final concentration of 60% (v/v) and the samples loaded on a 10% denaturing acrylamide (19:1, bis:mono) 1× TBE gel. After migration in 1× TBE, gels were analysed using a Phosphorimager TyphoonFLA9000 (GE Healthcare) and the Image Quant software (GE Healthcare).
Raw scanning force microscopy images were flattened using the manufacturer's software and converted into TIF files. Contour lengths (CLs) were measured by the read-through length method using SigmaScan Pro software (SPSS Inc, Chicago, IL, USA). Volumes calculated as half-ellipsoids as published  (38). Between 150 and 250 objects were scored for each condition. The 2D probability density map is a smoothed distribution that represents the convolution of the experimental distribution with a s 1 × s 2 gaussian pulse. To construct the 2D map, each protein/DNA complex with a raw DNA length L raw and a complex volume Vol complex contributes as gaussian distribution of respectively s 1 and s 2 width in L raw and Vol complex directions. Each pixel of the 2D map is the sum of the various gaussian contributions from the experimental data points.
SAXS SAXS experiments were performed at SWING beamline, synchrotron SOLEIL. TRF2, RAP1 and RAP1-RCT were set in the buffer containing 20 mM Tris pH = 7. 5, 150 mM NaCl, 5 mM 2-mercaptoethanol and 0. 2 mM PMSF. TRF2 was concentrated to 215 M (monomers), RAP1 to 326. 7 M, RAP1-RCT to 1015. 7M, TRF2 and RAP1 were mixed to 120 and 144M respectively, and TRF2 and RAP1-RCT were mixed to 171. 5 and 205. 8 M respectively, both corresponding to a RAP1/TRF2 molar ratio of 1. 2. All data were collected at SWING beamline at SOLEIL synchrotron using either the sample changer (RAP1 fulllength), or using the online HPLC system  (39) , equipped with a BIO-SEC3 column (Agilent) for all other proteins or complexes. After data collection, all leftovers from these preparations were analysed by sodium dodecyl sulphatepolyacrylamide gel electrophoresis (SDS-PAGE) to ensure no degradation occurred during the experiments.
Crystallization and structure determination Crystals of TRFH in complex with peptide RAP1-YLP 89 ENRERLELEAYRLGPASA 106 were obtained by hanging drop vapour diffusion at room temperature, with a concentration of TRFH of 34 mg/ml and a molar ratio of TRFH/Rap1-YLP of 1:3. 5 in a buffer containing 12. 5 mM Tris pH 8. 0, 100mM NaCl and DTT 2. 5 mM. The most suitable crystals grew in 16% PEGmme 550, 50 mM Hepes pH 8. 0, 5 mM MgCl2, 5 mM DTT. Native diffraction data were collected on PX1 beamline at SOLEIL synchrotron, and reduced with XDS  (40). The structure was solved by molecular replacement with PHASER (41), using one TRFH monomer from 3BUA PDB entry: as model probe  (15) , and refined with BUSTER5  (42).
SEC-MALS TRF2 protein at a concentration of 100 M (in a buffer containing 50 mM Tris, pH 7. 5, 150 mM NaCl, 10 mM 2-mercaptoethanol) was applied to Bio SEC-3 column (Agilent) on a HPLC Shimadzu system coupled to MALS/QELS/UV/RI (Wyatt Technology). Data were analysed using ASTRA software after calibration with a bovine serum albumin standard.
Model building and conservation analysis The BRCT domain of RAP1 was modelled using MOD-ELLER software  (44)  and the structure of the BRCT domain of Rap1 from S. cerevisiae (45, PDB entry 2L42). The resulting model and Myb domain of RAP1  (46)  were then manually positioned along the TRFH domain of TRF2 with Pymol (47, http://www. pymol. org) based on the TRFH/RAP1-peptide crystal structure and the protein footprinting results. Conservation analysis was performed with CONSURF software (48) using 14 sequences for both TRF2 and RAP1 from the same species of vertebrates (See sequence codes in Supplementary Data).
In order to delineate the structural determinants of this interaction we solved the crystal structure of the RAP1-YLP/TRFH complex at 2. 4 Å resolution (Figure  3A  and B ). The superimposition of our structure with this of TRFH in complex with the Apollo-YLP peptide (PDB entry: 3BUA, 15) shows that the structures are similar, although the N-terminal part of Apollo-YLP and RAP1-YLP peptides are oriented in opposite directions (Figure  3C ). In the case of the Apollo peptide, substitution of Tyr, Leu or Pro into Ala affects the interaction with the TRFH domain, although the effect was not equivalent for each position  (15). We mutated the region 99 YRLGP 103 into 99 ARAGA 103 in RAP1 full length and, after checking the structural integrity of this RAP1-ARAGA mutant by circular dichroism (Supplementary Figure  S4C -  E), we measured its interaction with TRF2.
Looking from the top of the TRFH domain, we observe that this interaction of the N-terminal region of RAP1 induces an unexpected dimerization of the BRCT domain (Figure  4C , right). The high conservation among vertebrates of the known YXLXP binding site of TRF2, of the YRLXP motif of RAP1 and of the surface of RAP1 involved in the secondary interaction also reveals that this secondary interaction of RAP1 and the capacity of TRF2 to interact with YRLXP motif containing proteins are of equal importance. The similar ITC interaction profiles between TRF2 and Apollo-YLP and between the preformed TRF2/RAP1 complex and Apollo-YLP also suggests that RAP1 interaction may probably not hinder Apollo interaction (Supplementary Figure  S7C  and D ). Similar analysis could apply to SLX4, which contains a TRFH binding motif ( 1014 RGLEVHRLAPW 1028 ), is characterized by a dissociation constant of 750 nM with TRF2, and adopts the same conformation than Apollo-YLP peptide in complex with TRFH (PDB entry: 4M7C, 16).
(A) TRFH/RAP1-YLP peptide crystal structure; (B) Juxtaposition of RAP1[1-121] 3D model calculated with Modeller (41), and RAP1-Myb nuclear magnetic resonance structure (PDB entry: 1FEX). (C) Positioning of RAP1 BRCT and Myb domains on TRFH surface based on combination of the crystal structure and footprinting experiments, showing on the right side the induced dimerization of BRCT domain (colour code identical than in Figure 3). (D) Surface representation of RAP1[1-208] coloured upon the conservation score of CONSURF software (48) with the trace of the TRFH domain in black shadow (left); Surface representation of TRFH domain of TRF2 coloured upon the conservation score of CONSURF software (48) with the RAP1-YLP peptide in black (right). All structure representations were drawn with software Pymol (47).
ACKNOWLEDGEMENTS The authors wish to thank  Stephen CY Ip ,  Stephen C West ,  Anne-Cécile Déclais  and  David MJ Lilley  for kindly providing resolving enzymes or plasmids to produce them. We thank  Dr Carl Mann  for his help with cell culture and for the HeLa cells he provided,  Magali Aumont-Nicaise  for her support in the use of ITC instruments at IBBMC supported by the  French Infrastructure for Integrated Structural Biology (FRISBI) ,  Valérie Campanacci  for her help in SEC-MALS experiments and  Centrino Moscalenko  for her help in drawing the AFM 2D maps. Initial discussions with  Delphine Benarroch-Popivker  and  Bianca Sclavi  were very useful for the design of the protein footprinting experiments. We are very grateful to PX1,  PX2  and SWING beamlines local contacts from synchrotron SOLEIL for their help during data acquisition.
Author contributions: G. G. , S. M. , S. P. , Y-VLB, R. T. , M-. J. G-. P. , E. G. and M-. H. L. D. conceived and designed the experiments. G. G. , S. M. , S. P. , R. B. , Y-. V. L. B. , C. T. L. , W. M. , P. R. , B. G. , R. T. , M-. J. G-. P. and M-. H. L. D. performed the experiments. G. G. , S. M. , S. P. , R. B. , Y-. V. L. B. , C. T. L. , W. M. , P. R. , B. G. , R. T. , M-. J. G-. P. , E. G. and M-. H. L. D. analyzed the data. G. G. , S. M. , S. P. , M-. J. G-. P. , E. G. and M-. H. L. D. wrote the manuscript. FUNDING  Agence Nationale de la Recherche  ( TELOLOOP grant ) [ ANR-1582-30020690 ]; Ligue contre cancer (EG équipe labellisée);  INCa  ( TELOCHROM grant ); Essonne committee of the Ligue contre le cancer (grant  M18756  and  M22897 ); Foundation  ARC pour la Recherche sur le Cancer  (grant  SFI20121205503 );  Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA) ;  French Infrastructure for Integrated Structural Biology (FRISBI) ;  Centre National de la Recherche Scientifique (CNRS) ;  Institut National de la Santé et de la Recherche Médicale  (IN-SERM).
Sources of data All laboratory-confirmed human cases of avian influenza A(H7N9) virus infection were notified to the Chinese Center for Disease Control and Prevention (China CDC) and relevant clinical and epidemiological data was recorded in an electronic database  [2, 3]. Data extracted for this study included age, sex, geographical location, underlying conditions and dates of illness onset and hospital admission for cases reported from March 2013 through August 2014. Exposure data were available for 203/395 (51%) of cases. In the majority of those cases, the information on exposure was recorded as intervals of 2 or more days during which infection was thought to have occurred rather than exact dates of presumed infection  [2]. For the subset of cases without available exposure data, we assumed their incubation time fell in the interval (0,14) days  [2].
In this analysis and the analyses described below, we specified flat priors for each parameter, and drew 10,000 samples from the posterior distributions after a burn-in of 5,000 iterations. Analyses were conducted using R version 3. 2. 2 (R Foundation for Statistical Computing, Vienna, Austria). The raw data and R syntax allowing reproduction of the results presented in this article are available from the Dryad Digital Repository (link to be provided in the published version).
Results There were 438 confirmed H7N9 cases included in the China CDC database as of the 5th August 2014, and 43 of these were recorded as "mild" cases and were excluded from the analyses here because they form only a small sample of mild H7N9 infections. Among the 395 patients included in this study who all required hospitalization for medical reasons, 173 (44%) patients died. The mean age was 58. 2 years old (±16. 6 years), 71% were male, 139 (35%) cases were residents of rural areas and 189 (68%) cases had underlying medical conditions. Fatal cases were significantly older compared to non-fatal cases (63. 0 vs 54. 5 years old, respectively; p<0. 001) and had a lower proportion of missing data on exposure (42% vs 54%, respectively; p = 0. 019) (Table  1 ). We estimated a mean incubation period of H7N9 in all cases of 3.
8-2. 0), which could reflect differences regarding pathogenesis between these different virus strains  [20]. We also observed a significant increased risk of death among older patients. To assess the effect of this potential cofounding factor, we applied a stratified analysis using two age groups (0-59 years old and >60 years old) and we still observed a longer incubation period among fatal cases, while the point estimate was larger among older patients (Table  4 ). However, these two variables were not linearly correlated in this study (Table  2 ). This result could reflect some potential uncontrolled cofounding effect between the length of incubation period and age, which has been reported in previous studies  [5, 6, 11]. Our study does have some limitations. Our estimates of the incubation period were based on self-reported exposure data which could suffer from recall bias.
Acknowledgments We thank staff members of the  Bureau of Disease Control and Prevention  and  Health Emergency Response Office of the National Health and Family Planning Commission  and provincial and local departments of health for providing assistance with administration and data collection; staff members at county-, prefecture-, and provincial-level Centers for Disease Control and Prevention in the provinces where human A(H7N9) cases occurred for providing assistance with field investigation, administration and data collection. The views expressed are those of the authors and do not necessarily represent the policy of the  Chinese Center for Disease Control and Prevention.
Acknowledgments This work was supported in part by grants from the  French National Agency for Research called BInvestissements d' AvenirL abex IRON  no. ANR-11-LABX-0018-01  and  Equipex ArronaxPlus  no. ANR-11-EQPX-0004. Open Access This article is distributed under the terms of the Creative Comm ons Attribution 4. 0 International License (http:// creativecommons. org/licenses/by/4. 0/),which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
47) and 48 (33-91; P = 0. 15) days among the MAC recipients. With a median follow-up of 5. 6 years, 41 relapses (30%) and 57 deaths (42%) were recorded. The cumulative incidence of relapse (CIR) at 10 years was 15% (95% CI 7-23) in the group of patients who experienced viral reactivations compared with 54% (95% CI 41-70) in the group of patients without viral reactivation (P < 0. 01) (Fig. 1A ). Ten year-CIR was also significantly lower in the CMV+ group (26%, 95% CI 18-38) compared with the CMV-group (45%, 95% CI 28-58) (P = 0. 03) (Fig. 2A ). In univariate analysis, viral reactivations and CMV+ serological status were associated with a significant reduced risk of relapse as well as chronic GVHD but not ELN classification, type of donor, conditioning regimen, stem cell source, or acute GVHD (data not shown).
Acknowledgments The authors thank all the members of the G. A. E. L ( Gaël Adolescent Espoir Leucémie ) and  A. G. M. O. M. P  ( Association des Greffés de Moelle Osseuse de Midi-Pyrénées ) associations for their kind support to patients. They would also like to thank the data management unit of  Toulouse University Hospital  and the  CAPTOR (Cancer Pharmacology of Toulouse Oncopole and Region)  project ( ANR-11-PHUC-001 ) for his financial support enabling e-CRF.
interpreted data, and wrote the manuscript. Funding: CR has received commercial research grants from  Amgen ,  Celgene , and  Chugai  and is a consultant/advisory board member of  Celgene  and  Sunesis Laboratories. This work has been granted by granted by the  French government  under the " Investissement d'avenir" program  ( ANR-11-PHUC-001 ). The authors have no funding and conflicts of interest to disclose.
For Cayenne alone, there were an estimated 7231 cases, with 2672 probable or confirmed cases, 340 of whom were hospitalized (4. 70%) 46 being severe (0. 64%), with 2 deaths(2. 7 per 10 000). The hospitalization rate was thus the highest to date. Patients that were not hospitalized were followed up every day at the infectious diseases outpatient department. The diagnosis of dengue was performed using NS1 tests, RTPCR or serology. Confirmed dengue was defined by positive NS1 or RTPCR, or seroconversion; probable dengue was defined as a single positive IgM serology result, or an evocative clinical presentation. Medical records used a standardized data collection form to collect demographic information, clinical signs and biological results and the date at which they were present. A research nurse then retrospectively collected standardized anonymized information from the data collection form.
Data analysis Data analysis was performed using Stata 13. Quantitative variables were categorized according to statistical criteria using the 10th and 90th percentiles, the first and third quartiles and the median. The failure event was the first central nervous system dysfunction reported (defined as decreased Glasgow coma scale and or convulsions). Crude and stratum-specific incidence rates were calculated and single failure Cox proportional hazard models were used to identify predictors of neurological signs. To reduce the number of variables in a single model thematic models were build to select the variables for a final parsimonious multivariate model. The first model was built for clinical covariates, then a second one with biological covariates, finally the significant variables from both models were used in a third model.
Discussion Here in a small city with easy access to emergency care, quality care and a policy of hospitalizing patients with any clinical, biological or social warning sign, over 20% of the patients seen for dengue fever had central nervous system dysfunction mostly around the 5th or 6th day of fever. This proportion is much higher than in the studies in South East Asia  [16] [17] [18] [19]  but similar to a study in Brazil  [20]. The study in Brazil recruited patients admitted to a tertiary care whereas our study included all patients seen at the hospital, both outpatients consulting an infectiologist and hospitalized patients. Given the non specific nature of the data collection form, it was difficult to know whether CNS signs were linked to encephalopathy or encephalitis, or if these signs reflected general exhaustion.
Genome Sequencing, Assembly and Annotation The genome of BrMV was extracted using the automated EZ1 Virus Mini-Kit v. 2 (Qiagen GmbH, Hilden, Germany) according to the manufacturer's instructions. DNA quality and concentration were checked using a nanodrop spectrophotometer (Thermo Scientific, Waltham, MA, USA). Sequencing was performed using the Illumina MiSeq instrument (Illumina Inc. , San Diego, CA, USA), with both paired end and mate pair applications, following the manufacturer's protocol for library constructions. The sequence reads were assembled de novo using the ABYSS software [  [30] ). Gene predictions were performed using FgenesV  [31] , RAST (Rapid Annotation using Subsystem Technology)  [32]  and GeneMarkS  [33]  tools, and merged. Functional annotation was inferred by BLAST searches against the GenBank NCBI non-redundant protein sequence database (nr) (using an e-value <10 ´5 as threshold), the set of clusters of orthologous groups of proteins (COGs) of the NCLDV (named NCVOGs  [34] ) and by searching specialized databases using the Blast2GO platform  [35].
Comparative Genomic and Pan-Genome Analysis The genome synteny between the BrMV and other marseilleviruses was checked using the MAUVE program  [37]. The Proteinortho tool  [38]  was used to define the strict core of bona fide orthologs shared among BrMV and amoebal marseilleviruses from lineages A-C, using the reciprocal best hit strategy with 10 ´5, 30% and 50% as thresholds for e-value, identity and coverage of amino acid sequences, respectively. In addition, we evaluated variations in the set of core genes (considering gene content from each new virus), and evaluated the intra and intergroup ratio of core genes/gene content. The OrthoMCL tool  [39, 40]  was used to identify the paralogous gene families among all marseillevirus genomes which were analyzed. The average amino acid identity (AAI) calculator tool  [41]  was used to compare identity between orthologous genes from BrMV and other marseilleviruses, and from representative members of marseillevirus lineages.
Phylogeny We performed a hierarchical-clustering based on the gene presence/absence pattern of 5443 NCVOGs, using the MeV tool  [43]  with Pearson correlation as distance metric. The phylogenetic tree was visualized using the FigTree v1. 4. 1 tool  [44]. In addition, the five Megavirales core genes, namely the family B DNA polymerase, the D6/D11 helicase, the VV A18 helicase, the D5 primase-helicase, and the Major Capsid Protein were used for the phylogenetic analyses. Amino acid sequences were aligned using the Muscle software  [45]. Phylogenetic trees were built using the FastTree software  [46]  and the maximum likelihood method. The supertree was built using the five previously reconstructed phylogenetic trees (supplementary data), using the spr-supertree software  [47]. The supertree algorithm was based on the subtree prune-and-regraft distance.
Brazilian Marseillevirus Genome and Annotation The BrMV genome (GenBank accession No. : KT752522) is a circular, double-stranded DNA molecule composed of 362,276 bp (Supplementary Figure  S2 ). This is compatible with the genome sizes of the other marseilleviruses, which range from 346,754 bp (Lausannevirus; NC_015326. 1) to 386,631 bp (Insectomime virus; KF527888). The mean G+C content of the BrMV genome is 43. 3%, which is similar to that of other marseilleviruses. A total of 491 open reading frames (ORFs) were identified after merging all coding sequence predictions. These ORFs are fairly evenly distributed on both negative (261 ORFs) and positive (230 ORFs) strands, which was quite similar to gene distribution on the Marseillevirus genome (233 and 224 ORFs on negative and positive strands, respectively)  [11].
Viruses 2016, 8, 76 5 of 16 A total of 446/491 ORFs (90. 8%) from the BrMV had significant BLASTp matches (coverage ě 50%; similarity ě 50%; e-value ď 10 ´6) to marseillevirus protein sequences available in the NCBI nr database, with a mean identity of 77. 2%. The greatest number of best hits was with the Tunisvirus isolate, with 237 hits showing a mean identity of 73. 2%. There were a lower number of best hit cases for the remaining marseilleviruses (mean: 52. 5, range: 17 to 138), with lower mean identity values (mean: 58. 8% ˘standard deviation (SD): 8. 7%; range: 55. 9% to 71. 0%). The number of best hits decreased with Insectomime virus, Lausannevirus, Cannes8 virus, Melbournevirus, Marseillevirus and finally Senegalvirus. Only 15 ORFs predicted in the BrMV genome showed identity values higher than 95% with marseilleviruses, namely Tunisvirus and Insectomime virus (group C).
Moreover, only two ORFs (ORF364, a hypothetical protein; ORF381, a ubiquinone) predicted in the BrMV genome showed 100% identity with another marseillevirus, Lausannevirus (group B). A BLAST search against the NCBI nr database identified one sequence (ORF258-181 aa), with 50% coverage and 34% identity (e-value: 3 ˆ10 ´8 with a hypothetical protein of Shrimp white spot syndrome virus, which is not found in any other marseillevirus. Moreover, 16 putative ORFs (shorter than 100 amino acids (14 ORFs ranging from 50 to 100 aa)), in addition to 29 ORFs larger than 100 amino acids (ORFans), showing no homology with sequences available in GenBank databases, were identified. The absence of these ORFs in other marseilleviruses was confirmed by nucleotide search using the BLASTn tool. The BrMV gene content consists of 59.