dataesr/scientific-paragraphs-categorization huggingface dataset:
JEL612  (Dee et al. 2015 ; the same intron insertion position S943) and Phlyctochytrium planicorne  (James et al. 2006b ; another intron insertion position S508). According to tblastn search against nr/nt database of NCBI, the endonuclease from Gonapodya sp. is the most similar to the endonuclease from the strain X-124. This indicates that the chyrid X-124 and monoblepharid Gonapodia sp. JEL612 obtained their homing endonuclease genes either "vertically" from an ancient common ancestor or horizontally from an unknown source. S943 introns are widely distributed in different fungi, amoebae, algae, cercozoans, and ciliates. The majority of these taxa include nonintronized and intronized species at the different phylogeny levels. However, S943 intron distribution is mosaic because only 1-5% species in each mentioned group carry this intron.
Another hypothesis solving the mosaic intron distribution issue is horizontal transfer. But this hypothesis explains the observed grouping of closely related filamentous fungi only if the horizontal transfer was limited to closely related species. According to the accepted phylogeny of the fungal species, we expected that S943 introns of the chytridiomycetes would form a sister clade to the filamentous fungi. However, the evolutionary path of S943 intron heredity in zoosporic fungi is still under question because of poor resolution of this part of the tree and lack of representative data. Similar ambiguity appears if we interpret the distribution of homing endonuclease genes, rather than the nucleotide sequences of S943 introns. Only two distantly related species of zoosporic fungi have a homing endonuclease gene in their S943 introns, and they are the most similar to each other among all the available homing endonuclease sequences in the NCBI database.
granulosporum Scherff. as a basyonym for description of new genus and species which belongs to the order Gromochytriales on the base of molecular phylogeny and zoospore ultrastructure. Etymology: after the name Rh. granulosporum-most similar to the strain X-124. GenBank Accession Numbers X-124a -MK179157, X-124b -MK179158. Type: Fig. 1. Karpov et al. this.
Acknowledgements The isolation, cultivation, morphological study of strain X-124, and the manuscript writing have been supported by  RSF  grant no. 16-14-10302 , and the molecular analysis by  ERC Advanced  Grant No. 322669  "ProtistWorld. "We also thank for support the RFBR grants No. 15-29-02734  and  18-04-01210 ; the  scholarship program  " Jean d'Alembert" of Paris-Saclay University ; the program of the  RAS Presidium "Evolution  of the organic world. The role and significance of planetary processes"; the  Research Resource Center for Molecular and Cell Technologies (RRC MCT) at St. Petersburg State University (SPbSU)  for access to the EM facilities;  ZIN RAS program   AAAA-A17-117030310322-3. The investigated strain has been cultivated at the  Center for Culturing Collection of Microorganisms of Research park of St.
In order to avoid selection bias, the SES distribution of the control group reflects the SES distribution of the entire département of Hérault to yield the control group similar to the general population of men of the same age in terms of SES. After the selection process, the distribution by SES between our control group and the male general population of the département of Hérault has been compared and no significant difference has been found, suggesting that no major selection bias by SES had occurred. To minimize differential classification bias that can persist in case-control studies, data were collected by the same clinical research nurses for cases and controls, and under the same conditions using a standardized questionnaire. To minimize possible differential misclassification bias, we rather used anthropometric indicators that have been measured at interview by the nurses than the selfdeclared indicators.
Data collection Cases and controls provided information about socio-demographic characteristics, occupational and residential history, lifestyle and leisure activities, personal and family medical history and anthropometric factors using a face-to-face standardized computerized questionnaire (CAPI, Computer Assisted Personal Interview) realized by research clinical nurses. Anthropometric factors of interest included height, weight, waist and hip circumferences. Self-reported height at 20 years old and weight two years before the reference date (i. e. , date of diagnosis for cases or date of interview for controls) were asked in the questionnaire and height, weight, waist and hip circumferences were measured at interview by the research clinical nurses. For cases, medical data such as Gleason scores, Prostate Specific Antigen (PSA) levels, and tumor stage at diagnosis were extracted from patient's medical records and validated by the Hérault Cancer Registry.
ACKNOWLEDGMENTS We would like to thank the clinical research nurses who were in charge of participants' interview, anthropometric measurements and biological sample collection ( Anne-Laure Astolfi ,  Coline Bernard ,  Oriane Boyer ,  Marie-Hélène De Campo ,  Sandrine Margaroli ,  Louise N'Diaye ,  Sabine Perrier-Bonnet ). We also would like to thank  Christian Prad  and  Nadine Soller  for help with patient medical data collection within the  Hérault Cancer Registry  ( Registre des tumeurs de l'Hérault, Montpellier, France ). Finally, we are grateful to the EPICAP study Group: Urologists:  Drs Didier Ayuso ,  Bruno Segui  ( Centre Hospitalier Bassin de Thau, Sète, France ),  Alain Guillaume ,  Jean-Paul Constans ,  Olivier Delbos ,  Pierre Lanfray ,  Damien Rizet ,  Etienne Cuénant  ( Cabinet Urologie du Polygone, Montpellier, France ),  Michel Locci  ( Centre Hospitalier, Béziers, France ),  Etienne Cuénant  ( Clinique Ste Thérèse, Sète, France ),  Nicolas Drianno ,  Bernard Marc ,  Paulo Soares  ( Polyclinique Saint Privat, Béziers, France ),  Antoine Faix ,  Samer Abdel Hamid ,  Bruno Segui  ( Service urologie ,  Clinique Beau Soleil , Montpellier, France),  Samer Abdel Hamid  ( Clinique Saint Louis, Ganges, France ),  Laurent Cabaniols ,  Maxime Robert ,  Rodolphe Thuret  ( Centre Hospitalo-Universitaire, Hôpital Lapeyronie, Montpellier, France ).
0) was 25 cm/min. The 1-μL samples were dosed automatically using Shimadzu AOCi-20 autoinjector operating in splitless mode with sampling time set to 1 min. Detection of individual analytes was conducted as selected ion monitoring (SIM) using 64 mass ions characteristic for the assessed hydrocarbons. The analysis of obtained chromatographic data was conducted using GCMS-Solution Ver. 1. 2 software (Shimadzu Corporation, Japan).
Method Participants were 170 children (93 girls) aged 6-12 years (M = 9. 25 years, SD = 1. 14). They were drawn from two elementary schools located in southeastern France. Most participants were Caucasian and came from middle-to upper-class backgrounds, although data on ethnicity and socioeconomic status were not collected. Written consent to take part in this study was given by their parents, the school's principal, and the regional supervisory school authority. The children had to solve a computerized short-form version of the standard matrices (SRPM). We selected 24 items (6 per series B to E) to represent the various rule types and degrees of difficulty of the SRPM. The task was administered on a laptop computer (15 screen with 1024 × 768 resolution) and the experiment was run using E-Prime 2 software (PST Inc.
RT, as well as individual mean Log. RTs for easy items, intermediate items, and difficult items. Items were ranked according to the item difficulty parameter, which was one minus the success rate for the whole dataset. A modulation index was also computed as the within-participant correlation between the individual RT by item and item difficulty. A participant with short RTs for easy items and longer RTs for difficult items was thus characterized by a high positive correlation reflecting high modulation. Conversely, the absence of modulation led to an index close to zero. This individual modulation index was then correlated with the children's age and total score on the short-form SRPM, as shown in Table  2. As expected, age and SRPM performance were correlated (r = 0. 45, p < 0. 01), and no correlation was found between age and overall Log.
2 The Rasch model was fitted using the eMr package  [29]  in R, which allows for maximum likelihood estimation of individual parameters. By contrast, when the difficulty of the items exceeded the ability level expected for their age, only some of the children modulated their RTs. For underachievers who performed far below expected levels (relative ability index = -3), RTs remained constant at around 10 s (9. 3 log units) whatever the items' relative difficulty. By contrast, the more difficult the items, the longer the overachievers (relative ability index = +3) spent on them, with RTs longer than 2 min (11. 7 log units) for the most difficult items. Children who performed at their expected level (relative ability index = 0) exhibited a less pronounced modulation pattern, with RTs of around 30 s (10.
S630 • OFID 2018:5 (Suppl 1) • Poster Abstracts who received VPT to VCT for surgical prophylaxis. Patients receiving other surgical prophylaxis regimens due to allergy or colonization history were excluded. Donor and recipient culture data from bronchoscopy samples were collected to determine the incidence of Pseudomonas in the 14-day post-transplant period. The secondary outcome was the incidence of post-transplant CDC-defined pneumonia. Statistical analysis was performed using SAS 9. 4 (Cary, NC). Results. One hundred patients were included in the pre-protocol group (VPT), and 65 in the post-protocol group (VCT). Pseudomonas was recovered in recipient BALs on post-op day 2-14 in 8 (8%) patients in the VPT group compared with 5 (7. 7%) patients in the VCT group (P = 1. 0). Mean time to Pseudomonas isolation was 8.
5% BSA, and 0. 01% sodium azide. Unspecific antibody binding was prevented by adding 2. 4G2 (antibody to the Fcc receptor II/III) during the staining. Dead cells were excluded by adding fixable viability dye conjugated to eFluor506 (eBioscience). A fixed amount of counting beads (123count ebeads, Thermo Fisher Scientific) was added to determine absolute cell numbers. Antibodies used for flow cytometry are summarized in Table  EV2. Samples were acquired on a LSRFortessa (4 laser, BD Biosciences) and analyzed using Flowjo Software (Tree Star, Inc). In BAL, eosinophils were gated as CD11c-CD3/19-Ly6G-CD11b hi SiglecF hi SSC-A hi , neutrophils as CD11c-CD3/19-Ly6G hi CD11b hi , B cells as CD11c-CD3/19 hi MHC-II hi and T cells as CD11c-CD3/ 19 hi MHC-II À.
Acknowledgements This work was supported by the  Flanders Research Foundation  (Grant Number  FWO13/ASP/138  to E. H. ), and  The Lung Foundation Netherlands  (Grant Number  3. 2. 11. 090FE  to M. J. v. H). The B. N. L. laboratory is supported by an  ERC   consolidator grant  ( 41D04510W ), several  FWO  project grants, a  Ghent University grant  ( GOA 01G02817 ), and an  FWO Excellence of Science (EOS)  award (Grant Number  G0G2318N ). The E. V. laboratory is supported by  ERC ,  ANR ,  Innate-Pharma ,  MSDAvenir, la Ligue Nationale contre le Cancer (Equipe labellisée "La Ligue ") and by institutional grants from  INSERM ,  CNRS ,  Aix-Marseille University  and  Marseille-Immunopole  to the CIML. The funding sources had no role in the study design, collection, and interpretation of the data or writing of the manuscript.
Twenty-four hours post-transfection, 50 mg/mL cycloheximide were added to the well for 40 hr of incubation. For WB, the ATAT1 antibody was used for the detection of ATAT1-GFP and b-actin as loading control. For fluorescence microscopy analysis of ATAT1-GFP images, nine images per well were acquired every 2 hr and for a total of 40 hr post-addition of cycloheximide and MG132 using an IN Cell 2200 microscope (GE). The remaining ATAT1-GFP signal was determined by measuring GFP signal intensity from individual cells after the subtraction of background intensity levels. Analyses were performed using IN Cell Investigator developer software with the following parameters: segmentation: sensitivity 75, kernel size 50; and post-processing: waterclamp shed, fill holes, sieve objects >100 mm.
Analysis and Statistics Data are presented as histograms of means ± SEMs. All of the experiments were performed under single-blind conditions, and the statistical analyses were generated with GraphPad Prism version 6. 0. One-way ANOVA was used to analyze axonal transport, locomotor behavior, and immunolabeling in mice and Drosophila. Two-way ANOVA was used to analyze lysosome and mitochondria percentage of moving vesicles and the ATAT1-GFP cycloheximide chase assay. For qPCR, WB, in vitro MTs-binding assay, and some immunolabeling, either an unpaired two-tailed Student's t test or a two-sided Mann-Whitney test were used (*p < 0. 05, **p < 0. 01, ***p < 0. 001, ****p < 0. 0001).
ACKNOWLEDGMENTS We thank  N. Krusy  and  C. D'Alessandro  for technical assistance. We are grateful to  M. Nachury ,  N. Perrimon , and  P. Verstreken  for sharing reagents. We thank  S. Ormenese  and  S. Freeman  for assistance at the GIGA imaging platform. We thank  E. Pichinuk  at the  Blavatnik Center for Drug Discovery in Tel-Aviv University  for facilities use and help. A. E. and M. W. are supported by the  Israel Science Foundation  (grant no. 8811688 ). L. N. is supported by the  Fonds de la Recherche Scientifique-Fonds de la Recherche Scientifique (FRS-FNRS ,  PDR DevoCortex-T. 007315 ), the  Fonds Leon Fredericq , the  Fondation Medicale Reine Elisabeth , the  Fondation Simone et Pierre Clerdent , the  Belgian Science Policy (IAP-VII  network  P7/20 ), the  Actions de Recherche Concertee (ARC)  ( ARC11/16-01 ), and the  European Research Area Network Neuron (ERA-NET) STEM-MCD.
Acknowledgements Funding: This work was supported by the  Québec Fonds Verts , the  Ouranos Consortium , the  Centre d' étude de la forêt, Natural Sciences and Engineering Research Council Discovery grants  (to E. M. and to S. C. ) and  Canada Research Chairs  (to E. M. and to S. C. ). We thank the  Bureau du forestier en chef du Québec  ( D. Pelletier ,  L. Fortier ,  J. Girard  and  L. Guérin ),  C. Périé ,  F. Lesmerises ,  R. St-Amant ,  A. M. Chubaty ,  L. Bélanger ,  L. Sirois ,  E. Landguth ,  M. Mazerolle ,  L. Parrott ,  S. Nielsen  and two anonymous reviewers for their help with the data and their processing, or with the manuscript. Ecoforestry maps and road database were provided by the  Ministère des.
Data Availability The habitat quality layers (raster layers) for each of the 24 scenarios are available at the DRYAD repository, https:// doi. org/10. 5061/dryad. n726pq6. The source code of the model presented here is available as a SpaDES module (https://github. com/PredictiveEcology/SpaDES-modules/tree/master/modules/caribou2Movements). SpaDES, or Spatial Discrete Event Simulator (https://cran. r-project. org/package=SpaDES), is an ecosystem of R-based spatial simulation models.
Densitometric analysis was performed using GeneTools software from Syngene. * P < 0. 05 and ** P < 0. 001; unpaired 2-tailed Student's t test. www. impactjournals. com/oncotarget CHOEP (cyclophosphamide, doxorubicin, vincristine, etoposide and prednisone) chemotherapy regimen, at final concentrations ranging from 100 to 300 nM. Like doxorubicin, etoposide increased miR-125b expression (Figure  6B ), showing that Topo II is involved in miR-125b regulation following doxorubicin treatment. By contrast, doxorubicin and etoposide did not affect miR-29a (Figure  6C ), a miRNA down-regulated through DNA methylation in NPM-ALK(+) ALCL cell lines  [3]. We next investigated whether the DNMT1 protein directly binds to the CpG-rich region upstream of the MIR125B1 gene using chromatin immunoprecipitation (ChIP) experiments (Figure  2A ).
ACKNOWLEDGMENTS AND FUNDING This work was supported by grants from the  "Fondation ARC pour la Recherche sur le Cancer ", n°  SFI20121205544 , the  "Fondation de France  n°Engt 201400047494 " awarded to FM; and  INCa  (projet PAIR Lymphomes) (LL). CHA was supported by a fellowship from " Fondation pour la Recherche Médicale_ ING20130526629 " and " Fondation de France_n°Engt 201400051606"; NT from "Année recherche 2014/2015 / Université Toulouse III-Paul Sabatier / Facultés de médecine Toulouse-Purpan et Toulouse-Rangueil ", and AC and NC from the " Labex TOUCAN / Laboratoire d'excellence Toulouse Cancer ". English proofreading was performed by Scientific Scripts.
naturalearthdata. com/, based on the World Data Bank dataset. We generated a grid of 1ºx1º squares that cover the earth and kept the center point of those grids that overlap with any coastline using spatstat and rgdal  (Baddeley, Rubak, & Turner, 2015; Bivand, Keitt, & Rowlingson, 2017). For each occurrence and potential habitat location, we identified the mean, maximum and minimum mean sea surface temperature and surface air temperature, and yearly ocean salinity values from BioOracle  (Tyberghein et al. , 2012)  and the monthly precipitation means from WorldClim  (Hijmans, Cameron, Parra, Jones, & Jarvis, 2005). Due to the difficulty in generating both ocean and terrestrial data points, we collected fifty randomly generated points within a 50 km radius of each occurrence point using raster and sp  (Bivand, Pebesma, & Gomez-Rubio, 2013; Hijmans, 2016) , and used its average in subsequent analyses.
| Niche shift analyses The first two axes of a principal component analysis of abiotic variables (termed the PCAenv) explained 71% of variation in climate data from all realized and potential habitats (Figure  3b , Table  1 ). The first axis (42%) was best explained by a negative correlation with mean sea and air temperatures, while the second axis (29%) was best explained by a positive correlation with among-month variation in sea and air temperature. Based on this PCAenv, we quantified niche shifts by comparing all native (Japan, South Korea, Russia, and China) versus non-native habitats. On average, non-native populations seemed to expand into habitats with colder temperatures and less seasonal variation in temperature relative to the full native range (see niche shift indicated by arrows of Figure  3c ).
ACKNOWLEDGEMENTS We thank  R. Hadfield  and  C. Sotka  for logistical support;  T. W. Greig  for use of the capillary sequencer;  N. Kollars  for help in compiling occurrence data; and  J. Byers ,  M. Fitzpatrick , and  N. Kollars  for comments. This work was supported by the  National Science Foundation  ( OCE-1357386 ;  DBI-1359079 ) and the  College of Charleston.
RESULTS The evolution of CsrBs within vibrios. In V. tasmaniensis LGP32, we identified four copies of csrB  (29). This prompted us to investigate the evolution of csrB copies in the Vibrionaceae. Differences in copy numbers in different species can result from gains or losses of csrB genes. In the case of a gain, we could envisage two scenarios to generate additional copies: they could have arisen from gene duplication events  (17) , or they could have resulted from horizontal transfers. To understand how multiple Vibrio csrB copies have evolved, we selected from the NCBI database 13 Vibrio and Aliivibrio sp. fully assembled genomes. By successive BLAST searches starting from the four copies of csrB identified in V. tasmaniensis, we established a catalogue of the csrB genes present in these genomes.
(i) A total of 38 csrB sequences from 14 species whose fully assembled genomes were present in public databases (11 Vibrio species corresponding to 7 different clades of the Vibrio genus, 2 Aliivibrio species, and 1 P. profundum species) were collected from the NCBI genome database after detection performed using BLAST repeatedly and visual inspection of the corresponding genomic regions to determine the most probable transcription start site and the Rho-independent terminator. For each copy, flanking coding DNA sequences (CDS) were examined to search for synteny conservation, with the help of Absynte (Archaeal and Bacterial Synteny Explorer; http://archaea. u-psud. fr/absynte/Default. aspx). To build the phylogenetic tree of csrB copies, csrB sequences (not including the predicted terminator) were aligned using MUSCLE (http://www.
ACKNOWLEDGMENTS We thank  Bonnie L. Bassler  and  Didier Mazel  for kindly providing plasmids and strains and  Stephanie Henry  for constructing some of the mutants used in this study. We are indebted to  Françoise Norel  for generously providing anti-S antibodies. This work has benefited from mass spectroscopy results obtained thanks to the excellent expertise of the SICaPS facility of the I2BC, supported by the  Région Ile de France  and the  Fondation pour la Recherche Médicale  (http://www. i2bc. paris-saclay. fr/spip. php?article201&langϭen). This work was supported by  Program Blanc Biodiversité ,  écologie et agronomie  ( ANR 11 BSV7 023 02  "Vibriogen" to A. J. , F. L. R. , and D. D. -G. ). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Statistical Analyses The results are presented as means (±standard errors). In the pot experiment, microbial activities measured in the planted condition are presented as the percentage relative to the unplanted condition in the same Cu treatment (control, 1 mg/kg CuO-NP or 100 mg/kg CuO-NP). We tested the effects of the CuO-NP and ionic Cu treatments on microbial and plant endpoints for each soil tested using a generalized linear model with the glm function (fitted with Gaussian or Gamma probability distribution) at the two sampling dates. We then performed post-hoc tests using the lsmeans package in the R software version 2. 3. 2 (R Core Team, 2015). We used a P < 0. 05 threshold for significance. Linear regression of microbial activities and abundances were explored and described with the Spearman correlation coefficient.
ACKNOWLEDGMENTS We thank the Serre et chambres climatiques platform ( Université Lyon1, FR BioEnviS ) for growing the plants and the  Activités Microbiennes dans l'Environnement platform  ( Université Lyon 1, UMR 5557 ) for microbial analyses. We thank  Nadège Roche ,  Julia Sanchez , and  Elise Lacroix  for their help with the plant culture, harvesting, and microbial analyses.
T his report outlines the structure of and summarizes the recommendations made at the Fifth International Conference on Reanalysis (ICR5), 1 attended by 259 participants from 37 countries, in Rome, Italy, on 13-17 November 2017. It first summarizes the conference structure. Then, the key recommendations of ICR5 are given for the five main conference topics: production, observations (data rescue and preparation), data assimilation methods, quality assurance of reanalysis, and applications in science, services, and policy making. Finally, five high-level recommendations are proposed for assisting agencies in how best to advance the field of reanalyses, which serves tens of thousands of users, via enhanced research, development, and operations. ICR5 STRUCTURE. ICR5 was the fifth in a series of international conferences for researchers, developers, and producers of reanalyses.