dataesr/scientific-paragraphs-categorization huggingface dataset:
Self-Measured Blood Pressure At the first visit, patients are provided with an HBP monitor (Tel-O-Graph ® , I. E. M. GmbH, Stolberg, Germany). Patients are trained in its use, and are instructed to measure HBP in triplicate twice daily after 5 min of seated rest at the same times each day (e. g. , 8: 00 am and 8: 00 pm). For each scheduled office visit, patients are instructed to bring their HBP monitor with them. Immediately following the measurement of AOBP, patients will then take SMBP in triplicate before site staff returns to the room. If a patient does not bring their HBP device, then only AOBP will be taken during that visit (SMBP data will be recorded as missing).
To minimize patient risk, laboratory assessment will be performed regularly through the trial, including serum creatinine, eGFR, and potassium measurements. An initial decrease in renal function is expected following the addition of spironolactone to a background regimen of 3 antihypertensive agents that include a diuretic and renin-angiotensin blocking agent. Investigators are recommended to follow KDOQI guidelines for the detection and management of early decreases in eGFR. According to KDOQI recommendations, significant declines from baseline in eGFR > 30% may require dose adjustment or discontinuation of spironolactone  [29]. An important consideration for the trial design was the use of 24-h ambulatory blood pressure monitoring. While we recognize the value of this technique, we reasoned that given frequent titrations of the drug and downstream blood pressure measurements, we may have missing data if we required frequent 24-h ambulatory blood pressure monitoring.
Acknowledgments Writing and editorial support services were provided by  Michael P. Bennett  of  Impact Communication Partners, Inc. , and funded by  Relypsa, Inc. , a  Vifor Pharma Group Company. Relypsa Inc. , a  Vifor Pharma Group Company  acknowledges the support of the  National Institute for Health Research Clinical Research Network (NIHR CRN ). Am J Nephrol 2018;48: 172-180 DOI: 10. 1159/000492622.
fancm-1 and bnaC. fancm-1 were sequenced on the same single lane while the corresponding double homozygous and WT F2s were sequenced on a single lane each. Raw short-read data are available in the NCBI BioProject PRJNA432890. Mutations were identified and annotated using the "homemade" pipeline MutDetect described in  Girard et al. (2014). Briefly, sequences were aligned against the reference B. napus genome sequence  (Chalhoub et al. , 2014)  allowing up to 2 mismatches and 1 indel per read. Alignments were cleaned up according to the Genome Analysis ToolKit (GATK) recommendations  (McKenna et al. , 2010). Raw variants were then filtered according to both quality and coverage criterions (quality> 100 and Depth>2). Homozygous variants detected on all samples were considered as natural polymorphisms between Darmor-bzh (reference) and Tanto accessions and were removed.
fancm_1-1 mutants and two of their WT siblings (Bna. FANCM_1-1) (Supplementary Figure  S2 ). Sequencing quality control process showed that around 70% of the reads were mapped (Supplementary Table  S4 ) covering around 80 % of the genome reference with a minimum depth of 3x (Supplementary Figure  S8 ). Using conservative criteria, we detected ∼20 763 EMS mutations in the sequenced plants (Supplementary Table  S4 ; Supplementary dataset 1), which was consistent with mutation density within BnaA. FANCM and BnaC. FANCM. ∼23 % (4714/20763) of those mutations were found in CDS and led to non-synonymous substitutions (including splice variant and non-sense mutations) in a total of 4,438 genes (∼4% of total gene number; Supplementary dataset 2). A subset of those genes (270 genes with 298 mutations; ∼8%) constituted homoeologous pairs (as established in  Chalhoub et al.
, 2014) ; in most cases  (193/298, 64%) , the mutations that we found in both copies of a given homoeologous pair were non synonymous or stop gained mutations (Supplementary dataset 2). None of these EMS mutations were found in the orthologs of genes that encode most other known anti-CO proteins (e. g. , MHF1, MHF2, FIGL1, FLIP, RMI1, TOP3α, RECQ4a/b) in A. thaliana (Supplementary Table  S5 ). Finally, overall all four sequenced plants, only 66 mutations targeting 30 homoeologous pairs were detected in the homozygous state at both loci in at least one plant. The risk of confusion between the effect of fancm mutations and that of another pair of homoeolog is thus very low. We then converted a subset of the EMS induced SNPs into genetic markers and compared crossover frequencies between mutant and WT F2 plants in the corresponding F3 progeny (Table  1 ; Supplementary dataset 3).
thaliana  (Crismani et al. , 2012). Looking to the future, new methodologies that increase the chance of finding nonsense mutations should be favored. This may involve the use of next-generation sequencing to "enable a deep search for mutations in targeted loci"  (Tsai et al. , 2011 ; see also  Gilchrist et al. , 2013)  or the development of sequenced mutant populations  (Krasileva et al. , 2017 ; see also http://revgenuk. jic. ac. uk/search-databases/ for B. rapa). As a matter of fact, screening the RAPTILL population for mutations along the entire coding sequence of BnaC. FANCM would have reduced the chances of detecting no nonsense mutations from ∼42 to ∼3. 5%. However efficient the new TILLING approaches may be, it remains that the use of highly mutagenized populations raises concern about the risk of mistaking the consequences of a background EMS mutation for a mutation in the targeted gene.
ACKNOWLEDGMENTS We would like to thank  Mathilde Grelon ,  Raphael Mercier ,  Fabien Nogue ,  Christine Mézard  and three reviewers for critical reading and discussion of the manuscript. We would also like to thank  Marie Gilet  for plant care, and  Aurélie Chauveau  and  Elodie Marquand  from  EPGV group  for producing the DNA libraries and processing the raw data, respectively. This work was funded through the  ANR  project  ANR-14-CE19-0004 -CROC  and with the support of  INRA BAP division  (Appel à Manifestation d'intérêt 2012; HyperRec). The IJPB benefits from the support of the  LabEx Saclay Plant Sciences-SPS  ( ANR-10-LABX-0040-SPS ). We want to acknowledge  CEA-IG/CNG  for supporting the  INRA-EPGV group  for QC of DNA and Illumina high throughput sequencing, especially  Anne Boland ,  Marie-Thérèse Bihoreau  and their staff.
We also want to acknowledge  Julien Schmidt at AELRED  and  Fran Robson at RevGenUK  for performing the TILLING experiment in B. napus and B. rapa, respectively and the plant genetic resources center BrACySol for providing seeds for B. napus cv Tanto. RevGenUK (https:// www. jic. ac. uk/technologies/genomic-services/revgenuk-tillingreverse-genetics/) was supported by the  Biotechnology and Biological Sciences Research Council, UK  ( BB/F010591/1  and  BB/I025891/1 ). ABlary was funded by a  Young Scientist Contracts (CJS)  from  INRA. AG is funded by the  Marie-Curie COMREC  network  FP7 ITN-606956. AL was funded by the  International Outgoing Fellowships   PIOF-GA-2013-628128 POLYMEIO.
A profile hidden Markov model (HMM) was constructed from the alignment corresponding to each element using the hmmbuild utility from the HMMER package (version 3. 1b1)  (32). This model was used to query the zebrafish Zv9 assembly (danRer7) using nhmmer (version 3. 1b1) with default parameters. All alignments were retained. The human and zebrafish matches were then realigned using LASTZ (version 1. 02. 00; -seed = match4 -hspthresh = 500 -gappedthresh = 500; HoxD55 scoring matrix; http://www. bx. psu. edu/~rsharris/lastz/). Only pairs scoring above 2000 were retained. GWAS-SNPs embedded specifically in gene regulatory regions conserved to zebrafish are expected to lie next to the orthologous gene(s) in both human and zebrafish. This property is known as synteny. Ensembl gene transcripts and ortholog mappings (Ensembl release 75)  (31)  were used to identify syntenic alignments.
Transcription factor binding site prediction We have curated an extensive library of monomer and dimer transcription factor binding motifs, each represented as a position weight matrix, from the UniPROBE  (33) , JASPAR  (34)  and TransFac  (35)  databases, secondary UniPROBE motifs, motifs from published ChIP-seq datasets and from other primary literature as described previously  (36). Sequences with a MATCH (37) score of at least 0. 8 to a position weight matrix (PWM) were overlapped with GWAS SNPs.
ACKNOWLEDGEMENTS We are grateful to  Drs Laure Bally-Cuif ,  Thomas S. Becker  and  Ben A. Barres  for critical reading of the manuscript. We thank  Drs Jeffrey L. Goldberg ,  Steven Sloan ,  Louis Leung ,  Aaron Wenger ,  Geetu Tuteja ,  Harendra Guturu ,  Evan G. Cameron  and  Ana Meireles  for insightful discussions and help. We are grateful to  Drs Neil C. Chi ,  David Traver ,  Nathan Lawson  and  William S. Talbot  for gift of reagents. We would also like to thank the  Stanford CSIF Imaging platform. Authors contributions: J. H. N. , C. C. C. and G. B. designed the computational study, wrote the algorithms and analyzed the genomic data. R. M. and P. M. designed and analyzed all the in vivo experiments. R. M. performed all the in vivo experiments with technical support of G. S. and C.
Samples (2 nM DNA + 15 nM protein) were mixed and incubated for 2 minutes before deposition into the mica. Samples were deposited for 2 min and next rinsed with 3 ml of deionized water, dried with nitrogen and kept in a desiccator until imaging. AFM Images were obtained with a Nanoscope IIIa microscope (Veeco, France) equipped with a type-E scanner and operating in tapping mode in air using AC160 TS Olympus cantilevers (Olympus Corporation, Japan) as described  23. Image analysis was carried out using MATLAB (MathWorks, USA) and distributions of the localization of proteins on DNA were represented as relative frequency histograms with bin sizes of 50 nm. The relative frequency of SpoIIIE at SRS or DNA ends (F) was quantified as the ratio between the number of SpoIIIE located at the first bin f x ( ) 1 and the total number of proteins bound to DNA ∑ = f x ( ) i n i 1 : = ∑ = F f x f x ( ) ( ) (1) i n i 1 1 The absolute error of the relative frequency estimation for the first bin displayed in Fig.
Acknowledgements We acknowledge support for this research from the  Human Frontiers Science Program (Career Development   Award 00017/2009  to M. N. ), the  Institut National de la Santé et la Recherche Médicale  (D. I. C. ) and the  European Research Council  (Starting Grant  260787  to M. N. ), the  Ministry of Science, Technology and Productive Innovation (MINCyT)/ECOS-Sud France  ( A16B01  to O. C. and M. N. ). O. C. is career researcher from  Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) of Argentina. Fluorescence anisotropy experiments were performed at the  Biophysics facility of the Centre de Biochimie Structurale (CBS)  funded by the  French Infrastructure for Integrated Structural Biology (FRISBI ,  ANR-10-INBS-05 ) and  France-BioImaging  ( FBI ,  ANR-10-INBS-04-01 ).
Acknowledgements This work was supported by  La Ligue  contre le cancer, the  Centre National de la Recherche Scientifique  and the  Institut Pasteur. BB was funded by  La Ligue contre le Cancer. SS is funded by the  ITN PolarNet Marie Curie  grant and is part of the  Ecole Doctorale Frontières du Vivant (FdV)  - Programme Bettencourt. We would like to thank members of the  SEM lab  for support and discussion, as well as  JB Manneville  for stimulating discussion and careful reading of the manuscript. We thank  E. M. Vallés ( Institut Curie ),  Carsten Janke  ( Institut Curie ),  Bruno Goud , ( Institut Curie ), and  Philippe Chavrier  ( Institut Curie ) for reagents and helpful discusions. We gratefully acknowledge  JY Tinevez  and  A Salles  and the  Imagopole of Institut Pasteur (Paris, France ) as well as the  France-BioImaging infrastructure network  supported by the  French National Research Agency  ( ANR-10 -INSB -04 ; Investments for the Future) and the  Région Ile-de-France  (program Domaine d' Intérêt Majeur-Malinf  for the use of the Elyra microscope.
Dried peptides were resuspended with 10 μL 0. 1% TFA mixed with 1:10 matrix solution (5 mg α-cyano-4-hydroxycinnamic acid in 50% ACN, 3% TFA) and spotted in quadruplicate onto a polished steel MTP 384 MALDI plate. MALDI-TOF-MS analysis was performed using a Bruker spectrometer (Autoflex III Smartbeam®) equipped with a 200 Hz pulsed nitrogen laser emitting at 337 nm. The extraction voltage was 20 kV and all spectra were recorded under delayed extraction conditions in the reflectron mode, improving mass accuracy and resolution. Spectra were also acquired with the automated and deflector mode (400 Da) and each spectrum represents an average of 4000 single laser shots. The search and identification of global modifications were performed using Biotools® software (Bruker Daltonics GmbH). Biotin-switch Assay -Cells (5.
Quantitative RT-PCR Total RNA was extracted from cells using Trizol (Invitrogen). 500 ng of RNA were reverse transcribed into cDNA using M-MLV Reverse Transcriptase, randoms primers and RNAse inhibitor according manufacturer's protocol (Promega). cDNA was quantified by real-time PCR with Sybr Green PCR Master mix (Invitrogen) on a 7500 fast system (Life technologies). Standard reaction volume was 20 µL and contained 10 µL Sybr Green mix, 2µL cDNA template, 125 nM of primers. The thermal cycling conditions were composed of a denaturation step at 95°C for 10 min, followed by 40 cycles of denaturation at 95°C for 15 s, primer annealing/extension at 60°C for 1 min. The final step was a 60°C incubation for 1 min. All reactions were performed in triplicate. mRNA abundance was calculated according to the change-in-cycling-threshold (ΔCt) method and data represented relatively to reference gene mRNA (β-actin).
Immunohistochemistry Human colon carcinoma samples were obtained from Centre Georges François Leclerc (CGFL), Dijon, France. TNFa immunohistostaining was examined in tissue sections collected from biopsy versus surgery following neoadjuvant therapy. Immunostaining method for human TNFa has been set up on human amygdala tissue used as positive control (data not shown). Tissue sections were deparaffinized, rehydrated and antigens retrieved. Following blocking of endogenous peroxidases, tissue sections were blocked and incubated overnight at 4°C with primary rabbit anti-TNFa antibody (1/100). Tissue sections were washed and incubated with secondary antibody ImmPress anti-rabbit (Vector labs), after which, sections were incubated with Novared (Vector labs) and counterstained with Harris' hematoxylin solution (Leica) and mounting for imaging.
Taxon and data sampling Eighteen sequences published by Buyck et al. [3]  and Lebel et al. [16]  for M. furcata, M. ochricompacta, M. stenophylla and M. zonaria were retrieved from GenBank (Table  1  Sequences produced in the present study are in bold. Two ITS copies were obtained from XHW2844 and DPL4293 by cloning respectively. https://doi. org/10. 1371/journal. pone. 0205840. t001 eleven M. furcata-like specimens, two of M. zonaria  [19]  and two of M. roxburghiae from central and southern China, three of M. aurantiophylla from New Caledonia, six of M. furcata and four of M. ochricompacta from central-southern and southeastern USA (Arkansas, Mississippi, Texas), and one of an undescribed species from eastern Australia were sampled to amplify the ITS region and 28S and rpb2 genes. In the DNA dataset of Lebel et al.
[16] , only ITS and 28S were sequenced for M. stenophylla and the ITS sequences were incomplete. We amplified the complete ITS region and rpb2 gene for four of the six specimens and one additional specimen of M. stenophylla collected from Tasmania, Australia (TL2462, MEL) to cover a broader geographical distribution. The samples/data used in this study covered all previously described species of Multifurca and included five holotypes (M. orientalis, M. pseudofurcata, M. zonaria and two new species described below) and two epitypes (M. furcata and M. stenophylla). In addition, we retrieved three ITS sequences from GenBank by BLASTn: KP071201 labeled as R. japonica (from a Malaysian sample), FJ656009 from a New Caledonian sporocarp sample by Prin et al. (unpublished) and KR364125 from a Chinese sample labelled as Multifurca sp.
[24]. These three sequences were included in the ITS dataset. To test if the monophyly of Multifurca could still be retrieved after adding newly introduced taxa, seven species of Lactarius, 11 of Lactifluus and eight of Russula were added to construct a phylogeny. These taxa represented the various subgenera of these three genera based on the phylogeny of Russulaceae and DNA data published in former literatures  [11, 24, 25] (S1 Fig). After testing monophyly of the genus, we reduced the outgroup sampling to infer internal relationships within Multifurca.
Alignments and molecular phylogenetic analyses Alignments were made using the online version of the multiple sequence alignment program MAFFT v7  [32] , applying the L-INS-I strategy and manually adjusted in BioEdit  [33]. To test if potential ambiguous sites in the ITS alignment would add noise to the phylogenetic analyses, we used different sets of parameters, from conservative to tolerant to select sites in Gblocks v0. 91b  [34]  and compared the generated Maximum Likelihood (ML) trees and the ML Bootstrap Proportions (ML-BP) from each parameter set with the 28S and rpb2 trees and corresponding ML-BP. When testing the reciprocal monophyletic relationships of Multifurca, Lactarius, Lactifluus and Russula, only 28S and exons of rpb2 were used. For the subsequent analyses, we kept the alignable intron of rpb2 and used the three loci.
In the concatenated ITS-28S-rpb2 dataset, we used duplicate sequences of 28S and rpb2 for the ITS copies of XHW2844 and DPL4293 respectively and removed the GenBank-retrieved sample xp2-20120922-01 of M. pseudofurcata because it has only ITS sequence (KR364125) that is identical with some of our sequences. The ITS, 28S and rpb2 alignments are deposited in TreeBASE as S21024. To test for combinability between the ITS, 28S and rpb2 genealogies, we conducted ML bootstrap and Bayesian analyses on individual datasets sampling only the taxa for which the three loci were available. Phylogenetic conflict was assumed to be significant when two different relationships (one monophyletic and the other non-monophyletic) for the same set of taxa were both supported with ML-BP � 70% and posterior probability of Bayesian Inference (BI-PP) � 95%.
Phylogenetic analyses were conducted using ML in RAxML v7. 2x  [35]  and BI in MrBayes v3. 2. 6  [36]. The dataset rpb2 was partitioned as follows: first and second codon positions, third codon position and intron. The ITS-28S-rpb2 combined dataset was partitioned as follows: ITS, 28S and the above three partitions for rpb2. ML analyses were conducted applying the Rapid Bootstrapping algorithm with 1000 replicates, followed by an ML tree search. For BI analyses, the best-fit models were selected using MrModeltest  [37]. The BI analyses were conducted using four runs with four chains each for one million generations sampling one tree every 100 th tree. Runs were inspected to make sure the average standard deviation of split frequencies went below 0. 01 and effective sampling sizes were > 200 in Tracer v1.
Biogeographical analysis We followed with minor modifications the methods of Dentinger et al. [42]  and Feng et al. [43]  to estimate the divergence times and infer the center of origin of Multifurca. Specifically, we used 28S and rpb2 datasets composed of 26 Multifurca and 36 outgroup taxa (S2 Table ). Rhizopus oryzae Went & Prins. Geerl. (Mucoromycotina) was used to set the time of the most recent common ancestor (tMRCA) of Ascomycota and Basidiomycota, four species to represent the major clades of Ascomycota and 31 species representative of the major clades of Basidiomycota  [44, 45]. We included Bondarzewia montana (Quel. ) Singer, Echinodontium tinctorium (Ellis & Everh. ) Ellis & Everh. , Stereum hirsutum (Willd. ) Pers. , Gloeopeniophorella convolvens (P. Karst. ) Boidin et al. , four species of Russula, three of Lactarius and four of Lactifluus to cover the genetic diversification of the russuloid clade and the sibling genera of Multifurca  [1, 11, 24, 44, 46].
The 26 samples of Multifurca were selected to cover the genetic differentiation of the genus as displayed by the ITS, 28S and rpb2 sequences. In order to refer to the geological times of Mycena-like and Rhizopogon-Suillus-like fossils  [47, 48] , we included Mycena aurantiidisca (Murrill) Murrill, M. galericulata (Scop. ) Gray, Rhizopogon nigrescens Coker & Couch and Suillus spraguei (Berk. & M. A. Curtis) Kuntze [formerly as S. pictus (Peck) Kuntze] to represent the possible phylogenetic position of Mycena and the suilloid clade  [49, 50]. For the rpb2 alignment, homogeneity of translated proteins was referred to improve the nucleotide alignment. The only intron of rpb2 was excluded from analyses. BEAST 1. 8. 0  [51]  was used to estimate divergence times. To produce the executable xml file by BEAUTi (implemented in BEAST), we set parameters as follows: 28S and rpb2 datasets were set as two partitions, with substitution and molecular clock models unlinked and trees linked; taxa were constrained to monophyletic sets by referring to the SSU+28S+rpb2 or nrDNA+rpb2+ef1a phylogenies of fungi  [44, 52] , the multi-gene phylogenies of Lactarius  [46] , Lactifluus  [24]  and Russula  [11]  and our three-locus phylogeny of Multifurca; Following the outcomes of model selection, GTR+I+G model was used as the substitution and site heterogeneity model and best frequencies were set as estimated; a lognormal relaxed clock was used for molecular clock analysis; Yule process was used as speciation for tree priors; ucld.
mean of the 28S and rpb2 datasets were set to 0. 033, with upper value = 1. 0 and lower value = 0; for fossil calibration, we set mean = 575 Ma with a standard deviation of 38. 26 Ma for the tMRCA of Ascomycota and Basidiomycota, inferred from the estimated time range of 500-650 Ma of the stem base of Ascomycota  [53]  based on the well-preserved ascomycetes fossil Paleopyrenomycites  [54, 55]. The reason why we selected this more ancient time origin instead of the more recent one of 452 Ma inferred by previous studies  [56, 57]  is that the distribution of Multifurca in the South Pacific seems to suggest a Gondwana affinity and an earlier origin will be in favor of testing such an assumption. Two independent runs were conducted in BEAST for 20 million generations. Logfiles of the runs were inspected in Tracer v1.
org. The online version of this work is archived and available from the following digital repositories: PubMed Central and LOCKSS. In comparison with the ITS dataset, the 28S and rpb2 alignments lack three samples, Multifurca sp 2676, K18C of M. aurantiophylla and xp2-20120922-01 of M. pseudofurcata due to unavailability of the other two loci (Table  1 ). All the samples of Multifurca have the same length of intron in rpb2, except that LPT1093 (M. pseudofurcata) is three base pairs shorter. Heterozygous loci in the rpb2 dataset are much more common than in the ITS and 28S datasets: among the 202 polymorphic sites of Multifurca, 69 sites are degenerated.
Phylogenetic relationships The three ITS datasets with sites selected by conservative to tolerant parameters in Gblocks produced similar topologies (trees not shown). The dataset produced by the most conservative setting gave less resolved topology among the samples of M. furcata, M. mesoamericana, M. orientalis and M. pseudofurcata and among M. aurantiophylla, M. australis and M. zonaria and produced the lowest support values on nearly all the branches. In contrast, the support values produced by the dataset selected by the tolerant setting and un-Gblocked dataset are more comparable with that by the 28S and rpb2 datasets. It seems that the ambiguous sites in the ITS alignment did not cause much noise in the phylogeny and based on this we decided to use the original ITS dataset for further analyses.