dataesr/scientific-paragraphs-categorization huggingface dataset:
DISCUSSION To ensure the accurate inheritance of genetic material one needs faithful completion of replication and chromosome segregation. Our work provides insight into the replisome's robustness in vivo and into its ability to circumvent the natural Tus-ter replication barriers. We characterize the effect of the Tus-ter complex on the stability and progression of the replisome when it encounters the barrier from the nonpermissive side. Our data suggest that the CW replisome (as assessed by studying YPet-DnaN and DnaQ-Ypet foci) does not disassemble after having encountered the Tus-terC complex from the non-permissive direction, but rather remains stably bound to the DNA (or is rapidly reloaded). This result is consistent with what has been observed in vitro during a head-on collision of the E.
(left, right) The dominant mechanism of polar fork arrest by a Tus-ter complex. (left) The DNA sequences of the different ter-sites. Here the conserved G is highlighted by a light blue rectangle. (right) The crystal structures of a non-forked Tus-bound ter-site and a forked Tus-bound ter-site approached from the non-permissive direction. Here the Tus protein is depicted in light gray. Images where generated using the Protein Data Bank (PDB) files, 1ECR and 2EWJ (23, 66). DNA molecules are represented in purple and brown, while the C(6) residue is highlighted in red. (C) The strain with an ectopic origin (oriZ-dnaN-strain) (38). Here the origin of replication (oriZ) is positioned at 344 kb on the E. coli genetic map. The insertion position of a lacO operator array at 3908 kb (ori1), and a tetO operator array at 366 kb (R2) are indicated with a red and blue star respectively.
0001), glycemia (p = 0. 01), platelet count (p = 0. 04) and prothrombin time (PT) (p < 0. 0001) than patients with CHB (Table  S2 ). In the CHB cohort, 58 and 44 patients with respectively F1-F2 and F3-F4 were included. Thirty-nine out of the 103 patients were HBe antigen positive (data not shown). CHB patients with F1-F2 had lower AST (p = 0. 047), ALP (p = 0. 0002), GGT (p = 0. 001), glycemia (p = 0. 027) and triglycerides (p = 0. 035) than CHB patients with F3-F4. CHB patients with F1-F2 had higher platelet count (p = 0. 003), PT (p = 0. 011) and albumin (p = 0. 002) than CHB patients with F3-F4 (Table  1 ). In the CHC cohort, 84 patients with F1-F2 and 94 with F3-F4 were enrolled (Table  1 ). The mean age at liver biopsy was 49 years. All genotypes were represented with 51. 95%, 14. 29%, 14.
Optical density of total RNA was measured at 260 nm. From serums. Total RNAs were extracted from 400 μ l of serum (MiRvana, Life science). Since there is no reliable serum miRNA stably expressed in the serum, 5. 6 × 10 8 copies of Caenorhabdditis elegans miR-39 (cel-miR-39, Qiagen) was added to each serum sample before the extraction  20, 60. MiRNAs quantification. The miRNAs content in both liver and serum samples was analysed by Taqman RT-qPCR. Quantitative values are obtained from the crossing point (Cp), number at which the increase in the signal associated with exponential growth of PCR products begins to be detected using Light Cycler ® 480 System Software (Roche Diagnostics), according to the manufacturer's manuals. Briefly, 1 ng of the reverse transcription product was used to assess the expression of each miARNs.
Statistical analysis. Data are presented as medians and interquartile range for continuous variables and frequencies with percentages for qualitative variables. Marginal association between single variables and F3-F4 fibrosis was assessed by a Wilcoxon rank-sum test for quantitative variables and Fisher's exact test. Multiple logistic regressions were used to determine a set of variables independently associated with F3-F4 fibrosis. Variables associated with intervention at a 0. 05 level were considered in the multiple models. The model selections were performed using a backward stepwise variable algorithm and Akaike Criteria. Odds Ratio (OR) are given, with their 95% Confidence intervals (95% CI). Performance of models and markers was assessed using Area under the Curve (AUC) and its 95% CI.
Acknowledgements This work was supported by the  French National Agency for Research on AIDS and Viral Hepatitis (ANRS)  ( SF/ CB/N°1178 ) and the  ANR  through  ERA-NET Infect-ERA program  ( ANR-13-IFEC-0002-01 ). KA was supported by a grant from  ANRS  ( NM/n°824/CSS 7/AO 2012-1 ).
3), anti-B220 (RA3-6B2), anti-CD11a (2D7), anti-CD11c (N418), anti-CD18 (C71/16), anti-CD24 (M1/69), anti-CD48 (HM48-1), anti-CD49d (R1-2), anti-CD62L (MEL-14), anti-TCRb (H57-597), anti-c-Kit (2B8), anti-NK1. 1 (PK136), anti-F4/80 (BM8), anti-Gr1 (RB6-8C5), anti-Ter119 (TER-119), anti-c-Kit (2B8), Annexin V, anti-Bcl-2 (3F11) and Hamster IgG1 Isotype control (A19-3). Biotinylated antibodies were revealed with Streptavidin-Allophycocyanin (APC) or Phycoerythrin-Cy5 (PE-Cy5). For surface staining all primary and secondary antibodies were diluted at 1:300 in PBS containing 0. 1% bovine serum albumin (BSA) and 0. 01% sodium azide. Cell death analysis of DN4 cells cultured overnight in medium was performed by Annexin V (1:100) staining following manufacturer's instruction (BD Pharmingen). Flow cytometry was performed according to standard protocol using FACSCalibur and CellQuest or FlowJo software.
, with the exception of H3K27ac (ab4729; Abcam). DNA was extracted from immunoprecipitated chromatin and was used to prepare sequencing library using TrueSeq ChIP-seq Library Preparation Kit (Illumina Inc. , USA) according to manufacturer's instructions, and sequenced on a Genome Analyzer II sequencing platform (Illumina Inc. , USA). Data processing, including input subtraction and wig files generation was performed as previously described  43. Small RNA-Seq. Total RNA was extracted from DN cells isolated from Rag2 À / À cells using TriZol Reagent (Life Technologies, USA). Total RNA of 10 mg was fractionated by TBE-Urea PAGE to isolate RNA fragments ranging from 15 nucleotides to 70 nucleotides length. These size-selected small RNAs were used to prepare sequencing library using Small RNA-Seq Library Preparation Kit (Illumina Inc.
, USA) according to manufacturer's instructions. Libraries were then sequenced on a Genome Analyzer II sequencing platform (Illumina Inc. , USA). The RNA-Seq data used is accessible in gene omnibus under the accession number GSE44578. OP9-DL1 co-culture assays and in vitro cultures. 4 Â 10 4 sorted WT or Vav-CreNfatc1aA fl/fl DN1-DN4 cells were co-cultured on monolayers of OP9 stromal cells expressing the Notch ligand delta-like 1 (OP9-DL1) in X-vivo 20 medium supplemented with rhFLT3 ligand (5 ng ml À 1 ) and rhIL-7 (1 ng ml À 1 ) for 4 days. Subsequently, thymocytes were analysed for differentiation into DP cells by flow cytometry. In vitro cultures of sorted DN1-DN4 cell populations or CD4 þ T cells were performed either in medium (RPMI-1640, 10% FCS) only or with CsA (100 ng ml À 1 ), 8-CPT-cAMP (50 mM), Forskolin (Fsk; 100 mM), CD48 (5 or 0.
Acknowledgements We thank  C. Linden  ( University of Wuerzburg ) for excellent FACS sorting,  Ilona Pietrowski  and  Doris Michel  for luciferase reporter assays,  D. Kioussis  ( Medical Research Council, National Institute for Medical Research, London ) for Vav-Cre mice,  J. Liu  ( University of Wuerzburg ),  A. Waisman  and  K. Reifenberg  ( University of Mainz ) for help in generating Nfatc1P2 fl/fl and Nfatc1-eGfp-Bac-DE2 tg mice. This work was supported by an ' EMBO Short Term Fellowship ' (ASTF No:  93-06 ), and a  'PostDoc Plus Funding ' grant ( Graduate School of Life Sciences; GSLS, University of Wuerzburg ) to A. K. P. , and by the  Deutsche Forschungsgemeinschaft (DFG)  grants  TRR52  (S. K. H. and E. S. ) and the  Wilhelm-Sander Foundations  (E. S. ).
aureus genes essential to infection in abscess and osteomyelitis models  [33, 34]. Among the intricate array of staphylococcal virulence factors known to contribute to osteomyelitis so far, Hla is the only one that: measurably influences local and systemic outcomes, even in the presence of PVL  [10] ; is common to virtually all S. aureus lineages  [35] ; and is already targeted by a monoclonal antibody being tested in a clinical trial (study identifier NCT02296320) to treat S. aureus infection  [36]. In this context, it seems reasonable to designate Hla as a more promising target than PSMs to treat severe CA-MRSA osteomyelitis, in agreement with recent conclusions drawn from a mice model of skin and soft tissue infection  [20].
ACKNOWLEDGEMENTS The authors would like to thank  David Martin  and  Matthew Nichols  for valuable advice in constructing the MNH figure. DH is supported by the  Swiss National Science Foundation  (SNSF). JPK acknowledges support from the  ERC  advanced grant LIDA and from  CNRS. MJ acknowledge support by the  Science and Technology Facilities Council  [grant number  ST/L00075X/1 & ST/F001166/1 ].
Acknowledgments We thank  E. Andrés ,  P. Cámara ,  C. Strickland-Constable ,  G. Torroba ,  D. Waldram  and specially  D. Marques  for useful discussions and comments. This work was partially supported by  EPLANET ,  CONICET ,  PICT-2012-513  and the  ERC Starting Independent  Researcher Grant 259133-ObservableString. G. A. thanks the  Instituto de Fisica Teorica (IFT UAM-CSIC) in Madrid  for its support via the  Centro de Excelencia Severo Ochoa Program  under Grant  SEV-2012-0249. G. A. and M. G. are grateful to the  Mainz Institute for Theoretical Physics (MITP)  and C. N. and A. R thank the A. S. ICTP for hospitality and partial support during the completion of this work.
Study Participants The trial enrolled patients aged 35 years or older with medically optimized emphysema (Figure  1 ). Participants were former smokers who recently completed pulmonary rehabilitation and/or were participating in exercise maintenance. Self-reported ethnicity and race were collected as fixed categories per Clinical Data Interchange Standards Consortium standards to appropriately adjust lung function and to account for any potential differences by treatment. Key inclusion criteria included postbronchodilator forced expiratory volume in the first second (FEV 1 ) of 45% predicted or less, total lung capacity (TLC) of more than 100% predicted, and residual volume (RV) of at least 225% predicted. The RV threshold was lowered to at least 175% predicted following enrollment of 169 patients to address the effectiveness and safety of endobronchial coils in a broader patient population.
Effectiveness Outcomes All end points compared baseline data vs results at 12 months after first treatment. Participants were not blinded, although walk and spirometry measurements were obtained using a blinded assessor. The primary effectiveness variable was the difference in absolute change in 6-minute walk distance between baseline and 12-month visit. Secondary end points included 6-minute walk distance response, defined as a 25-m minimal clinically important difference (MCID)  16  in 6-minute walk distance; mean percent change in FEV 1 (MCID, 10%)  17  ; and mean absolute difference in St George's Respiratory Questionnaire score (range, 0-100, with higher scores indicating worse quality of life). ] [20] [21]  Other exploratory effectiveness end points included St George's Respiratory Questionnaire response, defined using a 4-point or greater score reduction as the MCID  22  ; mean absolute difference in RV (MCID, 0.
05). (j-l) Fear-conditioning experiment. Animals were placed in a context and presented with an electrical shock (arrow) paired once with an auditory cue (Tone); data were analyzed using a two-way ANOVA (genotype, time) with n = 12 per genotype. (j) Cumulative freezing time counted during the 3-min conditioning period. There were no significant differences between genotype (F(2,33) = 1. 27; P not significant) and all genotypes showed a progressive increase in freezing after the Tone-shock pairing. (k) Cumulative freezing time plotted over time during the 3 min of the context recognition test. There was a significant effect of genotype (F(2,33) = 3. 30; *P o0. 05) and Nes-cre VEGFR2 lox/ -knockout mice showed reduced freezing time compared with heterozygotes and controls (*P o0. 05, Bonferroni post hoc test).
ACKNOWLEDGMENTS We thank  Annabelle Bouchardon  and  Amandine Durand-Terrasson  from the  Centre Commun de Quantimétrie (University Lyon 1 ) and the  Microscopy Platform (Grenoble Institut for Neurosciences)  for assistance. We are grateful to  Carmen Ruiz de Almodovar ,  Fanny Mann ,  Alain Buisson  and  Farida El Gaamouch  for helpful discussions. This study was supported by grants from the  Institut National de la Santé et de la Recherche Médicale , the  Lyon Neuroscience Research Center  (to CM) and from the  Deutsche Forschungsgemeinschaft (CRC1080)  (to AA-P and HJL), EXC  115 ,  EXC147  and  SFB 834  (to AA-P),  Gutenberg Research College (GRC)  (AA-P); PDR and MB were supported by a doctoral research contract from the  French Ministry of Higher Education and Research  and LM by a doctoral research contract  ADR ARC2  from the  "Région Rhône-Alpes ".
When eigenvectors of the genomic relationship matrix are used as regressors with fixed regression coefficients, e. g. , to account for population stratification, their removal from G does matter. Removal of eigenvectors from G can have a noticeable effect on estimates of genomic and residual variances, so caution is needed. Concepts were illustrated using genomic data on 599 wheat inbred lines, with grain yield as target trait, and on close to 200 Arabidopsis thaliana accessions.
CASE STUDIES WITH WHEAT AND ARABIDOPSIS DATA Wheat A publicly available wheat data set was employed to investigate several issues associated with removing markers or eigenvectors from G; including impact on maximum likelihood estimates of variance components. The wheat data were downloaded from package BGLR (Pérez and de los Campos 2014); these data have also been used by, e. g. ,  Crossa et al. (2010) ,  Gianola et al. (2011)  and  Long et al. (2011). The data originated from several international trials conducted at the International Maize and Wheat Improvement Center (CIMMYT), Mexico. There are 599 wheat inbred lines, each genotyped with 1279 DArT (Diversity Array Technology) markers and planted in four environments. The target trait was yield in environment 1. Here n ¼ 599 and p ¼ 1279.
GWAS: OLS vs. GLS analyses We compared SMR-OLS vs. GLS in the wheat data at two specified values of the variance ratio or, equivalently, of genomic heritability. Marker genotypes were centered to have a mean of zero, marker by marker, for all 1279 DArT polymorphisms; phenotypes were already standardized to have a null mean and variance 1. For OLS, computation was done using the lm function available in the R package (http://www. r-project. org/). In GLS, the genomic relationship matrix used was as follows: 1) with X being the matrix of centered markers, we formed G ¼ XX9=ðp dÞ ¼ fg ij g; here, d is the mean of the diagonal values of XX9=p and g ij measures similarity in state between individuals i and j. 2) We then formed V Ã ¼ G h 2 g 1 2 h 2 g þ I, and, for the purpose of examining sensitivity, set genomic heritability in the GLS analysis to h 2 g ¼ ð0:10; 0:25Þ; representing an increase in the signal to noise ratio when going from 0.
2015)  Effect of removing a single marker from G on genomic heritability Since our analytical developments assume that marker removal does not affect the partition of variance, we measured the extent to which this assumption held using the wheat data set. The likelihood was formed under y $ Nð0; Gs 2 g þ Is 2 e Þ. Here, we took G ¼ XX9=ð dpÞ, where d is the mean of the diagonal elements of XX9 (markers were centered) and estimated the two variance components by maximum likelihood using an eigen-decomposition algorithm of Gs 2 g þ Is 2 e (e. g. ,  Janss et al. 2012 ) that renders computation fast. Estimates obtained with all markers included in G were s2 g ¼ 0:60560:102and s2 e ¼ 0:53960:04; genomic heritability was 0. 529. Convergence was assessed and confirmed by beginning the iteration from different sets of starting values.
MDS inputs can be squared Euclidean distances between objects, in our case the p 2 dimensional genotypes of the 599 wheat lines or the 199 Arabidopsis accessions. There were 179,101 and 19,701 Euclidean distances between rows of X (or of G) in the wheat and Arabidopsis data sets, respectively. In MDS, distances are rotated into a matrix whose eigen-decomposition yields the K-dimensional coordinates, while preserving distances in some best fit sense. There are two types of MDS: classical and nonmetric. In classical MDS, differences and ratios between distances are preserved. In nonmetric scaling, only the order of the distances is relevant. The best fitting K is found at the eigenvalue in which an elbow of an eigenvalue decay plot is observed, or can be derived from a metric called STRESS. Here, squared differences between observed and fitted distances are summed over the two dimensions, and expressed relative to the sum of all observed squared distances.
The middle and bottom panels show STRESS (nonmetric MDS) for models of different dimensionality. In the wheat data set, a satisfactory fit (STRESS = 5-10%; Kruskal 1964b) was obtained with K ¼ 5 2 10 dimensions, but at least 70 dimensions were needed to fit the Arabidopsis distances reasonably well. The implication is that population structure in wheat may not be accounted properly with a single PC. In the Arabidopsis collection, the topology was less sharp, suggesting an aggregation similar to the family structure typically encountered in animal breeding or in humans (see Supplementary Figure  4  in  Atwell et al. 2010). If the latter is the case, use of a kinship matrix in the GWAS may suffice, without the need of fitting principal components as fixed effects. In wheat, on the other hand, a kinship matrix would account for similarity among lines, but not for differences in mean among the few strata suggested by Figure  4  and Figure  5.
ACKNOWLEDGMENTS de los Campos is thanked for providing the function for maximum likelihood estimation of variance components using an eigendecomposition. Part of this work was done while D. G. was a  Hans Fischer Fellow  at the  Institute of Advanced Study, Technical University of Munich, Germany  and a Visiting Scientist at the  Institut Pasteur de Montevideo, Uruguay. Research was partially supported by a  United States Department of Agriculture   Hatch grant  ( 142-PRJ63CV ) to D. G. , by project  URUGENOMES ,  ATN/KK-14584-UR  funded by  Inter-American Development Bank , and by the  Wisconsin Agriculture Experiment Station. M. I. F. was supported by  Agencia Nacional de Investigación e Innovación, Uruguay , project  PD_NAC_2013_10964. This work was supported by the  German Research Foundation  and the  Technical University of Munich  in the framework of the  Open Access Publishing Program.
Context. Changes in the spectral solar irradiance (SSI) are a key driver of the variability of the Earth's environment, strongly affecting the upper atmosphere, but also impacting climate. However, its measurements have been sparse and of different quality. The ''First European Comprehensive Solar Irradiance Data Exploitation project'' (SOLID) aims at merging the complete set of European irradiance data, complemented by archive data that include data from non-European missions. Aims. As part of SOLID, we present all available space-based SSI measurements, reference spectra, and relevant proxies in a unified format with regular temporal re-gridding, interpolation, gap-filling as well as associated uncertainty estimations. Methods. We apply a coherent methodology to all available SSI datasets.
Our pipeline approach consists of the pre-processing of the data, the interpolation of missing data by utilizing the spectral coherency of SSI, the temporal re-gridding of the data, an instrumental outlier detection routine, and a proxy-based interpolation for missing and flagged values. In particular, to detect instrumental outliers, we combine an autoregressive model with proxy data. We independently estimate the precision and stability of each individual dataset and flag all changes due to processing in an accompanying quality mask. Results. We present a unified database of solar activity records with accompanying meta-data and uncertainties. Conclusions. This dataset can be used for further investigations of the long-term trend of solar activity and the construction of a homogeneous SSI record.
Introduction Changes in the spectral solar irradiance (SSI) strongly affect the upper atmosphere, but also impact climate. In particular, a consistent dataset of SSI changes serves as an input for climate models  (Lean et al. 1995; Ermolli et al. 2013; Thuillier et al. 2014)  as well as a central parameter for space weather predictions. These models are in need of datasets spanning several decades of continuous and radiometrically accurate measurements. However, satellites measuring SSI usually have a life span of a few years up to a decade, before instrument degradation, equipment failure, or end of mission financing stops the data flow. Not a single instrument has measured SSI for two or more solar cycles, and even for those instruments that have measured an entire solar cycle, e. g. SUSIM, 1  instrument stability is not sufficient to properly assess the existence of long-term trends.
To obtain homogeneous SSI datasets, our approach is thus as follows. We develop a coherent methodology to estimate the precision and stability for all datasets, and we evaluate the uncertainties induced by each method. We rescale all data into a common time grid with daily resolution and remove nonphysical values. We take advantage of spectral coherency to estimate missing data in one wavelength band from a combination of other bands that display a similar temporal variability. We detect instrumental artifacts by taking advantage of an autoregressive model and combine the model with proxies as a qualitative indicator. Finally, we use proxy interpolation to handle data gaps. Our final product consists of three datasets per instrument: first, the original, unified dataset converted to common units including independent precision estimates; second, a homogenized and stratified ''close-to-original'' dataset that does not change any data except for re-gridding in time, accompanied by independent uncertainty estimates and quality flags; and third, a ''best-estimate'' dataset where missing data and identified outliers have been replaced by values obtained from proxy-based models.
This systematic approach to attain homogeneous SSI datasets in a unified format is part of the First European Comprehensive SOLar Irradiance Data Exploitation project (SOLID, http://projects. pmodwrc. ch/solid), whose objective is to attain a long-term SSI composite of daily resolution covering the satellite space-age era by utilizing all available data. This can be used by modelers of the Earth atmosphere and climate, researchers in stellar physics, planetary science or astrobiology, and as a cross-comparison for other models and instruments. Subsequently, Section 2 provides, after a short historic overview of SSI measurements, a description of all data incorporated in SOLID. Section 3 presents our uncertainty estimations. Section 4 details our pipeline approach, consisting of the pre-treatment of the data (Sect.
4. 1), the interpolation of missing data (Sect. 4. 2), the re-gridding of the data (Sect. 4. 3), the outlier detection (Sect. 4. 4), and the proxy-based interpolation (Sect. 4. 5). Section 5 specifies the content, availability, and the future of the SOLID database, while Section 6 concludes our paper. For better readability, we include most of our tables in Appendix A, followed by a formal description of the data format in Appendix B and our algorithms in pseudocode in Appendix C.