dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion The Stroke Riskometer TM is comparable in performance to two widely used stroke risk scoring systems. The variation found in our study may be due to several factors. The higher R 2 values for ARCOS are explained by the high number of stroke outcome data available. Many variables required for the QStroke algorithm were not available within the ARCOS data set (such as rheumatoid arthritis, chronic kidney disease, Table  2 ) therefore it is likely that the QStroke risk scores we observed under-estimate stroke risk, particularly amongst males in ARCOS. A large proportion of females in ARCOS were classified as high risk in both Stroke Riskometer TM and QStroke scoring (>50%, Table  5 ). Conversely, the Rotterdam study had a more complete data set of variables required for the QStroke algorithm calculation (Table  2 ), however this appears to have led to over-estimation of the stroke risk amongst females (Fig.
In addition, the app offers a higher level of interactivity via sending direct reminders to the smartphone that is always on hand when needed. Moreover, the availability of the app on the smartphone app stores that has global reach, and vast consumer base of various age groups allows wide range of consumers to benefit from the stroke risk assessment tool and allows the crowdsourcing of large research database. Finally, users who are at increased (even slightly increased) risk are provided with ways to reduce their risk of stroke according to their individual risk profile and recommended to seek medical attention. This could rapidly transform epidemiologic research and monitoring of health status of individuals, especially in the area of chronic NCD  (17). Current risk scores will inevitably become outdated with improvements in clinical outcomes and data recording and changes in population demographics  (56).
With the Lite version of the Stroke Riskometer TM being made freely available globally on both iOS and Android smartphones and users invited to partake in a large-scale study we will have the potential to amass a large database. Ethical approval for the study has been received. Anonymous data from individuals who consent to participate in the study will be collected and securely stored at study coordinating centre (AUT University, NZ). The aim of these planned epidemiological studies based on the Stroke Riskometer TM will be to generate a global, population-specific stroke and NCD risk scoring system. We will further assess the Stroke Riskometer TM in a cohort study to establish the efficiency of the algorithm and assess if the new collections of recommendations are useful for motivating users to actively reduce their risk of stroke.
Acknowledgements The contributions of the inhabitants, general practitioners, and pharmacists of the Ommoord district to the  Rotterdam Study , as well as contributions of study participants, general physicians, neurologists and health service providers of the NZ and Russian studies are gratefully acknowledged. We thank  Professor Peter Sandercock  ( The University of Edinburgh, UK ), Associate  Professor Chris Bullen ,  University of Auckland, NZ  for their contribution in the project design and comments on early version of the manuscript.
2007 (Miller et al. , 2013)) , the details of the calibration and systematics of which are shown and discussed in  Heymans et al. (2012). The data processing closely follows the procedures outlines in  Erben et al. (2009 Erben et al. ( , 2013)). Specific procedures applied to the CS82 imaging will be described in  Erben et al. (2014, in preparation). In our work, the source galaxies are selected with magnitudes iAB < 23. 5, signal-to-noise ν > 10, weight w > 0 and FITCLASS= 0, where w represents the inverse variance weight accounting for the intrinsic ellipticity distribution of the source galaxies and FITCLASS is the object classification provided by LENSFIT. We obtain the photometric redshifts for our source galaxies from overlapping multi-color data of Sloan Digital Sky Survey. We further remove source galaxies with photometric redshift z < 0.
(12) Since the lensing signal of the stellar component is much smaller than that from dark matter subhalo, we ignore this component for simplicity. The model is therefore described by 5 free parameters: the host halo mass, M ; the projected halo-centric distance rp; the subhalo mass M sub ; the subhalo characteristic density ρ 0,sub ; and the subhalo scale radius r s,sub. For simplicity, the concentration of the host halo is fixed using the concentration-mass relation of  Neto et al. (2007). We also ignore the center-offset here because it does not affect the lensing signal significantly. As in L13, we fit the data using a Monte Carlo Markov Chain (MCMC) method provided by the COS-MOMC package  (Lewis & Bridle 2002). The best-fit results are shown in the right-hand panels of Fig. 1. In order to illustrate the typical uncertainties and degeneracies among the various parameters, Figs.
Based on observations obtained with  MegaPrime/MegaCam , a joint project of CFHT and CEA/DAPNIA, at the  Canada-France-Hawaii Telescope (CFHT) , which is operated by the  National Research Council (NRC)  of  Canada , the  Institut National des Science de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France , and the  University of Hawaii. The Brazilian partnership on CFHT is managed by the  Laboratrio Nacional de Astronomia (LNA). This work made use of the CHE cluster, managed and funded by  ICRA/CBPF/MCTI , with financial support from  FINEP  and  FAPERJ. We thank the support of the  Laboratrio Interinstitucional de e-Astronomia (LIneA). We thank the  CFHTLenS team  for their pipeline development and verification upon which much of this surveys pipeline was built.
Background: The ethanol-producing bacterium Zymomonas mobilis has attracted considerable scientific and commercial interest due to its exceptional physiological properties. Shuttle vectors derived from native plasmids have previously been successfully used for heterologous gene expression in this bacterium for a variety of purposes, most notably for metabolic engineering applications. Results: A quantitative PCR (qPCR) approach was used to determine the copy numbers of two endogenous double stranded DNA plasmids: pZMO1A (1,647 bp) and pZMO7 (pZA1003; 4,551 bp) within the NCIMB 11163 strain of Z. mobilis. Data indicated pZMO1A and pZMO7 were present at ca. 3-5 and ca. 1-2 copies per cell, respectively. A ca. 1,900 bp fragment from plasmid pZMO7 was used to construct two Escherichia coli -Z.
The membrane blots were visualized chemiluminescently using SuperSignal West Pico Chemiluminescent Substrate (Pierce Biotechnology, Thermo Scientific, USA; cat. #34079), capturing images using a Bio-Rad ChemiDoc XRS instrument (Bio-Rad, USA). The plasmid sequences pZMO1A and pZMO7 were deposited to the NCBI GenBank database with the accession numbers NC_019198 and NC_019300, respectively.
Sequence analysis of pZMO7 (pZA1003) Plasmid pZMO7 has two predicted coding DNA sequences (CDS): pZMO7_01 (978 bp) and pZMO7_02 (1,449 bp). The pZMO7_01 CDS encodes a 326 aa replication initiation protein (Rep) [GenBank: YP_006962143], which belongs to the Rep_3 superfamily (pfam01051). The pZMO7_02 CDS encodes a 483aa mobilase/replicase protein (Mob) [GenBank: YP_006962142], which belongs to the relaxase/mobilisation nuclease domain family (pfam03432). The region between the mob and rep genes on pZMO7 (positions 424 to 699) contains the predicted plasmid replication origin (ori). As may be seen in Figure  1  and Additional file 3, the rep [positions 699 (ATG) to 1679 (TAA)] and mob [positions 3524 (ATG) to 424 (TAA)] genes are orientated in the same direction. Putative promoter start sites predicted using a Neural Network Promoter Prediction (NNPP) programme  [44]  suggest that the transcription of both the rep and downstream mob genes are driven by a single promoter.
2 ± 0. 1 when the rep gene was targeted, and was 1. 4 ± 0. 1 when the mob gene was targeted. In analogous experiments, the PCN of pZMO1A was found to be 5. 0 ± 0. 2 using the primer pair that targeted the rep gene, and was 5. 3 ± 0. 4 using the primer pair that targeted a predicted non-coding region of the plasmid. This data correlated closely with the estimates of relative pZMO1A and pZMO7 plasmid abundances determined using geldensitometry (see above). The consistent nature of the PCN values obtained indicated that both of the respective pairs of qPCR primers had equivalent target specificities and amplification efficiencies. We next used qPCR to investigate whether the PCNs of pZMO7 and pZMO1A in cultured Z. mobilis NCIMB 11163 cells varied considerably during the different phases of growth (Additional file 5).
mobilis, without apparent genetic (structural) alteration upon prolonged culture or repeated subculture. Our data suggests that there is direct competition between the native pZMO7 plasmids and recombinant pZMO7-derived shuttle vectors for access to the replication-related machinery within the NCIMB 11163 strain. This hypothesis is consistent with the previously-proposed competition between native pZMO2 and recombinant pZMO2-derived plasmids (e. g. pDS212) in the CU1 Rif2 strain  [20]. However, this competition for plasmid replication appears to be largely absent in the ATCC 29191 and CU1 Rif2 strains. Homologues of the Rep_3 superfamily replicase protein [pfam01051] encoded by pZMO7 do not appear to be present in plasmids belonging to any Z. mobilis strain sequenced to date, including ATCC 29191, ATCC 31821 and ATCC 10988.
These were the pyruvate decarboxylase (PDC), which catalyzes the decarboxylation of pyruvate, an intermediate in the fatty acid cycle glyceraldehyde-3phosphate dehydrogenase (G3P), which catalyzes the dehydrogenation of glyceraldehyde-3-phosphate, another intermediate in this cycle hydroxymyristoyl-ACP dehydratase (FabZ), which catalyzes the dehydration of short chain beta-hydroxyacyl-ACPs and long chain saturated and unsaturated beta-hydroxyacyl-ACPs); as well as and holo-acyl carrier protein synthase (AcpS) proteins  [50] , which is involved in the transfer of phosphopantetheine to ACP. To date, only the FabZ-AcpP and AcpS-AcpP protein binding associations have been described in the Database of Interacting Proteins (DIP)  [51] , STRING  [52] , or the Prolinks databases  [53]. However, it should also be noted that we did not detect additional protein interactions that were previously observed in E.
The DnaK chaperone protein is induced in response to cellular stresses such as hyperosmotic shock, and plays important roles in the replication of chromosomal and phage DNA  [56]. Elongation factors Ts and Tu work together, modulating the translation of proteins at the ribosome  [57]. Only the interaction between CTP synthase and KdsA is included in the current versions of the above protein-protein interaction prediction databases. It is conceivable that the other putative protein interactions may be due to functional interplay between DNA replication, translation and lipopolysaccharide biosynthesis within Z. mobilis. However, additional analyses, e. g. reciprocal protein binding interaction experiments are required to verify this speculation. There have been relatively few literature reports analyzing protein expression patterns in Z.
Acknowledgements We are grateful to  Prof. Constantin Drainas  and  Dr. Hideshi Yanase  for providing us with Z. mobilis strains and plasmids. We also acknowledge the technical assistance of  Mr. Alan Wong  and  Ms. Becky Cheung , and thank  Dr. Tianfan Cheng  for his help with the Western blotting experiments. We dedicate this paper to the life and work of  Prof. Constantin Drainas.
Another large Swedish study  (Navas-Acién et al, 2002)  involved linkage of cancer registry data with census data from 1960 and 1970 to determine occupation, and used a Swedish job-exposure matrix to estimate exposure. This study, however, found some evidence of an association with "possible" exposure but not with "probable" exposure to solvents. Despite the large sample size in the INTEROCC study the prevalence of exposure to chlorinated hydrocarbons was extremely low with only one case ever exposed to a chlorinated hydrocarbon. We were unable, therefore, to assess risk associated with exposure to Methylene chloride, perchloroethylene, 1,1,1-Trichloroethane or trichloroethylene, however the exposure prevalence was adequate for the other solvents. The recent US study  (Neta et al, 2012)  using expert assessment to estimate exposure found no evidence of an association between occupational exposure to chlorinated hydrocarbon solvents and meningioma.
Acknowledgements We would like to thank  Timo Kauppinen  of the  Finnish Institute of Occupational Health  for allowing us to use and modify the FINJEM as well as sharing his valuable expertise on the exposure assessment committee in the company of  Nils Plato  of the  Karolinska Institute in Stockholm. Jordi Figuerola  and  Rodrigo Villegas  of CREAL have been the backbone of the team in cleaning and preparing the data for analysis. The authors would like to thank  Avital Jarus-Hakak (Israel), Louise Nadon (Canada), Florence Samkange-Zeeb (Germany), Anne Sleeuwenhoek (UK) , and  Hélène Tardy (France)  who coded occupations and assisted in the data clean-up. We are grateful to  Drs Bruce Armstrong  (Australia),  Mary McBride  (Canada),  Maria Blettner  (Germany),  Joachim Schüz  (Germany),  Alistair Woodward  ( New Zealand ) and  Patricia McKinney (U.
Funding This work was funded by the  National Institutes for Health (NIH)  Grant No. 1R01CA124759-01. Coding of the French occupational data was in part funded by  AFSSET (Convention N°   ST-2005-004 ). The INTERPHONE study was supported by funding from the  European Fifth Framework Program, 'Quality of Life and Management of Living Resources'  (contract  100 QLK4-CT-1999901563 ) and the  International Union against Cancer (UICC). The UICC received funds for this purpose from the  Mobile Manufacturers' Forum and GSM Association. In Australia , funding was received from the  Australian National Health and Medical Research 5 Council  ( EME Grant   219129 ) with funds originally derived from mobile phone service licence fees; a  University of Sydney Medical Foundation Program ; the  Cancer Council NSW  and  The Cancer Council Victoria.
In New Zealand , funding was provided by the  Health Research Council, Hawkes Bay Medical Research Foundation , the  Wellington Medical Research Foundation , the  Waikato Medical Research Foundation  and the  Cancer Society of New Zealand. Additional funding for the UK study was received from the  Mobile Telecommunications, Health and Research (MTHR) program , funding from the  Health and Safety Executive , the  Department of Health , the  UK Network Operators  ( O2 ,  Orange ,  T-Mobile , Vodafone, '3') and the  Scottish Executive.
2004 ). However, the long-term monitoring of the UV irradiance is a major challenge. Measurements must be carried out in space, where instruments suffer from aging, degradation, and signal contamination particularly severe in the EUV and FUV spectral range  (BenMoussa et al. 2013). The first observational missions began in the early 1960s with some sporadic measurements, but it is only recently that continuous monitoring of the complete UV spectrum is available with the launch of two satellites: TIMED in 2002 for the EUV spectral range  (Woods et al. 2005)  and SORCE for the FUV and MUV parts  (Rottman 2005). The data in the 27-115 nm range come from the EUV Grating Spectrograph (EGS), which is part of the Solar Extreme Ultraviolet Experiment (SEE) on board TIMED (Thermosphere Ionosphere Mesosphere Energetics and Dynamics).
Since the solar reflected component represents 90% of the signal, the error on the solar flux becomes critical: an error of 1% on the flux can give rise to an error of at least 10% on the  estimation of the airglow and precipitation contributions, which contribute to planetary upper atmosphere and auroral processes. This error is in fact enhanced since the Uranus data are faint and thus noisy. If the solar absolute flux data are less accurate than a few percent, the absolute values deduced from this study are uncertain. This forces the question: Is the detection of the auroral event reported in  Barthélemy et al. (2014)  significant? Studies of the spectral shape of the additional emissions could give interesting additional information. However, the error bars when looking at the spectral component are much larger than in the case of integrated intensity.
It is therefore not unexpected that mutants displaying CF hypersensitivities include genes that affect trafficking of proteins or surface carbohydrate homeostasis, including chitin deposition and biogenesis. Genes implicated in the susceptibility to both CF and azoles include those encoding the calcineurin subunits Cna1 and Cnb1 and the PKC pathway components Wsc1 and Slt2. These results confirm that both pathways are necessary for a response to both drug classes and are consistent with data in many fungi showing the synergistic action of calcineurin inhibitors and azoles or CF  [36, 81, 84, 114, 115]. Comparison of azole-sensitive, AmB-sensitive and CF-sensitive mutants show that only a small number of gene deletion strains are susceptible to all three or to at least two compounds, which is consistent with their distinct mechanism of action.
Although gene synteny has been largely conserved between pathogenic an non-pathogenic yeasts such as C. glabrata and S. cerevisiae, extensive rewiring of signaling pathways generated distinct and species-specific functions for seemingly orthologous genes. Indeed, our work clearly demonstrates that comparing and predicting drug resistance or virulence phenotypes for C. glabrata based on data from even related yeasts requires extensive experimental verification and the use of loss-offunction approaches. This fungal pathogen deletion collection will pave the way for these future efforts.
Primer design and generation Oligonucleotide sequences for generation of the deletion cassettes and strain verification were automatically designed, using a custom-written Perl script called PrimerList (W. Glaser, unpublished data). PrimerList utilizes Bioperl to read and process nucleotide sequences and uses the EMBOSS  [130]  programs eprimer 3 and stssearch to find suitable primersets. For PCR-based generation of knock-out constructs, upstream and downstream fragments for genomic recombination were chosen to have a size between 450 and 550 nucleotides. 5959 (forward) and 3939 (reverse) primers were chosen to have a length of 20 to 30 bp, a GC content between 30 and 60% and a melting temperature of 50uC64uC with a GC clamp. 5939, 3959 primers were chosen to have a length of 20 to 30 bp plus the 20 bp constant overlap sequence (Figure  1 , Table  S3 , 'barcode sequence sheet'), a GC content between 30 and 60% and a melting temperature of 50uC64uC.
Strains with increased biofilm fitness had a relative biofilm fitness at least two standard deviations above the average fitness. Strains with decreased or increased biofilm fitness were further evaluated by performing a biofilm assay in quadruplicate for each of two independent isolates. Data obtained for the 58 candidate strains were compared to those obtained for wild type isolates (96 independent values) using the Wilcoxon test. A p value below 0. 01 was considered as indicative of a significant difference with the wild type strain. In this assay, a yak1D mutant was found significantly impaired in biofilm formation while a sir3D mutant showed significantly elevated biofilm production as previously shown  [75]. Figure  S4  Deletions with altered fitness under planktonic or biofilm growth conditions.
The OD 600 was determined in a microplate reader after 24 h and 48 h of incubation at 30uC. Each strain was tested in triplicates and mean values normalized to the untreated control were plotted against the antifungal concentration of fluconazole (A) and voriconazole (C). The IC 50 was calculated by nonlinear regression (curve fit), using GraphPad Prism for fluconazole (B) and voriconazole (D). Shown are data of 24 h measurements. Bars denote standard deviations. (TIF) Figure S6 Susceptibilities of C. glabrata mutants to AmB. AmB-susceptible strains identified in the primary robotic screening were subjected to IC 50 determination. Overnight cultures were grown to an OD 600 of 1. 0 and a microdilution assay carried out in YPD to determine IC 50 for AmB (A) as described in Materials & Methods.
The OD 600 was determined in a microplate reader after 24 h and 48 h of incubation at 30uC. Each strain was tested in triplicates and mean values normalized to the untreated control were plotted against the antifungal concentration. The IC 50 were calculated for each mutant by nonlinear regression (curve fit), using GraphPad Prism (B). Shown are data of 24 h measurement. Bars indicate standard deviations. (TIF) Figure S7 Sensitivity of C. glabrata deletion strains to cell integrity stressors. Deletion strain sensitivities were tested against CF, CW, CR, and 42uC in liquid culture and on plates. (A) Growth susceptibilities of C. glabrata strains to CF. Susceptible strains identified in the primary robotic screenings were subjected to IC 50 determination. Overnight cultures were grown to OD 600 of 1.
0 and a microdilution assay was carried out in YPD to determine IC 50 as described in Materials & Methods. The optical density (OD) of each well was determined at 600 nm on a microplate reader after 24 h and 48 h of incubation at 30uC. Each strain was tested in triplicates and mean values normalized to the untreated control were plotted against the antifungal concentration. The IC 50 was calculated by nonlinear regression (curve fit), using GraphPad Prism. Shown are data of 48 h measurement. Bars denote standard deviations. (B) Confirmation of CF sensitivity on plates. Strains were spotted in serial dilutions on synthetic medium supplemented with 120 ng/ml caspofungin (CF) and growth was monitored over 3 days at 30uC. (C) Congo Red (CR), heat and Calcofluor White (CW) sensitivity on plates.
(DOC) Table  S3  Summary of auxotrophic C. glabrata deletion strains generated in the HTL and his3 backgrounds derived from the clinical isolate strain ATCC2001. Sheet 1: deletion strains + corresponding barcodes. Independent transformants of all generated gene deletion strains are listed with corresponding UP and DOWN tags, position in storage plates, number corresponding to the individual biological replicate (IBR#) for a targeted gene (e. g. the second of three independent replicates for CAGL0A01133g has IBR #2) and the nourseothricin marker used. All data can be searched online under: http://funpath. cdl. univie. ac. at. (Sheet 2: barcode sequences only). Bar-codes used as unique genomic tags in C. glabrata deletion strains. 2696 upstream and downstream barcodes were used for every set of 96 gene deletion strains.
These can be amplified from constant regions (U1+U2; D1+D2) identical in every deletion strain. Strains labeled with BM or BG carry individual barcodes and were made in the histidine auxotrophic strain derived from ATCC2001. The reference strain in the HTL background carries a unique barcode not used for any other strain. Barcode sequences were adopted from the systematic S. cerevisiae gene deletion project (http://www-sequence. stanford. edu/group/ yeast_deletion_project/deletions3. html). (XLS) Table  S4  Summary of the phenotypic screening results of the C. glabrata deletion collection. The table shows all deletion mutants obtained and their corresponding phenotypes. For heat stress, CF, CR, CW and NaCl data the degree of growth inhibition was scored from 5 (wild type) to 0 (no growth).