dataesr/scientific-paragraphs-categorization huggingface dataset:
Progressive depletion of Pkh increases the transcription of genes required for fermentation and stress responses Depletion of Pkh led to progressive accumulation of mRNA of those genes involved in carbohydrate metabolism. Among the 81 and 228 genes found up-regulated (See figure on previous page. ) Fig. 1  Gene expression changes triggered by gradual depletion of Pkh. a Number of genes found up-(empty bars) and down-regulated (filled bars) in SDP8 versus WT cells after 8 and 24 h of treatment with 100 μg/ml doxycycline. The percentage respect the total number of genes with valid expression value data are denoted in brackets. b Cluster analysis of the expression profiles caused by depletion of Pkh. Genes whose expression was found changed after treatment of SDP8 cells with doxycycline (either 8 or 24 h) when compared to wild-type cells under the same conditions were hierarchically clustered (complete linkage clustering, uncentered correlation) by means of the Gene Cluster (v.
58e-04) including CTA1, coding for catalase A, the cytoplasmic peroxiredoxin TSA1, the mitochondrial thioredoxin peroxidases PRX1, the mitochondrial Fig. 3  Depletion of Pkh affects glycogen metabolism. The complete glycogen and trehalose biosynthesis pathways, based on Yeast Biochemical Pathway Database (YeastCyc) at the SGD  [74]. Numbers indicate the -fold induction of the specified genes in SDP8 when incubated in the presence of 100 μg/ml doxycycline for 8 and 24 h when compared to CML476 wild-type cells under the same treatment. Genes considered up-regulated are denoted in red. ND: no valid data were obtained superoxide dismutase SOD2, the genes involved in the 4-aminobutyrate metabolism GAD1 and UGA2 and iii) heat-shock response (8 genes; p-value: 9. 80e-04). Changes in expression for several of the genes detected in our microarrays analysis were also verified by semiquantitative RT-PCR (Additional file 3: Figure  S1 ).
The number of genes whose expression is controlled by each transcription factor is shown. A score for each transcription factor is given by a p-value that denotes the overrepresentation of the given transcription factor targeted genes in the list of up-regulated genes relative to the regulations of that transcription factor targeted genes in the whole Yeastract database triggered by the progressive depletion of Pkh proteins in the yeast S. cerevisiae. It is worth mentioning that depletion of Pkh proteins by this strategy does not imply a stressful growth condition for the cells and that, in any case, we have compared the expression profiles of two strains cultivated in the presence of doxycycline. Furthermore, the use of the doxycycline-regulated promoter allowed us to identify the transcriptional response of Pkhdeficient cells to heat stress, an experiment that cannot be properly done by using a strain carrying a temperaturesensitive allele.
However, we cannot discard that the down-(See figure on previous page. ) Fig. 7  Transcriptional response of Pkh-depleted cells to heat shock. a Venn diagrams of the number of genes with considered up-regulated (upper panel) and down-regulated (lower panel) mRNA expression under heat sock stress in the wild-type CML476 (WT) and SDP8 strains. b The expression patterns of the wild-type CML476 (WT) and SDP8 cells treated with doxycycline for 24 h and incubated at 40 °C for 40 min were compared with those of the same cells in the absence of the heat stress. A set of 803 genes with data in both strains that are differentially expressed at least in one of the strains were hierarchically clustered (complete linkage clustering, uncentered correlation) using the Gene Cluster software (v. 2. 11) and visualized with Java TreeView (v 3.
Informatics tools The ProtParam algorithm at the Expasy server was used to estimate the protein half-life  [67]. The pre-processing tool of the Babelomics platform (http://v4. babelomics. org/ ), was used to pre-process the microarray data, obtaining only one expression value for each gene  [68]. The MIPS Functional Catalogue Database (MIPS FunCatDB)  [69] , available http://mips. helmholtz-muenchen. de/funcatDB/, was used for the functional distribution of gene lists. The Publication Enrichment tool available at the YeastMine website  [70]  was used to identified significant overlaps between customized set of genes and genes from published expression patterns. The YEASTRACT (Yeast Search for Transcriptional Regulators And Consensus Tracking; http://www. yeastract. com/) tools were used for grouping genes based on their regulatory associations with documented transcription factors  [71].
Acknowledgements We thank  J. Ariño  for critical review of the manuscript. We are also grateful to the  Servei de Genòmica i Bioinformàtica de la UAB. The excellent technical assistance of  A. Vilalta  and  M. Robledo  is also acknowledged. This work was supported by Grants  BFU2009-11593  to A. C. ( Ministry of Science and Innovation, Spain and ERDF)  and by  Europrofession Foundation (Saarbrücken)  and  BMBF Go-Bio  programme to RMB.
Flow cytometry (FACS) Cells were collected by trypsinization, washed in PGE (glucose 1 g/l in PBS-1-mM ethylenediaminetetraacetic acid (EDTA)) and fixed in 70% ethanol in PBS-Glucose-EDTA (PGE) at 4 • C for 1 h. Cells were washed twice in PGE and nuclear DNA was stained with propidium iodide (4 g/ml; Sigma, St. Louis, MO, USA) in the presence of RNase A (10 g/ml; Invitrogen) for at least 30 min. Stained cells were analyzed on a FACScalibur (Becton Dickinson, Franklin Lakes, NJ, USA) using CellQuest software. Twenty to thirty thousand cells gated as single cells were analyzed.
TLS assay The construction of single-stranded plasmids containing either a single Cyclobutane Pyrimidine Dimer (CPD) lesion (pUCTT-CPD. ss) or a unique G-AAF adduct (pUC3G3-AAF. ss) has been extensively described  (32). Primer extension assays were performed as previously described  (33). Standard reactions (6. 25 l) were performed using 10 fmol of primed single-strand DNA and an XPV cell extract (20 g) supplemented with WT or mutated Pol (0. 2 l of reticulocyte lysates). The quantification of the levels of TLS was determined using the ImageQuant TL software after phosphorimaging (GE Healthcare). The percentage of TLS was calculated as the ratio of the intensity of the bands of nonslipped TLS (TLS 0) or slipped TLS (TLS-1) to the sum of the intensity of the TLS and L-1 bands.
Material and Methods -CAD/FEA Model A three-dimensional (3D) model was developed to analyze the magnitude and distribution of the shear and tensile stress loads on the CR and dentine-bonding interface when mechanical retentions are cut into the dentine. The analysis was based on a simplified model of 3 cylinder volumes that represented each element as follows: dentine (8 mm in diameter and 2 mm in thickness), adhesive (4 mm in diameter and 10 µm in thickness), and CR (4 mm in diameter and 2 mm in thickness). These models were designed using the software CATIA (V5R16 Dassault Systèmes, Versailles, France) and saved in a neutral format (. stp) for easy export to the analysis software. For our purposes, the analysis was circumscribed to the marked area in the figure  1. Considering the geometry representing the interface, the following two experimental models were developed to simulate the different adhesion conditions: -Model with no mechanical retentions (NRM): This model considers only adhesion on a flat surface with no additional mechanical retentions (Fig.
1A ). -Model with retention (RM): This model considers in its geometry 4 cylindrical holes in the dentine surface (Fig. 1B ), each ending in a hemisphere that is 1 mm in diameter and 1 mm deep, such that the resin penetrates inside of the dentine to generate a RM effect preventing its dislodgement. The model simulation was performed by exporting the models into the finite element software Ansys Workbench v. 14 (Ansys Inc. , Canonsburg, PA, USA), and the structures for static analysis were considered isotropic, homogeneous, flexible, and linearly elastic. The elasticity modulus and Poisson coefficient were obtained from the literature  (18, 19)  (Table  1 ). Additionally, the solid cylinders of dentine and CR were meshed with SOLID185-type tetrahedral elements and the adhesive surface with quadrilateral elements and triangular SHELL181-like membranes  (20)  For the RM, 149266 elements and 29497 nodes were obtained; for the NRM, the result was a total of 129258 elements and 24945 nodes.
These two sets of data were used to calculate brain tissue volumes. All volumes were then corrected for water expansion at the time of freezing (see Method section). Brain tissue volume measured using this method was not statistically different from brain volume deduced from the weight of fresh brain sampled from age-and weight-matched animals, assuming an overall density of 1 (data not shown). This correlation provides a good index of measurement accuracy. The complete set of volume data obtained for the twenty compartments at the three developmental stages is displayed in a table see Additional file 1. It should be noted that with the exception of the ventricular system and lateral recesses of the fourth ventricle, all spaces of interest contain, in addition to CSF, arachnoid trabeculae, immune cells, and vessels traveling through the spaces before entering the brain.
Finally the data show that the size of the ventricular system remains modest at all stages. The volume of the ventricles changed only moderately between E19 and P9, with a slight decrease for the lateral ventricles, an increase for the third ventricle and no change for the fourth ventricle (Additional file 1). By contrast, the size of choroid plexuses continues to enlarge during this period. The protein content of the lateral ventricle choroid plexuses increased from 100 ± 9 to 177 ± 13 μg between P2 and P9, and that of the fourth ventricle choroid plexus increased from 69 ± 9 to 131 ± 19 μg (mean ± SD of six animals at both ages). This increase in protein content parallels the change in size of dissected tissues observed under the stereomicroscope. This suggests there is increased flow of CSF through the ventricular system, which will be further enhanced by the concurrent increase in the rate of CSF secretion by the choroidal cells.
Overall, the volume data provided in this study for twenty compartments of the rat CSF system at different developmental stages (see Additional file 1) form reference figures which can be used in future studies to better delineate the role of the fluid environment in brain developmental processes. Taking into account the total CSF volume can also help to better interpret blood-CSF permeability measurements as exemplified below. Developmental changes in blood-CSF permeability constants for sucrose used as a marker of blood-CSF barrier efficiency We measured [ 14 C]-sucrose permeability constants by sampling CSF 20 min after injection. Blood concentration continuously increased during this period, minimizing the impact of tracer back flux. To account for changes in [ 14 C]-sucrose plasma concentration over time we calculated the integrated plasma concentration-time product.
Note also the alternation of the occurrence of the shape resonances: if a shape resonance shows up for the partial wave , another also occurs for the + 2 partial wave as demonstrated by B. Gao in the case of a R -4 long range interaction  [50]. 3. Electronic structure calculations for (Alk-Alke) + molecular ions The potential energy curves, permanent electric dipole moments (PEDMs) and transition electric dipole moments are computed following the same method described in details in Ref. [51, 52, 45]. We briefly recall here the main steps of the calculations, carried out using the Configuration Interaction by Perturbation of a Multiconfiguration Wave Function Selected Iteratively (CIPSI)  [53]  package developed at "Laboratoire de Chimie et Physique Quantiques, Université Toulouse III -Paul Sabatier" (France).
2c ). Taken together, these results highlighted how unique nsSNPs in a bacterial adhesin from a broad-host range serovar contribute to bacterial-host interactions, and likely participate in host specificity. fimH variants coincide with distinct host-adapted Salmonella. Based on our findings in the broad host-range serovar Typhimurium, we hypothesized that allelic variation of fimH would also associate with host specificity in more host-adapted serovars, potentially contributing to bacterial-host interactions that drive host adaptation. Although most S. enterica strains and serovars express type 1 fimbriae and some limited studies suggested fimH-host associations  14, 17, 18  , no systematic large-scale comparative study has yet linked fimH alleles to host-associated strains or serovars. Here, we collected 1,848 individual fimH genes from 76 different serovars (Supplementary Data 7), and identified a total of 152 unique fimH sequences for 105 different allelic FimH proteins with 166 amino-acid substitution sites and 1 three-nucleotide insertion.
Methods Bacterial strain and data collection. A total of 382 Salmonella Typhimurium strains were isolated in the United States America between 1988 and 2010 from different hosts or from the environment. Human and food isolates were obtained from collections at the US Centers of Disease Control and Prevention (CDC) and the US Food and Drug Administration (FDA), respectively, whereas animal isolates were from the Salmonella Reference Center at the University of Pennsylvania (UPENN). All the Salmonella Typhimurium isolates were identified by standard serotyping methods, using O-and H-antigen agglutination, based on the Kauffmann-White Scheme  36. Isolates were grown on LB (Lennox) medium, and single colonies were incubated in LB broth overnight at 37 °C. Bacterial cells were pelleted by centrifugation (3,700g for 10 min) and DNA was extracted using the Wizard SV 96 Genomic DNA Kit (Promega) according to the manufacturer's instructions.
DNA quality and quantity were evaluated by gel electrophoresis and determined with a NanoDrop 1,000 spectrophotometer (Thermo Fisher Scientific). Genomic templates were normalized to 5 ng ml À 1 for targeted massive parallel sequencing, as described below. An additional 12 complete genomes with metadata of serotype Typhimurium were downloaded from GenBank and sequence data from 186 Typhimurium genomes were collected from the NCBI SRA database. All 580 Typhimurium isolates are listed in Supplementary Tables  3  and 4. A total of 1,268 additional individual fimH gene sequences from 76 serovars with metadata of the corresponding strains were extracted from six publications  29, [37] [38] [39] [40] [41]  as well as new sequences produced from our lab. DNA sequencing. For targeted massive parallel sequencing, primer pairs for 15 genes, including the genes for 12 fimbrial adhesins (StcD, SafD, BcfD, FimH, StbD, SthE, StdD, StiH, StfH, LpfD, StjA, PefA)  21  and 3 outer-membrane proteins (OmpA, OmpC, OmpN) were designed and synthesized (Integrated DNA Technologies, Inc.
) with 3-4 primer pairs per gene (Supplementary Table  6 ). The sequencing libraries were prepared using the Access Array system (Fluidigm South San Francisco)  14. Quality and quantity of the amplicon libraries were evaluated with a 2,100 Bioanalyzer instrument (Agilent Technologies) and NanoDrop. The libraries were pooled in equal amounts for pyrosequencing with a 454 GS FLX sequencer using Titanium chemistry (454 Life Sciences, Roche) at the DNA Sequencing Facility of UPENN. An in-house Perl script was used for sequence splitting and barcode removal. Sequence assembly and mapping were done with SeqMan (DNASTAR, Inc. ). A total of 15 genes of 382 strains were sequenced with a coverage of more than 30 and a Phred quality score of more than 40 for data analysis. For Sanger DNA sequencing, the fimH gene of 210 clinical isolates from various S.
In general, P-values less than 0. 05 indicated a statistically significant, non-random association. P-values were calculated using the right-tailed Fisher exact test (Prism, GraphPad Software, Inc. ). All proteins with less than 50 amino-acid residues were removed from the core genome and pangenome analysis. The phage genes from the Typhimurium genome were determined by PHAST  44. All the pseudogenes were assigned by original genome annotation of the 12 complete Typhimurium genomes under manual correction. A total of 186 strains of Typhimurium with SRA data produced by Illumina pairedend technology were submitted for de novo genome assembly and annotation by using CloVR  45. CloVR used both virtual machine and cloud computation technology for high-throughput data processing. All the annotated genomic data were uploaded into SEED  43  for further data storage, sequence extraction and analysis.
The 15 genes studied for all the 186 strains had quality score of more than 30. SNPfinder  46  was used to detect the SNPs for the 12 S. Typhimurium complete genomes. Population and phylogenetic analysis. DnaSP5 (ref. 47) was used to estimate several measures of DNA sequence variation within and between populations, including neutrality analysis (Tajima's D) and SNP detection. Nucleotide diversity estimates  48  and recombination analyses were carried out by using DataMonkey  49. The homoplasious SNPs, that is, SNPs due to recombination and horizontal gene transfer, were detected by using START2 (ref. 50) with a threshold of 0. 6. Statistics and association analysis. All the SNPs and their corresponding metadata were used for association studies. The Akaike Information Criterion (AIC) of the multinomial logit (logistic regression) model was used for testing the genetic association of multiple phenotypes with the 'nnet' R package  15  and the following equation : AIC ¼ À 2 Log L þ 2((k À 1) þ s), where k is the number of levels of the dependent variable and s is the number of predictors in the model.
Bacteria were added at a multiplicity of infection of 200 to 1 and allowed to interact with the cells for 1 h at 37 °C in 5% CO 2. The cells were then washed five times with PBS and lysed with 1% Triton (Sigma). The number of CFU in each well was quantified by plating serial dilutions of cell lysates on LB plates. For inhibition, bacterial binding was tested in the presence of 50 mM methyl-D-mannopyranoside (a-mm). Binding data were the results of five individual repeated experiments. Bacterial binding was compared with the binding of recombinant E. coli that expressed the FimH3 (FimH of strain AJB3) set at 100% and the binding of recombinant bacteria that expressed no fimH, set at 0%. Percentage of bacterial binding mediated by FimH allele X (X representing any specific FimH allele studied) was calculated in the following way: % bacterial binding with X ¼ (CFU X À CFU AJB3 )(CFU AJB3 À CFU DfimH ) 4 -1.
Acknowledgements The study makes use of data generated by the  DECIPHER Consortium. A full list of centres that contributed to the generation of the data is available from http://decipher. sanger. ac. uk and via email from decipher@sanger. ac. uk. We thank all the contributors for sharing their Salmonella genomic data,  Jason P. Folster  and  Jean Whichard ,  Division of Foodborne, Waterborne and Environmental Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA , for strains,  Jeff Washeleski ,  Pennsylvania Department of Health , for technical help, and  Suzanne Loret ,  Ernst Heinen  and  Guy Dandrifosse ,  University of Liege, Belgium , for their help with bovine cell cultures. We appreciate the critical reading and helpful comments on the manuscript made by  Leslie King.
This work was funded by  NIH  grant  AI098041 ,  USDA  grant  2013-67015-21285  and funds from the  University of Pennsylvania Veterinary Center for Infectious Disease  and the  Center for Host-Microbial Interactions  to D. M. S. ; X. H. , C. Z. , X. M. and J. Z. were supported by the  China Scholarship Council (CSC).
The FVJ in France are mostly fruit juices, while the consumption of vegetable juices (mostly tomato) is very low. This study used the nationally representative 2013 CCAF database  [16]  to examine the impact of FVJ consumption on dietary nutrient density in France. FVJ consumption patterns were stratified by age group and by SES. The Nutrient Rich Food (NRF9. 3) index, a published and validated nutrient profiling model  [17] , adjusted for age and gender, was the principal measure of diet nutrient density. The hypothesis was that higher FVJ consumption in France would be independently associated with higher-quality diets, after adjusting for demographic and lifestyle covariates.
CCAF Participants Dietary intake data were based on the nationally representative 2013 Comportements et Consommations Alimentaires en France (CCAF) dietary survey that was conducted by CREDOC (Centre de Recherche pour l'ÉtuDe et l'Observation des Conditions de vie, Paris, France), between October 2012 and July 2013. The quota survey sampling method took into account the geographical region, town size, participant age, household size, and socio-economic status, based on the 1999 French census. Details of participant recruitment have been published  [16]. The survey was carried out in a national representative sample of 1250 French households resident in metropolitan France. Metropolitan France refers to France itself, as opposed to overseas possessions and territories. Children were oversampled to give a national representative sample of 1000 children 3-17 years old.
Dietary Intake Data Dietary intake data were based on a seven-day dietary history interview for all household members aged 3 years old and above. For children aged <9 years old, dietary information was provided by parents or caregivers. The participants (adults and children >9 years old) completed a seven-day food survey, where respondents reported the types and amounts of all food and beverages consumed in the preceding 24-h. The participants were provided with the SUVIMAX portion size atlas, used and validated in previous research  [19]  that provided photographs of food portions along with 7 potential response options. The portion size atlas was provided in the paper format (54%) and online (46%). Reported energy intakes were compared to the estimated energy requirements (1. 55 times the metabolic rate) for age, body weight and height  [20].
Energy and Nutrient Intakes Energy and nutrient intakes were estimated using the 2013 food composition table developed by the French agency for Food, Environmental and Occupational Health & Safety (ANSES). Usual intakes of total fruit (whole fresh fruit + cooked fruit + fruit juice), whole fruit, and 100% FVJ were assessed for the entire population and for population subgroups. The term "100% FVJ" covers fruit and vegetable juices NFC (not from concentrate) and FC (from concentrate). The 2013 CIQUAL database provided nutrient values for the principal 100% FVJ juices consumed: orange, apple, grape, grapefruit, pineapple, and multi-fruit and exotic fruit (mango, coconut) as well as tomato, carrot, and multi-vegetable juice. Nectars and juice-based soft drinks were excluded. Under European and French regulations, the addition of sugars to 100% FVJ is prohibited  [21].
Although FVJ cannot contain added sugars, they do contain naturally present "free" sugars. The World Health Organization (WHO) defines free sugars  [22]  as "all monosaccharides and disaccharides added to foods by the manufacturer, cook, or consumer, plus sugars naturally present in honey, syrups, and fruit juices". The values for added sugars and free sugars in the CIQUAL database were obtained from ANSES; from published nutrient composition data, and from the nationwide online study Nutrinet Santé  [23].