dataesr/scientific-paragraphs-categorization huggingface dataset:
Masson's trichrome staining demonstrated a extracellular matrix proteins fibres deposit in tumours formed by BxPC- 3-cadh-1 þ /cadh-3 þ , BxPC-3 cadh-1 þ /cadh-3 À , and CRCM110 (Figure  6B ). However, the presence of extracellular matrix proteins fibres was strongly reduced in cells that do not express cadherin-1. We then immunostained type I collagen. As observed on Supplementary Figure  S6 , type I collagen represents the main compound of the extracellular matrix proteins fibres stained by Masson's trichrome. Overall, our data suggest that cadherin-1 expressing malignant cells are able to drive type I collagen organisation in the tumour. To confirm these observations, cells were orthotopically implanted into the pancreas of nude mice. Three weeks after the implantation, pancreas weights were measured to evaluate tumoural growth.
Isolation and identification of strain Strain Marseille-P2915 T 's first growth was obtained in April 2016 on 5% sheep's blood-enriched Columbia agar medium (bioMérieux, Marcy l'Etoile, France) under aerobic conditions at 37°C. Once isolated on pure culture, proteomic analysis was carried out with MALDI-TOF MS as previously described  [15, 16]  using a Microflex spectrometer (Bruker Daltonics, Bremen, Germany). Strain Marseille-P2915 T spectra was thus obtained, imported into the MALDI BioTyper software (version 3. 0, Bruker) and processed by standard pattern matching (with default parameter settings) against the main spectra of 7567 bacteria. The comparison with the BioTyper database spectra enabled the rapid matching of the analysed species with those present in the database. The resulting score, if >2, enabled the identification at the species level, while a score of <1.
7 did not enable any identification. To obtain the 16S rRNA sequence of strain Marseille-P2915 T , PCR analysis was performed using a GeneAmp PCR System 2720 thermal cycler (Applied Biosystems, Bedford, MA, USA) as previously described  [17]. The sequencing step was performed on an ABI Prism 3130xl Genetic Analyser capillary sequencer (Applied Biosystems). Chromas Pro 1. 34 software (Technelysium, Tewantin, Australia) was used to fix the sequences, and a BLASTn (Basic Local Alignment Search Tool) search  [18]  was performed against the National Center for Biotechnology Information (NCBI) database (default parameters, uncultured/environmental sample sequences excluded). The rpoB gene sequence of strain Marseille-P2915 T was obtained using the 1730_F and 3700_R primers as previously described  [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19].
Phylogenetic analysis On the basis of the BLAST research results, 16S rRNA reference sequences (http://www. bacterio. net/streptococcus. html) of the closest species with standing in nomenclature were downloaded from NCBI. Because there is no officially recognized reference for rpoB, gene sequences were downloaded directly from the NCBI database after the BLASTn search. Sequences were then aligned using Muscle v3. 8. 31 with default parameters, and phylogenetic inferences were obtained using the maximum-likelihood method with 1000 bootstrap replicates within MEGA6 software.
Oxidase (Becton Dickinson, Franklin Lakes, NJ, USA) and catalase assays (bioMérieux) were done separately. Fatty acids analysis. Cellular fatty acid methyl ester (FAME) analysis was performed by gas chromatography mass spectrometry (GC/MS). Two samples were prepared with approximately 40 mg of bacterial biomass per tube collected from several 5% sheep's blood-enriched Columbia agar plates. FAMEs were prepared as described by Sasser  [20]. GC/MS analyses were carried out as previously described  [21]. FAMEs were separated using an Elite 5-MS column and monitored by mass spectrometry (Clarus 500-SQ 8 S, PerkinElmer, Waltham, MA, USA). A spectral database search was performed using MS Search 2. 0 operated with the Standard Reference Database 1A (National Institute of Standards and Technology, Gaithersburg, MD, USA) and the FAME mass spectral database (Wiley, Chichester, UK).
Genome annotation and comparison Open reading frames (ORFs) were predicted using Prodigal (http://prodigal. ornl. gov/) with default parameters. However, the predicted ORFs were excluded if they spanned a sequencing gap region. The predicted bacterial protein sequences were searched against the GenBank  [22]  and Clusters of Orthologous Groups (COGs) databases using BLASTP. The tRNAs and rRNAs were predicted using the tRNAScan-SE  [23]  and RNAmmer  [24]  tools, respectively. Signal peptides and number of transmembrane helices were predicted using SignalP  [25]  and TMHMM  [26] , respectively. Mobile genetic elements were predicted using PHAST  [27]  and RAST  [28]. ORFans were identified if their BLASTP E-value was lower than 1e-03 for an alignment length greater than 80 amino acids. If alignment lengths were smaller than 80 amino acids, an E value of 1e-05 was used.
1); Streptococcus pneumoniae strain R6 (AE007317. 1); Streptococcus dentisani strain 7747 (CAUK00000000. 1)) was estimated by average genomic identity of orthologous gene sequences (AGIOS) software  [12]. Overall, this software combines two other software packages: Proteinortho  [32]  (to detect orthologous proteins between genomes compared two by two, then to retrieve the corresponding genes) and the Needleman-Wunsch global alignment algorithm (to determines the mean percentage of nucleotide sequence identity among orthologous ORFs). To evaluate genomic similarity within the strains, we also performed digital DNA-DNA hybridization (http://ggdc. dsmz. de/), which exhibits high correlation with DNA-DNA hybridization  [33].
Phylogenetic analysis After three failed identification attempts with MALDI-TOF MS, the reference spectrum of strain Marseille-P2915 T (Fig. 1 ) was entered in our database and its 16S rRNA sequenced. The 16S rRNA comparison showed a sequence identity of 99. 0% with Streptococcus dentisani strain 7747 T and 98. 8% with Streptococcus tigurinus strain AZ-3a T (Fig. 2 ). Because the 16S rRNA phylogenetic analysis did not distinguish within different species belonging to the Streptococcus mitis group, the rpoB gene was sequenced, resulting in a 92. 6% sequence identity with the closest Streptococcus with an available rpoB sequence, Streptococcus infantis strain ATCC 700779 T (Fig. 3 ). A gel view comparing the spectrum of strain Marseille-P2915 T with other Streptococcaceae species is shown in Fig.
1(b ). The Streptococcus timonensis strain Marseille-P2915 T 16S rRNA accession number from European Molecular Biology Laboratory (EMBL)-European Bioinformatics Institute (EBI) is LT576411. The MALDI-TOF MS reference spectrum is available online and in the public domain (http://www. mediterranee-infection. com/article. php?laref=256&titre=urms-database).
64 Genes with paralogues (E value: 1e-25) 170 8. 61 Genes associated to hypothetical proteins 426 21. 58 Genes larger than 5000 nucleotides 6 0 COGs, Clusters of Orthologous Groups database; NRPS, nonribosomal peptide synthase; ORF, open reading frame; PKS, polyketide synthase.
18 Amino acid transport and metabolism F 72 3. 64 Nucleotide transport and metabolism H 57 2. 88 Coenzyme transport and metabolism I 50 2. 53 Lipid transport and metabolism P 64 3. 24 Inorganic ion transport and metabolism Q 18 0. 91 Secondary metabolites biosynthesis, transport and catabolism R 105 5. 31 General function prediction only S 90 4. 55 Function unknown - 753 38. 14 Not in COGs COGS, Clusters of Orthologous Groups database. a Total is based on the total number of protein-coding genes in the annotated genome.
64, Issue 2 (Special Issue), pp. 189-222 then, in the case of non-stationarity of our series, for co-integration), and verify the stability of our VAR models. The software used is R (R Development Core Team 2015) and its packages "urca" (Bernhard Pfaff 2008), "vrtest" (Jae H. Kim 2014), and "pdR" (Ho Tsung-wu 2015). We have also used "JMulTi Time Series Analysis with Java" by Lütkepohl and Markus  Krätzig (2004). Contrary to other VAR econometric packages, JMulTi proposes bootstrap simulations for the contemporary and long-run impact matrices.
Acknowledgements This review originated in the project  Arctic Development and Adaptation  to Permafrost in Transition (ADAPT), funded by the  Discovery frontiers Program of the Natural Sciences and Engineering Research Council of Canada. Preparation work was also supported by the  Network of Centres of Excellence of Canada ArcticNet  and the  Ouranos Consortium on Regional Climatology and Adaptation to Climate Change , through grants to  D. Berteaux. Daniel Fortier  and two anonymous reviewers provided helpful comments. Published by  NRC   Research Press Arctic Science Downloaded  from www. nrcresearchpress. com by  UiT   NORGES ARKTISKE UNIVERSITET on 03/13/18  For personal use only. Arctic Science Vol. 3, 2017 Published by  NRC   Research Press Arctic Science Downloaded  from www. nrcresearchpress.
Data from the European Clinical Trials Database (EudraCT) actually shows that non-commercial sponsors conduct an important proportion of clinical trials (figure  2 ). This figure does not provide a full overview of clinical research run by academia. Indeed, in oncology, drugs alone do not always provide the solution, as many cancers are managed with surgery and radiotherapy. Progress in these areas can only be achieved through clinical research conducted almost exclusively by academia. Hence, it could be argued that the overall contribution of academia to clinical research would be much higher. No global statistics exist in Europe, but based on the clinical trials register ' ClinicalTrials. gov', only 35% of cancer projects registered are funded by industry, with 65% being supported by health systems, government funds, universities and other research organisations.
To further determine, if there are moderate differences that might still be relevant, we used a less stringent cutoff of at least 10% difference in mean DNAm levels. With these thresholds 219 CpGs were hypomethylated, while 371 were hypermethylated in FCS-supplemented MSCs (Fig. 2c ). These differences were then compared with 58 publicly available DNAm profiles of MSCs that were cultured with FCS or HPL (6 different studies, Supplementary Table  S1 ). None of these studies has directly compared the two different culture conditions and therefore this cross-comparison might be influenced by other variables in experimental design or analysis. In fact, the DNAm differences of FCS-MSCs versus HPL-MSCs as observed in our study were hardly recapitulated in the comparison of publically available datasets (Fig.
For staining of the senescent cells the Abcam senescence detection kit was used according to manufacturer's instructions (Abcam, Cambridge, UK). DNA-methylation analysis. Genomic DNA of MSCs was harvested with the NucleoSpin Tissue kit (Macherey-Nagel, Düren, Germany), bisulfite converted with the EZ DNA Methylation TM Kit (Zymo Research, Irvine (CA), USA), and then analyzed on Infinium HumanMethylation450 BeadChip (Illumina, San Diego, CA, USA). Hybridization and initial data processing with the GenomeStudio (v2011. 1) Methylation Module (v1. 9. 0) was performed at Life&Brain (Bonn, Germany). Raw data has been deposited at NCBIs Gene Expression Omnibus (GEO, http://www. ncbi. nlm. nih. gov/geo/, accession number: GSE87797). RNA extraction, qRT-PCR analysis, and Gene Expression Profiles. RNA was isolated from the samples using the NucleoSpin RNA extraction kit (Macherey-Nagel, Düren, Germany) and analyzed with a NanoDrop ND-1000 spectrophotometer (Thermo Scientific, Waltham, MA, USA) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
Semi-quantitative qRT-PCR was carried out with the Power SYBR green master mix (Applied Biosystems, Foster City, CA, USA) and normalized to Beta Actin (Supplementary Table  S3 ). For gene expression profiling 1 µg of genomic RNA was hybridized to GeneChip ® Human Transcriptome Array 2. 0 (Affymetrix, Santa Clara, USA). Raw data were normalized with Robust Multichip Average (RMA) using the oligo R package. These data have also been deposited at GEO (GSE87796). For principle component analysis (PCA) and nonsupervised hierarchical clustering (Euclidean distance) we used the entire gene set without X and Y chromosomes. Cell aspect ratio and fluorescence microscopy. The cellular aspect ratio (AR; total cellular length:width) of MSCs was determined in phase-contrast images (EVOS, Thermo Fisher Scientific) using the ImageJ software.
Vinculin was stained with the antibody clone hVin1 (Sigma Aldrich, Hamburg, Germany) and actin was stained with Alexa Fluor488 phalloidin (Life Technologies, Darmstadt, Germany) and analyzed as described before  29. Statistical Analysis. Statistical tests were performed using R bioconductor package or GraphPad Prism 6 statistical software. Data are represented as arithmetic mean ± standard deviation. Data were tested for normality and equal variance before analysis. Significance of DNAm and gene expression changes was estimated using the R limma package with an adjusted paired p-value < 0. 05.
Acknowledgements This work was supported by the  German Ministry of Education and Research (OBELICS ,  01KU1402A ,  01KU1402B ) and by the  Fondation ARC pour la Recherche sur le Cancer. We thank  Jutta Schneidereit  and  Susanne Wiesner  (both  University of Würzburg ) and  Gregory Dore  ( INSERM U. 993 ) for excellent technical assistance.
We took the opportunity offered by strains carrying two Sc2. 0 chromosomes to further explore the power of the SCRaMbLE recombination assay in trans  (14, 15). The Cre recombinase was induced for 48 hours in strain yLM539 carrying synIII and synIXR (Fig. 4A  and fig. S15 ). Independent clones were sampled during the time course experiment, and two clones, HMSY029 (time T 2 = 2 hours) and HMSY030 (T 8 = 8 hours), were retained for in-depth analysis. Genome-wide Hi-C contact data have recently been shown to provide a convenient way to identify and solve chromosomal rearrangements (fig. S16 )  (34) (35) (36) (37). We therefore applied Hi-C to investigate the consequences of genome structural alterations in these two isolates. The contact maps identify gross chromosomal rearrangements in both SCRaMbLE strains, with each strain exhibiting deletion and translocation events, the latter representing a class of trans SCRaMbLE events not previously observed (Fig.
Generation and normalization of contact maps Sequencing pair-end data was processed as follows. For each library, PCR duplicates were collapsed using the 6 Ns present on each of the custom-made adapters and trimmed. Reads were then aligned using Bowtie 2 in its most sensitive mode against the S. cerevisiae reference genome adapted with the synthetics sequences  (39). An iterative alignment procedure was used: for each read the length of the mapped sequence increases gradually from 20 bp until mapping becomes unambiguous (mapping quality > 30). Read pairs were aligned independently and assigned to a restriction fragment (RF). Religation and other unwanted events were filtered out, taking into account the orientation of the reads, as described  (28, 40). Contact matrices were built for each strain by binning the aligned reads into units of single RF.
Analysis of rDNA contacts Genome-wide rDNA contact frequencies were investigated in Sc2. 0 strains carrying the rDNA either at its natural position on chromosome XII (data sets from strains YS031, yXZX538, yLM539, yLM896, HMSY012, yXZX573), on chromosome synXII (data sets from strains JDY465, JDY512, JDY452), on chromosome III (data sets from strains JDY448, JDY449), or on the 2μ plasmid (data set from strain JDY446). For each data set, pair-end reads were aligned on the reference genome of the corresponding strain lacking rDNA sequences and on an extra contig corresponding to a single rDNA unit (~9 kb). Contact maps of trans interactions were generated (bin size, 5 kb) and normalized  (40). To compare the contacts between the rDNA contig with the rest of the genome in different data sets, the values in the corresponding vector were divided by their median to alleviate differences of coverage and/or number of rDNA units.
Acknowledgments We thank  A. Cournac ,  M. Marbouty , and  L. Lazar-Stefanita  for fruitful discussions and advice. This research was supported by funding to R. K. from the  European Research Council (ERC)  under the  7th Framework Program  ( FP7/2007-2013 ,  ERC  grant agreement  260822 ),  Agence Nationale pour la Recherche (ANR)  (MeioRec  ANR-13-BSV6-0012-02 ), and  ERASynBio  and  ANR  ( IESY ANR-14-SYNB-0001-03 ). H. M. and V. F. S are partly supported by  Pasteur-Roux Fellowships. J. D. was funded by the  National Science Foundation of China  ( 31471254 ), Tsinghua.
5a , Supplementary Table  2  and Supplementary Data 1). Next, we examined if the FRS7-FRS12 complex could also assemble in LD, despite the low expression of these proteins under this photoperiod (Fig. 1e ). To this end, TAP-tagged FRS12 was purified from cell cultures entrained under LD and collected at day (ZT4) and night (ZT20) time periods. FRS7 was identified in all tested conditions, supporting the assumption that FRS7 and FRS12 assemble and that the corresponding complex is also active in LD photoperiods (Fig. 5a  and Supplementary Data 1). Furthermore, HON4 was also recruited by FRS12 in LD but only at night-time (ZT20), whereas AHL14 co-purified only at daytime (ZT4). These results suggest that the FRS7-FRS12 complex assembles at day-and night-times, and may recruit additional or distinct partners over the course of the diurnal cycle.
8b, c ). This overlap consisted for PIF4 of 519 genes (B 1 4 of PIF4-bound genes) and for AP1 of 991 genes (B 1 4 of AP1-bound genes), suggesting that FRS12 potentially represses large portions of PIF4 and AP1 (which is downstream of GI) gene targets. The comparison between the TChAP-Seq and the RNA-Seq datasets allowed pinpointing those genes that were both bound and regulated by FRS12. A total of 42 genes obeyed to these two criteria, corresponding to 12% of the genes detected as significantly altered in the RNA-Seq analysis (Fig. 6a  and Supplementary Table  3 ). Consistent with our co-binding comparisons, FRS12 bound to and repressed many target promoters of PIF4 and circadian clock TFs, designating FRS12 as a direct modulator of diurnal growth (Supplementary Fig. 9 ). The promoters of PIF4 and PIL1 illustrate diurnal growth targets of FRS12 (Fig.
To generate the CRISPR line, specific guide sequences targeting the 5 0 of the FRS genes (GN19-NGG type) were selected using CRISPR-P (http://cbi. hzau. edu. cn/cgi-bin/CRISPR)  45  (Supplementary Fig. 3a ) taking into account predicted-single guide RNA (sgRNA) efficiencies using sgRNAscorer (https://crispr. med. harvard. edu/sgRNAScorer/)  46. An updated overview of estimated sgRNA parameters by CRISP-OR (http://crispor. tefor. net/)  47  can be found in Supplementary Table  7. The CRISPR vector pDE-Cas9 (Km) was derived from pDE-Cas9 (ref. 48) by replacing the basta resistance cassette with an nptII module. The NOSp-NptII-NOSt cassette (NptII cassette) was amplified using primers NptII. For and NptII. Rev (Supplementary Table  4 ). The pDe-Cas9 vector was digested with AatII and PmeI to remove the PPT cassette and the NptII cassette was introduced by in-fusion reaction (Takara Bio USA).
Briefly, seeds were surfacesterilized and sown in ½ Murashige & Skoog (MS) medium with 0. 8% agar without sucrose. Seeds were stratified at 4 °C in CD for 3 days, and placed horizontally in SD or LD growth for 10 days with a light intensity of 80 mmol m À 2 s À 1. Hypocotyls were extended in new MS plates, plates were then scanned and the hypocotyl lengths were quantified using ImageJ 1. 46r software (http://imagej. nih. gpv/ij/). All values represent the mean of 16 to 20 seedlings, significant differences between genotypes and Col-0 wt were assessed using t test. Rosette leaf growth and movement dynamics were followed using a high-resolution in vitro growth imaging system (IGIS)  23. Arabidopsis plants (n ¼ 25) were grown randomly in petri dishes mounted on a rotating disk for 21 days, and images of each plate were taken in an hourly basis.
Cell cultures were grown either in continuous darkness or entrained in LD (16:8) conditions for 2 weeks before collecting at ZT4 or ZT20. Protein interactors were identified by mass spectrometry using an Orbitrap mass spectrometer  28. Proteins with at least two matched high confident peptides, of which at least one is unique, were retained (Supplementary Table  2 ). Afterwards, nonspecific interactors were filtered out based on frequency of occurrence of the co-purified proteins in a large dataset containing 543 TAP experiments using 115 different baits  27. Two biological replicates were analysed for each experiment. Phylogenetic analysis. The first 200 amino acids of FHY3 containing the DNA-binding domain were aligned by ClustalW2 (http://www. clustal. org/) to all members of the FRS family to retrieve a conserved region amongst these proteins.
Data were imported into the Biological Rhythms Analysis Software System and analysed by FFT-NLLS  57. Immunoblotting. Total protein was extracted using extraction buffer (25 mM Tris/HCl pH 7. 6, 15 mM MgCl 2 , 150 mM NaCl, 15 mM p-nitrophenyl phosphate, 60 mM b-glycerophosphate, 0. 1% NP-40, 0. 1 mM Na 3 VO 4 , 1 mM NaF, 1 mM PMSF, 1 mM E64, complete proteinase inhibitor (Roche), 5% ethylene glycol) and the protein concentration was determined using Bradford assay (Bio-Rad). Samples were denatured in Laemmli buffer, run on a 4-15% TGX gel (Bio-Rad) for 20 min at 300 V, and subsequently blotted on a 0. 2 mm PVDF membrane (Bio-Rad). Antibodies used were anti-HA (1:1,000 dilution, 3F10, Roche) and anti-actin8 (1:2,000 dilution, A0480, Sigma). Chemiluminescent detection was performed with Western Bright ECL (Isogen, http://www.
Chromatin was isolated from formaldehyde-treated cell cultures following two affinity purification steps; first by IMAC using a Ni-NTA Superflow resin (Qiagen), then by a Biotin binding step using a Streptavidin Sepharose resin (GE Healthcare). Finally, protein-DNA bound fragments were decrosslinked, deproteinized and purified using the QIAquick PCR Purification Kit (Qiagen)  52. Experiments were carried in two replicates. The TChAP DNA samples were processed by first preparing a Trueseq ChIP-seq library (Illumina) and then sequencing using Illumina HiSeq 2000 at 50 bp single read at an average depth of 15 million reads at GATC biotech Ltd, Germany. The quality of the raw data was evaluated with FASTQC (v0. 10. 0; http://www. bioinformatics. bbsrc. ac. uk/projects/fastqc/), and adaptors and other overrepresented sequences were removed using the fastx-toolkit (v0.
0. 13; http://hannonlab. cshl. edu/fastx_toolkit/). Reads mapping and filtering to the unmasked TAIR10 reference genome of Arabidopsis using BWA with default settings for all parameters (TAIR10_chr_all. fas; ftp. arabidopsis. org)  36. Peak calling was performed using MACS v2. 0. 10 (ref. 59) at default parameters except À g 1. 0e8 and FDRo0. 05, adding a cutoff stringency of 10. Peak regions were annotated based on the location of their summits. A peak was assigned to the closest gene as annotated in the TAIR10 release represented in the PLAZA2. 5 database  60  ; peaks can be assigned both 5 0 and 3 0 of a gene. Each assignment was considered as a potential TF-target interaction. The peak locations were categorized by assigning a peak to one of the following genomic regions: intergenic, 1 kb promoter (1 kb upstream of Transcription Start Site), 5 0 UTR, coding, intron, 3 0 UTR, and 1 kb down of the transcription stop site.