dataesr/scientific-paragraphs-categorization huggingface dataset:
The Significance Analysis of Microarrays (SAM), a more stringent statistical method, highlighted five out of the 66 genes resulting from the Rank Product test, all of which up-regulated: Adenylate cyclase 1 (brain) (ADCY1, FC = 6. 15); Glutathione peroxidase 7 (GPX7, FC = 2. 85); Forkhead box O3 (FOXO3, FC = 2. 63); Testis derived transcript (3 LIM domains) (TES, FC = 1. 48); Coiled-coil domain containing 92 (CCDC92, FC = 1. 46). To cluster the 66 deregulated genes for function/cellular process we integrated the Gene Ontology (GO) classification with information available through NCBI databank  [38]. Five major categories were identified (Figure  1C):  (1) regulation of cell proliferation; (2) regulation of programmed cell death; (3) response to oxidative stress; (4) cell adhesion, and (5) chemical homeostasis (more details in Additional file 3).
Mitochondrial functionality To investigate the effects of AFG3L2 missense changes in mitochondrial metabolism, we analyzed ATP synthesis both in SCA28 cells and in isolated mitochondria in the presence of selected substrates and inhibitors. We did detect neither a significant impairment in ATP synthesis in isolated mitochondria nor a reduction in the total ATP cellular content (data not shown). Next, we assessed the mtDNA copy number by realtime PCR to exclude mtDNA depletion. No statistically significant differences were detectable in patients compared to controls and no mtDNA deletions or large rearrangements were found (data not shown). We measured the expression levels of six mitochondrial proteins representative of respiratory chain complexes or regulators of mtDNA replication/transcription (i.
Intracellular ROS measured using the DCFH-DA were not increased in SCA28 cells, at least in the experimental condition adopted. However, looking at a long lasting damage induced by ROS by means of the TBARS analysis we found increased levels of lipid peroxidation. It is conceivable that the rapid metabolism of LCLs, along with the short half-life of ROS, led to a rapid turnover of oxidative species, masking the direct increase of intracellular ROS but leaving long-term by-products in the form of peroxidated lipids. Lipid peroxidation of cell membrane phospholipids also leads to the production of several highly reactive carbonyl compounds as by-products, which may form a variety of toxic adducts including cross-linked products on amino acids or DNA bases  [48]. Literature data have shown that these products are able to damage mtDNA and key mitochondrial constituents, including enzymes involved in mitochondrial respiration  [49].
Acknowledgments We are grateful to the patients' family members for their participation, to the  DNA and Cell bank of the Centre de Recherche de l'Institut du Cerveau et de la Moelle  épinière for technical assistance and to  Drs C Marelli ,  J Yaouang ,  M Ponsot ,  H Chneiweiss ,  D Ménard ,  S Schaeffer ,  A Lagueny ,  L Carluer  and  Y Boukhriche  as well as  Prof A Harding  for referring some of the patients and for clinical examinations. This work was funded by  Telethon Research  grant  GGP07110  and  GGP12217  (to  A Brusco ),  Regione Piemonte Ricerca Sanitaria Finalizzata , the  European Union  (to the  EUROSCA consortium) , the VERUM foundation (to  A Brice ) and the  Programme Hospitalier de Recherche Clinique  (to A Durr). We thank prof. G. Matullo  ( Human Genetics Foundation of Torino ) for providing control cell lines.
More efficient spread to, and the subsequent replication in neighboring cells should result in higher yields of do novo produced viruses in polarized T84 spheroids. We therefore measured the viral titer in the culture medium from infected T84 cell spheroids. For both viruses, titers were comparable at day 3 post-infection. Analysis at a later time point, when replication was detectable in cells based on hexon expression (data not shown), showed significantly more progeny virus was found in the culture medium of wt-Ad3GFP infected spheroids compared to mu-Ad3GFP (Figure  6B ). More efficient dissemination of wt-Ad3GFP was also demonstrated in a second cell culture model. Human lung cancer A549 cells polarize in culture to a certain extent but do not form mature tight junctions. Viral growth kinetics in A549 cells was comparable for wt-Ad3GFP and mu-Ad3-GFP (Figure  S10A ).
Shown are data from samples collected at day 9 post-infection. N = 3. The differences between wt-Ad3GFP and mu-Ad3GFP titers in the inner chamber are not significant (n. s. ). *P,0. 01. Virus titers in inner chamber were about 5 higher on day 7 than on day 4. Viral titers in the inner chamber remained stable from day 7 on (data not shown). Note that, the filter pore size of the chambers is 400 nm and should allow for the passage of 100 nm Ad virions). C) Viral spread in the presence of recombinant PtDd added to the inner chamber. T84 cells were cultured as desrcibed in B) and infected (in triplicate) with mu-Ad3GFP and wt-Ad3GFP at an MOI of 1vp/cell. Recombinant PtDd (5 mg/ml) was added to to the inner chamber on days 3, 5, and 7 post-infection. Medium in both chambers was changed on days 4, 6, 8, and 10 p.
Image morphometry Images of E-cadherin staining on T-84 transwell cultures and A549 tumor sections were taken using a Leica DFC300FX digital camera with a Leica DMLB microscope. Ten 206-magnification pictures per T84 transwell (five sections per well, collected at a distance of 50 mm, 2 infected wells) and fifteen 206-magnification pictures per A549 tumor (five sections per tumor, collected at a distance of 100 mm, 3 tumors) were analyzed using the Image-Pro Plus program (Media Cybernetics, Bethesda, MD) and the Ecadherin-positive area (% E-cadherin area) was calculated based on mm 2 E-cadherin per mm 2 tumor section. Technical details for morphometry have been described earlier  [29].
A less common alternative pathway is the ␣keto acid decarboxylase pathway, encoded by gene kdcA. This gene is only described for two strains of L. lactis  (8). In the genome sequences of C. maltaromaticum LMA 28 and ATCC 35586, an orthologous gene of kdcA was found (2) that is absent from the genomes of the other Carnobacterium strains. Nucleotide sequence accession number. The complete chromosome sequence of Carnobacterium maltaromaticum LMA 28 has been deposited at EMBL/GenBank under the accession number no. HE999757.
The latest such ATLAS results  [22]  use the full 2011 dataset and, within the context of SPS8 models, exclude values of Λ < 196 TeV, corresponding to m( χ0 1) > 280 GeV, at the 95% confidence level (CL). The limits on SPS8 models are less stringent in the case of a longer-lived NLSP. For example, recent CMS 95% CL limits  [23] , obtained using the E miss T spectrum of events with at least three jets and one or two photons, coupled with measurements of the photon arrival time, require m( χ0 1) > 220 GeV for cτ ( χ0 1) values up to 500 mm. The analysis reported in this paper uses the full data sample of 4. 8 fb -1 of 7 TeV pp collisions collected in 2011 with the ATLAS detector at the LHC, and considers the scenario where the χ0 1 has a finite lifetime and can travel some distance from its production point before decaying.
Test-beam measurements  [28]  of production EM barrel calorimeter modules demonstrated a timing resolution of ≈ 100 ps in response to high energy electrons. For this analysis, the arrival time of an EM shower is measured using the second-layer EM calorimeter cell with the maximum energy deposit. During 2011, the various LAr channels were timed-in online with a precision of about 1 ns. A large sample of W → eν events was used to determine several calibration corrections which were applied to further optimize the timing resolution for EM clusters. The calibration includes corrections of various offsets in the timing of individual channels, corrections for the energy dependence of the timing, and flight-path corrections depending on the position of the PV. The corrections determined using the W → eν events were subsequently applied to electron candidates in Z → ee events to validate the procedure as well as to determine the timing performance in an independent data sample.
B. Backgrounds The background is expected to be completely dominated by pp collision events, with possible backgrounds due to cosmic rays, beam-halo events, or other noncollision processes being negligible. The source of the loose photon in background events contributing to the selected TL sample is expected to be either a prompt photon, an electron misidentified as a photon, or a jet misidentified as a photon. In each case, the object providing the loose photon signature originates from the PV. The pointing and timing distributions expected for these background sources are determined using data control samples. Given their similar EM shower developments, the pointing resolution is similar for prompt photons and for electrons. The z DCA distribution expected for prompt photons and for electrons is therefore modeled using electrons in Z → ee data events.
IX. CONCLUSIONS A search has been performed for non-pointing photons in the diphoton plus E miss T final state, using the full data sample of 7 TeV pp collisions recorded in 2011 with the ATLAS detector at the LHC. The analysis uses the capability of the ATLAS LAr calorimeter to measure the flight direction of photons to perform the search, with the precision measurement of the arrival time of photons used as a cross-check of the results. No significant evidence for non-pointing photons is observed. Interpreted in the context of the GMSB SPS8 benchmark model, the results provide 95% CL exclusion limits in the plane of τ (the lifetime of the lightest neutralino) versus Λ (the effective scale of SUSY breaking) or, alternatively, versus the mass of the lightest neutralino. For example, for Λ = 70 TeV (160 TeV), NLSP lifetimes between 0.
Experimental design and data collection Plots with herbaceous vegetation were selected at each site to minimize the variability due to the effect of soil cover on microclimate conditions, mainly on soil temperature. For the savanna and alpine ecosystems, areas with natural vegetation were selected, but for the forest ecosystems, plots on managed grassland were selected. 14 C and 15 N labeled straw was mixed with soil, from the top 0-10 cm layer at each of the sites, in 14 × 15 cm porous bags. The top part of the bags had a 1 mm mesh to allow the passage of plant roots and mesofauna and the mesh of the bottom part was 0. 1 mm to minimize losses by gravity. The soil weight per bag was adjusted to reproduce the natural bulk density for a volume of 210 cm 3. The labeled straw was obtained by growing the wheat in a labeling chamber with controlled temperature, radiation, humidity and CO 2 concentration.
Back Close Full For all compartments (total soil, microbial biomass and mineral nitrogen) the percentage of the N in the samples that had come from the N added in the straw (%Ndff) was calculated as: %Ndff = %E comp %E straw • 100 where %E comp is the atom percent excess of the tracer in the compartment and %E straw is the atom percent excess in the straw. From this, the amount of N from the straw in each compartment was calculated as: mg N = %Ndff • N total 100 where N total is the total N in the sample in mg. Following the death of our colleague, Pierre Bottner, we recovered most of the experimental data, except the last results for BM and inorganic 15 N, where only the first five results were available for each site. All 15 N labeled data and 14 C labeled data  (Pansu et al. , 2010)  are expressed as a fraction of the labeled N and C added at the start of the experiment.
Back Close Full cycle in MOMOS-C  (Pansu et al. , 2004 (Pansu et al. , , 2010)) , using the subscript e (either C or N) to differentiate each element in the model. MOMOS (Fig. 1 ) was defined as a five compartment model centered on the activity of soil microbial biomass (MBe) that grows by assimilation of labile (VLe) and stable (VSe) fractions of plant necromass (NC) as well as labile (HLe) and stable (HSe) fractions of humus. The microbial mortality regulates humus formation. The only process which is considered more of a chemical process than a biological process is humus stabilization from HLe to HSe. The only difference between the C and N models is in the outputs from MBe to inorganic forms of C (CO 2 -C) and N (NH 4 -N) or possibly inputs from inorganic N into MB N. MOMOS has only seven first order kinetic parameters (dimension day -1 ) and does not need the partitioning coefficients used in other decomposition models.
The two examined clone PA14 strains from California and Germany were found to be of the same genome size and differ from each other in 0. 0035% of their nucleotide sequence. Since these data alone do not allow any general conclusions, we wanted to explore the impact of habitat, history and geographic origin on intraclonal genome diversity of P. aeruginosa in more depth. For that purpose two complementary scenarios of habitat differentiation were chosen. The three selected clone CHA strains were isolated from freshwater or CF patients at geographically distant sites within a 15-year period and represent the distant clone strain set. Conversely, the three selected clone TB strains were isolated during a local outbreak and represent the closely related clone strain set. Clones CHA and TB were chosen because we wanted to include the highly pathogenic strains CHA  [14]  and TBCF10839  [15]  in the comparative genome analysis.
Indels Nineteen small indels (< 4 bp) were identified in the coding region of the clone CHA genomes (Table  2 ), 14 of which were already known from other completely sequenced P. aeruginosa strains. The three frameshifts in the last codons of PA3124 and PA4161 or the stop codon of PA5282 are neutral sequence variations and the three in-frame indels in PA2091, PA2302, and PA3462 should modulate the function of the encoded gene products to only minor extent, but the majority of the other 13 out-of-frame indels are probably loss-of-function mutations. Five of the 19 indels are as yet undescribed in the Pseudomonas Genome Database (August 2012). Two of these have no functional consequences as mentioned above (PA3124, PA5282) and one destroys the reading frame of a chemotaxis transducer (PA4915).
Novel strain-specific genes ORFs were designated as 'novel genes' if they had yet not been described in completely sequenced P. aeruginosa genomes deposited in databases by June 1st, 2012. The number of novel genes correlated with the genome size of the strain, i. e. least genes were identified in strain CHA and most genes were detected in strain PT22 (see Additional files 8, 9, 10). The strain CHA genome incorporated a truncated variant of the Pseudomonas phage B3  [40]  and an aacC1 gene that confers resistance to aminoglycoside antibiotics. The aacC1 sequence contig probably originated from an enterobacterial integron that has the highest homology to the enterobacterial type I integron harboured by plasmid p1658/97  [41]. Annotation uncovered 114 strain-specific ORFs in the CF isolate 491 (see Additional file 10).
Most ORFs to which a function could be ascribed encode enzymes of DNA metabolism or mobility or elements of conjugation and type IV secretion. The closest ortholog or homolog was identified for all ORFs in beta-or gamma-proteobacteria that have   1  were incorporated into three pseudosequences derived from the PAO1 reference sequence by the script SequenceReplacer (available on request from the authors). The network was produced using the uncorrected P distance measure with normalisation followed by the NeighbourNet algorithm in the program Splitstree  [62]. The scale indicates the number of substitutions per site. Numbers on the branches are 100 bootstrap resampling values which give a measure of the confidence of the displayed tree topology. A network for clone TB is not shown as the isolates display up to two orders of magnitude less divergence than clone CHA strains, which cannot be visualised appropriately.
Conversely, shared de novo mutations and comparably very few individual de novo mutations highlight the close relatedness of the two clone TB CF isolates. The environmental isolate PT22 was endowed with the largest accessory genome of the investigated strains. PT22 Contigs from CHA are coloured black, those from PT22 are red and contigs from 491 are grey, while the dark blue boxes represent the annotated ORFs from the P. aeruginosa PA14 genome and the PAGI-2 genomic island, respectively. For details on the annotated ORFs, please refer to the respective original publications (  [4]  for RGP26 from PA14,  [39]  for PAGI-2). PT22 harbours a complete copy of the PAGI-2 island, while 491 has a partial copy and it is absent in CHA. Figures were produced using the R package Genomegraphs  [60]. was collected from the river Ruhr at a site with substantial anthropogenic pollution and contamination with industrial sewage (Wasserqualität der Ruhr 1992  [47] ).
Illumina genome analyser sequencing After preparing genomic DNA libraries according to the manufacturer's instructions, sequencing-by-synthesis was performed at GATC-Biotech (Constance, Germany) for each library with an Illumina Genome Analyser II generating 36 bp sequence reads. Illumina Genome Analyser Pipeline Version 0. 2 software was applied to qualify reads passing default signal quality filters. Obviously incorrect reads with homooligomers > 13 bases in length (not present in the P. aeruginosa genome) or an 'N'-base call in at least three positions were excluded from the analysis  [10]. All sequence data from this study have been submitted to the Sequence Read Archive (SRA) of the EBI (strain TB63741: study accession no. ERP001300; clone CHA strains CHA, PT22 and 491: study accession no.
Sequence and read alignment 36 bp reads data of the strains were individually mapped to the PAO1 reference genome (NC_002516. 2) using the accurate alignment software Novoalign V2. 07. 00 (Novocraft Technologies, 2010). The command: novoalign -d Indexed_reference_genome -f Reads. fastq -o SAM > out. sam, was used during the mapping to create "sam" formatted alignment files. Two pools of data consisting of the PAO1 mapped and unmapped reads were then extracted directly from the three alignment files using a custom script. Unmapped reads representing non-PAO1 DNA and the mapped reads representing the PAO1 DNA were assigned to not-in-reference and in-reference read pools, respectively.
Contigs that lacked similarity with others were designated as strain-specific DNA. These candidates were further validated using alignments of the short read data sets from both other strains using Novoalign. Contigs covered by reads were not considered to be strain-specific. Validated strain-specific contigs were aligned using blastx against the UniProt database  [59]  to identify sets of known (present in other P. aeruginosa) and novel (not present in other P. aeruginosa) genes in their accessory genomes.
Detection of horizontally transferred genomic elements in clone CHA Assembled contigs of the three clone CHA strains were aligned against all known P. aeruginosa genomic islands and insertions in regions of genome plasticity using blastn (1e-10 E-value threshold). Alignment results for all the searches were then visualized by GenomeGraphs  [60] , an integrated genomic data visualization package for R (http://www. r-project. org) to help determine which of the known horizontally transferred genomic elements are completely/partially present in the three clone CHA strains.
Figure3Phylogenetic network for clone CHA isolates based on identified SNPs. All SNPs mentioned in Figure1were incorporated into three pseudosequences derived from the PAO1 reference sequence by the script SequenceReplacer (available on request from the authors). The network was produced using the uncorrected P distance measure with normalisation followed by the NeighbourNet algorithm in the program Splitstree [62]. The scale indicates the number of substitutions per site. Numbers on the branches are 100 bootstrap resampling values which give a measure of the confidence of the displayed tree topology. A network for clone TB is not shown as the isolates display up to two orders of magnitude less divergence than clone CHA strains, which cannot be visualised appropriately.
Acknowledgments OKIB is grateful to  Oleg Reva ,  University of Pretoria , for supervision and intellectual support. This work was supported by a grant from the  Mukoviszidose eV  (project: Comparative phenotyping of highly virulent clinical Pseudomonas aeruginosa isolates from cystic fibrosis) during the initial stage of the project and later by grants from the  Deutsche Forschungsgemeinschaft  ( SFB 900 , projects  A2  and  Z1 ). OKIB received a stipend from the  German Academic Exchange Service (DAAD). Publication of this manuscript is supported by the  sponsorship 'Open Access Publication' of the Deutsche Forschungsgemeinschaft.
Indel is listed in the Pseudomonas Genome Database for completely sequenced P. aeruginosa genomes: 1 for strains PA14, 2192, C3719, PACS2, 39016; 2 for strains PA14, 2192, C3719, PACS2, 39016, PA7; 3 for strains 2192, C3719, PACS2; 4 for strains PA14, PACS2, 39016; 5 for strains PA14, 2192, C3719, PA7, 39016.
Images acquisition and analysis Fluorescence images from spheroid sections were acquired using a DM5000 (Leica) epifluorescence microscope, fitted with a Roper COOLsnap ES CCD camera coupled using a C-mount 0. 63X adapter. Using a 20X objective, the final magnification was 12. 5X and allows visualizing entire sections of small and large spheroids in the field of view with image quality high enough for subsequent analyses. Images were processed using Metamorph and ImageJ softwares. To quantify the percentage of Fucci-expressing cells depending on the distance to the spheroid surface, images were analyzed using the Cellomics Technologies software (Compartimental Bioapplication-Thermo Scientific). Briefly, all the nuclei from each section were segmented based on DAPI fluorescence. Then, the x and y coordinates and the fluorescence intensity corresponding to Fucci-Red or Fucci-Green channels were automatically extracted for each individualized object.
The same threshold was used to identify Fucci-expressing cells on all the spheroid sections from a single experiment. Numeric values were processed using Microsoft Excel and Prism software packages. For each section, the percentage of positive cells at a given distance was calculated by dividing the number of Fucci-expressing cells by the total number of nuclei included in the indicated range of distance. For each condition, 20 to 30 sections from 8 to 10 spheroids from 2 to 3 independent experiments were analyzed.
Acknowledgements We gratefully acknowledge the members of our group for discussions and support of this project. JL was a recipient of a doctoral fellowship from la  Ligue Nationale Contre le Cancer. The authors wish to acknowledge  Pierre Cordelier  for its contribution to the production of the Fucci cell lines, the support of the  BIVIC, TRI  and ITAV imaging facilities. The authors also thank  Fanny Grimal  for her help for image analysis. This work was supported by the C. N. R. S, l' Université Paul Sabatier, la Région Midi-Pyrénées, la fondation InNaBioSanté, la Ligue contre le Cancer (comité 31 ), le  Cancéropôle Grand Sud-Ouest and la Fondation pour la Recherche Médicale  ( Equipe FRM2011 ).
This work was financially supported by the  Institut Pasteur ,  CNRS ,  Fondation pour la Recherche Medicale  ( DCM20111223063  to S. Pochet) and by the  French Infrastructure for Integrated Structural Biology (FRISBI)   ANR-10-INSB-05-01. C. Amiable  was recipient of a fellowship from the  French Ministry of Research. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.