dataesr/scientific-paragraphs-categorization huggingface dataset:
Hit overlaps examined by cross-validation For the hit cross-validation analysis we only used data coming from the siRNAs of all unpooled libraries (11 in total). In each run, we ran PMM, MTT, and RSA on a subset of the data consisting of 10 individual siRNAs and used the remaining siRNA set as test set. For PMM we ranked the results according to the absolute value of the estimated c pg effects, for MTT we did ranking with respect to the absolute values of the estimated mean, for RSA we based the ranking based on the log(p) values and for the test set we ordered the genes by the absolute value of infection score. We counted the number of genes that appeared in top k (k = 1,…,100) in both the training and test sets. We determined the counts separately for each pathogen and averaged them in the end.
Influence of parallelism For selected pathogen p we generated 1000 new datasets by fixing the data of p and randomizing the data of the other 7 pathogens. We applied PMM to each dataset and saved the resulting ranking of p. In the next step we aggregated the 1000 rankings by taking the average over the c pg scores. We compared the averaged scores to the gene rankings obtained by PMM performed using the original dataset. We independently performed the study for each pathogen.
Figure5Summary of screening hits for all pathogens. (A) The heat map shows all genes which were significant (FDR < 0. 4) at least for one pathogen. We ordered the genes by their averaged c-values over all pathogens. The colors correspond to the estimated c-values. The black outlines indicate significant hits (FDR < 0. 4) and the green outlines high-light the strongest down and up hits for each pathogen. The rightmost column shows the sharedness scores for each gene. (B) The network shows the hit genes (FDR < 0. 4 for at least one pathogen) and their direct neighbors that had connections between kinases in STRING database (version 9. 0). The edges are functional interactions in the STRING database with edge threshold 850. We removed genes that were not connected to any other gene from the network.
Acknowledgements We acknowledge support by grants  51RT 0_126008  and  51RTP0_151029  for the Research and  Technology Development (RTD) projects InfectX and TargetInfectX , respectively, in the frame of SystemsX. ch,the  Swiss Initiative for Systems Biology. C. D. acknowledges grant  31003A-132979  from the  Swiss National Science Foundation (SNSF)  and  ERC  advanced grant  340330. P. C. would like to acknowledge the following grants:  ERC  advanced grant  233348 ,  ANR  grant  MIE-2009-SignRupVac ,  Fondation Le Roch  and  Fondation Jeantet. A. K. is a recipient of a scholarship from the  Pasteur-Paris University International Doctoral Program/Institut Carnot Maladies Infectieuses. E. S. was supported by the  ETH Zurich Postdoctoral Fellowship Program  and the  Marie Curie Actions for People COFUND program  (grant No.
FEL-13 12-1 ) (to E. S. and N. B. ). F. S. has been supported by  SystemsX. ch, the Swiss initiative in systems biology, under IPhd grant No. 2009/025  (to N. B. ). Work of S. H. L and A. C. was supported by the  International PhD Program "Fellowships for Excellence" of the Biozentrum. The work on Adenovirus and Rhinovirus screening infrastructure was supported by grant  SystemsX iPhD , grant  Novartis: Stiftung für Medizinisch-Biologische Forschung  and  University of Zurich: Bauten und Investitionen. Work in the Greber lab was funded by a grant from the  SNSF  ( 31003A_141222/1 ) and an  iPhD fellowship  to partly support A. Y. ( SXPHIO_142001/1 ). We acknowledge support from  Dr. A. Jurgeit  in the development of the Rhinovirus infection assay. We thank  Dr. Jean Pierre Gorvel  ( Centre d'immunolgie de Marseille-Luminy, Marseille, France ) for kindly providing B.
Recording was performed during 40 min under continuous isoflurane anaesthesia using a dedicated small animal PET system (Inveon, Siemens, Knoxville, TN, USA). FDG uptake was determined on collapsed short-axis slices in each segment from the 17-segment LV division from the American Heart Association  [18]  using the QPS software  [19]. Left ventricular (LV) end-diastolic volume (EDV), LV end-systolic volume (ESV) and LV ejection fraction (EF) were obtained from contiguous ECG-triggered short-axis slices using the QGS software. Mice were sacrificed with an overdose of isoflurane/ oxygen mixture. Blood was harvested by cardiac puncture. Heart was excised and immediately homogenized in Lysis Binding Buffer (mirVana isolation kit, Life technologies) for extraction of total RNA using the mirVana isolation kit (Life technologies, Merelbeke, Belgium) according to manufacturer's instructions.
Microarrays Agilent microarray platform was used with Low input Quick Amp labeling kit (Agilent) according to manufacturer's instructions. Briefly, one-color spike mix was added to 200 ng of total RNA prior to amplification and labeling steps. Complementary RNA was purified with RNeasy Mini kit (Qiagen) and hybridized onto mouse SurePrint G3 microarrays (8x60K, Agilent). High-resolution microarray scanner (Agilent) and Feature Extraction software were used to scan the slide and extract raw microarrays data. Microarray data are available in the NCBI Gene Expression Omnibus [http://www. ncbi. nlm. nih. gov/geo] under the accession number GSE46395. Pre-processing of raw data was performed using Limma  [20]  and VSN  [21]  packages rooted in the statistical computing environment R. Spots with a signal that was not significantly greater than the corresponding backgroundflag automatically established by Feature Extractionwere removed.
Normalization between arrays was performed with Agilent spike-in probes. Principal component analysis was performed with R package ClassDiscovery  [22]. After removing control probes and the probes that were detected in less than 4 samples per microarray slide, differentially expressed transcripts were determined using the t-test procedure within Significance Analysis of Microarrays version 3. 09 which uses data permutations to estimate false discovery rate for multiple testing  [23]. 100 permutations were used in our analyses. Heatmaps were created using Cluster 3. 0 and TreeView  [24]. Functional annotation and enrichment analysis of differentially expressed genes were performed with DAVID  [25]  (The Database for Annotation, Visualization and Integrated Discovery).
LncRNA identification and construction of correlation networks Microarrays were re-annotated for lncRNAs on a probe level. Briefly, microarray probes without accession prefix NM (i. e. protein-coding), according to the manufacturer, were aligned with lncRNAs from lncRNAdb  [26] , RefSeq  [27]  and Ensembl ncRNA  [28]  databases using BLAST +  [29]  rooted in the Perl environment. Only the probes that perfectly matched lncRNAs and did not match proteincoding RNAs (NM prefix transcripts from RefSeq) were considered as probes for lncRNAs. Spearman's rank correlation coefficient between selected lncRNAs and other remodeling-related transcripts from Gene database was obtained using the R package WGCNA  [30]. This package computes the correlation coefficients and significance is determined by Student's test.
Real-time quantitative PCR One μg of total RNA was reverse transcribed using Superscript II reverse transcriptase (Life technologies). Controls without reverse transcriptase were performed to ensure the absence of genomic DNA amplification during PCR. Real-time PCR was performed with IQ SYBR Green supermix in a CFX96 apparatus (Bio-rad, Nazareth, Belgium). PCR primers were designed using the Beacon Designer software (Premier Biosoft, USA) (Additional file 1: Table  S1 ). PCR conditions were as follows: 3 min at 95°C, 30 s at 95°C, and 1 min annealingextension (40-fold). Optimal annealing-extension temperature was determined for each primer pair. The specificity of the PCR reaction was confirmed by melting curve analysis. GAPDH was chosen as housekeeping gene for normalization. Expression levels were calculated by the relative quantification method (ΔΔCt) using the CFX Manager 2.
In situ hybridization coupled to immunostaining To determine the cellular localization of MIRT1, in situ hybridization was performed as described above, with sheep anti-DIG antibodies coupled to fluorescein instead of alkaline phosphatase. Then, slides were subjected to immunohistochemical staining with a rabbit polyclonal antibody against sarcomeric alpha-actinin (Abcam, Cambridge, UK) to detect cardiomyocytes, a rabbit monoclonal antibody against vimentin (Abcam) to detect fibroblasts, or a rat monoclonal antibody against CD45 (SantaCruz, Heidelberg, Germany) to detect leukocytes. Alexa Fluor® 635-coupled goat anti-rabbit antibody and Alexa Fluor® 633-coupled goat anti-rat antibody were used as secondary antibodies (Invitrogen, Merelbeke, Belgium). Vectashield was used to reveal nuclei. Images were recorded on a confocal microscope (Zeiss Laser Scanning Microscope LSM 510 Carl Zeiss Microscopy, Oberkochen, Germany) using the LSM 510 META software (Carl Zeiss Microscopy, Oberkochen, Germany).
Statistical analyses Results are presented as mean ± standard deviation (SD). Statistical analyses were performed with the SigmaPlot v11. 0 software. The Shapiro-Wilk normality test preceded all analyses. t-test and Mann-Whitney test were used to compare two groups of continuous variables following Gaussian and non-Gaussian distributions, respectively. Correlations between 2 variables were assessed using the Spearman test. Multiple group comparisons were performed using one-way analysis of variance and pairwise comparisons were performed using the Holm-Sidak method. All tests were two-tailed. A P value <0. 05 was considered significant.
Principal component 1 accounted for 42% of total variability and principal component 2 accounted for 22% of total variability. Then, genes differentially expressed between sham-operated and MI mice were identified using significance analysis of microarrays method. Genes with a fold-change in expression >2-fold and a q-value <5% were considered as differentially expressed. 704 genes (918 probes) satisfied these criteria (Figure  2B-C ). Data mining using the DAVID database revealed that differentially expressed genes were highly involved in inflammation-related pathways (such as Cytokine-cytokine receptor interaction pathway, Chemokine signaling pathway, and Toll-like receptor signaling pathway) (Additional file 1: Table  S2 ). We developed an analytical pipeline to extract lncRNA data from microarrays (Figure  3A ).
From the 55681 probes contained in the microarrays, we identified 26535 (48%) probes corresponding to transcripts with NM prefix (i. e. mature messenger RNAs, mRNAs). From the remaining 29146 probes, we identified 2831 probes corresponding to lncRNAs represented in lncRNAdb, RefSeq or Ensembl ncRNA database. These 2831 probes correspond to 5% of all probes on the microarray (Figure  3B ). From the 2831 probes, significance analysis of microarrays identified 20 lncRNAs significantly up-regulated in the MI group and 10 lncRNAs down-regulated in the MI group (Figure  3C  and Table  1 ). Therefore, this discovery phase allowed the identification of 30 lncRNAs regulated after MI.
Noteworthy, 2 lncRNAs displayed robust upregulation in the MI group: NR_028427 (6-fold, P = 0. 03) and ENSMUST00000100512 (12-fold, P = 0. 03). This is consistent with microarray results in which these 2 lncRNAs were also the most highly up-regulated in MI mice (5-fold and 13-fold for NR_028427 and ENSMUST00000100512, respectively; Table  1 ). We named NR_028427 as Myocardial Infarction-Associated Transcript 1 (MIRT1) and ENSMUST00000100512 as MIRT2. Second, we measured the expression levels of the same top 10 lncRNAs in an independent validation group of 16 mice (8 sham and 8 MI). The results obtained were very similar to that of the derivation group (Figure  4B ). Indeed, differential expression was confirmed for 7 of the 10 lncRNAs. Statistical significance was lost for NR_038041, although the trend remained the same (slight down-regulation in the MI group).
Association between MIRT1, MIRT2, and LV remodeling To gain further insight into the potential role of MIRT1 and MIRT2 into LV remodeling, we used the following approach. First, we identified a list of 47 genes known to Table  1  LncRNAs differentially expressed between MI (n = 4) and sham-operated (n = 4) mice as determined by microarrays using a fold-change >2 and a q-value <5% be involved in remodeling using the keywords ("myocardial infarction" AND "ventricular remodeling") AND ("homo sapiens"[Organism] OR "mus musculus"[Organism])" as a query to NCBI Gene database (="remodeling genes"). Among these 47 remodeling genes, 38 genes were detected on microarrays. Then, we used the microarray data of the derivation group of 4 sham-operated and 4 MI mice to determine the correlation between the expression values of these 38 remodeling genes and the expression values of MIRT1 and MIRT2.
We also measured Nppb, which encodes BNP, and we observed that, while most remodeling genes remained elevated 3 days after MI, Nppb had returned to baseline levels after 48 hours. This kinetic was similar to that of MIRT1 and MIRT2. Together, these data support an association between the lncRNAs MIRT1 and MIRT2, and genes known to be involved in LV remodeling.
25 for 10 ms and analyzed in the LTQ. MS/MS data were acquired in a data-dependent mode in which 20 most intense precursor ions were isolated, with a dynamic exclusion of 20 s and an exclusion mass width of 10 ppm. Data were processed with Proteome Discoverer 1. 4 software (Thermo Fisher scientific, San Jose, CA) coupled to an in-house Mascot search server (Matrix Science, Boston, MA; version 2. 4. 1). The mass tolerance of fragment ions was set to 7 ppm for precursor ions and 0. 5 Da for fragments. The following modifications were considered in mass calculation: oxidation (M), phosphorylations (STY). The maximum number of missed cleavages was limited to two for trypsin digestion. MS/MS data were searched against the SwissProt database (11/12/13 release) with the Saccharomyces cerevisiae taxonomy.
Western-blot analysis Total protein extraction from yeast cells was performed by the NaOH-TCA lysis method  (42). Samples were separated on 4-12% SDS-PAGE gel and transferred to PVDF membranes. Western-blot analysis was performed using the following antibodies: rabbit IgG-HRP polyclonal antibody (Dakocytomation), 1:5000; monoclonal anti-GFP (Roche Diagnostics), 1:500; monoclonal anti-HA (Covance), 1:1000; monoclonal anti-Pab1 (Santa-Cruz), 1:1000; polyclonal anti-Yra1 (  6 ), 1:1000; polyclonal anti-Nab2 (32), 1:100 000; polyclonal anti-Hpr1 (39), 1:1000; and polyclonal anti-Mex67 (39), 1:50 000. Quantification of signals was performed based on serial dilutions of reference samples using the ImageJ software.
Gene expression analysis Total RNAs were extracted from yeast cultures using Nucleospin RNA II (Macherey Nagel). For RT-qPCR, RNAs were reverse-transcribed with AMV reverse transcriptase (Finnzymes) and cDNA quantification was achieved through quantitative real-time PCR as above. For microarray analysis, 1 mg of total RNA was reverse transcribed and labeled with Cy5 or Cy3 using the amino-allyl protocol described at transcriptome. ens. fr/ sgdb/protocols/. A set of 52 519 probes matching the ORFs of S. cerevisiae, with 1-15 specific probes per gene, was designed using the Teolen software, with default parameters  (43). This probe design was deposited on the earray database (AMADID: 027945) and was used to produce Agilent arrays in a 8 Â 60 k format. These Agilent arrays were hybridized with the labeled cDNA using the Agilent hybridization protocol.
After washing following the supplier's recommendations, the slides were scanned using a 2-micron Agilent microarray scanner. The images were analyzed using the feature extraction software and normalized by global lowess using Goulphar  (44). For each gene, the Cy5/Cy3 ratios corresponding to the different probes were averaged. The hpr1-KR versus wt comparison was performed twice using independent samples and dye swap. The averaged log 2 of the mutant/wild-type ratios and the standard deviation between the two replicates were calculated for each gene. The genes showing a standard deviation >0. 5 were removed from the data. This filter eliminated $150 genes which were highly variable between replicates. The complete microarray data are available in Supplementary Table  S2  and in the ArrayExpress database (www.
ebi. ac. uk/arrayexpress) under accession number E-MTAB-2138. Cells carrying LacZ reporters were lysed and assayed for b-galactosidase activity using the NovaBright TM b-galactosidase Chemiluminescent Detection System (Invitrogen) following the manufacturer's instructions. Relative light units were normalized to the amount of cells as estimated by measurement of the OD at 600 nm.
Miscellaneous Fluorescence in situ hybridization (FISH) was carried out on fixed cells using a Cy3-(dT)50 probe  (45). Wide-field fluorescence images were acquired using a DM6000B Leica microscope with a 100Â, NA 1. 4 (HCX Plan-Apo) oil immersion objective and a CCD camera (CoolSNAP HQ; Photometrics). For Rad52 foci analysis, z-stacks sections of 0. 2 mm were acquired using a piezo-electric motor (LVDT; Physik Instrument) mounted underneath the objective lens. Images were scaled equivalently and 3D-projected using MetaMorph 5 (Universal Imaging), and further processed with Photoshop CS2 9. 0 software (Adobe). Hyper-recombination rates were determined as the frequency of deletions of the chromosomal leu2-k:: ADE2-URA3::leu2-k system based on two 2. 16-kb leu2 repeats as previously described  (46).
In contrast, mutation of the last 20 lysines within Hpr1 C-terminus (K46-65R) completely abolished its sumoylation (Figure  3D , compare lanes 6 and 3). Within this C-terminal domain, mutation of lysine 46-59 (K46-50R or K51-59R) did not prevent Hpr1 sumoylation, while simultaneous mutation of lysines 60-65 (K60-65R) fully abrogated this modification (Figure  3D , compare lanes 10 and 7). Similar results were obtained when the hpr1-K60-65R-HA allele was integrated at the HPR1 locus (Figure  3E ). Within this domain, the SUMOplot software (abgent. com/sumoplot) identified lysine 60 as the unique site with a high probability of modification. However, substitution of lysines 60 and 61 did not affect Hpr1 sumoylation in our in vivo assay (H. Bretes et al. , unpublished results). This is in agreement with numerous reports where mutation of single lysines does not abrogate monosumoylation and results in sumoylation at an adjacent site  (51) (52) (53).
The complete dataset used to draw this graph is available in Supplementary Table  S2. (B) mRNA levels for the YRO2, TDA6, TPO2, TPO3, ACT1 and HAA1 genes were measured by RT-qPCR (normalized to 25S rRNA values, mean ± SD; n = 3) in the indicated strains grown in MM4 medium and treated or not for 30 min with 60 mM acetic acid. *P < 0. 05 (Student's t-test, compared to wt). (C) Serial dilutions of the indicated strains were grown at 30 C on MM4 solid medium supplemented or not with 60 mM acetic acid. (D) Hpr1 binding onto the indicated mRNAs was quantified by RIP using an anti-Hpr1 antibody followed by RT-qPCR using specific primer pairs. RIP values (mean ± SD; n = 3) are the ratios between immunoprecipitated and input RNA amounts. Values were set to 1 (dotted line) for hpr1D cells (negative control for anti-Hpr1 immunoprecipitation).
Background: The symmetrical Lyon brace is a brace, usually used to maintain correction after a plaster cast reduction in the Cotrel's EDF (Elongation-Derotation-Flexion) frame. The new Lyon brace or ARTbrace is an immediate corrective brace based on some of the principles of the plaster cast which are improved due to advances in CAD/CAM technology. The aim of this paper is to describe concepts of this new brace to be not only a replacement of the plaster cast, but also a definitive brace. Methods: Instead of a plaster cast, three segmental CAD/CAM moulds are made with the instantaneous full 3D raster stereography digitizer (Orten): 1. In self axial elongation 2. In shift and lumbar lordosis 3. In shift and thoracic kyphosis A specific software (OrtenShape) makes up the overlay of the three moulds.
A better angular in-brace correction was noted with CAD/CAM, but it was not statistically significant  [14]. For Wong the in-brace reduction with the manual method is 0. 321 versus 0. 419 for the CAD/ CAM method, which is non-significant  [15]. Sankar reaches the same conclusion, but notes that patients prefer the CAD/CAM mould  [16]. Many previous studies are supporting the positive results with the casting and Lyon braces  [10, 11]  but the difficulty and cost of making the plaster cast can also explain the challenge that prompted a need for improvements, which ultimately resulted in the development of this new design concept. In 2013, the latest generation software (OrthenShape) allowed the overlay of different CAD/CAM moulds. The aim was to use this new software to replace the plaster cast with a new Lyon brace: the ARTbrace.
Modelling of the trunk shape with shapes overlay These modifications are made using the software OrtenShape. In the frontal plane moulding 2 is superimposed on moulding 1, then moulding 3 (Figure  13 ). Similarly in the sagittal plane, the second moulding is superposed on the first one, then on the third moulding (Figure  14 ). Changes are made at constant volume and detorsion which is a result of both corrections in the frontal plane and the sagittal plane (Figure  15 ).
Discussion The proposed concept should be verified with mathematical modelling and an advanced imaging technique (referred to the changes of bony geometry). All data are stored in ORTEN and constitute a database useful for further research. The current clinical outcomes of ARTbrace look quite promising but are limited to short-term in this paper (3 days follow-up). Immediate in-brace angular reduction is not the final treatment outcome, 2 years after weaning the brace; but many authors use this value to assess the effectiveness of a brace and some authors are even using it as a predictive criterion  [2, 32, 33]. Immediate in-brace reduction is related to the flexibility of scoliosis but also to the effectiveness of the brace. We can compare results in ARTbrace with the RSC  [20]. The initial Cobb angle is 2°less in our series, but the correction is significantly different (Figure  29 ).
Our study revealed that AURKA is a bona fide marker of the severity of the disease whereas PLK1 and MAP9 expression does not correlate with the tumor grade. Nevertheless, NCBI GEO data sets (http://www. ncbi. nlm. nih. gov/geoprofiles/) reveal that MAP9 and PLK1 expression is enhanced ∼2 times (GDS 3853) in breast tumors with respect to normal tissue, and AURKA is upregulated (∼×20-30). While this observation is in accordance with 16p and 20q amplification, it does not fit with deletion of the MAP9 4q region. In parallel, GEO data set analyses (GDS 2947) of colorectal tumors and adjacent normal tissue show downregulation of MAP9 and upregulation of AURKA and PLK1, with values that are similar to what we observed in this study. We show here that, in contrast to the two kinases, MAP9 is downregulated in colorectal tumors.
Acknowledgments The authors thank  J. Selves  and  R. Guimbaud  ( CRCT U1037 ) for providing tissue colon samples. They acknowledge  V. Bergoglio  for helpful comments regarding the PACS01 data and  B. Orsetti  and  C. Theillet  for helpful discussions. This work was supported by the  CNRS  and Grants from  Association de la Recherche contre le Cancer  ( ARC N ∘ 4027  to SR),  Ligue Nationale contre le Cancer  (comité de l'Hérault-2007, comité de l' Aude-2009 to SR),  Institut National du Cancer  (cancéropôle  GSO, ACI "Genetic instability as a negative outcome in cancer " (to CC)), and  Fondation Jérôme Lejeune  to SR.