dataesr/scientific-paragraphs-categorization huggingface dataset:
intestinalis sp. A-sp. B species and in the two morphologically very close species Botrylloides leachii and Botrylloides. nigrum (see triangles in fig. 3  and blue bars in fig. 2 ). These data suggest that    b ) congeneric ascidian pairs. Red: Botryllus schlosseri comparisons; blue: comparisons between cryptic or morphologically very similar species pairs. The number of pairs examined for each genus is reported in brackets, if >1. The analyzed mitogenomes are listed in table 1. dN rates were calculated with PAML v4. 4b package  (Yang 1997)  according to Goldman's codon substitution model  (Goldman and Yang 1994). FIG. 3. -Saturation plot of the first plus second codon positions (P12) of the 13 mitochondrial protein-genes, drawn for all congeneric and intraspecies ascidian pairs. Continuous violet arrowhead lines: gap between intraspecies and all congeneric distances.
Acknowledgments The authors thank  Riccardo Brunetti  and  Noa Shenkar  for helpful discussions on the Botryllinae taxonomy;  Loriano Ballarin ,  Nicola Franchi , and  Fabio Gasparini  for discussions on the B. schlosseri intraspecies variability;  Adriana Giumbo  and  Cosimo Di Fonzo  for support on the sequencing of some mt genomes. This work was supported by the  Ministero dell'Istruzione, dell'Universitae della Ricerca, Italy  ( PRIN-2009 ) to C. G. , Lifewatch ( Consiglio Nazionale delle Ricerche, Italy)  to G. P. , the  National Institute of Health  grants  RO1GM100315  and  1R01AG037968  to A. V. , and the  Agence Nationale de la Recherche  " Programme Blanc" (Tunicate Evo-Devo "TED")  to  E. J. P. D. This  is contribution No. 2014-YYY of the  Institut des Sciences de l'Evolution de Montpellier  ( UMR 5554 -UM2 + CNRS + IRD ).
Methods This was a retrospective observational study from a university hospital-based pediatric department (Centre Intercommunal de Créteil, Créteil, Val de Marne, France). We included data for all children from 3 months to 18 years old who were hospitalized in the pediatric department between January 2003 and May 2010 with a diagnosis of acute cervical lymphadenitis, suppurative cervical lymphadenitis, infections of the retropharyngeal and parapharyngeal space or cervical necrotizing fasciitis. Our institutional policy is to hospitalize all children when indicated, directly to the general pediatric department, and to manage them in close collaboration with the ear, nose and throat (ENT) specialists. Case history, biological data, contrast-enhanced CT scan data, treatments and clinical course were retrospectively collected from patient charts.
RNA extraction and quantitative RT-PCR Eight biological replicates were extracted from cell cultures using RNA PLUS reagent (QBiogene) according to the manufacturer's protocol. Quality of RNAs was checked using the 2100 BioAnalyzer (Agilent Technologies). Five microgram RNA was then reverse-transcribed using First-strand cDNA synthesis kit (GE Healthcare). A total of 93 genes (Table  S1 ) were selected from a bibliographical review on tumor metabolism and the KEGG pathway database (www. genome. jp/kegg/). The aim was to choose genes coding for enzymes implicated in the major metabolic pathways as classified by the KEGG database. We have preferentially selected genes that had previously deserved attention in cancer metabolism literature. TaqMan low density arrays (Applied Biosystems) were used to evaluate mRNA expression using an ABI Prism 7700 thermal cycler (Applied Biosystems).
5 ms), and tm the mixing time (10 ms). The 90u hard pulse was automatically calibrated for each sample before analysis to avoid peak phase and baseline distortions of spectra. The resonance of H 2 O (4. 78 ppm) was selectively irradiated with a continuous wave low power pulse during d1 and tm. For each sample, 512 transients were collected into 64 k data points over a spectral width of 20 ppm at 27uC. Prior to Fourier transformation, the free-induction decay was smoothed using an exponential function resulting in a line-broadening of 0. 3 Hz. A minimal baseline correction was applied to spectra using the Topspin Version 2. 0 software (Bruker Biospin, Karlsruhe, Germany). Spectra were referenced to the TSP resonance (0. 00 ppm). Then spectra were normalized to the integral of signal between 1.
0 and 4. 5 ppm, and identified signals were integrated. Signals were assigned to metabolites from literature tables and publicly available databases of chemical shifts, jcoupling constants and peak structures. LCMS spectra were obtained using a microTOF ESI-TOF mass spectrometer (Bruker Daltonik GmbH, Bremen, Germany) coupled to a HPLC system (Agilent 1200 Series High Performance Autosampler, Waldbronn, Germany) controlled by the HyStar chromatography software (Bruker Daltonik GmbH). A mobile phase system consisting of water and acetonitrile (each containing 0. 1% formic acid) was used, and separation was performed with an RP-18 column (Zorbax Eclipse XDB-C18 4. 66150 mm, 3. 5 m particle size, Agilent). Data sets were acquired in positive electrospray ionization mode in a scan range from 50 to 800 m/z at a sampling rate of 1 Hz.
Sodium formate solution was used for calibration and injected at the beginning of each chromatographic run. Quality control samples and blank runs were interspersed between the samples. MS raw data were converted into NetCDF files using the Metabolic Profiler software suite (Bruker Daltonik GmbH). Subsequent data processing was performed using XCMS (http://metlin. scripps. edu) including retention time alignment, matched filtration, peak detection, and peak matching. Then peaks were integrated. Metabolites were identified from publicly available databases and a home-made LCMS library of standards. In addition, 1 H-NMR spectroscopy was performed in intact cells according to the technique in reference  [25]. Briefly, NMR spectroscopy was performed on a small-bore 500-MHz Bruker Avance DRX spectrometer equipped with a high resolution magic angle spinning (HRMAS) probe.
Intact cell pellets (5-10610 6 cells) were set into 4 mm-diameter, 50-mL, free-volume, zirconium oxide rotor tubes. Rotors were spun at 4 kHz and cooled at 4uC, using the BCU-05 temperature unit. One-dimensional 1 H-NMR spectra were obtained using a nuclear Overhauser enhancement spectroscopy sequence with low-power water-signal presaturation (NOESYPR) during both the 3. 8-sec relaxation delay and the 100ms mixing time of the sequence. The spectral width was 12 ppm with 16,384 complex data points and 32 transients. This resulted in 2 min 50 sec acquisition duration. After Fourier transformation, spectra were phased. High performance thin layer chromatography (HPTLC) 40 mL of cellular lipid extract in chloroform was used for each sample. Lipids were separated by thin-layer chromatography on a silica gel plate (Merck, Darmstadt, Germany).
HPTLC plates were used after prewashing with a mixture of chloroform-methanol (1:1, v/v) followed by heating at 110uC for 10 min. Lipid extracts were applied under a flow of nitrogen on the HPTLC plate using a Linomat IV apparatus (CAMAG, Muttenz, Switzerland) and separated using the following sequential development system: development to half final distance in methyl acetate-chloroformpropanol-methanol-0. 25% KCl in water (25:25:25:10:9, v/v) followed by full development in hexane-diethylether-acetic acid (80:20:2, v/v) to resolve non-polar lipids. Quantification was performed after staining (10% CuSO4 w/v in 8% H 3 PO 4 (v/v)) and charring at 160uC. The plates were scanned and quantification was obtained using density measurements with SIGMA scan pro 5. 0 software.
Statistical handling of data Gene expression intensity and metabolite levels were normalized to the average of the SUM1315-LXSN cell line (set to 1, which preserved the control group variability). Fold variations were calculated for the SUM1315-BRCA1 cell line. Univariate analyses between groups were performed using the bilateral Mann-Whitney test, unless specified. Hierarchical ascending classification was performed on the whole set of data using the GeneCluster and Treeview 1. 6 software (University of California). The similarity criterion was the Spearman coefficient correlation and clustering was based on average linkage.
Results The SUM1315 cell line was chosen for our study since it carries the c. 68_69delAG mutation of the BRCA1 gene  [26]. In the Breast Cancer Information Core database (http://research. nhgri. nih. gov/bic/), this mutation is the most common mutation found in BRCA1 mutant breast cancer families. SUM1315 cells were stably transfected with a LXSN plasmid encoding wild-type BRCA1. We previously showed that unlike cells transfected with the empty plasmid (SUM1315-LXSN cells), BRCA1-transfected cells (SUM1315-BRCA1 cells) expressed the 220 kDa nuclear BRCA1 protein (  [24]  and Figure  1A ). In order to characterize SUM1315-LXSN and SUM1315-BRCA1 cell line phenotypes, we analyzed proliferation, apoptosis and cell cycle distribution. Although BRCA1 transfection resulted in a slightly increased apoptosis population (Figure  1D , p = 0.
FASN, one of the key lipogenic enzymes, was slightly up-regulated by BRCA1 at transcriptionnal level. This is in contradiction with our HPTLC data which showed a dramatic decrease of free fatty acids in SUM1315-BRCA1 cells (Figure  5A : -58% compared to SUM1315-LXSN, p,0. 01). In order to understand this contradiction, we studied protein regulation of FASN and ACCA, another important enzyme of free fatty acid metabolism. ACCA and FASN proteins were slightly up-regulated by BRCA1, although over several experiments, these findings were not significant (figure  S3 ). Pellets of intact SUM1315-LXSN and SUM1315-BRCA1 cells were also analyzed by HRMAS 1 H-NMR spectroscopy. With intact cells, the highest discriminating signals were those at 1. 30 and 1. 64 ppm, corresponding to fatty acids, which were decreased by approximately 78% in SUM1315-BRCA1 cells (Figure  5B ).
Study Design This was a double-blind, placebo-controlled, multicenter, multinational, parallel-group study to evaluate treatment with two doses of tiotropium (2. 5 and 5 mg once daily, two inhalations at the same time of day) compared with placebo over 12 weeks (ClinicalTrials. gov identifier: NCT00737100). The trial period was from 23 September 2008 to 2 April 2010. The study was conducted at 94 centers in Australia, Europe, Canada, and the United States. Ethical review was undertaken for each site/country by the local institutional review board/independent ethics committee and approval granted by the Competent Authority in each state.
Statistical Analyses The primary analyses were performed in all randomized patients who received at least one dose of study drug and had both baseline and at least one post-dose PFT measurement at or before 12 weeks for either co-primary efficacy variable. Mean change from baseline in the co-primary efficacy variables (FEV 1 AUC 0-4h and trough FEV 1 ) was analyzed using a restricted maximum likelihood-based mixed-effect model with repeated measures (MMRM). To model the within-patient errors, an unstructured covariance matrix was used. Analyses were implemented using Statistical Analysis System software version 8. 2 (SAS Institute Inc. , Cary, NC, USA). The primary comparisons were between treatments after 12 weeks. The first co-primary end point, FEV 1 AUC 0-4h , was also stratified by age group.
The duration of pulmonary exacerbation was calculated based on the AE listings. Safety end points were summarized descriptively. Data considered to be missing at random were not imputed, but handled in the analysis via the use of the MMRM model; only data that could be considered not missing at random were imputed. Randomly missing data with no subsequent non-missing values for that visit were imputed using the last observation carried forward technique (FEV 1 , FVC, and FEF 25-75 measurements). In order to detect a difference of five units in the percentage change from baseline in FEV 1 values between tiotropium and placebo with 80% power at a two-sided significance level of 5%, a minimum of 465 patients in the full analysis set were required (155 in each treatment group). Based on a previous study  [19] , an approximate estimate of the expected standard deviation for FEV 1 percent-predicted value at screening was used  (15.
Acknowledgments Writing and editorial assistance was provided by  Sarah J Petit  and  Elena Garonna  of PAREXEL. We also thank the  Cystic Fibrosis Foundation Therapeutics -Therapeutic Development Network Coordinating Center  and the  European Cystic Fibrosis Society Clinical Trials Network  for their support. The principal investigators for the  Tiotropium Cystic Fibrosis Study Group  are (by country):.
Rat serum analyses Flow cytometry: Cells were resuspended in PFN (phosphate-buffered saline 1Â, 2% fetal calf serum, 0. 1% sodium azide) and distributed into 96well, u-bottomed microtiter plates (Nunc Inc. , Napervile, IL). Anti-porcine IgG were detected by incubating the porcine cells with the heat-inactivated rat sera (1/100 in PFN), followed by incubation with an FITC-anti-rat Ig. Immunoglobulin isotypes were determined by incubating the PNC with antibodies directed against rat IgG1, IgG2a, IgG2b or IgG2c (Jackson Immunoresearch), and FITC-anti-mouse IgG was used as the secondary antibody. Fluorescent labeling was measured using a Canto cytometer (BD Biosciences) and analyzed with FlowJo 1 software (TreeStar, Inc. , Ashland, OR). Sera were analyzed independently on three independent cell batches, each time in triplicate.
Transplantation of PNC into the rat striatum induces a late humoral immune response The humoral response to intracerebral xenograft was evaluated by analyzing the sera of rats transplanted with PNC. For this purpose, PNC were transplanted into the striata of 46 immunocompetent rats, and sera were collected on day 3 (D3), D28, D42 and D63 (Table  1 ). Sera immunoreactivity was first tested on PNC that were cultured for 5 days in defined medium to promote their differentiation. Cultured PNC were incubated with rat sera and IgG binding was determined by exposing the cells to FITC-anti-rat IgG. Flow cytometry analyses show a progressive increase in the median fluorescence intensity over time with statistical significance at D42 and D63 (Figure  1A ). This increase was specific as it was not observed using rat neural cells (data not shown).
Some proteins of similar size were recognized by two or three sera, whereas others were recognized by only one serum. These data highlight the interindividual differences in the humoral response. Neurons are the major cell target of the anti-porcine elicited IgG antibodies Cell specificity of the humoral immune response was investigated by characterizing the cells that bind the antiporcine antibodies. Incubation of porcine astrocytes (Figure  2A ) or PAEC (Figure  2B ) with the rat sera generated positive signals on flow cytometry, but the median fluorescence values were much lower than the value for the PNC, which were mostly composed of neurons (over 90%) (Figure  1B ): PNC versus astrocytes: 316 AE 47. 89 versus 34. 92 AE 8. 06 for the scar group; PNC versus PAEC: 316 AE 47. 89 versus 30.
A large number of positive cells exhibited a neuronal shape. The neuronal identity of these cells was confirmed by double immunocytochemistry using Tuj-1, which labels the b-III tubulin (Tuj-1) in neurons. Tuj-1 þ cells were clearly immunostained with D63 rat sera (Figure  3B ), and the co-localization was confirmed by confocal microscopy (Figure  3C ). To determine if astrocytes expressed antigens that could be recognized by the anti-porcine elicited IgG antibodies, double immunocytochemistry was performed using CD44. As shown in Figure  3D , CD44 þ cells were present in the cultures of PNC, but no co-localization with anti-porcine IgG was observed. Similar results were obtained using anti-GFAP antibodies that also label astrocytes (data not shown). The humoral immune response was characterized in vivo by analyzing the deposition of complement and anti-donor antibodies in healthy and rejecting grafts (n ¼ 3 per group) at D28 and D42, respectively.
Patients and samples Samples of primary breast tumours excised from 152 women at Centre Ren e Huguenin (Saint-Cloud, France) from 1978 to 2008 and immediately stored in liquid nitrogen until RNA extraction were analysed. All patients who entered our institution before 2007 were informed that their tumour samples might be used for scientific purposes and had the opportunity to decline. Since 2007, patients entering our institution have given their approval also by signed informed consent. This study was approved by the local ethics committee (Breast Group of Ren e Huguenin Hospital). All patients (mean age 69 years, range 52-86) met the following criteria: primary unilateral non-metastatic breast carcinoma; ERa positivity; complete clinical, histological and biological data available; no chemotherapy before surgery; and full follow-up at Centre Ren e Huguenin.
Real-time RT-PCR qRT-PCR was performed with the ABI Prism 7900 sequence detection system (Perkin-Elmer Applied Biosystems, Foster City, CA, USA) and PE biosystems analysis software according to the manufacturer's manuals. RNA levels were normalized to the level of TBP (TATA box-binding protein) and calculated as N PRKD1 = 2 DCtsample. The detailed procedures of qRT-PCR were followed as previously described  [24]. The primers for TBP and PRKD1, ESR1, PR and ERBB2 genes were chosen with the assistance of the Oligo 6. 0 program (National Biosciences, Plymouth, MN, USA). dbEST and nr databases were scanned to confirm the total gene specificity of the nucleotide sequences chosen for the primers and the absence of single nucleotide polymorphisms. Primer sequences for PRKD1 are ACAGGAACCAACTTGCACAGAGAT (PRKD1-U2) and GTGCTGATGTCCACATTTTCTTGA (PRKD1-L2), those of the other genes are as previously indicated  [24].
Statistical analysis For in vitro experiments, statistical significance of differences between experimental groups was performed by Student's t-test by using the GraphPad Prism 5. 03 software (San Diego, CA, USA). P-values <0. 05 (*) were considered significant. The distributions of PKD1 mRNA levels in breast samples were characterized by their median values and ranges. Relationships between mRNA levels of the different target genes, and between mRNA levels and clinical parameters, were identified by using non-parametric tests, namely chi-square test (relation between two qualitative parameters), Mann-Whitney U-test (relation between one qualitative parameter and one quantitative parameter) and Spearman rank correlation test (relation between two quantitative parameters). Differences were considered significant at confidence levels greater than 95% (P < 0.
05). To visualize the efficacy of a molecular marker (PKD1 mRNA level) to discriminate between two populations (patients that developed/did not develop metastases) in the absence of an arbitrary cut-off value, data were summarized in a ROC (receiver operating characteristic) curve  [25]. The area under curve was calculated as a single measure to discriminate efficacy. Metastasis-free survival (MFS) was determined as the interval between initial diagnosis and detection of the first metastasis. Survival distributions were estimated by the Kaplan-Meier method, and the significance of differences between survival rates were ascertained with the log-rank test.
Patient Selection Transplantation modalities were made as homogenous as possible using the following inclusion criteria: patients older than 18 years with MDS who were referred for first allo-SCT. The source of stem cells was the bone marrow or blood from either a sibling or an unrelated donor that was HLA-A, -B, -Cw, -DR, and -DQ identical at allelic level. Patients with chronic myelomonocytic leukemia and those who received allo-SCT from an HLAmismatched donor or cord blood or a T celledepleted graft were excluded. Thymoglobuline (Genzyme Corporation, Cambridge, MA) was the only ATG administered to the patients, as this is the only brand approved in France for use in allo-SCT. Participating centers verified the data recorded for each patient in the French Bone Marrow Transplantation Registry and provided additional information.
Quality of the data and HLA matching were controlled by using a computerized search for discrepancy errors. Consequently, 461 consecutive patients who underwent allo-SCT between October 1999 and December 2009 in 24 French and Belgian centers were identified. Thirty-six patients were excluded because their files lacked data. Because the objective of this study was to investigate the impact of ATG on patients with progressive MDS, we excluded the 183 patients who responded to pretransplantation treatment according to International Working Group 2006 criteria  [6]. Of the 242 remaining patients, 93 received ATG during conditioning (ATG group) and 149 did not (no-ATG group, n ¼ 149) (Figure  1 ).
Donors and recipients were only required to be HLA-A, -B, -DRB1 and -DQB1 identical (8 out of 8 alleles), and HLA-C mismatch was present in 35 cases. The addition of ATG Fresenius resulted in a decreased incidence of acute and chronic GVHD without increasing relapse and NRM, and without compromising OS. Data from Mohty et al. [13]  confirmed these results with ATG Thymoglobuline in a retrospective report on 120 patients with acute leukemia and MDS undergoing allo-SCT from matched unrelated donors after MAC. The impact of rabbit ATG was also analyzed with RIC in a retrospective multicenter study on 1676 adults undergoing transplantation for hematologic malignancies. Soiffer et al. [21]  reported a higher risk of relapse with ATG compared to T cellereplete regimens (51% and 38%, respectively; P <.
In multivariate analysis, the use of rabbit ATG was the only factor associated with an increased incidence of relapse (HR, 4. 8; 95% CI, 1. 8 to 12. 9; P ¼. 002) and a reduced progression-free survival (HR, 2. 9; 95% CI, 1. 3 to 6. 2; P ¼. 04). This demonstrates that ATG may have a different impact on relapse depending on the disease treated with allo-SCT. We, therefore, chose to restrict our study to only 1 disease and focused on progressive patients, hypothesizing that ATG before transplantation could have a significant impact on outcome in this setting. Because the outcome of allo-SCT depends on the degree of donor-recipient HLA matching  [31] , we only included patients who received allo-SCT from  HLA-identical siblings or 10/10 matched unrelated donors. Donor-recipient HLA-matching was verified in the database of the French National Donor Registry as previously described  [32].
ACKNOWLEDGMENTS The authors would like to thank  Raja Prince  for collecting and checking data on site. Special thanks to  Nicole Raus , the SFGM-TC data manager. Ibrahim Yakoub-Agha would like to thank the  "Association Capucine"  for their support in his research. Financial disclosure: M. M. and I. Y. -A received research support and honoraria from  Genzyme/Sanofi , whose product is discussed in this study. Conflict of interest statement: There are no other conflicts of interest to report. Authorship statement: R. D. , M. M. , A. D. , G. D. , and I. Y. -A. designed the study, wrote, and edited the paper; R. D. , A. D. , and I. Y. -A. analyzed and interpreted the data; all authors provided study materials or patients, collected and assembled data; and all authors reviewed and approved the final version of the manuscript.
7). This is a generalized eigenvalue problem  (Cliffe et al. 1994). The eigenvalues of (3. 10) approximates the eigenvalues of the continuous problem. The generalized eigenvalue problem (3. 10) is solved using DOLFIN  (Logg & Wells 2010) , an interface to the FEniCS package  (Eds et al. 2010). This is a framework for automated solution of differential equations by the Finite Element method. The package allows the construction of the matrices A and B using a high level formulation of the weak problem. It also handles the computation of eigenvalues and eigenfunctions through the SLEPc package  (Hernandez et al. 2005) , a software library for the solution of large scale sparse eigenvalue problems. For given values of the non-dimensional parameters C and L, the solution of the eigenvalue problem posed by equation (3.