dataesr/scientific-paragraphs-categorization huggingface dataset:
The initial clinical responses were so encouraging that crizotinib is currently tested in a growing number of advanced ALK-positive tumors (clinicaltrials. gov). Nevertheless, the tumors invariably develop resistance to the inhibitor, mostly through mutations of the kinase active site. 19, 20  Therefore, it appears necessary to design alternate treatments or to associate TKIs with other molecules. One promising strategy would be to impair distinct functions of the oncogenic tyrosine kinase through targeting different sites of the ALK protein. We recently demonstrated that the ALK receptor tyrosine kinase belongs to the functional family of so-called 'dependence receptors'. 21, 22 Such dependence receptors function with a dual signaling: in the presence of ligand (or a situation mimicking a ligand, e.
Acknowledgements. This work was supported by INSERM and Université Paul Sabatier  and by a grant ( R07055BB ) from the  Fondation de France  (MA). We thank  Dr Frédérique Gaits  for helpful suggestions,  Marie Terville , the  GenoToul Proteomic facility of Toulouse , and the cellular imaging facility of INSERM UMR 1043 of Toulouse for technical assistance.
Study design overview The economic analysis was performed from the perspective of the United Kingdom National Health Service and Personal and Social Services. The study population comprised non-neutropenic patients aged ≥16 years with confirmed C/IC receiving intravenous first-line treatment. As the study modelled data from the published literature, ethics approval and patient consent were not required. A decision analytic model was constructed in Microsoft Excel to estimate the potential treatment costs of anidulafungin versus comparator agents (Fig. 1 ). A decision tree was deemed to be the most appropriate model to use in this analysis due to the short time horizons associated with the treatment of C/IC. The model time horizon was the 6-week inpatient follow-up period with an extrapolation to an average patient's lifetime for those surviving the 6-week period.
Resource use Resource use was derived from United States database analysis of C/IC treatment clinical success and failure (Premiere Database, Pfizer, Data on File). Data were validated by clinical experts and were assumed to reflect current practice in the European Union and the United Kingdom. Length of hospitalisation differed between patients whose treatment was successful and patients whose treatment failed (Table  2 ). Most resource costs associated with antifungal treatment were assumed to be related to the length of bed stay, whereas other costs, such as laboratory costs, were assumed to be minimal and, therefore, were not modelled  [22].
Mortality All-cause mortality data were taken from estimates in the published literature for overall treatment  [19]. To accurately project drug-acquisition costs for the patients that died during therapy and those that completed therapy, the proportion of patients who died following treatment failure was determined using data derived from the study by Reboli and colleagues (Pfizer, Data on File). Among the modified intent-to-treat population, 34 % of anidulafungin-treated patients and 46 % of fluconazoletreated patients died during therapy (Pfizer, Data on File). The average of these two values (41 %) was used in the model for all agents. The average time to death in patients who died during the 6-week study period was assumed to be approximately 22. 8 days, based on a mean time to death of 22.
Discussion The relative cost of antifungal therapies has become an increasingly important issue in recent years due to growing concerns about the rising costs of healthcare and the lack of data demonstrating the superiority of one agent over another  [26]. Pharmacoeconomic analyses can play an important and useful role in the allocation of healthcare resources, and integrate the efficacy and safety data obtained from clinical trials, and healthcare resource use and quality-of-life information from the literature, expert opinion and analysis of databases  [27]. The pharmacoeconomic evaluation described in this paper applies to the treatment of C/IC in non-neutropenic patients from the United Kingdom perspective. Our model demonstrated that anidulafungin could be considered cost-effective compared with fluconazole in terms of life years gained with total costs below the generally accepted United Kingdom cost-effectiveness threshold (often referred to as society's willingness to pay for an additional unit of health gain, the 'quality-adjusted life year') of £20,000-£30,000  [28].
For imaging the closure dynamics of the gaps, patterns were microcontact printed on non-culture treated Petri dishes (Greiner) and blocked with 0. 2% Pluronics. Cells were seeded at high density and allowed to adhere for 1-2 h to completely fill the adhesive region of the pattern. Floating cells were washed off and the closure was imaged on a Biostation (Nikon). For closure of circular adhesive epithelial gaps by cell crawling, micropillar stencils removal assay was performed  10. The closure dynamics (contour of the non-adhesive gap) was obtained using the ABsnake plugin for Image J, fitted with an ellipse using MATLAB. For confocal imaging, patterning was done on glass bottom Petri dishes spin coated with a thin layer of polydimethylsiloxane (PDMS). Cells were imaged using a laser confocal microscope (Leica).
Acknowledgements We thank  A. J. Kabla ,  R. -M. Me  `ge,  W. J. Nelson  and group members from the  MBI  and the IJM for helpful discussions. We also thank  M. Ashraf  and  S. Vaishnavi  for the microfabrication and  F. Deshayes  for the gift of actin-GFP cell line. Financial support from the  European Research Council  under the European Union's  Seventh Framework Programme  ( FP7/2007-2013) / ERC  grant agreement  n°617233 , the  Human Frontier Science Program  (grant  RGP0040/2012 ),  Agence Nationale pour la Recherche  ( REGENR ANR-11-BSV5-0021 ) and the  Mechanobiology Institute  are gratefully acknowledged. B. L. and H. L. -M. acknowledge the  Institut Universitaire de France  and the  LABEX 'Who am I?'  for their support. X. T. acknowledges support by the  European Research Council  ( StG 242993 ) and the  Spanish Ministerio de Economı ´a y Comptetitividad  ( BFU2012-38146 ).
Participants Eighty-six young adults of both genders with DS, aged 16-34 years, with any of the three DS genetic variations (trisomy 21, mosaic, or translocation) were enrolled in the study, mainly through the Fundació Catalana de Síndrome de Down (Barcelona) a local foundation specialized in providing health care services and educational programs to participants with DS and their families. The data reported in the present work correspond to the baseline cognitive performance of a cohort of DS participants that participated in a clinical trial NCT01699711, that has been registered in https://clinicaltrials. gov/ct2/show/NCT01699711. All participants were drug free during the baseline assessment. Upon arrival at the research center (Hospital del Mar Medical Research Institute-IMIM), participants, parents and legal guardians (in case of legal incapacitation) were informed of the ensuing protocol and they gave their written informed consent before participating.
These included the assessment of verbal episodic memory (Cued Recall Test), executive components of inhibition (Cats and Dogs) and mental flexibility (Weigl Sorting Test). We also administered the child's version of the ToLDx for the planning task to avoid floor effects. The cognitive tests were presented in a fixed order to allow adequate intervals for delay trials on measures of episodic memory. In addition, parallel versions of episodic memory tests were used to control for learning effects. Regarding the tests selected from the CANTAB, only clinical versions were administered. To perform the comparison of our sample of DS participants with typically developed participants, test scores from normative data provided by the test publishers and normative studies for subjects of the same age range of our study (16-39 years) were employed.
(1) For the analyses of CANTAB tests, we used norms derived from 51 to 199 control subjects reported in the CANTAB standard norm database (see  Robbins et al. , 1997 Robbins et al. , , 1998 , for a description of part of these data 1. The Cambridge Cognition website http://www. cambridgecognition. com/technology provides a practical demonstration of the tests used). (  2 ) For the analyses of paper and pencil tests, we used normative data from 84 to 87 participants (18-34 years old) from the Spanish Multicenter Normative Studies NEURONORMA young adults Project;  (Peña-Casanova et al. , 2012). (  3 ) For the analyses of ToLDx results, as a child's version had been used, normative data from 76 participants (13-15 years) was selected  (Culbertson and Zillmer, 2005) , so that it better matched our sample.
Similar analyses could not be carried out for performance on verbal episodic memory, mental flexibility, and response inhibition, due to the lack of normative data from typically developed adults for these tests. This battery was developed, and is currently being used, in a longitudinal, randomized, double blind, placebo-controlled Phase II trial conducted by our research team in young adults with Down syndrome (the TESDAD study; De la  Torre et al. , 2014). In the present work, only baseline neurocognitive results from the TESDAD study are reported.
Statistical Analysis The first step consisted of a descriptive analysis of the sociodemographic and clinical parameters of all the participants at baseline. Descriptive analyses were also carried out for all neuropsychological variables, providing measures of mean, standard deviation, and maximum and minimum values in the case of quantitative variables. In order to detect the presence of significant ceiling or floor effects in the variables, frequencies and percent were computed. Variables in which more than 10% of the sample obtained the maximum or the minimum score, and/or exhibited a significant absolute skewness index (>2) were categorized as having ceiling or floor effects. We compared the DS group test scores of each cognitive variable to previously published normative data from agematched healthy controls.
Acknowledgments This work has been supported by the  Jérôme Lejeune Foundation (Paris, France ) the  Instituto Carlos III  ( ISCIII/FIS PI11/00744 ), and  Spanish Ministry of Education and Science  ( SAF2010-16427 ),  Spain. The  CIBER de Enfermedades Raras  and the  CIBER Fisiopatología de la Obesidad y Nutrición are initiatives of the ISCIII. The laboratory of MD  is supported by  DURSI  ( 2009SGR1313 ) and the laboratory of RTF by  DURSI  ( 2009SGR718 ). Dr. Susana de Sola  is a post-doctoral fellow from the  FRAXA Foundation. Laura del Hoyo  is recipient of a predoctoral fellowship from  ISCIII  [ FI12/00319 ]. We wish to thank  Fundació Catalana de Síndrome de Down (Barcelona, Spain)  for their assistance with recruitment of volunteers and for providing.
) chromatograph equipped with a FID. A split injector was used and the injected volume was 1 ll. The column used was a CP-Wax 52CB column (30 m • 0. 25 mm i. d. ; Varian Inc. , Middelburg, The Netherlands). The carrier gas was helium and the total gas flow rate was 1 mL/min. The initial and final column temperature was 170 and 230 °C, respectively, and the temperature was increased by steps of 4 °C/min. The injector and detector temperature was 230 °C. Data were processed using a Varian Star Workstation v 6. 30 (Varian Inc. , Walnut Creek, CA, USA). Results were expressed as the relative percentage of each individual FA present in the sample. Sterol composition: Sterol composition was determined using the NFT 60-254 method as previously described  (Hilali et al. , 2005). After trimethylsilylation of the crude sterol fraction, using a Varian 3800 instrument equipped with a VF-1 ms column (30 m; 9 0.
25 mm i. d. ) and helium (flow rate 1. 6 mL/ mn) as carrier gas a splitless injector was used and the volume injected set at 1 ll. Column temperature was isothermal at 270 °C, injector and detector temperature was 300 °C. Injected quantity was 1 lL for each analysis. Data were processed using a Varian Star Workstation v 6. 30 (Varian Inc. , Walnut Creek, CA, USA).
Patient Positioning Control and Study Parameters: CLD and ICM Interfraction movements were daily assessed using an electronic PI device. The portal images of the medial tangential beam treating the whole mammary gland were acquired before each of the 25 first fractions. The central lung distance (CLD) and the inferior central margin (ICM) (Figure  1 ) were measured on the first acquired portal image by the medical physicist and compared with the digital reconstructed radiography (DRR)  (6, 10). The CLD and ICM were defined to assess the interfraction variations along the anteroposterior and craniocaudal axes, respectively. The CLD and ICM were delineated on every daily portal image by the medical physicist. The measured data were then verified by both the medical physicist and the radiation oncologist.
According to the methods reported in previously published articles, the measurements were performed on portal images (Figure  1 ), so that the lateral shifts could not be quantified  (6, 7, 11, 12). The DRR, created from the simulation data, was the reference image for every radiotherapy session. The interfraction variations evaluation was based on the comparison of the CLD and ICM estimated on the daily portal images with the DRR data. Considering the CLD and ICM individually, the SD, random, and systematic errors were assessed. The SD was determined according to the formula reported by Fein et al. (6). The random and systematic errors were estimated using the methods published by Rosenthal et al. (13). The random error corresponds to the deviation of the data measured on the daily portal images from the mean values.
Statistical Analyses Quantitative data were expressed in mean values and SDs considering the sample size. Qualitative data were expressed in percentages. TP2 results were compared with those obtained from TP1 using a Wilcoxon test for the mean values as the variables were non-normally distributed, whereas qualitative data were compared using a chi-square test. Significance level was 0. 05. Statistics were performed using the Statistical Analysis System software SAS ® 9. 2 (SAS Institute Incorporation, Cary, NC, USA).
, 2010; Nakamura and Lipton, 2013; Sengupta and Holmgren, 2013). This PTM triggers conformational changes of proteins, can affect their activities, sub-cellular localization and interactions with partners. Over the past 20 years, thanks to the emergence of dedicated approaches such as the biotin-switch technique (BST, see below), over 3000 protein candidates for S-nitrosylation under normal and/or pathological conditions have been identified in animal cells  (Hess and Stamler, 2012). A database (dbSNO 2. 0) centralizing S-nitrosylated proteins collected from the literature is available at dbSNO 2. 0 http://dbSNO. mbc. nctu. edu. tw (Chen et al. , 2014). These proteins cover a wide range of cellular functions and include, amongst others, receptors, ion channels, signaling proteins, metabolic enzymes, proteases, chaperones, and structural proteins (as examples see  Seth and Stamler, 2011; Nakamura et al.
Third, enzymatic denitrosylation mechanisms occur through Trx and GSNO reductase  (Malik et al. , 2011; Kneeshaw et al. , 2014). In recent investigations,  Kovacs and Lindermayr (2013)  and  Chaki et al. (2014)  focused on the structural features of Snitrosylation sites of plant proteins. For this purpose, the authors performed a computational prediction of S-nitrosylation sites of plant proteins experimentally found as S-nitrosylated and for which the corresponding Cys residue(s) have been identified by MS analysis. The programs GPS-SNO, SNOSites, and iSNO-PseAAC were used. The programs all predicted Snitrosylation sites in those proteins. However, the number of Cys residues and their identity differed according to the computational programs. The GPS-SNO best matched the MS analysis. This performance confirmed a previous work demonstrating that amongst 485 potentially S-nitrosylated proteins collected from PubMed, the GPS-SNO program predicted at least one putative S-nitrosylation sites in 74% of them  (Xue et al.
, 2010). Another in-depth analysis of the structural features of plant S-nitrosylated proteins was provided by  Fares et al. (2011). Using the Motif-Xalgorithm (http://motif-x. med. harvard. edu/) extracting overrepresented patterns from a sequence data set, these authors screened for motifs flanking S-nitrosylated Cys-residues (± 10 residues) amongst 53 proteins found to be constitutively regulated by this PTM in Arabidopsis thaliana. Three motifs involving hydrophobic residues were found (A-X(9)-C, C-X(6)-G, and C-X(2)-I). Interestingly, at least one of these motifs was detected in about half of 121 proteins that were previously identified as putatively S-nitrosylated in other studies. Amongst the selected proteins, 38 sites for S-nitrosylation were also predicted using the program SNOSite.
Identification of the Cys residues of interest is also required to further characterize the physico-chemical, biochemical and structural features of S-nitrosylation sites. In addition, this approach will enrich the current databases centralizing S-nitrosylated proteins and, consequently, will help in defining parameters that must be fed into computational prediction of S-nitrosylation sites. Such combinations of proteomic-scale approaches with bioinformatics tools could therefore hold great promise for the elucidation of NO functions in plant cells. Another issue concerns the quantitative aspects of the BST. So far, few studies provided a quantitative analysis of S-nitrosylated plant proteins. This might be partly explained by the fact that in most of the studies published so far, S-nitrosylation has been investigated through the use of NO donors delivering doses of NO beyond the range of physiological concentrations.
ACKNOWLEDGMENTS Our work was supported by the  Burgundy region PARI AGRALE 8 project , the  University of Burgundy Bonus Qualité Recherche project  and the  ANR PIANO  ( Sébastien Aimé ,  Angélique Besson-Bard ,  Siham Hichami ,  Olivier Lamotte  and  David Wendehenne ), by the  CAPES-COFECUB program  Sv  785-13  (all the authors). We thank our colleague  Hoai-Nam Truong  for her careful reading of the manuscript.
For incident/dynamic AUC(t), semi-parametric methods using a Cox model have been proposed to estimate incident sensitivity and dynamic specificity, while standard numerical integration techniques are used to compute an estimate for AUC I,D (t). Non-parametric methods have also been proposed  [14]. Most of these estimators have been made available in standard softwares such as R  [15]  with the timeROC, risksetROC, survivalROC and survAUC packages  [16, 17, 18, 19].
ILLUSTRATING EXAMPLE We used prospectively recorded data to assess the prognostic value of biomolecular markers in acute myeloblasticleukaemia (AML). This cohort study was nested into a randomised controlled trial that showed the event-free survival and overall survival benefit of gemtuzumabozogamicin (GO) during induction and consolidation in AML patients aged 50-70 years (ALFA-0701 study)  [20]. We used three biomarkers based on analysis of karyotype by single nucleotide polymorphism array (lesions of SNP-A) or molecular analysis (DNMT3A mutation, or NPM1 mutation), all measured at baseline as potential predictors of death. Among the 278 patients enrolled in the study, 131 died during follow-up, with 1-year and 2-years overall survival rates estimated at 71. 3% (95%CI: 66. 1% -76. 8%) and 48.
4% (95%CI: 42. 1% -55. 7%), respectively and median survival of 22. 2 months. Table  1  reports the estimated hazards ratios of death (data truncated at 2 years) of these biomarkers, which exhibit varying strengths of association with binary covariates from 1. 4 (NPM1 wild type) to 2. 5 (SNP-A lesions). We further assessed the discriminative value of these biomarkers, first based on the AUC C,D (t) computed for increasing values of time using the timeROC R package as illustrated in Figure  1  (upper panel). There were some surprising findings. First, at some specific time points, there was no direct relationship between the value of the AUC C,D (t) and the estimated HR for binary covariates. For instance, while the estimated HR of SNP-A was higher than that of  DNMT3A, the AUC C,D (t) associated with DNMT3A was sometimes higher than that of SNP-A.
Material and Methods The procedures followed were in accordance with the Declaration of Helsinki, and samples were obtained following patients' written informed consent. The data bank is registered with the number # 1255461in the CNIL (national data protection agency) and an ethical approval was obtained by the institutional ethics committee "Comité de Protection des personnes EST I". Prior to analysis, all samples were anonymized and de-identified. A total of 298 ET patients from the haematology laboratory, diagnosed according to 2008 WHO diagnostic criteria  [13]  at the University Hospital of Dijon, France, were retrospectively studied. Purification of granulocytes and peripheral blood mononuclear cells (PBMCs) and extraction of DNA were performed as previously described  [14]. The JAK2V617F mutation was analysed by allele-specific real-time quantitative PCR to estimate the JAK2V617F mutated allele burden according to the method published by Lippert et al.
To do so, we used the neuroinformatics platform for large-scale brain simulations, called The Virtual Brain (TVB)  [3]  and developed a preprocessing pipeline to incorporate experimental data (e. g. , structural MRI, diffusion-weighted MRI) in TVB  [4]. We prepared ten individual models based on ten randomly selected subjects from the Human Connectome Project dataset  [5]. For each individual model we performed simulations under two conditions during rest: (i) noise driven, using a bistable neural mass model, and (ii) after stimulation, using an excitable neural mass model. We investigated the effect of heterogeneous and homogeneous connectivity on large-scale brain dynamics by different numbers of regions in the parcellation (70 to 2240) and by varying the local connectivity coupling strength.
acknowledgments Authors' contributions: BF and MC have made substantial contributions to conception and design. BF wrote the manuscript. BF, GAvK, BV, and MC have made substantial contributions to the final manuscript. All authors read and approved the final manuscript. Conflict of interest statement: All the authors of the present work are partners of the SPRINTT consortium, partly funded by the European Federation of Pharmaceutical Industries and Associations (EFPIA). Dr. Cesari served as consultant for and/or received honoraries for scientific presentations from Nestlé, Novartis, and Pfizer;.
Analysis of the stained images was conducted using Image Pro Plus software (version 6. 1). For each animal the average score was used for statistical analysis. Multiplex gene expression analysis. Gene expression of fetal femur articular cartilage was detected by Multiplex gene expression analysis, which included 3 housekeeping and 12 target genes and was run on the GenomeLabGeXP Genetic Analysis System (Beckman-Coulter) using the GenomeLab TM eXpress Profiler software (Beckman-Coulter, Fullerton, CA)  59. Multiplex optimization (e. g. , primer validation and attenuation) was completed according to the manufacturer's instructions. Briefly, a primer pair was considered valid if only one PCR product of less than one nucleotide differed from its predicted size after being run on the GenomeLabGeXP Genetic Analysis System 59.