dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We thank  A. Danielson ,  M. Dorfman ,  I. Gomez-Caraballo ,  B. Kousari ,  M. Ledo ,  Dr N. Srivastava ,  M. Stewart  and  P. Wettenstein  for technical assistance, and  H. Rieiro  for his comments. This study was supported by a challenge grant from  Research to Prevent Blindness Inc. to the  Department of Ophthalmology at SUNY Downstate , the  Empire Innovation Program (Awards  to S. L. M. and S. M. -C. ), the  Barrow Neurological Foundation  (Awards to S. L. M. and S. M. -C. ), Mrs. Marian Rochelle  (Award to S. L. M. ), the  Science Foundation Arizona (Award CAA   0091-07  to S. L. M. ) and the  National Science Foundation  ( Awards 0643306 ,  0852636  and  113786  to S. M. -C. and Awards 0726113 and  1523614  to S. L. M. ). X. G. T. was a Fellow of the  Caja Madrid Foundation (Spain).
Study Selection A systematic literature review was conducted to identify economic evaluations of vertebroplasty and kyphoplasty. Relevant studies were identified from the following databases: MED-LINE, PASCAL, COCHRANE and the National Health Service Economic Evaluation Database (NHS EED) at the University of York. Searches were undertaken in March 2014, with no limitations concerning publication date. The search strategy was developed in MEDLINE and was then adapted for the other databases. The search terms employed included: Cementoplasty/ economics[Mesh]; "Costs and Cost Analysis"[Mesh] AND "Cementoplasty"[Mesh]; "Economics"[Mesh] AND "Cementoplasty"[Mesh]; cost[Title/Abstract] AND kyphoplasty[Title/ Abstract]; cost[Title/Abstract]) AND vertebroplasty[Title/Abstract]. We are aware that "cementoplasty" is a broad term encompassing vertebroplasty and kyphoplasty, but also other procedures, such as osteoplasty and sacroplasty.
Data Collation and Analysis We used two different methods to evaluate the level of evidence provided by the studies included. This methodology was inspired by previous works on the quality of economic evaluations in healthcare  [13]. First, we considered the extent to which the study complied with methodological recommendations from internationally recognized guidelines published by Drummond et al. and generally referred to as the British Medical Journal (BMJ) checklist  [14, 15]. These recommendations provide general guidance about the way in which the results of economic evaluations should be reported. The authors are required to indicate the study perspective (the point of view from which the study is conducted), to provide a description of comparators, to specify the type of costs used for the analysis, to report the incremental cost-effectiveness ratio (ICER), to perform uncertainty analysis and to disclose funding sources.
Using this method, two researchers (CD and NM) extracted the following data independently from each of the studies included: authors' names, publication year, country of origin, type of economic evaluation, perspective, time window of the study, description of comparators, type of costs used, ICER calculation, uncertainty analysis and source of funding. The different types of economic evaluation carried out were classified as follows: (i) partial economic evaluation (PEE), (ii) cost-minimization analysis (CMA), (iii) cost-effectiveness analysis (CEA), (iv) cost-utility analysis (CUA) and (v) cost-benefit analysis (CBA)  [14]. The studies were considered to include a PEE if the comparison did not include both the costs and consequences of therapeutic strategies  [14]. By contrast, CMA, CEA, CUA and CBA were considered to be full economic evaluations.
Quality of the Data Sources Used in the Economic Evaluations Reviewed We used the hierarchy scale of Cooper et al. to classify the data sources used in the 21 studies included. The details of this analysis are shown in Table  3. The data sources for determining clinical effect sizes and safety were of the highest level of quality (A) for 12 studies (57%), whereas one study (5%) used data sources of poor quality (C). For the baseline clinical data, nine studies (43%) used poor-quality data (level C). Six of these nine studies did not indicate their sources. Only one (5%) study specifically analyzed administrative databases covering patients from the jurisdiction of interest. The data sources used to analyze resource use were of high quality for almost all studies, as 19 studies (91%) used level A information sources.
The data sources for determining costs were also generally of high quality, with 15 studies (71%) using information sources of ranks 1 and 2. Nevertheless, the data used in two studies (10%) were extracted from level C data sources, and one of these two studies did not clearly state the sources of the information used. By combining the two analyses, we focused on the quality of evidence used by the three CEAs in complete accordance with methodological recommendations. One study used sources from level A for each data component except for the determination of baseline clinical data, but this was not clearly stated in the paper. Another study used level A sources for all data components except clinical effect size and safety, for which the data were extracted from sources with a rank of 4 (level B).
Again, very few of the CEAs included proposed a sensitivity analysis, and this rendered the results difficult to interpret. It is difficult to determine whether ICER and/or sensitivity analyses were not provided due to missing data or due to an inability of the authors to perform such analyses correctly. The rationale behind the decision not perform such evaluations was only very rarely explained. Total costs were thus analyzed from a societal perspective in only a minority of studies. Such evaluations should, as far as possible, be carried out from a societal perspective when assessing the overall costs of the interventions. In the case of vertebroplasty and kyphoplasty, the use of a societal perspective is particularly relevant because productivity losses are a major component of the impact to be assessed  [38].
For example, it would have been useful to know whether the final version of the manuscript had to be approved by the sponsor before its submission  [40]. The quality of the data sources used for the economic evaluations was generally high. However, this observation might conceal significant differences between data components. For example, information on resource use was determined with high-quality data in almost all studies, whereas the sources of baseline clinical data were frequently of poor quality or not stated. One possible explanation for these discrepancies is that some data are undoubtedly harder to obtain than others, particularly for medical devices  [42]. For example, it is difficult to account for all the cost items associated with medical device use, because these products often have far-reaching consequences for organization affecting many components  [4].
Finally, this review has several limitations worthy of discussion. First, we restricted the selection of studies to those written in French and English. This led to the elimination of two studies written in German that were potentially relevant for our analysis. We used several databases, but some economic evaluation studies are probably published in data sources other than scientific journals. In this review, we focused exclusively on articles published in scientific journals and did not include economic evaluations from gray literature. Finally, assessment of the quality of economic evaluations is difficult and can be subjective. This point has already been highlighted by a number of authors  [50, 51].
Acknowledgements We would like to thank the  University of Athens , the  University of Bern , the  École Polytechnique  and the  University of Thessaloniki , where the workshop Aspects of fluid/gravity correspondence was organized. All these institutions have provided hospitality and finan- cial support during our collaboration meetings. We also thank our colleagues  M. Caldarelli ,  C. Charmousis ,  A. Gorantis ,  N. Halmagyi ,  R. Leigh  and  D. Klemm  for useful discussions. The research of J. Gath is supported by  VILLUM FONDEN  research grant  VKR023371. Ayan Mukhopadhyay  and  A. C. Petkou  are supported in part by  European Union 's  Seventh Framework Programme  under grant agreements ( FP7-REGPOT-2012-2013-1 ) no  316165 , the  EU-Greece program Thales   MIS 375734. Their research is also co-financed by the  European Union (European Social Fund ,  ESF ) and Greek national funds through the  Operational Program Education  and  Lifelong Learning  of the National Strategic Reference Framework (NSRF) under Funding of proposals that have received a positive evaluation in the 3rd and 4th Call of  ERC Grant Schemes.
The work of  A. C. Petkou  is partially supported by the re- search grant ARISTEIA II, 3337, Aspects of three-dimensional CFTs, by the  Greek General Secretariat of Research and Technology , and also by the CreteHEPCosmo-228644 grant. The research of K. Siampos is supported by the  Swiss National Science Foundation. Jakob Gath ,  P. M. Petropoulos  and  K. Siampos  acknowledge the  Germaine de Stael  francoswiss bilateral program 2015 (project no  32753SG ) for financial support.
Acquisition of RAS mutations as a mechanism of resistance Some patients develop RAS mutations during therapy with anti-EGFR monoclonal antibodies  [51] [52] [53]. For example, among 24 KRAS wild-type patients who received treatment with panitumumab, 9 developed KRAS mutations during therapy, typically within 6 months of initiation of therapy  [52]. Development of such mutations during therapy may be a result of expansion of KRAS-mutant subclones present before initiation of therapy and may represent a potential mechanism of resistance to anti-EGFR therapy  [52]. Preclinical studies have suggested that combined anti-EGFR and MEK inhibition might overcome such resistance  [54] , and this hypothesis is being evaluated in ongoing clinical studies (ClinicalTrials gov identifier, NCT01750918).
In the PRIME study, the presence of BRAF mutations did not appear to be associated with lack of treatment effect to panitumumab  [44]. Similarly, BRAF mutations were not predictive for the treatment effect of cetuximab in the CRYSTAL study, but were associated with poor prognosis  [59]. Careful consideration should be given to enrollment of patients with BRAF mutant tumors into clinical trials to address this high unmet need. It is encouraging to note that early phase prospective studies are currently evaluating novel treatment combinations of anti-EGFR monoclonal antibodies and BRAF inhibitors in patients with BRAF mutant mCRC (ClinicalTrials gov identifiers, NCT02164916; NCT01750918).
RNASeq reveals skipping of PIGH exon 2 and pinpoints an intronic mutation as the likely causative variant The findings described in the previous paragraph suggested that the causative mutation was either regulatory or affecting splicing otherwise. To pursue this hypothesis, we took advantage of available RNASeq data (cfr. M&M) from liver (83 Mb uniquely aligned) and cerebral cortex (105 Mb) of a 60-day post fertilization Belgian Blue fetus shown by SNP genotyping to carry the arthrogryposis risk haplotype. Sequence reads were analyzed using TopHat and Cufflinks  [6]  and predicted transcripts mapping to the arthrogryposis locus visualized in the IGV browser  [7]. We readily noticed skipping of the second exon of approximately half (20/45) of the PIGH (phosphatidylinositol glycan anchor biosynthesis class H) transcripts (Figure  3A ).
RNAseq data generation and analysis As part of a companion project, bovine embryos were produced by directed mating between a sire carrier for the arthrogryposis haplotype and a wild-type cow. A panel of tissues -including pituitary, cerebral cortex and liverfrom two embryos diagnosed as carrier based on a haplotype test, were collected at 60 days post fertilization (dpf); total RNA was extracted and cDNA librairies were produced using the TrueSeq mRNA kit from Illumina, following manufacturer's instructions. Equal amounts of each indexed library were combined and sequenced 2X100bp on one lane of a HighSeq2000 instrument. Transcriptomes were analyzed using the RNASeq tool kit TopHat and Cufflinks  [6]. Mapped RNASeq reads for the carrier embryo were visually evaluated in IGV (Integrative Genome Browser)  [7].
Sequence traces were aligned and compared to bovine cDNA sequence using the Phred/Phrap/Consed package (http://www. phrap. org/phredphrapconsed. html). 5′ exonuclease diagnostic assay of the PIGH c211-10C > G splice acceptor site mutation A 5′ exonuclease assay was developed to genotype the PIGH c211-10C > G mutation, using 5′-ATG GCA GCA GAG AGG ATC ATG -3′ and 5′-GGA GTT GAC TTA TTA ACC AGC AGA GA -3′ as PCR primers, and 5′-TGT CTG GCT [C]TC TCT TC-3′ (wild type C allele) and 5′-TCT GGC T[G]T CTC TTC -3′ (mutant G allele) as probes (Taqman, Applied Biosystems, Fosters City, CA). Reactions were carried out on an ABI7900HT instrument (Applied Biosystems, Fosters City, CA) using standard procedures. They will be publicly available with the next dbSNP Build (B145), planned for fall, 2015. Additional files 6 and 7 provide respectively the list of "ss" numbers, genomic positions (Bos taurus assembly: BosTau6/UMD3) and the list of corresponding sequence variations.
Acknowledgements We are grateful to the breeders and practitioners for their collaboration and to the  Walloon Breeding Association (AWE)  and the  Belgian Blue Beef Herd-Book (HBBBB)  for pedigree data. We also thank all the members of  INRA experimental units , especially  Alexandre Neveux ,  Valérie Gelin ,  Céleste Le Bourhis ,  Nicolas Stadler ,  Johann Kergozien ,  Gilles Gomot ,  Jean-Philippe Dubois  for cow management (breeding, ultrasound scanning, and euthanasia). TD and CC are respectively Research Associate and Senior Research Associate of the  Fonds National de la Recherche Scientifique (Belgium). This work was funded by grants from the  Walloon Ministry of Agriculture (Rilouke) , the  Belgian Science Policy Organization (SSTC Genefunc PAI)  and the  University of Liège.
Lactococcus lactis was cultivated in M17 medium supplemented with 0. 5% glucose in 100 mL Schott bottles at 30 °C. Lactobacilli were grown at 37 °C with limited aeration in de Man, Rogosa, Sharpe (MRS) broth in 100 mL Schott flasks while E. coli was grown at 37 °C in LB medium and B. longum was grown anaerobically in MRS broth supplemented with 0. 05% L-cysteine-hydrochloride (Sigma, St Quentin Fallavier, France). Yeasts and fungi were grown in 100 mL of potato dextrose broth in 500 mL Erlenmeyer flask, at 25 °C and shaken at 200 rpm. All strains were grown until the late stationary phase (as measured in preliminary growth experiments; data not shown). The reference strain preparations were prepared as follows: stationary-phase microbes were washed twice in PBS and resuspended in PBS containing 20% glycerol to adjust the cell density to McFarland 3 using a portable photometer (Densimat, bioMérieux, Craponne, France)  (Araujo, Rodrigues, & Pina-Vaz, 2004 ).
2 µl from dilutions of the first PCR mixtures (94 • C, 3 min; 32 cycles of 94 • C, 45 s; 60 • C, 1 min; 72 • C, 18 s; and elongation at 72 • C, 10 min). PCR products of three independent reactions were pooled in equal volumes and purified by employing the Wizard SV Gel and PCR Clean-Up System (Promega, Madison, USA). Sequence libraries were generated by a paired-end approach using the Illumina MiSeq platform (Eurofins MWG, Ebersberg, Germany). The nucleotide sequences are available in the European Nucleotide Archive (www. ebi. ac. uk/ ena) under the accession number PRJEB8107. Data analysis was performed by employing the open source software package QIIME 1. 8  (Caporaso et al. , 2010a). Sequencing reads with more than three consecutive low quality base calls (Phred quality score ≤ 20) were truncated at the position where their quality began to drop, and only reads with >75% consecutive high quality base calls, without any ambiguous characters, and longer than 200 nucleotides in length were retained for further analyses.
All quality sequences were adjusted in the same orientation and clustered into operational taxonomic units (OTUs) with uclust  (Edgar, 2010) , using 3, 5, and 10% dissimilarity thresholds. From each OTU the most abundant sequence was selected as the representative one, and the taxonomy of the representative set was assigned with the uclust-based consensus taxonomy assigner using an 80% confidence threshold. The representative sequence set was aligned with PyNAST  (Caporaso et al. , 2010b). Chimera check was performed with ChimeraSlayer and potentially chimeric sequences were discarded. OTU tables at the different dissimilarity levels were constructed, and OTUs not assigned to the class of Gammaproteobacteria as well as singletons were removed from the dataset. For alpha and beta diversity analyses, OTU tables were rarefied at 13,610 reads.
Diversity indices Shannon  (Shannon, 1997)  and Chao1  (Chao and Bunge, 2002)  were determined based on the normalized clustering data. Significant differences were calculated with PASW Statistics 18 (SPSS Inc. , Chicago, IL, USA) using Tukey and Games-Howell post hoc tests, depending on the homogeneity of variances. Beta diversity was analyzed based on weighted UniFrac distances  (Lozupone et al. , 2007)  and 10 jackknife replicates of the total rarefied datasets. Statistical analyses were performed using the adonis test with 999 permutations. Taxonomy based ring-charts were created with Krona 2. 2  (Ondov et al. , 2011). Profile clustering network analyses were performed in order to highlight single taxonomic groups corresponding to genus level (OTUs at a dissimilarity level of 3% summarized at taxonomic level 6) with considerable differences between banana plants grown in Nicaragua and in Costa Rica and between those grown with and without associated trees.
Representative images corresponding to the quantification of cell infiltration are shown in Fig  3D. We next analyzed the cellular composition of the immune inflammatory infiltrate by determining gene expression of surface markers characteristic of various immune cell populations by qRT-PCR and normalizing the data from infected animals respect to non-infected controls. In agreement with histological findings, infection in COX-2 -/-mice compared to COX-2 +/+ mice, led to lower expression of the common leukocyte marker Ptprc (CD45) as well as of Cd4, Cd8, Cd68, and Itgax (CD11c) as markers of T helper cells, cytotoxic T cells, macrophages and dendritic cells, respectively  (Fig 4A). To characterize the immune response in hearts of COX-2 -/-infected mice, gene expression of chemokines and cytokines were analyzed.
Nine pictures of different sections, separated by at least 50 μm, per heart were taken. The degree of inflammatory-cell infiltration was quantified using the Fiji package  [39]  and the plugin Trainable Weka Segmentation developed by Ignacio Arganda Carreras (Versailles, France)  [39]  (Image J macro used for automated image analysis is detailed in S1 File) and expressed as the percentage of the nuclei/tissue area ratio.
Blocking of unspecific secondary antibody binding was achieved by addition of 2% of normal serum of the species in which the secondary antibody was raised. As a negative control, sections were treated in the same manner, except that incubation with primary antibody was omitted. Nuclei were stained using 1 μg/ml of DAPI (268298, Merck). Prolong Gold Antifade Reagent (Invitrogen) was used to mount the slides that were kept at 4°C until observation. Stained slides were observed with the confocal laser scanning microscope LSM710, coupled to an AxioimagerM2 microscope (Zeiss). The micrographs were processed using the software ZEN (Zeiss) or the Fiji Package. Isolation of Ly6G + and CD11b + Ly6G -cells by magnetic sorting BALB/c (n = 15) or C57BL/6 mice (n = 15) were infected i. p. with 2,000 trypomastigotes of the Y strain.
Statistical analysis For in vivo experiments, data are shown as means ± SEM. All the in vitro experiments were performed at least three times. Significance was evaluated by Student's t-test when two groups were compared. ANOVA one way followed by Tukey post-test was used when groups of samples from an experiment had different time points. ANOVA two way followed by Bonferroni post-test were used when the experiment included time and mice strain as variables. For survival analysis, we used Gehan-Breslow-Wilcoxon method. GraphPad Prism 5. 00 software (La Jolla, CA, USA) was used for statistical analysis.
Acknowledgments The authors would like to thank  Beatriz Barrocal  for taking care of the animals and  Maria A. Chorro  and  Maria C. Maza  for their excellent technical assistance. We thank  Dr. Alejandro Pascual  and  Dr. Laura García-Bermejo  from the  Ramón y Cajal Hospital  for their precious help with the histologic analysis. We also thank the personal of the  Confocal Microscopy Service (S. M. O. C. ) at the CBMSO  for their excellent assistance.
Then, the analogue data from all channels is digitized by an Analog-to-Digital Converter (ADC). Finally, a pure digital electronics card, the FEMINOS board  [47] , gathers ADC data, performs the pedestal subtraction and sends them to the data acquisition (DAQ) system by means of an ethernet connection. Special attention has been given to grounding in the electronics design: signal paths are surrounded by a ground layer at the detector, the interface card and the flat cables to avoid any coupling; the AFTER-based cards and the preamplifier are fixed to the inner part of a Faraday cage to minimize induced noises and each of the high voltage lines has a dedicated low-frequency filter to dim ripples from HV sources. The 3D reconstruction of an event is made combining the strip pulses, whose temporal position determines the z axis, and the detector decoding, used for the spatial coordinates, x and y on the detector plane.
3). A spot-calibration can be seen in Figure  14. An intensity map is shown on the left, while on the right, the energy spectrum acquired during such a calibration is plotted. The higher end of the spectrum is suppressed due to the drop in efficiency of the optic at these energies. Reference runs with the x-ray finger were performed just after the alignment of the system, before and after the sunrise detector shielding was in place. The low count rate from the source at such a distance enforces runs of approximately 8 h in order to collect data with significant statistics. For this reason, spot-calibration runs cannot be taken very often so as not to disturb the normal data-taking program of the experiment. Two more spot-calibration runs were performed, one after the installation of the sunset Micromegas detectors and their shielding at the opposite end of the magnet and one after the data taking period, in mid-November 2014.
The installation, commissioning and first calibration data have been described in detail. The expected specifications, in terms of spot size and throughput, agree with first experimental data. The background level of the detector has once more improved over previous designs, reaching a value of (1. 0 ± 0. 2)×10 -6 keV -1 cm -2 s -1 , the lowest achieved at CAST so far; this value corresponds to 5. 4×10 -3 counts per hour in the energy RoI and signal spot area. This performance translates to the best signal-to-noise ratio by far obtained by any detection system of the CAST experiment, and will contribute to push the sensitivity of the experiment for the ongoing data taking campaign in 2015. The system has been conceived as a technological pathfinder for the future International Axion Observatory (IAXO), as it combines two of the techniques (optic and detector) proposed in the conceptual design of the project.