dataesr/scientific-paragraphs-categorization huggingface dataset:
Separate interim analyses were planned for patients with and without FGF pathway amplifications, owing to the faster enrollment expected for the FGF pathwaynonamplified subgroup. The first interim analyses occurred when 36 PFS events had been documented in the FGF pathway-nonamplified subgroup, and the second interim analysis occurred when ≥10 (20%) of 50 PFS events had been documented in the FGF pathway-amplified subgroup. The intent of these interim analyses was to assess the efficacy or futility of the study treatment. If the futility criteria were met (HR >0. 81 in the first interim analysis; HR >0. 7 in the second interim analysis), the study could be terminated early by the data monitoring committee. The key secondary endpoint, ORR, was summarized as a percentage rate with 95% CI. OS was estimated using Kaplan-Meier analysis for each treatment arm; patients still alive at the time of analysis were censored at the last contact date.
Patient demographics From 15 May 2012 to 26 November 2014, a total of 97 postmenopausal patients with HR + , HER2 -locally advanced or metastatic breast cancer that had progressed during or after hormone therapy were enrolled in 36 centers. The last patient's last visit was on 3 April 2015. All patients received fulvestrant; 47 were randomized to receive dovitinib and 50 were randomized to receive placebo (Fig. 1 ). Overall, 31 patients were classified as FGF pathway amplified (15 in the dovitinib arm vs 16 in the placebo arm); 725 patients were screened to enroll 31 FGF pathway-amplified patients. Although the data monitoring committee recommended continuing the study after 2 interim analyses, it subsequently recommended early termination of the study on 30 October 2014 due to lower than anticipated frequency of FGF pathway amplification and slow enrollment of patients with FGF pathway-amplified status.
Currently, researchers in a phase Ib trial (ClinicalTrials. gov identifier: NCT01928459) are investigating the pan-FGFR inhibitor BGJ398 in combination with the selective PI3K inhibitor alpelisib (BYL719) in patients with solid tumors with FGFR1, FGFR2, and FGFR3 alterations and phosphatidylinositol 4,5-bisphosphate 3kinase catalytic subunit α mutations. Thus, further exploration of the use of FGFR inhibitors in combination with other agents is warranted. The present study was terminated early because of slow accrual. The rates of FGF pathway amplification observed in this study were lower than previously reported. In the previous phase II monotherapy study, 10% of the patients screened who were enrolled in the study had FGFR1 amplification  [38] , whereas approximately 5% of patients screened and randomized in this study had FGF pathway amplifications.
A novel idea to increase rapid recruitment of patients with rare molecular markers is to develop molecular screening programs that screen several genes at a time in a large patient pool, using next-generation sequencing assays, and then to guide patients to specific clinical trials on the basis of their specific biomarkers  [52, 53]. One example is the National Cancer Institute's Molecular Analysis for Therapy Choice (NCI MATCH) trial (ClinicalTrials. gov identifier: NCT02465060); patients are screened for approximately 200 genes, assigned to a study arm on the basis of a molecular abnormality, and followed for response and PFS  [52]. The NCI MATCH study currently includes 24 arms, in one of which investigators are evaluating the FGFR inhibitor AZD4547 in patients with FGFR pathway aberrations (FGFR1-FGFR3 amplification, mutation, or translocation).
Acknowledgements We thank  Alejandro Yovine ,  Seven Gogov ,  Andrea Kay ,  Ying Wang , and  Beth McGrain  for their involvement in the study design, statistical analysis, and data analysis. Editorial assistance was provided by  Pamela Tuttle, PhD , CMPP, and  Katherine Mills-Luján, PhD , of  ArticulateScience LLC  and was funded by  Novartis Pharmaceuticals. This study was previously reported in abstract and poster format at the American Society of Clinical Oncology 2012 and 2013 congresses in Chicago, IL,  USA , and at the  American Association for Cancer Research San Antonio Breast Cancer Symposium in San Antonio, TX, USA , in 2012.
The large difference in litter mass added to the litterbags resulted from interspecific differences in leaf size (mean AE SD: 108. 6 cm 2 AE 50. 3; min. : 55. 6 cm 2 ; max. : 195. 3 cm 2 ) and leaf volume (leaf size 9 thickness; 1. 84 cm 3 AE 0. 8; min. : 0. 8 cm 3 ; max. : 3. 1 cm 3 ; data of specific mean leaf size taken from Kraft and Ackerly 2010). We did not collect the largest leaves (e. g. , from M. malacocalyx or N. viburnoides species), as we wanted to avoid having litterbags with dramatically higher leaf-litter mass with a comparable number of leaves (two to five). Litterbags were set in groups of five treatments, each with a randomized set of species, in a 50 9 80 m grid-type plot (see Appendix S6: Fig. S1  for details). Mesh bags were collected for analyses after 104 days of decomposition (mass loss of ~58% on average for the same eight species after 103 days, see C ardenas 2013).
2008 ). Ward's method was chosen as it has been shown to produce more clearly defined clusters than does average linkage  (Pla et al. 2012). Cluster analysis was performed using InfoStat v. 2012 software (InfoStat Group, Córdoba, Argentina) with default program data standardization  (Di Rienzo et al. 2012). Description of the structural and functional organization of soil invertebrate communities. -Using data from all samples combined, we first used rank plots  (Magurran 2004 ) to describe the community structure of Yasun ı soil fauna in relation to abundance (Appendix S2) at the levels of Order and morphospecies. Morphospecies rank plots were also used to compare, in detail, the relative abundance of the different functional groups of soil fauna that make up the invertebrate community. Additionally, following Preston's (1948) boundaries of octaves as a measure of the degree of commonness, we classified the number of species per functional group in relation to its abundance in eight categorical ranges.
Finally, data were fitted to lognormal (equations of the form y ¼ a Â e ðÀ0:5ðlnðx=bÞcÞ 2 Þ , where a is the intersection with the y-axis and b and c are parameters of the slope expression) and logarithmic (for mesoregulators only) distributions using Table Curve 2D software v. 5. 01 (Systat Software Inc. , San José, California, USA). Rarefaction "sample-based" accumulation curves were used to compare the efficacy of different sampling methods used in the same area  (Sanders 1968 , Longino et al. 2002 , Ellison et al. 2007 ) and to assess whether pitfall traps and Winkler extractions reached an asymptote for species richness and functional groups. For this, we used Past v. 3. 07 software (Oslo, Norway;  Hammer et al. 2001 ) that implements the analytical solution in which standard errors are transformed in AE95% confidence intervals.
Soil invertebrate spatial heterogeneity The Sørensen similarity index showed that species identity in the soil food web was heterogeneous at all spatial scales. In a range between 0 and 1, where 1 means full similarity, all functional groups showed values <0. 165 (mean AE SD): herbivores (H): 0. 065 AE 0. 18; predators (P): 0. 057 AE 0. 15; litter transformers (LT): 0. 163 AE 0. 16; Os: 0. 135 AE 0. 17; mesoregulators (Me): 0. 111 AE 0. 20; Pds: 0. 04 AE 0. 14 (Fig. 7 ). Fig. 7  shows that approximately the same levels of heterogeneity were found in small and large sampling areas, especially for litter transformers and omnivores. In Appendix S8, where we considered the full dataset, similarity indexes were plotted and analyzed using four different components of biodiversity: morphospecies identity, abundance, functional group allocation, and biovolume.
39). There was one significant difference between mesh treatments when the averaged pooled dataset was analyzed (Appendix S11). We found that mass loss was larger in the coarser mesh treatment T5 compared with the finer ones T1 and T2 (Dunn's z T1vs. T5 = 2. 57, P = 0. 010; Dunn's z T2vs. T5 = 2. 61, P = 0. 001; Appendix S11: Fig. S1 ). This is in line with GLM results that show a general positive and significant effect of mesh size treatments over leaf-litter decomposition (Table  4 ). Finally, t-test comparisons of weighted and arithmetic means for the eight species showed no significant differences (P = 0. 853; Appendix S9). Principal components analysis of 22 nutrient contents has shown that Ca, K, Mg, and S were the factors explaining most of the variance among species (PC1 = 69. 57%; PC2 = 24.
2014). Our experiment highlighted how resources are exploited following non-random, gradual extinction of larger soil detritivores in a natural scenario. Results suggest that the different body size classes in a detritivore community (averaged across the pooled dataset) played a redundant rather than complementary role in fragmenting leaf litter for five of the eight plant species treatments  (Andr en et al. 1995 , cf. Nielsen et al. 2011). Our pooled dataset also fitted to a linear regression (P = 0. 058, with a slope of 0. 19; results not shown). The potential presence of larger detritivore fauna did not drastically and significantly increase OM mass loss for most of our treatments (also revealed by the weighted-arithmetic means comparisons), contradicting our fourth hypothesis that leaf litter exposed to a smaller food web community would decompose at significantly lower rates than that exposed to larger soil fauna.
1982, Fig. 12. Plot showing the effect of the geographical distance on the similarity of leaf-litter composition collected in traps, among 28 common plant species of the YFDP (data from C ardenas et al. 2014). A value of 1 on the y-axis means full similarity. Chapin et al. 2002 , Talbot and Treseder 2012 , C ardenas et al. 2015) , shows to be positively and significantly related to decomposition, suggesting in this particular case, that the smaller groups of detritivores and very probable, decomposers such as fungi and bacteria, are those that are directly and largely affected by higher proportions of lignin content face to N. Rank-abundance plots are used based on the assumption that loss of some species will have a greater impact on ecosystem that would others, especially those that make up a dominant part of the total community biomass.
ACKNOWLEDGMENTS We thank the staff of the  Yasun ı Research Station , in particular the administrative personnel,  David Lasso ,  Carlos Padilla ,  Miguel Rodriguez , and  Karla Rivadeneira  for constant support during the stays at the station. We also thank  Pablo Alvia  for sharing his invaluable plant taxonomic expertise, and help in field and laboratory work. This experiment would have been logistically impossible to perform without him. We also thank  Katherine Padilla ,  Mario Herrera ,  Dolly Muñoz , Fig. 13. Theoretical multi-species interactions at all macrofauna body size ranges of the potential mechanisms controlling leaf-litter decomposition in the Yasun ı tropical rain forest. Biomass (based on biovolume calculations for this study); S: the number of species; FGs: functional groups; "top-down" refers to the effect of predators exerting pressure over detritivores; (+) = positive effect; (À) = negative effect.
GTT and hepatic triacylglycerol measurement After 3 months of HFD, an IPGTT or OGTT were performed. Briefly, for the IPGTT, 6 h fasted mice were injected with glucose (1 g/kg) into the peritoneal cavity, as previously described  [22]. An OGTT was performed via oral administration of glucose (1. 5 mg/g) following a 6 h fast. Blood glucose levels were measured 30 min before glucose administration and at 0, 15, 30, 60, 90 and 120 min following glucose challenge. For both IPGTT and OGTT, the glycaemic index was calculated as the sum of the blood glucose values (mmol/l) divided by the total time of the curve in min to present value in mmol/l × min, or additionally multiplied by 1000 to give value in μmol/l × min. Liver triacylglycerol content was measured by a colorimetric assay using free glycerol and triacylglycerol reagents (Sigma Aldrich, St Louis, MO, USA) and the plate was read using the Multiskan Spectrum plate reader and the SkanIt RE software (both Thermo Labsystems, Beverly, MA, USA).
Hepatic microarray analysis Total RNA was isolated from the right lobe of the liver using TRIzol (Life Technologies, Villebon sur Yvette, France) according to the manufacturer's protocol. Preparation, labelling and hybridisations of cDNA were performed as per the manufacturer's protocol. Samples were analysed using an Agilent SurePrint G3 Mouse GE 8 × 60K chip (design 028005; Agilent Technologies, Courtaboeuf, France). The hybridised microarrays were washed and scanned using an Agilent G2505C scanner. Data were extracted from the scanned image using the Agilent Feature Extraction software version 10. 10. 1. 1. All of these steps were performed at the GENOTOUL GeT-TRIX facility at the French National Institute for Agricultural Research (INRA; Toulouse, France).
Statistical analysis Statistical analyses were performed by two-way ANOVA followed by the Dunnett's post hoc test, or using the unpaired Student's t test, using GraphPad Prism version 7. 00 for Windows 7 (GraphPad, San Diego, CA, USA). A p value <0. 05 was considered significant. Cluster analysis was performed using PermutMatrixEN software (http://download. cnet. com/PermutMatrix/3000-20432_4-75325452. html, accessed 20 June 2016)  [24]. Multivariate analyses were performed using the Spearman correlation coefficient and p values were adjusted using the Benjamini-Hochberg correction (available at www. marum. de/Binaries/Binary745 /BenjaminiHochberg. xlsx, accessed 12 November 2016). A String analysis was performed to study the network of genes targeted by miR-21; these genes were identified using the software miRTarBase (http://mirtarbase.
Acknowledgements We thank the  Société Française d'Hypertension Artérielle  and the  Société Francophone du Diabète  for supporting  V. Blasco-Baque ; the zootechnie-Rangueil Inserm/UPS  US006  CREFRE (Toulouse, France); the  GeT-TRIX facility at INRA (Toulouse, France ). We also thank  S. Dejean  from the  Institut de Mathématiques de Toulouse  ( Toulouse, France ) for helping with the statistical analysis.
Data availability The data that support the findings of this study are available from Vaiomer SAS but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. However, data are available from the authors upon reasonable request and with permission of Vaiomer SAS. Funding This work was supported in part by grants from  Agence Nationale pour la Recherche (ANR)  to RB and collaborators ( ANR-Bactimmunodia  and  LPS diagra) , and by the  European Commission 's  Seventh Framework programme  under grant agreement No. 241913  (FLORINASH) to RB.
Study population and data collection This non-interventional observational and usual care study was prospectively conducted in the 12-bed ICU of the tertiary university hospital Ambroise Paré (Boulogne-Billancourt, France). As for all our non-interventional studies, patients or their relatives were routinely informed that data recorded during hospitalization in the ICU may be used for observational research and scientific publications and that they may refuse at any time. Consecutive patients were included if they met the following inclusion criteria: • Patients >18 years old admitted to ICU. • Taken in charge by at least two shifts of nurses during their stay in our ICU. Our nurses operate 12-h shifts and each cares for between two and three patients, as recommended by French law. Patients given nursing care for a single shift, i.
Comparison with already known sequences was made with the BLAST program (Basic Local Alignment Search Tool, blast. ncbi. nlm. nih. gov) from the National Center for Biotechnology Information. ESBL acquisition was defined as a negative first screening at admission with a positive one during the ICU stay, at least 48 h after admission. ESBL colonization was defined as a positive ESBL screening at admission. All acquired carriers were considered as possible cases of patient-to-patient transmission. Patient-to-patient transmission was analyzed in three steps. The first step was the identification of potential index patients defined as known ESBL carriers hospitalized at the same time as the newly acquired carrier. The second step was the description and identification of ESBL as well as their comparison according to their CTX M 1 or 9 groups.
1) chips (Stilla Technologies, Villejuif, France) were first primed with PCR oil using the Stilla-loading device. A total of 4 PCR reactions of 20μl each were then loaded per Sapphire chip before being compartmentalized into 15,000 to 20,000 droplets using the Stilla loading device. Finally, the inlet and outlet ports of the Stilla chips were overlayed with Capping oil (Stilla Technologies), prior to thermocycling using the Naica Geode prototype thermocycler. Cycling conditions were 95˚C for 10 minutes, followed by 45 cycles of 95˚C for 10 seconds and 62˚C for 15 seconds. Sapphire chips containing the 2D crystals of droplets generated were imaged using the Naica Prism3 reader and fluorescent data were analyzed using Crystal Miner software (Stilla Technologies). Each patient sample was tested in duplicate.
The enrichment was then performed with the Ion One Touch ES (Enrichment System) and the enriched Ion Spheres were loaded into a 316v. 2 Ion Sequencing Chip. Sequencing data were analyzed using the Torrent Suite Variant Caller 4. 2 software and reported somatic variants were compared to the reference genome hg19. The variants were called if >5 reads supported the variant and/or total base depth >50 and/or variant allele frequency >1% was observed. All the variants identified were visually controlled on. bam files using Alamut Visual v2. 8. x software (Interactive Biosoftware, Rouen, France). All the germline variants found in 1000 Genomes Project or ESP (Exome Sequencing Project database) with frequency >0. 1% were removed. All somatic mutations were annotated, sorted and interpreted by an expert molecular biologist according to available databases (COSMIC, TCGA).
Determination of the limit of blank of multiplex dPCR assays The limit of blank (LOB) was measured for each target detected in the 2 multiplex assays. A total of 32 independent dPCR assays were performed on human wild-type DNA ranging from 639 to 12393 copies per dPCR reaction, representing 2. 1 to 40. 9 ng of DNA. No correlation was found between the quantity of wild-type DNA in dPCR reaction and the number of false positives (no statistical significance under Spearman's rho test; data not shown). The mean number (μ) of non-expected positives droplets occurring in the wild-type controls was measured and found to fit a Poisson distribution. The LOB with 99% confidence level was defined as the smallest number of events (positive droplets) at which the cumulative Poisson distribution with parameter μ exceeding 99%.
The tracking system provides a measurement of momentum, p, of charged particles with relative uncertainty that varies from 0. 5 % at low momentum to 1. 0 % at 200 GeV/c. The minimum distance of a track to a primary vertex (PV), the impact parameter (IP), is measured with a resolution of (15 + 29/p T ) µm, where p T is the component of the momentum transverse to the beam, in GeV/c. Different types of charged hadrons are distinguished using information from two ring-imaging Cherenkov detectors. Photons, electrons and hadrons are identified by a calorimeter system consisting of scintillating-pad and preshower detectors, an electromagnetic calorimeter and a hadronic calorimeter. Muons are identified by a system composed of alternating layers of iron and multiwire proportional chambers. Online event selection is performed by a trigger, which consists of a hardware stage, based on information from the calorimeter and muon systems, followed by a software stage, in which all tracks with p T > 500 (300) MeV/c are reconstructed for data collected in 2011 (2012).
Here the index i runs over all candidates in the fitted data sample, W i is the signal weight for candidate i and is determined using the sPlot procedure  [36]  from the fits in Fig. 2 , and i is the efficiency for candidate i. The efficiencies are evaluated including contributions from the LHCb detector acceptance, selection and trigger. The acceptance and most selection efficiencies are calculated from simulated samples with, where appropriate, data-driven corrections applied, while the particle identification efficiency is determined from control samples  [31]. The phase space for a P → V P P decay, where V (P ) indicates a vector (pseudoscalar) particle, has four degrees of freedom, but for B + → D * -K + π + it is found that the efficiency depends strongly only on the squares of the two-body invariant masses m 2 (D * -π + ) and m 2 (K + π + ).
The disparity between the chronological age of an individual and their brain-age measured based on biological information has the potential to offer clinically-relevant biomarkers of neurological syndromes that emerge late in the lifespan. While prior brain-age prediction studies have relied exclusively on either structural or functional brain data, here we investigate how multimodal brainimaging data improves age prediction. Using cortical anatomy and whole-brain functional connectivity on a large adult lifespan sample (N = 2354, age 19-82), we found that multimodal data improves brain-based age prediction, resulting in a mean absolute prediction error of 4. 29 years. Furthermore, we found that the discrepancy between predicted age and chronological age captures cognitive impairment. Importantly, the brain-age measure was robust to confounding effects: head motion did not drive brain-based age prediction and our models generalized reasonably to an independent dataset acquired at a different site (N = 475).
One major confound in functional and structural MRI is head motion  (Satterthwaite et al. , 2013; Power et al. , 2012; Reuter et al. , 2015; Alexander-Bloch et al. , 2016). For instance, head motion can make cortex appear thinner  (Reuter et al. , 2015). An age-related increase in head motion might give rise to a supposedly 'brain-based' age predictor that relies heavily on head motion. Furthermore, while machine learning models are trained on one dataset and evaluated on another, in neuroimaging these datasets often come from the same study, i. e. , same site and scanner. In such cases, models may overfit one site's subtle idiosyncrasies, rendering poor predictive power for data from another site. Therefore, in the current study we aimed to address these confounds by determining the effect of head motion on brain-based age prediction and predictive performance on data from a novel site.
The present study investigates (i) whether incorporating multiple imaging modalities increases prediction accuracy, (ii) whether cognitive impairments are related to brain aging, and (iii) how robust our predictive models are, specifically regarding head motion and generalizabilty to new datasets. Using data from brain anatomy and functional connectivity, we show that (i) incorporating multiple modalities increases predictive performance, (ii) cognitive impairments are related to advanced brain aging, and (iii) our models are robust as they are not driven by head motion and generalize reasonably to new datasets.