dataesr/scientific-paragraphs-categorization huggingface dataset:
C. Simulation and Analysis Software Environment The simulation and analysis software framework called PandaRoot  [29, 30]  is used for the feasibility study described here. PandaRoot is a collection of tools used for the simulation of the transport of particles through a GEANT4  [31]  implementation of the PANDA detector geometry, as well as detailed response simulation and digitization of hits in the various detector elements that takes into account electronic noise. Software for the reconstruction of tracks based on the simulated tracking detector hit points is implemented in PandaRoot, as well as the association of reconstructed tracks to signal in outer PID detectors. A PID probability is assigned to each track based on the response in all the outer detectors, using a simulation of five possible particle species: e ± , µ ± , π ± , K ± , p ±.
III. THEORETICAL DESCRIPTION OF THE SIGNAL CHANNEL The feasibility study presented here is carried out at three values of the square of the center-of-mass (c. m. ) energy s: 12. 3 GeV 2 , 16. 9 GeV 2 and 24. 3 GeV 2. The first value is chosen to coincide with existing data from E835 for pp → J/ψπ 0  [17] [18] [19]. The remaining two values are chosen at the incident p momenta of 8 GeV/c and 12 GeV/c, respectively, to explore the kinematic zone between the first point and the maximum available p momentum at FAIR of 15 GeV/c.
94%). The quantity N J/ψπ 0 is the number of reconstructed J/ψπ 0 events in a particular bin in t, and ∆t is the width of the bin. The location of the point on the t axis is determined by the mean t value of all the entries in the given t-bin at the generator level. For the efficiency calculation, a separate simulation data set of the signal channel was used. The efficiency correction ε(t) in a given bin [t min , t max ] is defined as the ratio of the number of reconstructed events to the number of the generated events within that window: ε(t) = N REC J/ψπ 0 (t min < t REC < t max ) N GEN J/ψπ 0 (t min < t MC < t max ). (22) We note that in the numerator, the number of signal events is counted in a bin determined by the reconstructed value of t, denoted by t REC , whereas in the denominator the generated (true MC) value of t, denoted by t MC , is used.
VII. CONCLUSIONS In this study, the feasibility of measuring J/ψπ 0 production in pp annihilation reactions with PANDA at the future FAIR facility was investigated. The study is based on the TDA model for the description of the signal. A combination of available data and the established hadronic event generator DPM was used to describe the background with only pions in the final state. Non-resonant J/ψπ 0 π 0 was also considered, for which a PHSP event generator was used for the event distributions and conservative estimates were made for the cross sections given the lack of constraints from existing data. Generated events were simulated and reconstructed using the Pan-daRoot software based on the proposed PANDA setup. Using events selected to include a π 0 and an e + e -pair with invariant mass inside a broad window around the J/ψ mass, background reactions with no J/ψ in the final state can be reduced to the level of a few percent.
The residual back-ground can be subtracted using the procedure outlined. The signal efficiency decreases from 18% for beam momentum of 5. 5 GeV/c to 9% for 12. 0 GeV/c. To reject the J/ψπ 0 π 0 background reaction to the 2% level, additional selection based on kinematic fits is needed, which further reduces the signal efficiency by about an additional 30%. The severeness of these cuts will however be adjusted depending on the measured yield for this background channel. The cross section plots were produced with the assumption of a 2 fb -1 integrated luminosity which could be accumulated in approximately five months of data taking at each beam momentum setting with the full design luminosity of the FAIR accelerator complex. The resulting uncertainties to measure the differential cross section as a function of the four momentum transfer in the two validity regions is expected to be of the order of 5 -10%.
ACKNOWLEDGMENTS The success of this work relies critically on the expertise and dedication of the computing organizations that support PANDA. We acknowledge financial support from the  Science and Technology Facilities Council (STFC) ,  British funding agency ,  Great Britain ; the  Bhabha Atomic Research Center (BARC)  and the  Indian Institute of Technology, Mumbai, India ; the  Bundesministerium für Bildung und Forschung (BMBF) ,  Germany ; the  Carl-Zeiss-Stiftung   21-0563-2. 8/122/1and 21-0563-2. 8/131/1 , Mainz , Germany; the  Center for Advanced Radiation Technology (KVI-CART) ,  Gröningen, Netherland ; the  CNRS/IN2P3  and the  Université Paris-Sud , France; the  Deutsche Forschungsgemeinschaft (DFG) ,  Germany ; the  Deutscher Akademischer Austauschdienst (DAAD) , Germany; the  Forschungszentrum Jülich GmbH, Jülich, Germany ; the  FP7   HP3 GA283286 ,  European Commission  funding; the  Gesellschaft für Schwerionen-forschung GmbH (GSI) ,  Darmstadt, Germany ; the  Helmholtz-Gemeinschaft Deutscher Forschungszentren (HGF) ,  Germany ; the  INTAS, European Commission  funding; the  Institute of High Energy Physics (IHEP)  and the  Chinese Academy of Sciences, Beijing, China ; the  Istituto Nazionale di Fisica Nucleare (INFN), Italy ; the  Ministerio de Educacion y Ciencia (MEC)  under grant  FPA2006-12120-C03-02 ; the  Polish Ministry of Science and Higher Education (MNiSW)  grant No.
Instrumentation Iodine determination was performed by ICP-MS using a quadrupole mass spectrometer "X Series II" (Thermo Fisher Scientific TM , France). From a ASX-520 autosampler (Cetac Technologies, USA), the sample is injected and transported by specific tubings through the sample introduction system composed by a standard peristaltic pump and a Meinhardt nebulizer fitting into a classic spray chamber. The sampler and skimmer cones used were in nickel. The skimmer cone was of type Xt more suited to loaded matrices. For each experiment, all instrument parameters controlled from PlasmaLab software version 2. 6. 3. 340 (2007) were optimized daily using a tuning iodide solution (40 µg•L -1 ) to obtain the highest sensitivity and to minimize possible interference effects (oxide levels and doubly charged ions).
To get a general picture, hereafter values of ICP-MS acquisition settings that we could have: forward Rf power (1403 W), pole bias (-6. 00 V), hexapole bias (-1. 70 V), cool gas flow (13. 02 L•min -1 ), auxiliary gas flow (0. 80 L•min -1 ) and nebulizer flow (0. 76 L•min -1 ). Iodine was determined at m/z = 127 and tellurium (Te), as internal standard, at m/z = 125 ( 125 Te) in the pulse counting mode of data acquisition.
Statistical Analysis The experimental data were analyzed using GraphPad software version 5. 0. Once all experiments were carried out, prior the evaluation of each criteria, the distribution of the measured data was examined by using Shapiro-Wilk W test. A Gaussian distribution was observed for all data at each concentration level. Relating to Wilcoxon W test employed for comparison of both methods on rat urine samples, it is considered that no statistically significant difference is observed between the results when p > 0. 05.
Results LXRs are gatekeepers of Pten-null prostate tumor progression. We have recently reported that LXRs attenuate prostate intraepithelial neoplasia (PIN) in vivo  14. To evaluate the status of the LXR-controlled transcriptional program in advanced prostate tumors we monitored the expression of a canonical set of LXR target genes by analyzing public datasets of human PCa collections. Unexpectedly, ONCOMINE analyses identified upregulation of the LXR transcriptional program, which was most prominent in metastatic PCa (Figs. 1a, b  and Supplementary Fig. 1A ). Interestingly, evaluation of enrichment profiling (Gene Set Enrichment Analysis, GSEA) of gene sets sensitive to PTEN loss supported the existence of an inverse correlation between expression of LXR target genes and PTEN status in humans (Fig.
The lower chamber contains RPMI-1640 medium (Invitrogen) supplemented with penicillin/streptomycin (100 mg ml -1 ), L-glutamine (2 mM) and 10% FBS (Biowest). Cells were incubated for 48 h before fixation using Paraformaldehyde 4% and staining with Hematoxylin (Sigma). Remaining cells in upper chamber were removed with cotton tips. Cell number has been counted using ImageJ software. Western blot analysis. Proteins were extracted from tissues and cells using a buffer solution with Hepes 25 mM, NaCl 400 mM, MgCl 2 1. 5 mM, EDTA 200 mM, Nonidet-P40 1% supplemented with phenylmethylsulfonyl fluoride 1 mM, Na 3 VO 4 0. 1 mM, NaF 0. 1 mM and complete protease inhibitor cocktail (Roche Diagnostics, Meylan, France). Lysates were resolved on SDS-polyacrylamide gel electrophoresis and transferred to nitrocellulose membrane (Hybond-ECL, GE Healthcare).
Separation was carried out on a 30 m capillary column (HP-5MS 30 m 0. 25 mm ID, 0. 25 µm thickness). Quantification of oxysterols was made by the isotope dilution method. Human data set analysis. Box plots and heatmap were performed using ONCOMINE portal (www. oncomine. org). GSEA has been used with a list of 24 genes (e. g. , genes with functionally characterized LXRE in human promoter sequence). Analysis was performed using http://www. broadinstitute. org platform with GSEA software v2. 2. 2  53, 54. When more than one probe are available in the dataset, the probe with maximum signal was used. Mouse embryonic fibroblasts. MEFs have been derived from 13. 5 dpc embryos WT, Lxrα -/-, Lxrβ -/-or Lxrαβ -/-. Briefly, dorsal part of the dissected embryos have been sliced and incubated with PBS Trypsin-EDTA digestion mix (Sigma-Aldrich) at 37 °C for 45 min.
7 µm. Raw data (. CEL Intensity files) were extracted from the scanned images using the Affymetrix GeneChip Command Console version 4. 1. 2. CEL files were further processed with Affymetrix Expression Console software version 1. 4. 1 to calculate probe set signal intensities using Robust Multi-array Average algorithms with default settings. Gene expression microarray data have been deposited in the GEO database with the accession number GSE96545. Reverse transcriptase-quantitative PCR. For cells experiments, total RNA was isolated using Trizol reagent (Invitrogen) according to the manufacturer's instructions. For prostates tissues, mRNA were extracted using the NucleoSpinRNAII kit (Macherey Nagel EURL, Hoerdt, France). cDNA was synthesized with MMLV-RT (Promega, Charbonnières, France) and random hexamer primers (Promega) according to the manufacturer's instructions.
Acknowledgements We are grateful to  Dr. David Mangelsdorf  ( Department of Pharmacology and Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX ) for providing the Lxrαβ -/-mice. We thank  Dr. André Mazur  ( INRA, Theix ) for providing APOE antibody. We thank  Sandrine Plantade ,  Kheredine Ouchane  and  Philippe Mazuel  for efficient and fruitful work in mouse husbandry and care. We are grateful to  Pradeep A. Val  for discussion and improvement of the manuscript. We thank  Dr. Axel Poulet  ( GReD, Clermont-Ferrand ) for excellent work in formatting data for GSEA analysis. We thank  Christelle Damon-Soubeyrant  and Anip@th platform ( GReD, Clermont-Ferrand ) for histological exploration of mouse phenotypes. We warmly thank  Dr. Petra van Duijn  and  Pr. Jan Trapman  ( Erasmus Medical Center, Rotterdam ) for providing of LNCaP-PTEN-inducible cell line.
This reduces motor response fluctuations and has also been shown to improve nonmotor complaints commonly associated with chronic oral levodopa treatment  [9] [10] [11] [12] [13] [14]. To date only a few studies have assessed the long-term safety and efficacy of LCIG treatment in routine clinical care and a majority of these studies included a limited number of patients or lacked systematic collection of efficacy data and adverse events  [11, [15] [16] [17] [18] [19]. The objective of the GLORIA registry (global long-term registry on efficacy and safety of LCIG in patients with advanced Parkinson's disease in routine care) was.
ACKNOWLEDGEMENTS This work was funded by  AbbVie Inc. AbbVie participated in the study design, research, data collection, analysis, and interpretation of data, writing, reviewing, and approving the publication. Medical writing support was provided by  Amy M. Spiegel of AbbVie, Inc. The EDC system used to collect clinical data was provided by  Koehler eClinical Ltd. , Freiburg, Germany. The statistical analysis was performed by Koehler eClinical, funded by  AbbVie. Christoph Redecker ,  Department of Neurology, Jena University Hospital, Jena, Germany ;  Christoph Schrader ,  Hannover Medical School, Hannover, Germany ;  Mariachiara Sensi ,  Neurology Department Arcispedale S. Anna, Ferrara, Italy ;  Mihaela Simu ,  UMF"Victor Babes", Timisoara, Romania; Cleanthe Spanaki, University Of Crete, School Of Medicine, Neurology Department, Iraklio, Greece ;  Alexander Storch ,  University of Rostock, Rostock, Germany; Anette Storstein, Haukeland University Hospital, Bergen, Norway ;  Volker Tomantschger ,  Gailtal-Klinik Hermagor , Hermagor,Austria; Chris van der Linden,  Department of Neurology, St.
Methods-systematic search of the literature The Medline database was used to identify Medical Subject Headings (MeSH) to select search terms. In addition to MeSH terms, we also used free-text words. Search terms referred to aspects of the ICU organization ("Intensive Care department", "organization", "management", "staffing") as well as related topics ("cost reduction", "patient outcome", "lean", "Toyota", "total quality management", "Toyota Production System", and "monitoring"). Relevance of each paper was assessed using the online abstracts. In addition, the reference lists of retrieved papers were screened for potentially important papers.
Materials and methods In this randomized, double-blind, placebo-controlled trial, men with biopsyproven low-intermediate risk prostate cancer (up to Gleason 3+4 and PSA up to 15 ng/ml) who had an MR visible lesion of >/= 0. 2ml on T2-weighted sequences were randomized to daily dutasteride 0. 5mg or placebo for 6 months. Lesion volume was assessed at baseline, 3 and 6 months, with an image-guided biopsy to the lesion at study exit. The primary endpoint was percentage reduction in lesion volume over 6 months. This trial was registered with the European Clinical Trials register (EudraCT 2009-102405-18).
An integration of population structure, genetic variations, networks and annotation data was performed using a theory described here as emergence-selection-diffusion (ESD) model. Bioinformatic results on significant mutations and related biological pathways were used to test the model and evaluate the process of emergence and selection in specific small subpopulations, followed by diffusion in an admixed population. This model defined for a descriptive approach is similar to the population shifting balance and metapopulation theories in population genetics that were successfully implemented for the analysis of P. falciparum populations  [25, 26]. In total, 21,257 non-synonymous SNPs were identified using specific filters among 167 isolates from the genomic dataset on which the parasite population structure was described earlier  [12].
Data acquisition The genome sequencing data of Cambodian parasite isolates was recovered from the ENA (European Nucleotide Archive) database server, submitted by the Welcome Trust Sanger Institute. Out of the 293 P. falciparum whole genome sequences from 2008 to 2011, which were used to define the P. falciparum parasite population structure in Cambodia  [11, 12] , 167 sequences were recovered successfully (Additional file 1) in BAM format and converted to much readable VCF (v4. 1) files  [28]  using SAMtools v0. 1. 19 [29]. Plasmodium falciparum 3D7 strain (genome sequence annotation version 2) was used as the reference genome, and was recovered from the PlasmoDB Plasmodium Genomics resource database (release version 5. 5)  [30]. The 167 genome sequences originate from four locations: Pailin (14 sequences), Tasanh (26 sequences) and Pursat (81 sequences) in western Cambodia and Ratanakiri (46 sequences) in eastern Cambodia.
Correspondence between different genome versions The correspondence of the SNP coordinates between P. falciparum genome sequence version 2 and 3 was recovered using BLAST (Basic Local Alignment Search Tool) from NCBI (National Centre for Biotechnology Information), for each chromosome separately. For the chromosomes 4, 7, 8, 10 and 13 very short lengths of alignments were obtained depicting major changes in the genomic sequence between version 2 and 3. Correspondence for these chromosomes was then obtained by defining specific regions for BLAST. Correspondence for approximately all SNPs in all chromosomes was recovered, and the 3105 unmapped SNPs in the recovered dataset were removed from the analysis. NCBI BLAST was performed for each chromosome, with genome version 2 (PlasmoDB release version 5.
Annotation of the recovered SNPs To describe the distribution of the SNPs over the genome, the 167 strains were annotated using VCF-annotator Perl script (developed at the Broad Institute, Cambridge, MA). The GFF3 (General Feature Format version 3) file was recovered from Ensembl database server (release version ASM276v1. 21) corresponding to the P. falciparum genome sequence version 2. The annotation shows that the recovered SNPs are mostly in introns, exons and 5pUTR. To define the coordinates of the chromosome end regions the chromosomes corresponding to genome version 3 (PlasmoDB release version 11) were visualized using the genome browser provided by Plas-moDB. The regions containing the genes with descriptions such as CLAG, DBL, Rifin, hyp, Stevor, GARP, RESA, VAR, PfEMP, Surfin, PHIST, KAH and EMP in a consecutive organization, were considered as chromosome end regions.
The gene location in the coding region was determined and chromosome end coordinates were defined (Table  1 ). The final set of 21,257 non-synonymous SNPs in the coding region was described, using the recovered annotation and chromosome ends region coordinates (Additional file 7). This dataset is referred to as IBC dataset in the manuscript and is used for parasite population study in Cambodia. There are 3714 modified SNPs (as described in the section above) in the set of these 21,257 SNPs.
Clustering To describe the P. falciparum population structure in Cambodia, unsupervised hierarchical clustering was performed on the IBC dataset (all the statistical analysis is performed in R v3. 0. 1 and v3. 2. 3). The pairwise distance between two isolates was estimated as the proportion of base substitution between them over the whole set of recovered SNPs. Ward minimum variance method was used as a metric to build the dendrogram. The correspondence between previously described parasite subpopulations in Cambodia  [12]  and the 167 isolates were recovered from the Sanger Institute. Eight subpopulations were described based on the hierarchal clustering results: KH1. 1, KH1. 2, KH2. 1, KH2. 2, KH3, KH4, KH5 and KHA. In order to choose the optimal number of clusters in the dendrogram, the value of k was set to 2 to 10 and the clusters obtained at k = 8 overlapped both, clusters based on different k13 alleles and the previously described KH subpopulations.
Chromosome Positions excluded from start of chromosome Positions excluded from end of chromosome Chromosome length (bp) networks were analysed. The interaction network data was recovered from STRING v10, which provides functional and predicted protein-protein interactions from other publicly available data sources and literature  [32]. Networks based on co-expression data for all the subpopulations based on significant genes were recovered. Only edges with a STRING confidence score for co-expression higher than 0. 5 were considered for the analysis. The networks were imported and analysed in Cytoscape v3. 2. 1  [33]. The complete P. falciparum interaction network based on co-expression data (confidence score ≥ 0. 5) was also recovered from STRING v10 database. Out of the 5777 genes identified in the genome of P.
Network based subpopulation description The population structure of 167 parasite isolates was also questioned using the method of Network Based Stratification  [27]  which clusters the isolates together having diffusion paths associated to mutated genes in similar network regions. The list of mutated genes for each isolate was projected on the full P. falciparum interaction network recovered from STRING v10  [32]. All prediction sources such as co-expression, co-occurrence, gene fusion, databases, experimental evidence, text-mining and neighbourhood were considered for the full P. falciparum interaction network. The results were obtained for the top 10% gene-gene interactions based on combined confidence score provided by STRING database  [32]. The mutated genes were propagated to the neighbourhood network (network smoothing) and based on the node score matrix of the resulting diffusion network for each isolate, clustering was performed using non-negative matrix factorization (NMF) method  [37].
Description of P. falciparum subpopulations Identification of P. falciparum subpopulations from 2008 to 2011 Cambodian samples revealed specific origin of artemisinin resistant k13 alleles. Hierarchical clustering was performed based on 21,257 non-synonymous SNPs (Additional file 7) to classify 167 samples into eight subpopulations (Fig. 1 ; Additional file 8). The P. falciparum parasite population structure described earlier  [12]  was confirmed and refined. Isolates carrying one of the three dominant k13 alleles C580Y, Y493H and R539T found in the dataset are referred to as ART resistant isolates and the five subpopulations of which nearly all the isolates were carrying the k13 alleles are referred to as artemisinin resistant (ART-R) subpopulations (Additional file 8). The subpopulations KH2 and KH3 are the donor populations for the most dominant allele C580Y (the isolates in KH2 are classified into two subpopulations KH2.
KH1. 1 is one of the largest subpopulations and KH1. 2 is the smallest subpopulation. The other large subpopulation is the admixed subpopulation KHA with around 52% of the ART-R isolates and 48% ART-S isolates. The parasite population structure in Cambodia was also confirmed using a stratification method  [27]  based on co-expression network data recovered from STRING database  [32]. Only some admixed subpopulation KHA samples were differentially classified, suggesting potential close relationship with the donor subpopulations in terms of gene expression (Additional file 9). Consequently, out of the 49 isolates in this subpopulation, 10 isolates were clustering with other subpopulations (Fig. 1b ). The clustering of 6 mutant k13 and 4 wildtype k13 isolates with the ART-R donor subpopulations was intriguing regarding the diffusion of k13 alleles after mating between gametocytes.
Frequency of isolates having at least one significant mutation or a rare mutation was calculated for the ART-R subpopulations and KHA parasites. Plasma membrane and endoplasmic reticulum membrane are represented by grey bars. Schema was built from protein-protein interactions or relationship given in databases and literature. Orange boxes: genes from the 57 genes set; White boxes: significant genes from the 265 set. AKT has grey box because it contains no significant mutations, but only rare mutations Altogether, these results suggest that selection of the artemisinin genetic background happened in the daughter subpopulations and not in the ancestral population.