dataesr/scientific-paragraphs-categorization huggingface dataset:
gondii proliferation was determined by high-content fluorescence imaging as described previously  (Palencia et al. , 2017). Briefly, 10,000 HFFs were seeded in each well of well in 96-well plate and then infected with 4 Â 10 4 parasites. Invasion was synchronized by briefly centrifuging the plate at 400 rpm, and plates were incubated at 37 ˚C for 2 hr. Infected cells were then washed three times with PBS and further incubated for a total of 24 hr of growth. Nuclei were stained with Hoechst 33342 at 5 mg/mL for 20 min and after fixation and permeabilization, parasite vacuoles were labelled using an anti-GRA1 antibody (specific to Toxoplasma). Images were automatically acquired using the ScanR microscope system (Olympus) to determine the number of tachyzoites per vacuole. The experiments were done in triplicate from two independent assays, and data were processed using the GraphPad Prism software.
For each condition, total RNAs from two independent biological replicates were pooled to prepare cDNA libraries which were then sequenced using Illumina technology in a single replicate dataset. RNA-sequencing was performed by GENEWIZ (South Plainfield, NJ, USA). Briefly, the RNA quality was checked with an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, California, USA) and Illumina TruSEQ RNA library prep and sequencing reagents were used following the manufacturer's recommendations (Illumina, San Diego, CA, USA). The samples were paired-end multiplex sequenced (2 Â 125 bp) on the Illumina Hiseq 2500 platform and generated at least 70 million reads for each sample (Supplementary file 3). The RNA-Seq reads (FASTQ) were processed and analyzed using the Lasergene Genomics Suite version 14 (DNASTAR, Madison, WI, USA) using default parameters.
The paired-end reads were uploaded onto the SeqMan NGen (version 14, DNASTAR. Madison, WI, USA) platform for reference-based assembly using either the Mus musculus genome package (GRCm38. p3) or the Toxoplasma Type II ME49 strain (ToxoDB-24, ME49 genome) as reference template. The ArrayStar module (version 14, DNASTAR. Madison, WI, USA) was used for normalization, differential gene expression and statistical analysis of uniquely mapped paired-end reads using the default parameters. The expression data quantification and normalization were calculated using the RPKM (Reads Per Kilobase of transcript per Million mapped reads) normalization method. Pathway and functional annotation analyses of the differentially expressed genes were conducted using the hallmark gene sets of GSEA  (Mootha et al.
Mass spectrometry-based proteomics Protein bands were excised from colloidal blue-stained gels (Thermo Fisher Scientific), treated with DTT and iodoacetamide to alkylate the cysteines before in-gel digestion using modified trypsin (sequencing grade; Promega). Resulting peptides from individual bands were analyzed by nanoLC-MS/MS (UltiMate 3000 coupled to LTQ-Orbitrap Velos Pro; Thermo Fisher Scientific) using a 25 min gradient. Peptides and proteins were identified and quantified using MaxQuant (version 1. 5. 3. 17) through concomitant searches against ToxoDB (20151112 version), SwissProt (Homo sapiens taxonomy, 20151112 version), and the frequently observed contaminant database embedded in Max-Quant. Minimum peptide length was set to seven amino acids. Minimum number of peptides, razor +unique peptides, and unique peptides were all set to 1.
Quantitative real-time PCR Total RNA was isolated using TRIzol reagent (Thermo Fisher Scientific) and RNA quality and integrity was assessed by agarose gel electrophoresis and quantification of 28S and 18S ribosomal RNA. cDNA was synthetized using the High Capacity RNA-to-cDNA kit (Applied Biosystem). Samples were analyzed by real time quantitative PCR for Ccl17, Ccl22, Ccl24 and Ifnb1 using TagMan Gene Expression Master Mix (Applied Biosystems) according to the manufacturer's instructions. Tbp was used as an internal control gene for normalization. Data were analyzed using the 2 -DDCt method, and statistical analyses were conducted on the DCt values. Data are represented as mean value ± s. d. of three technical replicates and the results presented are representative of at least two independent experiments.
In vitro cytokine ELISA About 10 6 BMDMs were seeded per well of a 24-well-plate. Cells were left uninfected or infected with freshly egressed T. gondii tachyzoites at an MOI of 1:5. At 24 hr post-infection, supernatants were collected and stored at À80 ˚C for storage. CCL17 and CCL22 levels were determined using Mouse CCL17/TARC and Mouse CCL22/MDC Quantikine ELISA Kits from R and D Systems according to the manufacturer's instructions. Data are mean value ± s. d. of four independent experiments from two biological replicates. DOI: https://doi. org/10. 7554/eLife. 39887. 013. Supplementary file 2. Y2H screen results. DOI: https://doi. org/10. 7554/eLife. 39887. 014. Supplementary file 3. Gene expression profiles in BMDMs and T. gondii with and without LPS stimulation. RNA-Seq Reads Mouse. Summary of total RNASeq reads and average reads mapped to the mouse genome.
Acknowledgments This work was supported by the  ANR   Jeune Chercheur 2012 ToxoEffect  ( ANR-12-JSV3-0004 -01 ), the  European Research Council  ( ERC Consolidator Grant  No  614880 Hosting TOXO ), and the  LabEx ParaFrap  ( ANR-11-LABX-0024 ). The authors have no competing financial interests.
DOI: https://doi. org/10. 7554/eLife. 39887. 015. Transparent reporting form DOI: https://doi. org/10. 7554/eLife. 39887. 016DataavailabilityDatasets Generated: Transcriptomic analysis by Next Generation Sequencing (RNA-seq) have been deposited in GEO under accession code GSE103113. The following dataset was generated: Database and Author(s) Year Dataset title Dataset URL Identifier He H, Brenier- 2018 Transcriptomic analysis by Next https://www. ncbi. nlm. NCBI Gene Pinchart M, Braun L, Generation Sequencing of mouse nih. gov/geo/query/acc. Expression Omnibus, Kraut A, Touquet B, bone marrow derived macrophages cgi?acc=GSE103113 GSE103113 CouteY, Tardieux I, (BMDMs) infected by Wild-Type Hakimi M, Boug- and gra18 mutant strains of T. dour A gondii.
Procedures Data were collected between November 2011 and July 2012 (Experiment 1) and in July 2014 (Experiment 2) at an Experimental Lab of a large German university, and both experiments were implemented in z-Tree  [34]. 8 Overall, we conducted 26 sessions with up to 15 subjects per session (Experiment 1: 23 Sessions, Experiment 2: 3 Sessions). Upon arrival, subjects were seated at a random computer terminal, and a printed version of the general instructions was handed out and read aloud by one of the experimenters. Any form of communication between participants was not allowed, and questions were answered in private. Subjects could not participate in more than one session and submitted their decisions anonymously. For this purpose, they generated a personal code that was also used for anonymous payment.
MATERIALS AND METHODS One-hundred twenty one patients submitted to LT at the Portuguese Hospital of Salvador, Bahia, Brazil who underwent surgery in a period of 5 years were retrospectively evaluated. All medical and surgical charts as well as electronic files were reviewed by a single observer in order to collect data regarding perioperative and postoperative variables, previously associated with adverse outcomes after LT, including demographics; etiology of liver disease; indication for LT; severity of liver disease assessed by MELD and Child-Pugh scores; perioperative parameters such as cold ischemia time, duration of surgery, need for inotropic support, FB and use of vasoactive drugs; Acute Physiology and Chronic Health Disease Classification System (APACHE II) score, peak lactate, AST and ALT levels; occurrence of postoperative complications, including early allograft dysfunction (EAD) and primary graft non-function (PGNF), biliary strictures or leaks, hepatic artery thrombosis or stenosis, AKI and requirement for RRT, acute rejection, sepsis and septic shock; cumulative FB in the first 12 h and 4 d; length of stay (LOS) in the ICU and in the hospital; mortality and causes of death in the first 28 d.
GE067-005 Study Plasma samples from MCI participants enrolled in the GE067-005 study 2   (Wolk et al. , 2018)  were included in the independent validation study (n = 173, Table  2 ). This included amnestic MCI subjects who converted to probable AD within a 3year time frame (MCI Converter, n = 52) and subjects who remained MCI over this time period (MCI non-converter, n = 121). Participants were assessed clinically every 6 months until conversion, dropout or completion of the 3-year follow-up. [ 18 F]Flutemetamol PET amyloid imaging data were available for all subjects, who were categorized as having either an "abnormal" PET amyloid scan (positive for the presence of amyloid, n = 68) or a "normal" PET amyloid scan (negative for the presence of amyloid, n = 105). Visual image interpretation of the PET scan was performed by five independent trained readers who were blinded to the participants' clinical history and diagnosis.
EMIF 500 Study The EMIF (see text footnote 1) is a precompetitive, publicprivate Innovative Medicines Initiative funded platform facilitating access to cohort studies and real world observational data from across Europe. We used EMIF to identify three cohorts with samples suitable for validation studies. Plasma samples from AD, MCI and cognitively healthy participants (CTL), for whom a measure of CSF Aβ 42 , tTau and pTau was available, were included in this independent validation study (n = 494, Table  3 ). Participants were recruited by three separate centers; Clinica Neurologica, Universita di Perugia (n = 252), Hospital Sant Pau, Barcelona (n = 154) and the Alzheimer Unit of Fondazione Ca Granda, IRCCS Ospedale Maggiore Policlinico, Milan (n = 88). Diagnoses were made according to standard criteria  (McKhann et al.
Discovery Phase: Gel LC-MS/Mass Spectrometry Based Proteomics Discovery proteomics was carried out by gel LC-MS/Mass Spectrometry (LC-MS/MS) coupled with tandem mass tagging (TMT). The data acquisition and preprocessing pipelines are described in detail elsewhere  (Ashton et al. , 2015). In brief, the proteomics workflow consisted of plasma samples labeled in a TMT6plex configuration with TMT126 -TMT130 (Thermo Fisher Scientific), and the study reference with TMT131. The tagged samples within each TMT6plex were pooled and then separated by one-dimensional gel electrophoresis. Ten equal fractions were excised from each gel and the gel pieces were destained, tryptically digested and peptides extracted. LC-MS/MS acquisition was performed using the Orbitrap Velos Pro instrumentation (Thermo Fisher Scientific) coupled to a Proxeon EASY-nLC II system (Thermo Fisher Scientific).
The LC-MS/MS raw Excalibur data files (Thermo Fisher Scientific) were processed by Proteome discover (Thermo Fisher Scientific, version 1. 3) using Mascot 3  (version 2. 3) to determine peptide identifications. Processing of the Mascot output data files was performed in R, and included median ratio normalization, calculation of peptide ratios and subsequent protein scores using median and mean roll-up methods of peptide ratios as described  (Ashton et al. , 2015). Where the same protein was observed by electrophoresis in multiple different molecular weight regions of the one-dimensional gel, these observations were treated as separate protein molecular weight isoforms in subsequent analysis. Analysis of each protein molecular weight isoform was performed on the data produced from both the mean and median protein roll up methods and age, sex, APOE ε4 allele presence and sample storage duration were included as covariates in regression models.
, 2003; Liu et al. , 2006; Thambisetty et al. , 2010; Ijsselstijn et al. , 2011; Hu et al. , 2012; Song et al. , 2012; Hye et al. , 2014; Ashton et al. , 2015; Westwood et al. , 2016). Proteins were measured by commercially available singleanalyte enzyme-linked immunosorbent assays (ELISAs) according to the manufacturer's instructions (Supplementary Table  1 ). ELISA absorbance at 450 nm was detected using a microplate reader (PHERAstar FS, BMG, LABTECH). The background corrected (570 nm) absorbance data were exported into Sigma Plot (Systat Software; version 12. 5) for estimation of protein concentrations using a 5-parameter logistic fit. Intraassay and inter-assay variability was assessed by calculation of the percentage coefficient of variation (% CV). Average intra-assay CVs were calculated using the duplicate measures for each sample and average inter-assay CV was calculated using the measurement of a control sample, which was analyzed on each plate.
In total 21 proteins were measured by multiplex bead assays using the Luminex 200 instrument and by commercially available ELISAs as described earlier (Supplementary Table  1 ). As plasma proteins were measured in singular, the data were assessed for outliers on a protein-by-protein basis. Extreme outliers were defined as values falling outside three times the inter-quartile range of all samples measured and were removed from the dataset prior to subsequent statistical analysis. The following covariates were included in regression models: age, sex, APOE ε4 allele presence, center, and batch variation.
Pathway Analysis: LC-MS/MS Proteomics in the Amsterdam Dementia Cohort In order to explore the potential biological significance of these findings, we then performed a pathway analysis. The total summed p-values were calculated for 77 proteins from 233 protein MW isoform p-values for inclusion in gene enrichment analysis. Using STRING this list was expanded to include proteins for which there is direct experimental evidence of an interaction, giving a total of 769 proteins. When comparing this protein set to the Reactome database, three pathways were significant after FDR correction for multiple comparisons; HDLmediated lipid transport (q = 0. 010), lipoprotein metabolism (q = 0. 035), and lipid digestion, mobilization, and transport (q = 0. 035) (Table  5 ). Comparison to the DisGeNet database revealed three diseases were significant post FDR correction; hypercholesterolemia, familial (q = 0.
Spa genotyping and multi-locus sequence typing (MLST) Spa genotyping and MLST were performed as described elsewhere  (Enright et al. , 2000; Harmsen et al. , 2003). Spa typing was performed on all S. aureus isolates. Spa types were clustered into clonal lineages using the BURP algorithm of Ridom Software and the SpaServer (http://www. spaserver. ridom. de/). MLST was performed on selected isolates to confirm the spa clustering results. Profiles were submitted to the SpaServer and the MLST database (https://pubmlst. org/saureus/).
, 1998). For example, 94. 0% (8838/9403) of sequenced S. aureus isolates encoded the coA gene (https://www. patricbrc. org/; 04. 09. 2017). Moreover, all murine ST890 isolates lacked an hlb hybridization signal (see Table  S2  in online version at DOI:10. 1016/j. ijmm. 2017. 09. 014). The related spa types t1736 and t1773 have been described in different animals and humans, where they were always assigned to CC130  (Azara et al. , 2017; Cuny et al. , 2011; Gharsa et al. , 2015; Haenni et al. , 2014). The corresponding isolates in this study, however, were assigned to ST890 based on MLST and DNA array data. The comparison of array data revealed a high concordance between human CC130 strains and the two CC130 (t843) strains originating from this study (see below), while the ST890 isolates in this collection were distinctive in several ways.
Acknowledgements The support of  Birke Böttcher ,  Hanan Sheik Ali ,  Elisa Heuser ,  Marie Luisa Schmidt ,  Dörte Kaufmann ,  Anke Mandelkow  and  Christin Trapp  in small mammal trapping;  Sabrina Schmidt ,  Dörte Kaufmann ,  Hanan Sheikh Ali ,  Stephan Drewes ,  Luise Grund ,  Christin Trapp ,  Anke Mandelkow ,  Christoph Gertler ,  Marie Luisa Schmidt ,  Elisa Heuser ,  Susanne Röhrs ,  Jens Jungton ,  Julia Schneider ,  René Ryll ,  Petra Strakova ,  Sandra Jagdmann ,  Dewi Murni ,  Maysaa Dafalla ,  Chao Wen ,  Arne Auste  in dissection;  Dörte Kaufmann ,  Anke Mandelkow ,  Chao Wen ,  Petra Strakova  and  David Kohlhause  in molecular species confirmation;  Erika Friebe  and  Fawaz Al Sholui  for genotyping analyses, and  Stefan Weiß  for support in data visualization is kindly acknowledged.
Fungal Strain and Cultivation The strain A118 of Emericellopsis alkalina Bilanenko and Georgieva was isolated from alkaline soil on the edge of the Zheltyr Lake, Kulunda steppe, Russia. It was deposited at the Collection of Fungi from Extremophilic Habitat Department of Mycology and Algology Biological Faculty Lomonosov Moscow State University and All-Russian Collection of Industrial Microorganisms (Moscow, VKPM F-1428). Species identification was conducted by molecular-genetics methods based on sequence data of ITS rDNA, LSU rDNA, SSU rDNA, TEF-1α, β-tub, and RPB2 in Laboratory of Genetics, Plant Sciences Group, Wageningen University, the Netherlands. The DNA sequences were deposited to GenBank: ITS1, ITS2, 5. 8S (ID: KC987155. 1); LSU rDNA (ID: KC987230. 1); SSU rDNA (ID: KC987193. 1); TEF-1α (ID: KC998977.
Mass Spectrometry The peptide sample was analyzed with an LC-MS/MS system (Agilent Technologies, Santa Clara, CA, USA) consisting of a nanopump (G2226A, Agilent) with a four-channel micro vacuum degasser (G1379B, Agilent), a microfluidic chip cube (G4240-64000, Agilent) interfaced to a Q-TOF mass spectrometer (6530, Agilent), a capillary pump (G1376A, Agilent) with degasser (G1379B, Agilent), and an auto-sampler with thermostat (G1377A, Agilent). All modules were controlled by Mass Hunter software (version B. 06. 00, Agilent). A microfluidic reversed-phase HPLC chip (Zorbax 300SB-C 18 , 5-µm particle size, 0. 75 × 150 mm) was used for peptide separation. A mixture of 96. 9% water, 3% acetonitrile, and 0. 1% formic acid (v/v) was used as the sample loading solution and solvent. Buffer B was 99.
Antibacterial Activity Determination of the minimum inhibitory concentration (MIC) was carried out by conventional broth microdilution methods based on the Clinical and Laboratory Standards Institute (CLSI) adapted for antimicrobial peptides  [34]. The overnight cultures of the test strains were diluted in Muller Hinton broth (HiMedia, Mumbai, India) in order to obtain 10 6 CFU/mL. Prepared inoculums were mixed with two-fold dilutions of emericellipsin A and incubated for 24 h in 96-wells microtiter plate (Eppendorf, Hamburg, Germany). The indolicidin (Research Institute of Highly Pure Biopreparations, Saint Petersburg, Russian Federation), vancomycin (Sigma-Aldrich, St. Louis, MO, USA), and norfloxacin (Sigma-Aldrich) were used as positive controls. After incubation, the optical density of planktonic cells was assessed by reading the absorbance data at 620 nm.
These data were obtained by the IEMS MF spectrophotometer (Labsystems, Vantaa, Finland). Antimicrobial activity of emericellipsin A was indicated by the minimal inhibitory concentration, which was defined as the lowest dose at which no visible growth was detected. Determination of bactericidal activity of emericellipsin A was performed by plating of the treated bacteria from the wells on agar medium (Muller Hinton, HiMedia). Following incubation, CFU counting was conducted.
Experimental Approach to the Problem A randomised and counter-balanced testing protocol was utilised to evaluate the effects of altering barbell position and hip-and knee-angles upon the reliability of force-time characteristics produced in the IMTP. Participants undertook three testing sessions, with the first serving to familiarise them with the experimental protocol and for the collection of anthropometric data (height, body mass, right femur length), barbell height and grip width. The subsequent two testing sessions were then conducted 7 days apart, with participants performing three maximal effort IMTPs in each of the four positions presented in Table  1  during each session.
Isometric Force-Time Curve Analysis All collected force-time curves were analysed using custom LabVIEW software (Version 14. 0, National Instruments). The onset of force application for each trial was determined visually, with this method chosen over automated methods as it has been performed previously in the literature relating to the IMTP  [32]  and is suggested as the gold standard method for force onset detection in isometric trials  [36, 37]. After analysis, the average value of each force-time characteristic generated across the three trials was calculated for each position in a custom Excel spreadsheet (Microsoft, Redmond, WA, USA). The maximum force generated during each IMTP trial was reported as the PF. Additionally, force at 50, 90, 150, 200 and 250 milliseconds (ms) from the initiation of the pull was calculated for each trial.
Pharmacovigilance data This data set is derived from a database for reporting, investigating and monitoring adverse drug reactions due to the Medicines and Healthcare products Regulatory Agency in the United Kingdom. It contains the number of reported cases of amnesia as well as the total number of adverse events reported for each of the m = 2446 drugs in the database. For more details we refer to  Heller and Gur (2011)  and to the accompanying R-package 'discreteMTP'  (Heller et al. , 2012) , which also contains the data. Heller and Gur (2011)  investigate the association between reports of amnesia and suspected drugs by performing for each drug a Fisher's exact test (one-sided) for testing association between the drug and amnesia while adjusting for multiplicity by using several (discrete) FDR procedures.
Next generation sequencing data We also revisit the next generation sequencing (NGS) count data analysed by  Chen and Doerge (2015b) , to which we also refer for more details. More specifically, we reanalyse the methylation data set for cytosines of Arabidopsis in  Lister et al. (2008)  which is part of the R-package 'fdrDiscreteNull'  (Chen and Doerge, 2015a). This data set contains the counts for a biological entity under two different biological conditions or treatments. Following Chen and Doerge (2015b), m = 7421 genes whose treatment-wise total counts are positive but row-total counts are no greater than 100 are analysed using the exact binomial test, see  Chen and Doerge (2015b).
Summarizing the findings from this section, it appears that the amount of power that is lost by avoiding randomisation depends primarily on the proportion of alternatives. The Pharmacovigilance data set may serve as an example for a small proportion of alternatives. In this setting, no power is lost -on average -by using discreteness and avoiding randomisation. When the proportion of alternatives is large however (the Arabidopsis methylation data may be considered a prototype example here) we think that the behaviour of the randomised/discrete procedure is determined primarily by how the quantity of signal is estimated. To support this fact, we propose in Appendix D a new procedure that combines our approach with the Storey estimator which rejects the same order of hypotheses as  [r-Storey].
Acknowledgements We would like to thank two anonymous referees and an associate editor for their helpful comments. This work has been supported by the  CNRS (PEPS FaSciDo)  and the  French  grants  ANR-16-CE40-0019  ( SansSouci project ) and  ANR-17-CE40-0001  ( Basics  project). We would also like to thank  Xiongzhi Chen  and  Thorsten Dickhaus  for helpful discussions.
Bioinformatics analyses are described in the Appendix. The sequencing data are available from European Nucleotide Archive (accession number PRJEB27292, http://www. ebi. ac. uk/ena/data/view/PRJEB27292) for all TTS sequencing samples under the accession codes ERS2548668 to ERS2548690 and for all RNA sequencing samples under the accession codes ERS2548828 to ERS2548845.