dataesr/scientific-paragraphs-categorization huggingface dataset:
BiRewire can be also used for the randomization of general presence (1)-absence (0) matrices, where the presence distributions must be preserved. Specifically, BiRewire enables users to gen-erate bipartite graphs from any "0-1" matrix, as well as rewired versions of these graphs. DEsubs  [275]  is an R package designed to extract differentially expressed, disease-associated subpathways from a pathway network generated from RNA-seq experiments. It comes with advanced visualization and enrichment analysis with regard to various biological and pharmacological features. Its circular representation could be potentially useful for the visualization of bipartite networks.
Dataset collections Last, we present some repositories (databases) that hold numerous biological network datasets, including bipartite ones. Even though some of the datasets mentioned earlier are highly curated and biologically important, here we restrict our attention to collections of datasets and thus we do not list specific datasets. Some of these databases contain various datasets, even of nonbiological origin (such as the Stanford Large Network Dataset [SLND], Colorado Index of Complex Networks [ICON], and Koblenz Network Collection [KONECT]), whereas there are several databases specialized for ecological networks, highlighting the importance of such data in current network research. SLND accompanies the SNAP library  [276] , which has been actively developed since 2004 and is organically growing as a result of the Leskovec group's research in analysis of large social and information networks.
The datasets available on the website were mostly collected for the research performed by the team, and the website has been active since 2009. [277]. ICON  [278]  is a comprehensive index of network datasets from all domains of network science, including social, web, biological, ecological, transportation, and technological networks. Each network record is annotated with its graph properties, description, size, and similar information, and many records include links to multiple networks. The contents of ICON are curated by volunteer experts from Professor Aaron Clauset's research group at the University of Colorado-Boulder. KONECT  [279]  is a project to collect large network datasets of all types in order to perform research in network science, collected by the Institute of Web Science and Technologies at the University of Koblenz-Landau.
KONECT contains several hundred network datasets of various types, including directed, undirected, bipartite, weighted, unweighted, signed, and rating networks. The networks of KONECT cover many diverse areas such as social networks, hyperlink networks, authorship networks, physical networks, interaction networks, and communication networks  [280]. The ecological databases include the Web of Life, the Interaction Web Database, and the Kelpforest Database. The Web of Life  [281]  provides a graphical user interface, based on Google Maps, for visualization and download of data on ecological networks regarding species interactions. It is designed and implemented in a relational database, allowing sophisticated and user-friendly searches. Data can be downloaded in several common formats, and a web-service for data transmission in JavaScript Object Notation is also provided.
The Interaction Web Database  [282]  contains datasets on species interactions from several communities in different parts of the world. Data currently available cover a variety of interaction types, including plant-pollinator, plant-frugivore, plant-herbivore, plant-ant mutualist, and predator-prey interactions. The developers' goal is to expand the database to make it a repository of data on any kind of interactions. The Kelpforest Database  [283]  serves as a repository for the knowledge of identities, life histories, and interactions between the species present in the near shore kelp forest ecosystems of the eastern Pacific Ocean, focusing on central and southern California. The information that it contains could aid in the interpretation of species' spatial and temporal patterns and serve as the basis on which to construct and parameterize mathematical models of these species' rich communities  [284].
Extensive propagation simulations have been carried out using the commercial software FiberDesk [23] to solve the extended nonlinear Schrödinger equation (NLSE) for the electric field envelope giving access to the complete dynamics (pulse amplitude, gain, spectral buildup, timing, …). Here, we typically solve: ( ) ( ) 2 ! 1 2 ( ) ( ) d (1 )( d ) n n n A i n z n T n i T T R t A A e i i A AT t t α ω ω β ω ω γ τ ∂ ∂ ∂ ∂ ≥ - ∂ ∂ ′ = + ′ ′ - + + -       (3) where α(ω) is the linear absorption spectrum, τ -1 = ω p the "shock" time for self-steepening, and R(t) the normalized function accounting for both the instantaneous electronic and delayed Raman response. In this scalar 1D simulation neither transverse mode structure, nor vectorial effects (polarization) were included.
(I-L) Thrombin generation was initiated by direct addition of liposomes to plasma as described in Methods, at 10% HETE-PC, and measured in the absence (I and K) or presence (J and L) of 80 nmol/l anti-TFPI antibody preincubated for 15 minutes, in either normal (I and J) of FVIII-deficient plasma (K and L). Data is shown as Tukey box plots, with 1-way ANOVA with Tukey post hoc multicomparison test. *P < 0. 05. The fold-increase in peak thrombin observed with HETE-PLs in the presence of anti-TFPI was less than in the absence of anti-TFPI and was no longer dependent on FVIII (Figure  3, A  and B ). This is also consistent with a model in which HETE-PLs stimulate the activities of all coagulation complexes in tandem. HETE-PEs prevent bleeding in mice lacking FVIII. To extend our findings with FVIII-deficient human plasma to an in vivo model, we administered 12-HETE-PE (78 ng)/TF liposomes to FVIII-deficient mice, which are unable to stop bleeding following a tail cut.
Extrinsic tenase (TF/FVIIa) activity was first determined by measuring cleavage of FX to FXa. This was significantly increased by 12-HETE-PE or 15-HETE-PE, but not by 12-HETE-PC (Figure  4, A  and B ). As control, HETE-PLs had no effect on cleavage of the chromogenic substrate by FXa (data not shown). Similarly, all 3 HETE-PLs enhanced intrinsic tenase (FVIIIa/FIXa), with a lower effect for HETE-PC than -PEs (Figure  4, C  and D ). Last, 12-and 15-HETE-PE substantially increased thrombin generation by FXa/FVa (prothrombinase), while 12-HETE-PC was ineffective (Figure  4, E  and F ). Overall, HETE-PEs were more effective than PC analogs, with only HETE-PC significantly elevating intrinsic tenase activity. We note that enhancement of individual complexes is lower than the overall effect on the full cascade, as would be expected due to amplification effects of multiple coagulation pathways working in tandem, as in plasma.
However, thrombin generation was significantly increased by the inclusion of HETE-PLs, although the increase in post-CPB plasma appeared slightly lower. Along with our data using FVIII-deficient plasma and mice, this further supports the idea that eoxPL have the potential to improve coagulation in the context of a bleeding defect due to reduced levels of coagulation factors. mean diameter (n = 4, mean ± SEM). (E) X-ray diffraction was carried out at beamline I22 (Diamond Light Source). Samples in glass capillary tubes were held at 37°C ± 0. 1°C, and images were integrated as described in Methods (n = 3, mean ± SEM). (F-H) SPR analysis of protein binding to nanodiscs demonstrates increased binding in the presence of HETE-PE. Control discs were composed of 15% SAPS, 30% SAPE, and 55% DSPC. Nanodiscs containing HETE-PE were composed of 15% SAPS, 20% SAPE, 55% DSPC, and 10% HETE-PE.
Products were analyzed in the multiple reaction monitoring (MRM) mode monitoring transitions from the parent ion to daughter ion of 179. 1 (12 HETE [M-H]-) every 200 ms with a collision energy of -45-42V. The AUC for the parent to 179. 1 was integrated and normalized to the internal standard. For quantification of these lipids, standard curves were generated with purified standards for each HETE-PE/PC. Thrombin generation assays. Thrombin generation assays in plasma were performed using a Fluoroskan Ascent plate reader (ThermoLabsystems). Cleavage of prothrombin to thrombin was measured using 0. 5 mmol/l fluorogenic substrate Z-Gly-Gly-Arg-AMC and thrombin activity compared with thrombin calibrator (Stago). Thrombin generation was calculated from raw fluorescence data  (48). In some experiments, plasma congenitally deficient in FVIII, FIX, or FXI was used and/or anti-TFPI antibody was added at 80 nmol/l.
). Liposomes (50 μl) containing 15-HETE-PE, generated as above, were added to 950 μl deionized water and placed in a clear plastic ζ cell (DTS 1070, Malvern) and equilibrated for 2 minutes at 25°C prior to measurement. Each was measured at least 4 times. Liposome diameter was also measured using by nanoparticle tracking analysis using a NanoSight LM10 system (Malvern Instruments Ltd. ) running NTA-software v2. 3 and configured with a temperature controlled, 488nm LM14 laser module and a high-sensitivity camera system (OrcaFlash2. 8, Hamamatsu C11440). In brief, 4-mM liposomes were diluted 1,000 times in nano-particle free water (Fresenius Kabi) and analyzed under controlled fluid flow at 37°C, as previously described  (49). Data were combined from 4 preparations done on different days, with each analyzed 5 times.
25 m from the sample position. Diffraction images were integrated using a custom software package developed using the IDL programming language and calibrated against silver behenate, which has a well-defined layer spacing of 58. 38 Å  (50). Nanodisc preparation and surface plasmon resonance (SPR). Nanodiscs of varying lipid compositions were prepared as described with the following modifications  (51). Lipids were mixed in buffer containing 56. 3 mM deoxycholate at 43°C so as to facilitate solubility. All steps up to the addition of Bio-beads were performed at 43°C. Prothrombin and FX binding to nanodiscs was evaluated using a Biacore 3000 instrument as described  (37). Binding isotherms were plotted using the maximal steady-state binding response units (RU) vs. concentration of protein flowed over the chip, from which K d and maximal protein-binding RU (RU max ) values were derived using the single-site ligand binding equation.
Molecules of protein bound per leaflet were determined using the following equation: ([RU max /RU disc ] × [MW disc /MW protein ])/2, where RU disc equals the RU change from disc loading, MW disc equals the molecular weight of the Nanodisc, and MW protein equals the protein molecular weight. Statistics. Statistics were analyzed using 1-way ANOVA. Post hoc Tukey tests were used to determine P values between individual data groups. The Mann Whitney U test was applied to examine differences between unrelated variables, while the Wilcoxon Rank test was used to examine differences between related samples. Analysis of multiple related samples was performed using Friedman's test. P < 0. 05 was considered significant. Study approval. All blood donations were approved by the Cardiff University School of Medicine Ethics Committee, were with informed consent (SMREC 12/37, SMREC 12/10), and were in accordance with the Declaration of Helsinki.
(I-L) Thrombin generation was initiated by direct addition of liposomes to plasma as described in Methods, at 10% HETE-PC, and measured in the absence (I and K) or presence (J and L) of 80 nmol/l anti-TFPI antibody preincubated for 15 minutes, in either normal (I and J) of FVIII-deficient plasma (K and L). Data is shown as Tukey box plots, with 1-way ANOVA with Tukey post hoc multicomparison test. *P < 0. 05.
toplasmic staining, A combined score of 4 or greater was considered positive for p1(tNraa overexpression. HPV genotyping was performed using the Type-Specific E7 PCR bead-based multiplex assay (TS-E7-MPG, IARC, France)  [17,  22f. Given that HPV serology was available on all cases; our analysis defined a HPV+ tumor as HPVI6 E6 antibody positive. We subsequently compared this to tumor results based on p16 expression and HPV DNA. Participants underwent a one-time follow-up conducted between 2012 and 2015. Mortality data including cause and date of death were obtained from at least two information sources for 7 5Yo of cases, and one source for the remaining 25Yo. ln Prague and Aviano follow-up was completed by review of medical charts alone. In all other centers, medical chart reviews together with information from population-based registries at the regional or national level were used.
The sequencing reaction was then performed using the Beckman Dye Terminator Cycle Sequencing (DTCS) kit (Beckman Coulter, California, USA), and sequence detection was made by capillary electrophoresis in a Beckman Coulter capillary electrophoresis CEQ 8000 system. Newly obtained sequences were first blasted against the whole nucleotide NCBI database  [17]. The Max Planck Institute Geno2Pheno [HCV] tool was then used to confirm the genotype  [18]. A final step of phylogenetic analysis was performed using the MAFFT alignment tool  [19]  from the Japanese Computational Biology Research Consortium. The phylogenic tree was built using reference sequences described in Murphy et al  [20]. Our sequencing assay is regularly assessed by the Quality Control for Molecular Diagnostics (QCMD) scheme (catalogue code: QAV034117).
CTA Simulations We performed our simulations with the ctools (v1. 4. 2) public analysis package  [20]   1  and the public CTA instrument response files 2  (IRF, v. prod3b-v1). We chose the IRFs based on the source visibility from both CTA sites (with a zenith angle ∼ 20 • ) and with analysis cuts optimized for exposures comparable to both the source variability timescales and CTA long term observing plan. The basic input of our simulations is the spectrum of the source, derived as an extrapolation of the best-fit Fermi spectra to the CTA energy range, including the effects of the γ-ray absorption both along the path to the Earth (EBL)  [21] , and inside the source (internal absorption)  [22] , which was modelled by a cut-off at ∼30 GeV. We considered three gamma-ray states: • quiescence, described by a broken power law  [7]  with a break at E b = 1 GeV, photon indices Γ 1 = 2.
Acknowledgments The authors acknowledge contribution from the grant  INAF CTA-SKA , "Probing particle acceleration and γ-ray propagation with  CTA and its precursors" (PI F. Tavecchio). This research made use of ctools, a community-developed analysis package for Imaging Air Cherenkov Telescope data. ctools is based on GammaLib, a community-developed toolbox for the high-level analysis of astronomical gamma-ray data. This research has made use of the CTA instrument response functions provided by the  CTA Consortium and Observatory , see https://www. ctaobservatory. org/science/cta-performance/(version prod3b-v1) for more details. We gratefully acknowledge financial support from the agencies and organizations listed here: http://www. cta-observatory. org/consortium_acknowledgments. This paper went through internal review by the  CTA Consortium.
Modelling Full orbit simulations of the observed fast-ion transport induced by the externally applied 3D fields have been carried out using the ASCOT code, a realistic fast-ion distribution and the 3D perturbations fields calculated using the vacuum approach and the plasma response given by MARS-F  [20]. The magnetic fields were generated as the combination of the axisymmetric equilibrium provided by the CLISTE code  [21]  with the 3D perturbation calculated by MARS-F and interpolated in ASCOT from a cylindrical In this case, the initial fast-ion distribution was calculated for NBI#8 as this beam is more energetic and presents more associated fast-ion losses. The beam deposition was calculated from the profiles at the phase where coils are turned on (figure 2(a)) as the ion deposition in the scrape-off layer (figure  2 (b) and (c)) is very sensitive to density variations, entailing a significant impact on fast-ion losses.
under grant agreement number 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission. The simulations were partly performed on the MARCONI supercomputer (CINECA) under project reference FUA32 ASCOT-US. D. Z. acknowledges support from the A*MIDEX project (no. ANR-11-IDEX-0001-02) funded by the Investissements d'Avenir French Government program, managed by the French National Research Agency (ANR).
Characterization of early stages viral transactivation We followed high throughput transcriptomics approach to understand viral transcriptome during transactivation. Separate sequencing studies were carried out to evaluate sncRNAs as well as mRNAs. Biological duplicate samples prepared on two different days were processed for each study with appropriate controls. DMSO and TSA treated U2OS cells without having viral genome were used for normalizing the sequencing data for further analysis. Viral mRNA profile upon HHV-6A transactivation. mRNA library was prepared from both solvent (DMSO) control treated as well as TSA treated U2OS cells carrying latent HHV-6A or without having any viral genome. Next generation sequencing revealed minor changes in viral transcription upon TSA treatment (Fig. S3 ).
Total RNA was extracted and were used for cDNA synthesis and subsequent RT-PCR. Data represent the mean ± SEM of three independent experiments. dpi, days post infection. d Immunoprecipitation (IP) of HHV-6 IE2 protein was carried out to test immediate early protein synthesis. U2OS cells carrying latent HHV-6A were treated with DMSO or TSA for 2 days. Total cell lysates were extracted and used for immunopreciptation. A smaller ~55 kDa fraction of IE2 was detected in IP. e Viral DNA replication was studied by qPCR. U2OS cells carrying latent HHV-6A were treated with 80 ng/ml of TSA or DMSO for two different time intervals. Total genomic DNA was extracted and were used for qPCR analysis. Data represent the mean ± SEM of three independent experiments. dpi, days post infection. f Detection of several different HHV-6A encoded small non-coding RNAs by Northern hybridization.
Impact of viral transactivation on host cell physiology Loss of viral genome, lack of major increase in viral replication and protein expression suggested negligible impact of viral transactivation on host cell. To further evaluate this, we analyzed human transcriptome in the previously described set up. Viral transactivation in U2OS cells was associated with upregulation and downregulation of several human transcripts (Fig. S4 ). Altered transcriptome profile of HHV-6A transactivation was compared to known molecular pathways using publically available datasets like gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (Table  S3 ), which suggested a complex effect of viral transactivation on host cell. Similar analysis of human miRNA transcriptome revealed substantial changes in human miRNAome upon TSA-mediated viral transactivation (Fig.
Quantitative real time PCR Quantitative PCR (qPCR) was performed using PerfeCTa qPCR SuperMix (Quanta Biosciences) on a StepOnePlus real time PCR platform (Applied Biosciences) using manufacturer's protocol and SYBR Green chemistry. Amplified data was analyzed using StepOne Software v2. 1. HHV-6 genome equivalents per cells was calculated by determining host cell number by amplification of the PI15 gene as described before. 23 The list of primers used for amplifying mRNA transcripts are summarized in supplementary Table  S6.
Sequencing and raw data processing. Expression profiling libraries were sequenced on Illumina HiSeq 3000/4000 instruments in 50base-pair-single-end mode and base calls provided by the Illumina Real-Time Analysis (RTA) software were subsequently converted into BAM format (Illumina2bam) before de-multiplexing (BamIn-dexDecoder) into individual, sample-specific BAM files via Illumina2bam tools (1. 17. 3 https://github. com/wtsi-npg/ illumina2bam). Transcriptome analysis. Transcriptome analysis was performed with the Tuxedo suite. For each sample, NGS reads passing vendor quality filtering were aligned to a combination of the hg38 reference genome assembly provided by the UCSC Genome Browser based on Genome Reference Consortium GRCh38 and the Human betaherpesvirus 6 A (NCBI RefSeq NC_001664) with the TopHat2 (v2.
1. 1, http://genomebiology. com/2013/14/4/R36/ abstract), a splice junction mapper utilizing the Bowtie2 short read aligner (v2. 2. 9 http://www. nature. com/nmeth/journal/v9/n4/full/ nmeth. 1923. html). Thereby, "basic" Ensembl transcript annotation from version e87 (December 2016) and the Human betaherpesvirus 6 A annotation parsed from the RefSeq entry served as reference transcriptome. Cufflinks (v2. 1. 1, http://www. nature. com/ nbt/journal/v31/n1/full/nbt. 2450. html) allowed for transcriptome assembly, customary including novel transcript structures, on the basis of the reference transcriptome and spliced read alignments, as well as raw transcript quantification. Before differential expression calling with Cuffdiff (included in Cufflinks v2. 1. 1, http://www. nature. com/nbt/journal/v28/n5/full/nbt.
1621. html), transcriptome sets of each sample of each group to be compared were combined via the Cuffmerge algorithm. Finally, the cummeRbund (http://www. bioconductor. org/packages/release/ bioc/html/cummeRbund. html) and biomaRt (http://www. bioconductor. org/packages/release/bioc/html/biomaRt. html) Bioconductor libraries were utilized in custom R scripts to perform quality assessment and further refine analysis results. Sequencing of small RNAs Sequencing libraries for 24 samples were prepared. First the total RNA was checked for signs of degradation on a 2100 Bioanalyzer instrument (Agilent). Second small RNA stranded libraries from total RNA (1uq RNA per library) were prepared using the CleanTag Ligation Kit (TriLink BioTechnologies). The Bioanalyzer was then used to check the libraries for the intended miRNA fragment peak at 141 bp.
After confirmation a Pippin Prep instrument (Sage Science) was used to select the wanted fragment size range. Quality and concentrations of the final libraries were measured by PicoGreen on an infinite F200 instrument (Tecan). Libraries were then sequenced on a NextSeq 500 platform (Illumina) using highoutput v2 kits with 75 cycles and producing 38Mio single-end reads in mean per sample. Bioinformatics for miRNA. Reads that passed the chastity filter on the NextSeq 500 were subject to de-multiplexing and trimming of TriLink adapter residuals using Illumina's bcl2fastq v2 software (v2. 19. 1). To refine the output, read quality was checked with FastQC software (v0. 11. 5) and reads shorter 10 bases or longer 25 bases or containing "N" as a base call, were discarded. In a first analysis the cleaned reads of each sample were de-replicated using the USEARCH software (v8.
1. 1681) resulting in a list of unique sequences annotated with their frequency in the cleaned read data. These lists of sequences were then searched for via Blast in the X83413. 1 Human betaherpesvirus 6 A, variant A DNA reference sequences download from the NCBI database. As the size of the database is small an evalue threshold of 0. 0001 was set to pre-filter possible hits. The second analysis of the cleaned reads consisted in read mapping to the human reference genome (assembly hg38) using the RNA mapping software STAR (v2. 5. 1) with a minimum of 16 matching bases between mapped read and reference, a maximum of 1 mismatch and switched off slice awareness. Uniquely mapped reads to miRBase annotated mature miRNAs were then counted with HTSeq software (v0. 6. 0). The raw counts were then normalized and analyzed for differential miRNA expression with the DESeq2 (v1.