dataesr/scientific-paragraphs-categorization huggingface dataset:
Bioinformatics of mouse array datasets Statistical analyses and text processing were carried out using the R (version 3. 3. 1) and Perl software, respectively. Signal intensity values were obtained from CEL files after robust multichip average  [56, 57]. Differentially expressed genes were identified using linear models for microarray data  [58]. In this case, adjusted P values for multiple comparisons were calculated applying the Benjamini-Hochberg correction method  [59]. The heatmap3 package (http://CRAN. R-project. org/package=heatmap3) was then used to generate the expression heatmaps for the indicated genes. GSEA was performed with the described gene sets using gene set permutations (n = 1000) for the assessment of significance and signal-to-noise metric for ranking genes  [60]. THE EMT-associated gene signature was obtained from the Molecular Signatures Database (MSigDB)  [30].
The Gene Expression Omnibus (GEO) accession codes for other datasets used in this work include GSE25332 (endometrial cancer cell line)  [32] , GSE40059 (breast cancer cells)  [33, 34] , and GSE19631 (4TO7 breast cancer cells)  [35]. For the discovery of transcription factor binding motifs in the promoters of the deregulated miRNAs, the iRegulon software was used  [61]. A collection of 9713 position weight matrices (PWMs) was applied to analyze 10 kb centered around the transcription start site. Motif detection, track discovery, motif-to-factor mapping and target detection were performed with a maximum false discovery rate (FDR) on motif similarity below 0. 001. The gene set containing the targets for Nr2f1 was obtained from a previous work  [38].
Bioinformatics of human array datasets from tumors and breast cancer cell lines Heatmaps were plotted using the heatmap3 package, as indicated above. Coexpression matrices were calculated from the corresponding expression matrices for the indicated genes using the corrplot package (http://CRAN. R-project. org/package=corrplot). Correlations with a statistically significant (P value < 0. 05) Pearson correlation coefficient (r) according to the number of samples were labeled with asterisks in the figures. These statistically significant values were achieved with r > 0. 23 (in the case of dataset 1), > 0. 13 (in the case of dataset 2), and > 0. 17 (in the case of dataset 3). Survival analyses were performed through Kaplan-Meier estimates  [62]  of distant recurrence-free survival according to the level of enrichment of the described transcriptional signatures.
This enrichment was calculated using ssGSEA  [28, 60, 63]  and, subsequently, the Mantel-Cox test  [64]  was applied to statistically validate the differences between the survival distributions. The GEO accession codes for the datasets used were GSE36133 (for the Cancer Cell Line Encyclopedia expression analyses)  [65] , GSE65194 (dataset 1)  [66] , GSE25066 (dataset 2)  [67, 68]  and GSE78958 (dataset 3)  [69]  (for the coexpression analyses), GSE25066  [67, 68]  and GSE2603  [70]  (for the survival analyses), and GSE2603  [70]  (metastasis freesurvival).
Acknowledgements We thank  M. Blázquez ,  A. Abad , and  E. Fermiñán  for lab work, animal work, and microarray analyses, respectively. XRB is supported by grants from the  Castilla-León Government  ( CSI049U16 ), the  Spanish Ministry of Economy and Competitiveness (MINECO)  ( SAF2015-64556-R) ,  Worldwide Cancer Research  ( 14-1248 ), the  Ramón Areces Foundation , and the  Spanish Association against Cancer  ( GC16173472GARC ). MD ( BFU2014-52729-P ),  JMP  ( SAF2015-66015-R, PIE15/00076 ), and  PMF-S  ( SAF2014-51813-R ) are supported by  MINECO  grants. Spanish funding is partially supported by the  European Regional Development Fund. LFL-M, JC, and SR-F were supported by funding from the  Spanish Ministry of Education, Culture and Sports  ( LFL-M, FPU13/02923 ) and the  MINECO (JC ,  CD15/00113 ; SR-F,  BES-2013-063573 ).
, 2017; Rodriguez et al. , 2015). Indeed,  Hill et al. (2017)  confirmed that delivery mode and gestational age significantly influence bacterial composition in the infant gut during the first 24 weeks of life. The gut virome is an area of growing interest with relation to the microbiota  (Breitbart et al. , 2003; Minot et al. , 2013)  and gut virome alterations have been recorded between healthy and diseased states; for instance, an increase in the taxonomic richness of Caudovirales has been associated with IBD  (Norman et al. , 2015). However, there is a significant knowledge gap about healthy human viral populations, with large portions of the sequence data from human virome metagenomic studies representing uncharacterised viruses either not present in current databases or described using in silico methods without host information or taxonomic assignment  (Krishnamurthy & Wang, 2017).
Metagenomic analysis The quality of the raw reads was visualized with FastQC v0. 11. 3. Nextera adapters were removed with Cutadapt v1. 9. 1  (Martin, 2011)  followed by read trimming and filtering with Trimmomatic v0. 36  (Bolger, Lohse & Usadel, 2014)  to ensure a minimum length of 60, maximum length of 150, and a sliding window that cuts a read once the average quality in a window size of 4 falls below a Phred score of 30. Levels of Bacterial contamination were estimated by classifying reads with SortMeRNA v2. 0  (Kopylova, Noé & Touzet, 2012)  against the SILVA database and by aligning reads against the cpn60db  (Hill et al. , 2004)  with bowtie2 in end-to-end alignment mode  (Langmead & Salzberg, 2012). Reads were then assembled with the metaSPAdes assembler  (Nurk et al. , 2017). Virome sequence reads were classified into known viral orders and families using the Kaiju metagenomic classifier  (Menzel, Ng & Krogh, 2016)  and the NCBI non-redundant protein database (NCBI Resource  Coordinators, 2018).
The number of Torque Teno virus (TTV) homologues was counted by predicting genes from all contigs with Prodigal  (Hyatt et al. , 2010) , and then by BLASTp search against ORF1 from known TTV genomes  (Hsiao et al. , 2016). Prototypical crAssphage was downloaded from GenBank using accession number NC_024711. 1  (Dutilh et al. , 2014). Assembled contigs, in this study and from the Reyes et al. dataset, with similarity to crAssphage were detected by BLAST homology  (Reyes et al. , 2015). Complete, or near complete, crAss-like genomes (96-99 kb) were compared using the 'Pyani' program (https://github. com/widdowquinn/pyani), implementing the ANIm method with a 500 bp window size. The pyani percentage identity comparison calculations were exported to R and graphed using the gplot 'heatmap. 2' package.
Statistical analyses 16S OTU tables from the INFANTMET  (Hill et al. , 2017)  cohorts were obtained and used in this study to examine the connection between the virome and the bacteriome. In order to account for partially assembled viruses, abundances were correlated and those with a Spearman correlation of greater than 0. 9 were grouped into a single feature. All statistical analyses were performed in R v3. 3. 0 (R Core Team, 2016). Alpha diversity metrics including Chao1 richness and Shannon index were computed with PhyloSeq v1. 16. 2 (McMurdie & Holmes, 2013)  and plotted with ggplot2 v2. 2. 1  (Wickham, 2016). Between-group differences in alpha diversity were tested with a Mann-Whitney test (also known as a two sample Wilcoxon test). Unweighted Bray-Curtis distance was used as input for a Principle Coordinates Analysis (PCoA) as performed by the pcoa function in the ape package v4.
1. Adonis tests were performed using the vegan package v2. 4. 3  (Oksanen et al. , 2007)  in to test community level differences. Differential abundance analyses for both virome and 16S rRNA datasets was carried out with DESeq2  (Love, Huber & Anders, 2014)  based upon the previous reporting that it has increased sensitivity on datasets with less than 20 samples per group  (Weiss et al. , 2017).
RESULTS & DISCUSSION Sequencing resulted in a mean of 924,917 paired end reads per sample, which dropped to 697,558 following strict quality control, making this the deepest sequenced infant virome dataset to date  (Lim et al. , 2015; Reyes et al. , 2015). Paired end sequence reads were classified against the nr database from NCBI using Kaiju  (Menzel, Ng & Krogh, 2016)  which translates reads into six possible read frames for classification based on amino acid homology (Fig. 1A ). As with previous published findings, a large portion of sequence reads from the viromes could not be classified to any known viral taxonomic group  (Norman et al. , 2015; Reyes et al. , 2015) , with a mean 46. 59% unclassified reads per sample in this cohort (Fig. 1A ). For viruses which were classifiable, it was only possible to do so at higher taxonomic ranks.
, 2015) , contained genes that corresponded to at least one known Prokaryotic Virus Orthologous Groups (pVOGs)  (Grazziotin, Koonin & Kristensen, 2016)  or showed nucleotide homology to a known virus in the nt database  (Coordinators NR, 2016)  were used for further analysis. This resulted in a total of 2,028 assembled contigs (Table  S4 ) being taken forward for analysis, out of a possible 5,629, which recruited a median of 64. 075% of reads per sample. There was no difference detected in the percentage of reads recruited between birth mode groups (Wilcox test, p = 0. 57). Close to half of these assemblies (925, 45. 1%) bore no homology at any length to anything in the nt database with an E-value cutoff of 1e-5, highlighting the lack of viral representation in current databases  (Krishnamurthy & Wang, 2017).
Data Availability The following information was supplied regarding data availability: The raw sequence data has been deposited in the NCBI Sequence Read Archive under the accession number SRP106048. Accession numbers for each individual subject are available in Table  S1. FastQC reports, R code, assembled sequences, BLASTn output against the nt database, taxonomic assignments 16S sequences and count tables for both virome and 16S rRNA data were deposited in FigShare and are available at Ryan, Feargal (2018): INFANTMET Virome Study. figshare. Fileset. https://doi. org/10. 6084/m9. figshare. 5948443. v1.
After three washings with PBS and one with deionized water, the coverslips were mounted onto glass slides using the mounting medium Mowiol (Sigma-Aldrich, MO). The observations were performed on a Zeiss confocal microscope LSM800 (Munich, Germany) using a x63 apochromatic objective (NA 1. 4), 0. 7 μm optical sections and photos were analyzed using Zen software for microscopy. All experiments were performed in triplicate.
2a ). For sake of consistency, the same rectangular grid has been used when scanning the SOL width on the plane containing the plasma centroid. Specifically, SOL width λ q of 2, 5 and 10 mm have been considered. Here, HFE configuration characterized by the presence of 2-nearby divertor poloidal field nulls have been designed and optimized by means of CREATE-NL code (non-linear plasma evolution code), described in  [17]. The procedure proposed for the design and optimization of the equilibria using the CREATE-NL code exploits the linearized relation between the plasma-wall gaps (the distance between the plasma surface and the first wall, measured along a given direction  [18] ) and the PF currents in two steps. The first step allows to have a first cut of the HFE equilibrium starting from a standard Single Null (SN) LFE configuration; a new equilibrium with a second null point within a limited distance from the LFE x-point is obtained, forcing the plasma boundary to be almost unchanged, apart from the region in the nearness of the null point.
4  for JET-ILW discharges. Both inner and outer f x,xp increase when moving from LFE (σ = 1) to HFE configuration (0. 25 < σ < 0. 45). The maximum flux expansion increase has been obtained for the discharge #92086 by relaxing the plasma distance to the inner wall. It should be noted that this configuration cannot be used in H-mode discharges because of the limitations on the permitted operational plasma-wall distance for heated plasmas. Finally, the aforementioned LFE and HFE configurations have been recently used to address the physics of a possible dependence of radiative volume and total radiated power on the distance between the two nulls  [15]. Aim of this study has been the evaluation of the impact of main magnetic divertor geometry parameters, as the flux expansion and the connection length, on the radiation pattern disentangled by the change of recycling happening at the same time, focusing on bolometer and Langmuir probe measurements analysis supported by EDGE2D-EIRENE code  [22, 23]  interpretative modelling.
Acknowledgments The authors would like to acknowledge  Prof. R. Albanese ,  Dr. F. Crisanti  and  Dr. G. Artaserse  for their fruitful suggestions. This work has been carried out within the framework of the  EUROfusion Consortium  and has received funding from the  Euratom  research and training programme  2014-2018  under grant agreement No. 633053. The views and opinions expressed herein do not necessarily reflect those of the  European Commission.
This is an exciting report on a new strategy to assess inflammation by using a specific ligand for an antimicrobial molecules. This strategy might pave the way to new tools for visualization of inflammatory processes in general and therefore is of broad interest. My only concern is related to the issue whether lactoferrin is granulocyte specific. I acknowledge that the authors tested whether Lactoferrin is expressed in CD14+ human monocytes, Cd19+ B cells and CD3+ T cells. However, according to Immgen database (https://www. immgen. org/) lactoferrin  (lactotransferrin, Ltf)  is expressed in BM-macrophages, Ly6C+ classical monocytes; some expression also in B cell precursos and hematopoetic stem cells in the mouse  (Immgen database; immgen. org). Since the authors claim that Lactoferrin might serve as a marker for granulocytes I feel that a analysis of these cell types is warranted as well (e.
5, and MUB40#4 theo MW 4. 8 kDa; exp Mr 20,4 kDa) (Figure  1D ). The structure of MUB40 peptides was analyzed by Circular Dichroism (CD). The four resulting signals were almost similarly shaped and could be assigned to unstructured peptide chains or polyproline II-like scaffolds  (Fig 1E). In regards to the thermal transition curves (data not shown), no obvious conformational changes were identified and we assumed a global unordered structure for all peptides. Nevertheless, slight differences were observed between the CD spectra, mostly in the negative band within the 200 nm range: MUB40#1 showed a lower intensity signal, significantly 1 to 1,5 nm red-shifted, as compared to other MUB40 peptides (#2, #3 and #4) minima. Even if no structural element was evidenced from the CD profiles, this singularity could reflect a specific feature of MUB40#1.
Flow cytometry Human. Neutrophils and PBMCs were separated as described in Supplementary Methods. Naïve cells were resuspended in PBS + EDTA 2mM. Fixed and permealized were were obtained by incubation in PFA 3. 2% for 30 min and resuspention in PBS + Triton 0. 1% for 30 min. Naïve and fixed/permeabilized cells were incubated with CD45-FITC and MUB40-Alexa405 peptide (1 L/mL) for 15 min at room temperature. Cells were analyzed with a FACSCANTO II (BD) and data were analyzed using Flowjo software. Mouse. Blood leucocytes were purified by dextran, washed in PBS EDTA and kept on ice. For hematopoietic populations staining, 2 to 3 million cells were resuspended in PBS EDTA, blocked with 16/32 for 15 minutes and stained with antibodies for 30 minutes at 4°C (CD45 PE-CF594, CD3e FITC, B220 PE-CY7, NKP46 FITC, CD11b PE from BD biosciences, and Ly6G APC-H7, Ly6C APC from Biolegend).
Competing financial interests The authors declare no competing financial interests (shown in Figure  S1B ). (C) Colonic goblet cell granules were labelled with MUB40#1-Cy5 (1 g/mL, magenta), which was not the case for MUB70-Cy5  (Coïc et al. , 2012)  or MUB40#2-#4 peptides (data not shown). Actin (red) ; bar, 20 m. (D) Elution profiles of MUB40 peptides (#1 -#4) were obtained by analytical gel filtration (absorbance at 280 nm). Samples were prepared at 10µg/ml in the elution buffer (20 mM phosphate buffer, 150 mM NaCl, pH7. 4). MUB40#1 assembled as a trimer, similarly to MUB70  (Coïc et al. , 2012) , not MUB40#2, MUB40#3, and MUB40#4. The relative masses  (15,9 ; 22,0 ; 20,5 and 20,4 respectively)      (A) Human neutrophil granules were purified and fractionated on a 3-layers Percoll gradient  (Kjeldsen et al.
Samples were directly incubated on the injection sampler thermostated at 37°c. HPLC and LC-MS analyses were performed as previously described in Supplementary Information, applying a 15% to 40% linear gradient of acetonitrile in 10mM ammonium acetate over 20 minutes. An Aeris Peptide 3. 6µ XB-C18 column was employed for LC-MS analysis of the L-peptide digest fragments, which were identified in positive electrospray ionization mode (data not shown).
Half of each sample was loaded and separated at 250 nl. min -1 on a home-made C 18 30 cm capillary column picotip silica emitter tip (75 µm diameter filled with 1. 9 µm Reprosil-Pur Basic C 18 -HD resin, (Dr. Maisch GmbH, Ammerbuch-Entringen, Germany)) equilibrated in solvent A (0. 1 % FA). Peptides were eluted using a gradient of solvent B (ACN ,0. 1 % FA) from 2% to 5% in 5 min, 5% to 35% in 30 min, 30% to 50% in 5 min at 250 nL/min flow rate (total length of the chromatographic run was 50 min including high ACN level steps and column regeneration). Mass spectra were acquired in data-dependent acquisition mode with the XCalibur 2. 2 software (Thermo Fisher Scientific, Bremen) with automatic switching between MS and MS/MS scans using a top-15 method. MS spectra were acquired at a resolution of 60000 with a target value of 3 × 10 6 ions.
The scan range was limited from 300 to 1700 m/z. Peptide fragmentation was performed via higher-energy collision dissociation (HCD) with the energy set at 28 NCE. Intensity threshold for ions selection was set at 1 × 10 5 ions with charge exclusion of z = 1 and z > 6. The MS/MS spectra were acquired at a resolution of 17500 (at m/z 400). Isolation window was set at 2 Th. Dynamic exclusion was employed within 30s. Data were searched using MaxQuant 1 (version 1. 5. The following search parameters were applied: carbamidomethylation of cysteines was set as a fixed modification, and oxidation of methionine and protein N-terminal acetylation were set as variable modifications. The mass tolerances in MS and MS/MS were set to 5 ppm and 20 ppm, respectively. Maximum peptide charge was set to 7, and 5 amino acids were required as minimum peptide length.
Acknowledgements We are thankful to  A. -M. Nicola  and the  Plate-Forme d'Imagerie Dynamique (Institut Pasteur, Paris)  for help with live imaging experiments. F. J. is an employee of the  Centre National de La Recherche Scientifique (CNRS). This work was supported by the  Fondation Laurette Fugain  ( LF-2015-15 ) ( BSM ) and  ANR   JCJC grants  ( ANR-17-CE15-0012 ) (BSM) -( ANR-16-CE15-0012-01 ) (FJ). with their migration on SDS gel and their iBAQ (Intensity based Absolute Quantification) metrics 2.
(2017b)  to explain the extended Lyman-α, He iiλ1640 and C ivλ1549 emission, and their kinematics. In addition, the two brightest detections at 850 µm ( f 850 > 18 mJy) sit at the density peak of the LAEs overdensity, likely pinpointing the core of the protocluster. Future multiwavelength and spectroscopic datasets targeting the full extent of the BOSS1441 overdensity have the potential of firmly characterizing a cosmic nursery of giant elliptical galaxies, and ultimately of a massive cluster.
A complete view of these systems requires a multiwavelength dataset. In particular, submillimeter galaxies (SMGs;  Smail et al. 1997)  have been shown to be linked to merger events (e. g. ,  Engel et al. 2010; Ivison et al. 2012; Alaghband-Zadeh et al. 2012; Fu et al. 2013; Chen et al. 2015; Oteo et al. 2016)  and to be good tracers of protoclusters (e. g. ,  Smail et al. 2014; Casey 2016; Hung et al. 2016; Wang et al. 2016; Oteo et al. 2018; Miller et al. 2018). For these reasons, and to directly test whether our newly discovered ELANe could be powered by intense obscured star-formation, we have initiated a submillimeter campaign with the James Clerk Maxwell Telescope (JCMT) and the Atacama Pathfinder EXperiment (APEX) telescopes to map the obscured star-forming ac-tivity (if any) associated with these rare systems and their environment.
2) embedded in it, (ii) extended emission ( 30 kpc) in He iiλ1640Å and C ivλ1549Å and (iii) double-peaked line profiles with velocity offsets of ≈ 700 km s -1 for Lyα, He ii, and C iv. In light of these evidences,  Cai et al. (2017b)  explained this ELAN as circumgalactic/intergalactic gas powered by photoionization or shocks due to a galactic outflow, most likely powered by an enshrouded AGN. With the SCUBA-2 data we can start to better constrain the nature of this powering source. This work is structured as follows. In Section 2, we describe our observations and data reduction. In Section 3 we present the catalogs at 450 and 850 µm, along with reliability and completeness tests. In Section 4, we describe how we determined the pure source number counts, estimated the underlying counts model through Monte Carlo simulations, and how we used this models to get the true counts.
Second, we obtained the raw number counts by summing up the number densities of the sources within each flux bin. Finally, to get to the pure source differential number counts, we subtracted the number counts similarly obtained from the true noise maps, if any, from the counts obtained from the signal maps. Figure  5  shows the obtained pure source differential number counts (black data points) for both 850 (top panel) and 450 µm (lower panel). To obtain the underlying counts models we ran Monte Carlo simulations following e. g. ,  Chen et al. (2013a,b). First, we create a simulated image by randomly injecting mock sources onto the jackknife maps. The mock sources are drawn from an assumed model and convolved with the PSFs. For the counts models we use a broken power-law of the form dN dS =        N 0 S S 0 -α if S ≤ S 0 N 0 S S 0 -β if S > S 0 , (1) and started from a fit to the observed counts.
Cai To constrain the nature of source B, we compiled all its data available from the literature, and compared them to known SED. We summarize all the available observations in Table  7   11  , while we plot them in Figure  11. To compare these data-points to known SEDs, we fixed the redshift of the source to the redshift z = 2. 319 determined from the He ii line emission  (Cai et al. 2017b ), and we fitted the data leaving the normalization free. We first take in consideration the average SED for SMGs obtained from the 99 sources in ALESS F. Arrigoni Battaia et al. : Overdensity of submillimeter galaxies around the z 2. 3 MAMMOTH-1 nebula  (da Cunha et al. 2015) , and all the available average SEDs from that publication. The left panel of Figure  11  shows this test, highlighting the shortage of emission at the WISE bands for these SED templates (we plot only two to avoid confusion) in comparison to the source B's data-points.
Summary We are conducting a survey of all the known ELANe  (Cantalupo et al. 2014; Hennawi et al. 2015; Cai et al. 2017b; Arrigoni Battaia et al. 2018)  with the JCMT and APEX telescopes to assess the presence of starburst activity in these systems and their environments. In this work we focused on the SCUBA-2/JCMT data at 450 and 850 µm obtained for an effective area of ∼ 127 arcmin 2 around the ELAN MAMMOTH-1 at z = 2. 319  (Cai et al. 2017b) , and thus targeting the known peak area of the LAE overdensity BOSS1441  (Cai et al. 2017a ). Thanks to this dataset we found that 1. the 850 µm source counts are 4. 0 ± 1. 3 times higher than in blank fields  (Chen et al. 2013b; Casey et al. 2013; Geach et al. 2017) , confirming also in obscured tracers the presence of an overdensity. Intriguingly, the two brightest submillimeter detections, MAM-850.