dataesr/scientific-paragraphs-categorization huggingface dataset:
This study was conducted within the  RESERVOIRS program  supported by  European (ERDF/FEDER)  funds and assistance from  CollectiviteTerritoriale de la Guyane and Direction Regionale pour la Recherche et la Technologie , and the  MicroBIOME project granted by Laboratoire d'Excellence CEBA "Investissement d'Avenir " and managed by the  Agence Nationale de la Recherche  ( CEBA, Ref. ANR-10-LABEX-25-01 ). AC benefits from a PhD grant from the  French Guiana University. JFG is sponsored by  Institut de Recherche pour le Developpement , the  Centre National de la Recherche Scientifique, Institut national de la recherche agronomique and Montpellier University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Definition of the Mesa structure The aim is to create a structure, which can improve the distribution of the electric field at the triple point. Figure  5  presents the principle of the mesa structure which consists in creating a trench at the bottom of the two electrodes of the conventional structure. Indeed, the metallization of copper is flush with the vertical side, burrowed in the ceramic, forming a plateau (mesa). As we will see below, the distribution of the electric field at the triple 20903-p4 Fig. 6. FEM simulation of the conventional structure (Fig. 4 ). point will depend on the permittivity and the conductivity of the materials (permittivity, conductivity) and the geometrical parameters of the mesa, which are the height h and the width e of the groove (as defined in Fig. 5 ). In order to estimate the benefits on the reduction of the maximum electric field, a finite element study (FEM) of the proposed structure is carried out with Comsol Multiphysics software.
Isolation and growth conditions In 2016, the strain Marseille-P2799 T was isolated from a urine sample from a 2-month-old child with rotavirus gastroenteritis. Using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), the strain has not been identified. The screening was performed on a Microflex LT spectrometer (Bruker Daltonics, Bremen, Germany), as previously reported  [8]. Spectra obtained (Fig. 1 ) were imported and analysed using the BIOTYPER 3. 0 software against the Bruker database, which was constantly updating from the MEPHI database http://www. mediterranee-infection. com/ article. php?larub=280&titre=umrs-database  [1]. The strain Marseille-P2799 T was isolated after 72 hours of incubation at 37°C on 5% sheep's blood-antioxidant agar homemade R-medium (Hôpital de la Timone, Marseille, France) in anaerobic atmosphere generated using the GENbag anaer system (bioMérieux, Marcy-l'Étoile, France)  [9].
Strain identification In order to classify this bacterium, the 16S rRNA gene was amplified using the primer pair fD1 and rP2 (Eurogentec, Angers, France) and sequenced using the Big Dye ® Terminator v1. 1 Cycle Sequencing Kit and 3500xLGenetic Analyzer capillary sequencer (Thermofisher, Saint-Aubin, France), as previously described  [10]. The 16S rRNA nucleotide sequences were assembled and corrected using CODONCODE ALIGNER software (http://www. codoncode. com). Strain Marseille-P2799 T exhibited 98% sequence similarities to Corynebacterium appendicis strain IMMIB R-3491 T (GenBank Accession no. AJ314919), the phylogenetically closest species with standing in nomenclature (Fig. 3 ). We consequently proposed classifying strain Marseille-P2799 T as a new species within the genus Corynebacterium belonging to the phylum Actinobacteria.
Genome sequencing Genomic DNA was extracted using the EZ1 biorobot with the EZ1 DNA tissue kit (Qiagen, Hilden, Germany) and then sequenced on a MiSeq sequencer (Illumina Inc. , San Diego, CA, USA) with the Nextera Mate Pair sample prep kit and Nextera XT Paired End (Illumina), as previously described  [11]. The assembly was performed using a pipeline containing several softwares (VELVET  [12] , SPADES  [13]  and SOAP DENOVO  [14] ), and trimmed (MISEQ and TRIMMOMATIC  [15]  softwares) or untrimmed (only MISEQ software) data. GAPCLOSER was used to reduce assembly gaps. Scaffolds <800 bp and scaffolds with a depth value < 25% of the mean depth were removed. The best assembly was selected by using different criteria (number of scaffolds, N50, number of N). The genome of Strain Marseille-P2799 T was 2.
26 Mb with 63. 4% G + C content. The degree of genomic similarity of the strain with closely related species was calculated using ORTHOANI software  [16]. ORTHOANI values among closely related species (Fig. 4 ) ranged from 60. 04% between Corynebacterium gottingense and Corynebacterium lipophiloflavum to 84. 98% between Corynebacterium imitans and Corynebacterium gottingense. When Corynebacterium urinapleomorphum was compared with these closely related species, values ranged from 62. 43% with Corynebacterium gottingense to 74. 85% with Corynebacterium mycetoides.
1f ). Using a published cohesin HiChIP dataset  34  , we found a close correlation (r = 0. 76-0. 77) between Xistdependent gain of Polycomb-mediated histone modifications and topological proximity to the Xist transgene (Supplementary Fig. 1f, g ). To classify gene promoter chromatin states, we employed ChromHMM  35  to integrate multiple ENCODE ChIPseq datasets defining chromatin states in mESC. Genes were further classified according to the chromatin state surrounding the TSS region (see Methods). To rank the contribution of the aforementioned parameters to silencing efficiency after 1 day of Xist RNA induction, we applied a machine learning approach to train a classifier to discriminate high or low silencing efficiency based on combinatory features for both iXist-Chr3 and iXist-ChrX lines (see Methods), and then scored the importance of each feature (Fig.
j, k Scatterplots and boxplots illustrating more efficient silencing of genes that have pre-existing mESC H3K27me3 (pre-H3K27me3) chromatin/low expression level in iXist-Chr3 cells (j) and iXist-ChrX cells (k). p values calculated using two-sided Wilcoxon rank-sum test. For all the boxplots (i-k) the lower and upper edge of the box represent the first and third quartile, respectively. The horizontal line inside the box indicates the median. Whiskers identify the farthest data points within 1. 5× the interquartile range (IQR)  or Xist RNA levels (Supplementary Fig. 2e ). As above, we assessed Xist-mediated silencing using allelic ChrRNA-seq after 1 day of Xist RNA induction. Surprisingly, none of the three mutations abrogated gene silencing by Xist RNA, and in the case of Rbm15 null mESCs, silencing efficiency was if anything enhanced (Fig.
7a, b ). Thus, all uninduced controls, which are tightly clustered together, are clearly separated from induced datasets, in accord with the occurrence of Xist-mediated silencing. Notably, Xist-induced datasets for Spen knockout and the A-repeat deletion are close to or overlapping uninduced controls, indicating a dramatic silencing deficiency. Knockouts of genes encoding subunits of the Rbm15/m6A-MTase complex, LBR and associated Xist deletions (after Xist RNA induction), on the other hand, cluster closer to WT induced, with somewhat greater separation evident for iXist-ChrX compared to iXist-Chr3 cells. Pcgf3/5 and ΔPID datasets for iXist-Chr3 and iXist-ChrX, respectively, are further separated with a distinct direction relative to all the other induced WT and mutant datasets. This observation implies a unique role for the Polycomb system in the Xist-mediated silencing cascade.
To further depict relative silencing deficiencies we performed hierarchical clustering of allelic silencing (induced-uninduced), for datasets in iXist-ChrX cells (Fig. 7c ). The results emphasise the dramatic and equivalent abrogation of silencing in Spen null and A-repeat deletion lines. Of the other pathways, Polycomb, predominately PRC1-linked H2AK119ub (inferred from deletion of Xist PID region), is the most important factor, with Rbm15/ m6A-MTase and LBR playing a relatively minor role (Fig. 7c, d ). LBR/LBS and Rbm15/m6A-MTase broadly impact silencing of all genes to an equivalent degree, but Polycomb has a more pronounced effect towards specific subsets of genes, notably those that are normally silenced most efficiently and associated with pre-existing H3K27me3 chromatin (Fig. 7c, d ).
Slides were mounted with Vectashield with 4,6-diamidino-2-phenylindole (DAPI) (Vector labs) and sealed with nail varnish. Cells were analysed on an inverted fluorescence Axio Observer Z. 1 microscope using a PlanApo ×63/1. 4 NA oil-immersion objective. Images were acquired using AxioVision software. Immunofluorescence. Cells were plated on gelatinised slides or coverslips (13 mm diameter coverslips from VWR), at least a day before the experiment. On the day of the experiment, cells on slides were washed with PBS and then fixed with 2% formaldehyde for 15 min followed by 5 min of permeabilisation in 0. 4% Triton X-100. Cells were briefly washed with PBS before blocking with a 0. 2% PBS-based solution of fish gelatine for three washes of 5 min each. Primary antibody dilutions were prepared in fish gelatine solution with 5% normal goat or normal donkey serum depending on the secondary antibodies used.
A complete list of antibodies used in the study is shown in Supplementary Table  3. Cells on slides were incubated with primary antibodies for 2 h in a humid chamber at room temperature. Slides were washed three times in fish gelatine solution. Secondary antibodies were diluted 1:400 in fish gelatine solution and incubated with cells on slides for 30 min in a humid chamber at 37 °C. After incubation, slides were washed twice with fish gelatine and one time with PBS before mounting using Vectashield mounting medium with DAPI. Excess mounting medium was removed and the coverslips were sealed to slides using nail varnish. Cells were analysed on an inverted fluorescence Axio Observer Z. 1 microscope using a PlanApo ×63 /1. 4 NA oilimmersion objective. Images were acquired using AxioVision software.
Membranes were blocked by incubating them for 1 h at room temperature in 10 ml TBS, 0. 1% Tween (TBST) with 5% w/v Marvel milk powder. Blots were incubated overnight at 4 °C with the primary antibody (see Supplementary Table  3 ), washed four times for 10 min with TBST and incubated for 40 min with secondary antibody conjugated to horseradish peroxidase. After washing four times for 5 min with TBST, bands were visualised using ECL (GE Healthcare). Original western blot images are available from the Mendeley Data depository from this link [https://doi. org/10. 17632/52pjcxy486. 1] Chromatin RNA-seq. Chromatin RNA was extracted from one confluent 15 cm dish of mESCs. Briefly, cells were trypsinised and washed in PBS. Cells were lysed on ice in RLB (10 mM Tris pH 7. 5, 10 mM KCl, 1. 5 mM MgCl 2 , and 0.
Paired reads where one mapped to Chr3 and the other to the plasmid containing the Xist transgene were identified and quantified. The region in Chr3 that contained the highest concentration of these chimeric reads was Chr3:125. 8097-125. 8145MB. The integration site was also confirmed by using combined reads from previously generated ATAC-seq data  10. Chromatin state segregation by ChromHMM. Using mESC ENCODE ChIP-seq data for various histone modifications and transcription factors, we defined 12 chromatin states (strong enhancer, promoter, gene body, etc) by ChromHMM (v1. 11)  35   Weak/poised_Enhancer; state 12: LowSignal/RepetitiveElements). ChromHMM was used to determine the chromatin state of each gene based on 2 kb flanking either side of the TSS. When multiple transcripts were annotated, we chose the TSS used for the highest number of unique transcripts, or one at random if multiple TSSs were equally frequent.
When multiple chromatin states were present in the TSS ± 2 kb region, the predominant state was assigned to the gene. RNA-seq data analysis. The following analysis strategy was used for Chromatin RNA-seq and mRNA-seq. The RNA-seq data mapping pipeline was similar to our previous study  10. Briefly, the raw fastq files of read pairs were first mapped to an rRNA build by bowtie2 (v2. 3. 2)  48  and rRNA-mapped reads discarded. The remaining unmapped reads were aligned to the "N-masked" genome (from mm10 coordinates) with STAR (v2. 4. 2a) using parameters "-outFilterMultimapNmax 1 -outFilterMismatchNmax 4 -alignEndsType EndToEnd" for all the sequencing libraries  49. Unique alignments were retained for further analysis. We made use of 23,005,850 SNPs between Cast and 129S genomes and employed SNPsplit (v0.
2. 0; Babraham Institute, Cambridge, UK) to split the alignment into distinct alleles (Cast and 129S) using the parameter "-paired". The (allelic) read numbers were counted by the program featureCounts (-t transcript -g gene_id -s 2)  50  and the alignments were sorted by Samtools  51. BigWig files were generated by Bedtools  52  and visualised by IGV  53  or UCSC Genome Browser. For biallelic analysis, counts were normalised to one million mapped read pairs (as CPM) by the edgeR R package. Genes with at least 10 SNP-covering reads across all the samples were further taken to calculate the allelic ratio of Xi=ðXi þ XaÞ, where Xi and Xa indicate inactive and active allele, respectively. In the iXist-Chr3 XY cell line the inducible Xist transgene expresses from the Cast allele, whereas in the iXist-ChrX XX line the endogenous Xist from the 129S1 allele is induced (see Fig.
Data generated in Suz12 KO lines and corresponding wild-type iXist-Chr3 after 3 days in differentiation media were processed with the same pipeline as above. The p values were calculated by Student's T-test based on the three biological replicates with 0. 05 as the significance cutoff, and additional Repression Score (RS) analysis was performed as our previous study  10. PCA analysis was performed by R function prcomp and plotted with the R package ggplot2. Native ChIP-seq calibration and data analysis. For ChIP-seq experiments quantitatively calibrated with Drosophila SG4 cells, raw fastq read pairs were mapped to the "N-masked" mm10 genome concatenated with the dm6 genome sequence by STAR (v2. 4. 2a)  49  using the same parameters as for RNA-seq data with the additional parameter "-alignIntronMax 10".
Allelic split of mm10mapped reads was conducted by SNPsplit as for RNA-seq. We then normalised the mm10-mapped reads to spiked-in Drosophila library size, and scaled down the WT sample to 10 million reads and the other calibrated samples by the same factor, for processing by Bedtools 52 into bedGraph files for normalised signal. All the parameters and normalisation intermediates can be found in the Source Data. We calculated absolute gain of H3K27me3 and H2AK119ub upon Xist induction by the formula ðXi À XaÞ Dox À ðXi À XaÞ NoDox for further analysis and visualisation as BigWig files. Custom scripts (Extra-ctInfoFrombedGraph_AtBed. py) were used to extract values from sorted bed-Graph files for different regions (e. g. 250 kb windows or ChromHMM annotations), with signal from regions of different sizes comparable by FPKM.
sh), and then visualised in IGV or UCSC. HiChIP data analysis and virtual 4C. To integrate the data of higher order chromosome structure in mESCs, we downloaded two biological replicates of cohesin HiChIP-seq data in mESCs  34  and processed data according to the HiC-Pro pipeline  56. The Xist loci in iXist-Chr3 and iXist-ChrX were used as viewpoints for virtual 4C visualisation at 1 MB resolution across Chr3 or ChrX. For comparison we also extracted calibrated ChIP-seq signal of H3K27me3 and H2AK119ub gain averaged at 1 MB resolution across Chr3 or ChrX. The correlations between Xist virtual 4C and ChIP-seq or RNA-seq were calculated using these 1 MB windows across the chromosome excluding the regions containing Xist locus as well as its flanking 10 MB. Machine learning. The random forest classifier in the h2o R package (https:// github.
com/h2oai/h2o-3) was implemented to train models (key parameters: ntrees = 50, keep_cross_validation_predictions = T, nfolds = 5) for predicting the silencing efficiency ("High" vs "Low" silenced on the basis of above or below the median of silencing degree; i. e. 1 vs 0 in the training, validation and testing matrices) in both iXist-Chr3 and iXist-ChrX C7H8 line (Xist was expressed in Cast allele under the engineered TetOn promoter). Three types of features based on different characteristics of genes were used as inputs. (1) Gene expression. Original gene expressed level (FPKM), which was calculated from Cuffnorm program (v2. 2. 1)  54. Each gene was assigned a value from 0 to 1 using two different strategies. In the first method, the highest expressing gene was normalised to one and the rest scaled down accordingly.
Acknowledgements We thank  Amanda Williams  for assistance with NGS sequencing and  Andrew Bassett  for CRISPR/Cas9 sgRNA design for Wtap and Rbm15 mutagenesis;  Neil Blackledge  for providing the Tir targeting construct;  Martin Houlard  for providing TIGRE gRNA and HR construct;  Michal Gdula  for preliminary analysis of LBR datasets. This work was funded by grants to N. B. from the  Wellcome Trust  ( 103768 ) and the  European Research Council  ( 340081 ). C. -X. S. is supported by the  Ludwig Institute for Cancer Research, Cancer Research UK  ( C63763/A26394 ),  NIHR Oxford Biomedical Research Centre , and  Conrad N. Hilton Foundation. Y. B. is supported by  China Scholarship Council.
Data availability High-throughput sequencing data (ChrRNA-seq, m6A-seq, ChIP-seq) generated in this study have been deposited at GEO under accession number GSE119607. Original unprocessed gel images in this manuscript have been deposited to Mendeley Data and are available following this link [https://doi. org/10. 17632/52pjcxy486. 1]. Raw data used for ChIP-seq calibration and raw data underlying all reported averages in graphs and charts are provided as a Source Data File. All other relevant data supporting the key findings of this study are available within the article and supplementary files or from the corresponding author upon reasonable request.
following the instructions given at [https://github. com/guifengwei/ ChromHMM_mESC_mm10] (state 1: CTCF-binding; state 2: Intergenic_Region; state 3: Heterochromatin; state 4: Enhancer; state 5: RepressedChromatin; state 6: BivalentChromatin; state 7: ActivePromoter; state 8: StrongEnhancer; state 9: TranscriptionTransition; state 10: TranscriptionElongation/GeneBody; state 11:.
Also, the body weight was measured to the nearest 0. 01 g with a top loading Mettler balance (Sartorius Model E12000). Data obtained from measurements of lengths (TL, SL CL, and RL) and weight were transformed to their natural logarithm equivalents before used to model growth patterns subject to various X ; Y regression relationships as expressed below: Relationships between; • Total length-Body weight (TL-to-BW); • Standard length-Body weight (SL-to-BW); • Total length-Carapace length (TL-to-CL); and • Total length-Rostral length (TL-RL); were obtained based on sex groupings. Non-linear regression graphs were obtained using Microsoft Excel (2010) software package to establish values of constants (a), (b), (r) and (R 2 ) from corresponding regression equation; W = a L b Ln W = Ln a + b Ln L where W = the weight of the prawn in grams; L = the standard length of the prawn in millimeters.
Acknowledgments This study was made possible through the technical support given by the staff of  Water Research Institute, Aquaculture Research and Development Centre, Akosombo ,  Eastern Region ,  Ghana. Dr. Felix Attipoe  is specially appreciated for his mentorship and study materials provided. Mr. Jonas Darkey  (a fisheries production staff of ARDEC) is also appreciated for his roles in sample collections throughout the entire period of study. The  Nigerian Tertiary Education Trust Fund  is also appreciated for the research grant released to  Dr. D. O. Odedeyi  and A. A. Eniade in 2016 to pursue their research interest on the study of freshwater prawns.
Heterogeneity analysis, calibration and in-line monitoring Heterogeneity analysis. First, the cell culture process was subject to heterogeneity analysis using off-line data from three batch cultures in bioreactors. Analysis of the relationship between cell concentration and cell dry weight, as well as cell differentiation and morphology was performed. Second, principal component analysis (PCA) was used to reduce the dimension of spectral data and then reveal dissimilarities, leading to qualitative analysis of the impact of cell heterogeneity on NIR spectra. Calibration. Three batch cultures were used to collect in-line (NIR spectra) and off-line (cells properties) data. Then both types of data were used to generate calibration models. Models for parenchyma, chlorenchyma and sclerenchyma cells, were created using partial least squares Regression (PLSR) with venetian blinds cross-validation and the NIPALS algorithm.
Spectra acquisition was captured directly from the analyzer. Then multivariate calibration models and statistical analysis were carried out using PLS-Toolbox 8. 2. 1 (Eigenvector Research Inc. ) in the R2016a MATLAB® environment (MathWorks Inc. ). In-line monitoring and validation of models. To evaluate the capacity of the models for performing real-time and in situ monitoring, NIR spectra collected every 30 min during batch cultures, were used as inputs for the calibration models. Then off-line and in-line kinetic profiles were compared for internal validation.
Bioreactor cultures and in-line spectra acquisition Cell cultures were performed in 3 L benchtop bioreactors (Applikon, the Netherlands) with 2 L working volume. Three batch cultures were performed for obtaining off-line and in-line data of cultures. Agitation of suspension culture was performed by a spin-filter coupled to a marine impeller. The set points for all cultures were for temperature 30 °C and stirring 90 rpm. Aeration of cultures consisted in air flux of 200 mL. min -. Dissolved oxygen (DO) and pH (5. 6) were maintained at 50% saturation and 5. 6, respectively, in only one batch culture (batch 1) (Applikon Bio controller ADI 1010). For the other two batches (batch 2 and 3), pH and DO were monitored but not controlled. Bioreactors were illuminated by a LED light panel below the jar in a 16 h/d photoperiod (50 μmol.
Acknowledgements The authors acknowledge the agencies which granted  Daniel. A. Zavala-Ortiz :  The National Council of Science and Technology of Mexico  for a PhD scholarship, the  Veracruz Institute of Technology  for a tuition fee scholarship, the  French Ministry of Europe and Foreign Affairs  for an  Eiffel Excellence scholarship , and the  French National Agency for Research (ANR)  for supporting the  ProCell-In-Line  project.
2011). Despite this there is a growing number of polarised sources being found at low frequencies (e. g. Bernardi et al. 2013; Mulcahy et al. 2014; Jelić et al. 2015; Orrù et al. 2015; Lenc et al. 2016; Van Eck et al. 2018; O'Sullivan et al. 2018; Neld et al. 2018; Riseley et al. 2018). J1235+5317 was discovered to be polarised at 144 MHz by  Van Eck et al. (2018) , in LOFAR data imaged at an angular resolution of 4. 3. The source was first reported by  Schoenmakers et al. (2001) , and the first optical identification (SDSS J123458. 46+531851. 3) was proposed by  Banfield et al. (2015). However, our new observations show that the previously assumed host galaxy is accidentally located close to the geometric centre between the two lobes and that the real host galaxy is actually connected to the south east (SE) lobe by a faint jet.