dataesr/scientific-paragraphs-categorization huggingface dataset:
Methods Stress assays. Stationary-phase bacterial cultures were diluted at a final OD 600 of 0. 1 in TSB broth. Exponential-phase bacterial cultures were diluted to a final concentration of 10 8 bacteria per mL and subjected to either 500 µM H 2 O 2 , 10 mM H 2 O 2 , 10 mM Tertbutyl hydroperoxide, 10 mM Cumene hydroperoxide (1 h); pH 5. 5 (1 h); 0. 05% SDS (4 h); or 10% human serum (1 h). The number of viable bacteria was determined by plating apspropriate dilutions of bacterial cultures on Chocolate Polyvitex plates at the start of the experiment and after the indicated durations. Cultures (5 mL) were incubated at 37 °C with rotation (100 rpm) and aliquots were removed at indicated times, serially diluted and plated immediately. Bacteria were enumerated after 48 h incubation at 37 °C. Experiments were repeated independently at least twice and data represent the average of all experiments.
Cells were infected with bacteria for 10 h (MOI of 1000:1), washed three times with PBS and incubated with DCFDA diluted in PBS for 1 h (15 μM). Images of the cells were captured with an Olympus CKX41 microscope and treated with Image J software. Cell counts were performed over 5 images of approx. 50 cells. Confocal experiments. J774. 1 macrophage cells were infected (MOI of 1,000) with wild-type F. novicida U112 (WT), the Δfba isogenic mutant (Δfba), or an isogenic strain deleted for the "Francisella Pathogenicity Island" (ΔFPI) in standard DMEM (DMEM-glucose) or DMEM without glucose and supplemented with either glucose or glycerol (5 mM each) for 30 min at 37 °C. Cells were then washed three times with PBS and maintained in fresh DMEM supplemented with gentamycin (10 μg mL -1 ) until the end of the experiment.
). Cells were examined using an × 63 oilimmersion objective on a LeicaTSP SP5 confocal microscope. Co-localization tests were quantified by using Image J software; and mean numbers were calculated on more than 500 cells for each condition. Confocal microscopy analyses were performed at the Cell Imaging Facility (Faculté de Médecine Necker-Enfants Malades). Mouse infection. WT F. novicida and Δfba mutant strains were grown in TSB to exponential growth phase and diluted to the appropriate concentrations. Six to 8week-old female BALB/c mice (Janvier, Le Genest St Isle, France) were intraperitoneally inoculated with 200 μl of bacterial suspension. The actual number of viable bacteria in the inoculum was determined by plating dilutions of the bacterial suspension on chocolate plates. For competitive infections, WT F.
1% trifluoroacetic acid for LC-MS/MS. For each run, 1 µL was injected in a nanoRSLC-Q Exactive PLUS (RSLC Ultimate 3000, ThermoScientific, Waltham, MA, USA). Peptides were separated on a 50 cm reversed-phase liquid chromatographic column (Pepmap C18, Thermo Scienfitic). Chromatography solvents were (A) 0. 1% formic acid in water, and (B) 80% acetonitrile, 0. 08% formic acid. Peptides were eluted from the column with the following gradient 5 to 40% B (120 min), 40 to 80% (10 min). At 131 min, the gradient returned to 5% to re-equilibrate the column for 30 min before the next injection. Two blanks were run between triplicates to prevent sample carryover. Peptides eluting from the column were analyzed by data dependent MS/MS, using top-10 acquisition method. Briefly, the instrument settings were as follows: resolution was set to 70,000 for MS scans and 17,500 for the data dependent MS/MS scans in order to increase speed.
The MS AGC target was set to 3×10 6 counts, while MS/MS AGC target was set to 1×10  5. The MS scan range was from 400 to 2000 m/z. MS and MS/MS scans were recorded in profile mode. Dynamic exclusion was set to 30 s duration. Three replicates of each sample were analyzed by nanoLC-MS/MS. Data processing following nanoLC-MS/MS acquisition: The MS files were processed with the MaxQuant software version 1. 5. 3. 30 and searched with Andromeda search engine against the NCBI F. tularensis subsp. novicida database (release 28-04-2014, 1719 entries). To search parent mass and fragment ions, we set a mass deviation of 3 and 20 ppm respectively. The minimum peptide length was set to 7 amino acids and strict specificity for trypsin cleavage was required, allowing up to two missed cleavage sites. Carbamidomethylation (Cys) was set as fixed modification, whereas oxidation (Met) and N-term acetylation were set as variable modifications.
The false discovery rates at the protein and peptide level were set to 1%. Scores were calculated in MaxQuant as described previously  71. The reverse and common contaminants hits were removed from MaxQuant output. Proteins were quantified according to the MaxQuant label-free algorithm using LFQ intensities  71, 72  ; protein quantification was obtained using at least 2 peptides per protein. Statistical and bioinformatic analysis, including heatmaps, profile plots, and clustering, were performed with Perseus software (version 1. 5. 0. 31) freely available at www. perseus-framework. org  73. For statistical comparison, we set three groups, each containing biological triplicate. Each sample was run in technical triplicates as well. We then filtered the data to keep only proteins with at least 2 valid values out 3 in at least one group.
Complete follow-up was available through 30 th November 2014 for England and Wales and 31 st December 2014 for Scotland. Cancer incidence data were coded using the 10 th Revision of the International Classification of Diseases (ICD-10). Proximal colon cancer included those within the caecum, appendix, ascending colon, hepatic flexure, transverse colon, and splenic flexure (C18. 0-18. 5). Distal colon cancer included those within the descending (C18. 6) and sigmoid (C18. 7) colon. Overlapping (C18. 8) and unspecified (C18. 9) lesions of the colon were also included. Cancer of the rectum included cancer occurring at the rectosigmoid junction (C19) and rectum (C20).
Acknowledgements This work has been conducted using the UK Biobank Resource under Application Number  25897  and we express our gratitude to the participants and those involved in building the resource. UK Biobank  is an open access resource. Bona fide researchers can apply to use the UK Biobank dataset by registering and applying at http:// ukbiobank. ac. uk/register-apply/. KEB was supported by a  Girdlers' New Zealand Health Research Council Fellowship.
uvic. ca/ grasp/gils/, www. sigenae. org, and http://esharkgenome. imcb. a-star. edu. sg/, respectively. Sox genes along with their accession numbers and/or coordinates are available in S1 Table. Nucleotide sequences were loaded into MEGA  [51] , translated into proteins and aligned using ClustalW  [52, 53]. Sequence alignments were further refined manually using Seaview (version 3. 2;  [54] ).
Evolutionary rate computations Alternative models with different branch-specific dN/dS ratio were compared using the codeml program of PAML  [56]. The data set includes two mammals (Mus musculus and Homo sapiens), the chicken Gallus gallus and five species of teleosts (zebrafish, medaka, platyfish, tilapia and fugu). When available, sequences from the frog Xenopus tropicalis, the two non-teleost fishes spotted gar and coelacanth, and the six teleost fishes salmon, Tetraodon, cod, stickleback, orange-spotted grouper (Epinephelus coioides) and african sharp tooth (Clarias gariepinus) were included into the analyses. Alignments based on protein sequences were produced with ClustalW implemented in MEGA  [51]  and computations were performed on the alignments after removal of positions presenting at least one gap.
By applying CaTCH to published Hi-C data sets, we show that previously reported folding layers appear at different insulation levels. We demonstrate that although no structurally privileged folding level exists, TADs emerge as a functionally privileged scale defined by maximal boundary enrichment in CTCF and maximal cell-type conservation. By measuring transcriptional output in embryonic stem cells and neural precursor cells, we show that the likelihood that genes in a domain are coregulated during differentiation is also maximized at the scale of TADs. Finally, we observe that regulatory sequences occur at genomic locations corresponding to optimized mutual interactions at the same scale. Our analysis suggests that the architectural functionality of TADs arises from the interplay between their ability to partition interactions and the specific genomic position of regulatory sequences.
A comprehensive analysis that considers all previously identified topological levels simultaneously and compares them to one another in terms of their functional and physical properties is currently lacking. A small number of algorithms that identify hierarchies of topological domains are available  (Filippova et al. 2014; Lévy-Leduc et al. 2014; Shin et al. 2015; Weinreb and Raphael 2015; Chen et al. 2016; Shavit et al. 2016). However, none of them provides a quantitative description of how the various layers of domains differ from one another. In addition, these algorithms define hierarchies of interaction domains depending on one or more parameters that do not have a clear biological or structural interpretation. To overcome these limitations, we developed a novel algorithm called CaTCH (Caller of Topological Chromosomal Hierarchies) that identifies nested topologies of structural domains in Hi-C data sets based on a single parameter, the reciprocal physical insulation between domains, which is a simple and biologically relevant measure.
S1e ), where 78% of boundaries of previously identified contact domains are also detected by CaTCH. However, CaTCH detects more domains than those identified in  Rao et al. (2014)  (Supplemental Fig. S1f ), which explains the lower proportion of domains delimited by convergent CTCF sites in our data set. Thus, sub-TAD contact domains are detected by CaTCH as relatively lowly insulated regions. We next sought to identify the scale in the folding hierarchy where domains detected by CaTCH most closely resemble TADs. Since directionality index analysis  (Dixon et al. 2012 ) has been used to define TAD boundaries in a number of previous studies, here we adopted this benchmark definition of TADs and refer to these domains as 'diTADs' (directionality index TADs). It is important to point out that the set of diTADs identified in a Hi-C experiment depends on the value of two tunable parameters, one setting a limit to the maximal genomic distance over which Hi-C interactions are evaluated (Supplemental Fig.
S1h, i ). Most (74%) CaTCH boundaries not corresponding to TADs indeed divide diTADs in smaller domains (Supplemental Fig. S1j ). Thus, diTADs are detected by CaTCH as domains that are more robustly insulated than contact domains. At even higher reciprocal insulation, hierarchical domains detected by CaTCH correspond to regions of increasingly longerrange associations between TADs, in the range of meta-TADs described in  Fraser et al. (2015) , themselves contained into even larger domains occurring at very high insulation (around 85%) (Fig. 1D , right). These domains largely overlap with consecutive stretches of genomic sequence belonging to either the 'A' or 'B' compartments  (Lieberman-Aiden et al. 2009) , as detected by eigenvector analysis  (Imakaev et al. 2012)  on the same ESCs Hi-C data set (Fig.
To study the effect of sequencing coverage, we performed CaTCH and CTCF enrichment analysis on a down-sampled ESC Hi-C data set obtained by reducing by half the total number of sequenced reads. CTCF enrichment at domain boundaries was maximized at very similar reciprocal insulation value as in the full data set (67% vs. 65%) (Supplemental Fig. S2i ), largely corresponding to the same set of domains (Supplemental Fig. S2k ). Thus, sequencing depth is not likely to have a strong impact on the reciprocal insulation values where TADs appear. Next, to understand the impact of using Hi-C data sets obtained using different experimental protocols, we performed a comparative analysis of two data sets obtained in mouse fetal liver cells  (Nagano et al. 2015)  using either the 'dilution'  (Lieberman-Aiden et al.
The local complexity in chromosomal folding correlates with transcriptional activity and CTCF binding We next used the CaTCH algorithm to quantify local chromosome folding complexity within each TAD and correlate it to the level of local transcriptional activity. To this aim, we first computed the number of hierarchical sublevels that can be identified within a domain (see Methods) as a measure for local folding complexity. We then used the RNA-seq profiles to assign transcripts to domains based on the genomic position of their promoters. We did not limit our analysis to the exonic signal (corresponding to mature mRNA), but we also considered the intronic reads, the latter being a more reliable measure of transcriptional activity (see Methods section). We found that at the level of single TADs, a quantitative correlation exists between the number of sublevels and both total (exonic) and unspliced mRNA reads per domain (Fig.
Acknowledgments Research in the  Giorgetti lab  was supported by the  Novartis Research Foundation. Initial analyses for this study were conceived and established in  Edith Heard's laboratory, Institut Curie and PSL (Paris) , where L. M. 's salary was paid for by an  EMBO ASTF 563-2012  fellowship to L. M. and SyBoSS 62012 grant to Edith Heard. We thank  Federico Comoglio  for assistance on code development and for critically reading the manuscript,  Stéphane Thiry  and  Tim Roloff  for assistance on RNA-seq library preparation and sequencing,  Edith Heard  for critically reading the manuscript, NIBR computing resources and  Stefan Grzybek  for help with cluster and server supports, and  Mikael Attia  for cell culture. We acknowledge The  ENCODE Project Consortium and in particular the Ren and Hardison laboratories for ChIP-Seq data sets in ESC  and  CH12 , and the  Myers laboratory  for ChIP-seq data sets in fetal liver cells.
miRNAs as Biomarkers in CVD. It has been now 17 years since the existence of microRNAs (miRNAs) was shown in human. These short endogenous interfering RNAs are coded by the human genome, represent a new class of thousands of RNAs of approximately 20 to 25 nucleotides (see specialized Internet databases, such as miRbase http://www. mirbase. org/ cgi-bin/mirna summary. pl?org=hsa), and have emerged as regulators of numerous physiological and pathological processes  [31] , including CVDs  [32, 33]. Their number is now estimated to be around 2,000 but a recent study using thorough RNA purification from human cells and next generation sequencing claims that there exist up to 5,000 miRNAs, with more than a half being human specific  [34].
Long Noncoding RNAs (lncRNAs). We now know that miRNAs are regulated at least in part by lncRNAs, long transcripts (>200 nt) that do not code for proteins. The biogenesis and molecular mechanism of action of miRNAs and lncRNAs have been described in greater detail in other reviews  [26, 33, 44, 45]. According to recent databases 56018 and 46475 lncRNA genes have been, respectively, found for human and mouse. lncRNAs differ from miRNAs, as they regulate gene expression not only at the transcriptional and but also at the posttranscriptional and chromatin remodeling levels. They also have high tissular specificity and are not evolutionarily conserved. lncRNA can act as decoy for microRNA to allow microRNAs' target mRNA to escape from degradation (reviewed by  [44] ). The use of lncRNAs as innovative biomarkers in the field is still in its infancy compared to the miRNA field.
Patients This international retrospective cohort study included 13 unique A883F carriers from eight unrelated families. At the International Workshop on Multiple Endocrine Neoplasia (WorldMEN) 2014 in Vienna, Austria, the World-MEN 2016 workshop in Utrecht, the Netherlands, and during various other scientific meetings, all known MEN2 centers were asked to contribute relevant data to this study. Eleven A883F carriers were identified. Additionally, a systematic literature search was performed. Of 199 unique citations, 12 reported A883F germline carriers  (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25). The reference list of each citation was scrutinized to uncover carriers published more than once. When this was insufficient, an author of the concerned publication was contacted for clarification.
Six of the 12 citations described an A883F carrier who had been reported previously  (14-16, 19, 22, 23). The remaining six citations were found to be the original reports of 12 A883F carriers  (17, 18, 20, 21, 24, 25) , two of whom had not been identified by the inquiries at the WorldMEN workshops. Thus, a total of 13 unique carriers were identified and included. Data collection was performed using a uniform data sheet for each registrant. One carrier had been lost to follow-up several years before, and only data already published in relation to this carrier could be retrieved  (15, 18, 19). This study was approved by the respective institutional review boards for human subjects' protection in accordance with the ethical standards of each country and center.
Results A total of 13 carriers from eight unrelated families were included. Demographic, clinical, surgical, and follow-up data are shown in Table  1. De novo mutations were recorded in five (45%) of the 11 carriers with pertinent data. Carriers and families originated from the United States (four carriers from one family), United Kingdom (four carriers from three families), France (two carriers from one family), Germany (one carrier from one family), Denmark (one carrier from one family), and Australia (one carrier from one family).
Acknowledgments We are deeply grateful for the help of the following researchers in locating data providers and securing a cohort of unique A883F carriers:  B. A. J. Ponder  (Cambridge),  J. S. Paterson  (Cambridge),  J. Cook  (Sheffield),  B. J. Harrison  (Sheffield),  J. Barwell  (Leicester),  A. Frilling  (London),  D. Benn  (Sydney),  E. Baudin  (Paris),  S. Giraud  (Lyon),  D. Prunier-Mirebeau  (Angers), and the  Groupe des Tumeurs Endocrines, réseau des laboratories (TENgen network ) in France. Address all correspondence and requests for reprints to: Jes Sloth Mathiesen, MD,  Department of Otorhinolaryngology Head and Neck Surgery, Odense University Hospital, Sdr. Boulevard 29, DK-5000 Odense C, Denmark. E-mail: jes_mathiesen@yahoo. dk. Disclosure Summary: The authors have nothing to disclose.
1 Terminator Cycle Sequencing chemistry (Applied Biosystems, California, USA). Multiple sets of PCR primers were used (Table  S2 ). The older herbarium specimens yielded degraded DNA, and markers were consequently amplified in short overlapping fragments. The resultant chromatographs were manually corrected in Geneious v. 5. 3. 6. All Sanger sequences were deposited in the NCBI GenBank database (KY991068-KY991366). Four Themeda triandra, two Heteropogon Pers. and one Themeda quadrivalvis accessions were subjected to low-coverage whole-genome sequencing (genomeskimming), as described in  Lundgren et al. (2015). In brief, samples were individually barcoded, pooled and sequenced on an Illumina HiSeq-2500 or HiSeq-3000 at the Genopole platform of Toulouse. In total, 1/24th of a lane paired-end data were generated per sample, with all raw data deposited in the NCBI Sequence Read Archive (project identifier PRJNA377519; Table  S3 ).
Assembly, alignment and phylogenetic inference A complete chloroplast genome (hereafter plastome) was assembled de novo for one sample using the genome-walking method described in  Besnard et al. (2013). In brief, a combination of extractread2 (included in the OBITools package, http://metabarcoding. org/obitools) and velvet  (Zerbino and Birney 2008)  was used to identify overlapping chloroplast reads in the raw data and subsequently assemble them. For each sample, we then mapped the paired-end Illumina data back to this initial reference using bowtie2 v. 2. 2. 9  (Langmead and Salzberg 2012). Indels and SNPs were called with SAMtools mpileup function v. 1. 2 (Li et al. 2009 ) and filtered using the accompanying vcfutils. pl script (parameters: d = 10, a = 5 and Q = 30). Plastome sequences for each sample were generated using vcftools v.
0. 1. 11 (Danecek et al. 2011). To remove sequencing errors from SNP calls, we discarded minor alleles that had a within sample frequency of < 0. 2. Plastome sequences were submitted to GenBank (accession numbers: KY707767-KY707773). The newly generated plastomes were aligned with others publicly available for Andropogoneae and Arundinella Raddi using MAFFT v. 7. 123b  (Arthan et al. 2017; Katoh and Standley 2013). The alignment was manually refined and the inverted repeat region removed. The Sanger sequencing data, and additional data retrieved from GenBank, were aligned to the plastome matrix using MAFFT and then concatenated by sample. A phylogeny was obtained using Bayesian inference, as implemented in MrBayes version 3. 2. 0 (Huelsenbeck and Ronquist 2001)  with the GTR + G + I substitution model.
Two analyses, each composed of four chains, were run for 10 million generations, sampling a tree every thousand generations. Convergence was evaluated with Tracer v. 1. 5. 0  (Drummond and Rambaut 2007) , and a consensus was computed using all the trees sampled after a relative burn-in period of 10%. To verify the effect of missing data on phylogenetic inference, we also constructed a phylogeny using a trimmed alignment containing five chloroplast genes (trnK-matK, rpl16, ndhF, rpoC2 and trnL-trnF) either obtained via Sanger sequencing or extracted from plastomes. The ITS sequences were similarly aligned with MAFFT, and a Bayesian phylogeny was inferred as above.
Genome-wide phylogenetic tree The seven genome-skimmed individuals were also genotyped across the nuclear genome as described in  Olofsson et al. (2016). In brief, the reads were cleaned using NGS QC Toolkit v. 2. 3. 3  (Patel and Jain 2012)  and mapped onto the chromosomes of the closest available model species (Sorghum bicolor (L. ) Moench, version Sorbi1;  Paterson et al. 2009 ) using Bowtie2 v. 2. 2. 3  (Langmead et al. 2009). Only reads uniquely aligned in pairs were subsequently used for SNP calling using SAMtools v. 0. 1. 19 and previously published scripts  (Olofsson et al. 2016). The low-coverage genome-skimming data mean that some alleles are likely missed, leading to an overestimation of homozygosity. However, no bias is expected in the missing allele, so that the low coverage is unlikely to lead to spurious groupings  (Olofsson et al.
Phylogenetic relationships based on the nuclear ITS A majority of the clades from the plastid phylogeny were congruent with the phylogeny inferred from the 625bp ITS alignment containing 71 samples (59 sequenced Table  1. Themeda species used in this study and their distribution. In total, we sequenced 18 out of the 27 known species. the clade assignment is based on chloroplast and nuclear markers, with the number of samples sequenced indicated (n), and ecological information derived from  Morales (2014). SNPs were used to infer a Bayesian phylogeny, with a mean of 11% missing data per samples. All nodes were fully supported (Figure  3 ). The tree was rooted on the branch separating Heteropogon from Themeda. Unlike in the chloroplasts and ITS phylogenies (Figures 1, 2, S2), T. quadrivalvis collected from Madagascar is strongly supported as sister to T.