dataesr/scientific-paragraphs-categorization huggingface dataset:
1) IDENTIFY EDDY OCCURRENCES We isolate events with high salinity anomalies coinciding with dipping isopycnals (an example of which is shown in Fig. 3a ). Data encompassing three days before the first detection of the salinity anomaly and three days after its last detection are used in the next steps. An anomaly is considered significant when the salinity exceeds the mean plus one standard deviation of the average salinity in a given year between 200-and 300-m depth (the layer where the highest salinities are typically found). Values for this salinity threshold ranged from 34. 91 to 34. 99. The presence of an eddy event is then verified from hodographs following  Lilly and Rhines (2002). D-shaped hodographs indicate observations where r , R max (the eddy core is crossed), circles imply observations where all r.
2) FIND THE DIRECTION OF EDDY TRANSLATION PAST THE MOORING Following  Lilly et al. (2003, hereafter L03) , this can be done by identifying the two time points T 1,max and T 2,max when the eddy core R max crosses the mooring, and extracting the observed velocities at those times (V 1,maxtot and V 2,maxtot ). These observed velocities are averaged from 200-to 800-m depth (a layer that incorporated most of the eddy velocity signal). Here we depart from L03 by not using the velocity observations to determine T 1,max and T 2,max because the velocities in our dataset are asymmetric and not centered on the eddy high salinity core. This is likely due to barotropic circulations and noneddy flows. Instead, we prefer to find the times when the maximum isopycnal slope or horizontal pressure gradient passes the mooring, using the time derivative of pressure dp/dt as a proxy for the horizontal pressure gradient.
(2000)  at that location. Our eddy translations are consistent with that larger-scale middepth gyre circulation pattern. The Rossby number Ro is defined as Ro 5 jV max j/ (R max f ) (see  Hebert et al. 1990 ). There are a few choices for the horizontal scale and velocity maximum that can be used in the calculation of Ro; here, the variables R max at V max are used because they represent the dynamic variables associated with eddy velocities. The Rossby numbers of the mooring anticyclones ranged between 0. 01 and 1 and had a mean value of 0. 3. These Rossby numbers suggest eddies with geostrophically dominated flow. The total number of anticyclones observed each year is shown in Fig. 4d  (including those whose core was not crossed). Counts represent eddy totals beginning each June. The counts for the period 2003/04 are extrapolated because of sampling gaps that year; we estimate the total number of eddies that would have been observed during this period if we had a full dataset by dividing the eddy count by the time fraction during which data are available that year.
Thus, the closer the transect is through the center of the eddy, the more difficulty we have obtaining a converging solution. Ultimately, what is needed for the glider method to work is the turning of velocity vectors, which is easily achieved by the glider dataset because the glider did not move in a straight line. It is also achieved for straight transects far from the eddy center and outside of the core radius; however, in this situation one does not obtain information about the eddy radius, R max. Because of these limitations, the method outlined in section 3 was developed to work specifically for a mooring.
The salinity threshold method is based on our previous observations of anticyclones having anomalously high salinities. This method uses a determined salinity threshold beyond which profiles are considered anticyclones. Transects across the Irminger Sea (e. g. , Va ˚ge et al. 2011) show a gradient in salinity with low values to the west, so choosing one threshold to apply across all eddies in the Irminger Sea would be inappropriate. Instead, thresholds are defined as a local mean salinity plus one standard deviation; these values are calculated from a combination of float profiles and climatology from the World Ocean Atlas 2009 (WOA09) product. This method and the WOA09 dataset are described in detail in the appendix. Salinity thresholds used in this method ranged from 34. 92 to 34. 99, spanning similar threshold values used in the CIS mooring analysis.
We first examine the properties of eddies obtained by the altimetry method. The salinity and temperature at 260 m (a typical anticyclone core depth) of the float anticyclones determined by this method are plotted as gray circles in Fig. 7b , along with the mean properties from the mooring eddies (red stars). Care was taken to only examine profiles located within the blue ellipse shown in Fig. 7a ; this is to avoid contaminating the data with profiles from the boundary current. The float profiles all exhibited high salinity (often. 35. 0), confirming the presence of salty anticyclones as seen by the mooring and glider throughout the Irminger Basin. The highest anticyclone salinities in Fig. 7b  exceed mooring anticyclone core salinities; these high values were found in the most northeast region of the Irminger Basin (see Fig.
Discussion At the CIS mooring, we have observed warm, salty anticyclones that are found throughout the Irminger Basin. Eddies observed at the mooring are of EGIC origin, and eddies originating from the RR region do not typically reach the mooring location. The benefit of the mooring and glider observations is the ability to obtain a detailed, quantitative representation of eddy structure and frequencies which cannot be done with existing datasets spanning large spatial domains. Although our analysis suggests two separate formation regions for the Irminger Sea anticyclones, satellite altimetry appears to identify only one of them. As mentioned, the gridded satellite altimetry product dampens eddy signals smaller than 40 km  (Chelton et al. 2011). The mooring anticyclones had a mean R max of 6 km; since this corresponds to an eddy size of 24 km, most of the altimetry signal of these eddies will be dampened.
This suggests that the eddies detected by satellite altimetry and which appear to form at the RR region are larger than those observed at the mooring site. Because we do not observe the larger eddies at the mooring, we do not have sufficient data to analyze them. The horizontal scales of the eddies observed in the CIS appear to scale with the first baroclinic Rossby radius of deformation R 1  (Emery et al. 1984; Chelton et al. 1998). We calculate this quantity following  Emery et al. (1984)  and compare it to our observed eddy scales. As in  Emery et al. (1984) , values of the squared buoyancy frequency are linearly extrapolated from the deepest measurement to zero at the sea floor. We calculate R 1 using our available datasets. The mean R 1 obtained from the mooring, glider, Argo floats, and Ovide transects is 5.
Acknowledgments. We thank the teams of LPO/ IFREMER, LOCEAN/CNRS,  PO/IFM-GEOMAR , and  PORD/SIO  for performing the 2006 Spray glider mission, and specifically Thierry Terre (LPO) and  Jeff Sherman  ( SIO ) for making the mission possible. Gratitude goes to the reviewers and  Sarah Gille  for valuable advice on the manuscript. This work benefitted from discussions with  George Carnevale  and  William Young. Funding  for the CIS mooring was provided by the  European Ocean Observatory Network (EuroSITES)  and the glider was operated with MERSEA support. Altimeter data was provided via the AVISO website (http://www. aviso. oceanobs. com). Argo data was provided by the  USGADAE  Project website (http://www. usgodae. org). Drifter data was provided by the  NOAA AOML Global Drifter Program  website (http://www.
If the evidence is IDA, then the property was directly observed for a live isolate by one of the authors or an expert mentioned in the acknowledgements. Standards in Genomic Sciences When queried against GenBank, the highest 16S rRNA sequence similarity exhibited by strain phI T was 91. 0% when compared to Collinsella aerofaciens and Coriobacterium glomerans. The organism occupied an intermediate phylogenetic position between these two genera (Figure  1 ). By comparison with type species of genera from the family Coriobacteriaceae, E. massiliensis exhibited a 16S rRNA sequence similarity ranging from 84 to 91%. These values are lower than the 95% threshold recommended by Stackebrandt and Ebers  [36]  to delineate a new genus without carrying out DNA-DNA hybridization, thus suggesting that strain phI T may be classified as a member of a novel genus.
Adlercreutzia equolifaciens (AB306661) Asaccharobacter celatus (AB266102) Phylogenetic tree highlighting the position of Enorma massiliensis strain phI T relative to other type strains within the Coriobacteriaceae family. Genbank accession numbers are indicated in parentheses. Sequences were aligned using CLUSTALW, and phylogenetic inferences obtained using the maximum-likelihood method within the MEGA software. Numbers at the nodes are percentages of bootstrap values obtained by repeating 500 times the analysis to generate a majority consensus tree. Bifidobacterium bifidum was used as outgroup. The scale bar represents a 2% nucleotide sequence divergence. Growth at different growth temperatures  (25, 30, 37, 45°C)  was tested; no growth occurred at 25°C or 30°C. Growth occurred between 37 and 45°C, but optimal growth was observed at 37°C after 48 hours of incubation.
Twelve distinct deposits were prepared for strain phI T from twelve isolated colonies. Each smear was overlaid with 2µL of matrix solution (saturated solution of alpha-cyano-4hydroxycinnamic acid) in 50% acetonitrile, 2. 5% tri-fluoracetic-acid, and allowed to dry for five minutes. Measurements were performed with a Microflex spectrometer (Bruker). Spectra were recorded in the positive linear mode for the mass range of 2,000 to 20,000 Da (parameter settings: ion source 1 (IS1), 20 kV; IS2, 18. 5 kV; lens, 7 kV). A spectrum was obtained after 675 shots at variable laser power. The time of acquisition was between 30 seconds and 1 minute per spot. The twelve phI T spectra were imported into the MALDI BioTyper software (version 2. 0, Bruker) and analyzed by standard pattern matching (with default parameter settings) against the main spectra of 3,769 bacteria, which were used as reference data in the BioTyper database.
The method of identification included the m/z from 3,000 to 15,000 Da. For every spectrum, 100 peaks at most were taken into account and compared with spectra in the database. A score enabled the identification, or not, from the tested species: a score > 2 with a validly published species enabled the identification at the species level, a score > 1. 7 but < 2 enabled the identification at the genus level; and a score < 1. 7 did not enable any identification. For strain phI T , no significant score was obtained, thus suggesting that our isolate was not a member of a known species. We incremented our database with the spectrum from strain phI T (Figure  4 ). Finally, the gel view highlighted the spectral differences with other members of the family Coriobacteriaceae (Figure  5 ).
Genome project history The organism was selected for sequencing on the basis of its phylogenetic position and 16S rRNA similarity to other members of the family Coriobactericeae, and is part of a study of the human digestive flora aiming at isolating all bacterial species within human feces. It was the seventh genome of a Coriobactericeae and the first genome of Enorma massiliensis gen. nov. , sp. nov. A summary of the project information is shown in Table  3. The Genbank accession number is CAGZ00000000 and consists of 35 contigs. Table  3  shows the project information and its association with MIGS version 2. 0 compliance  [31].
Genome annotation Open reading frames (ORFs) were predicted using Prodigal  [38]  with default parameters but the predicted ORFs were excluded if they spanned a sequencing gap region. The predicted bacterial protein sequences were searched against the GenBank database  [39]  and the Clusters of Orthologous Groups (COG) databases using BLASTP. The tRNAScanSE tool  [40]  was used to find tRNA genes, whereas ribosomal RNAs were found by using RNAmmer  [41]  and BLASTN against the GenBank database. Signal peptides and numbers of transmembrane helices were predicted using SignalP  [42]  and TMHMM  [43]  respectively. ORFans were identified if their BLASTP E-value Standards in Genomic Sciences was lower than 1e-03 for alignment length greater than 80 amino acids. If alignment lengths were smaller than 80 amino acids, we used an E-value of 1e-05.
Such parameter thresholds have already been used in previous works to define ORFans. To estimate the mean level of nucleotide sequence similarity at the genome level between E. massiliensis strain phI T and other members of Coriobacteriaceae family, we compared genomes two by two and determined the mean percentage of nucleotide sequence identity among orthologous ORFs using BLASTn. Orthologous genes were detected using the Proteinortho software  [44]. We compared E. massiliensis strain phI T with Collinsella aerofaciens strain ATCC 25986 (GenBank accession number AAVN00000000), Collinsella tanakaei strain YIT 12063 (ADLS00000000) and Coriobacterium glomerans strain PW2 (NC_015389). Artemis  [45]  was used for data management and DNA Plotter  [46]  was used for visualization of genomic features.
Using an API 50CH, fermentation or assimilation was not observed. Positive reactions were observed for α-galactosidase, βgalactosidase, arginine dihydrolase, arginine arylamidase, proline arylamidase, histidine arylamidase, α and β-glucosidase, mannose and raffinose fermentation. Cells are susceptible to amoxicillin, amoxicillin-clavulanic acid, metronidazole, imipenem, vancomycin, nitrofurantoin, rifampicine, gentamycin 500 and resistant to erythromycin, penicillin, doxycyclin, ciprofloxacin, ceftriaxone and trimethoprim/sulfamethoxazole. The 16S rRNA and genome sequences are deposited in Genbank and EMBL under accession numbers JN837493 and CAGZ00000000, respectively. The G+C content of the genome is 62. 0%. The habitat of the organism is the human digestive tract. The type strain phI T (= CSUR P183 = DSMZ 25476) was isolated from the fecal flora of an obese French patient.
Figure1. Phylogenetic tree highlighting the position of Enorma massiliensis strain phI T relative to other type strains within the Coriobacteriaceae family. Genbank accession numbers are indicated in parentheses. Sequences were aligned using CLUSTALW, and phylogenetic inferences obtained using the maximum-likelihood method within the MEGA software. Numbers at the nodes are percentages of bootstrap values obtained by repeating 500 times the analysis to generate a majority consensus tree. Bifidobacterium bifidum was used as outgroup. The scale bar represents a 2% nucleotide sequence divergence.
After the reads were cleaned by removing the adapters, de novo assembly was performed on the sequences and more than 73,696 contigs were generated with a mean contig length estimated at 585 bp ranging from 189 bp to 14,773 bp. Once a Blastx search against NCBI Non Redundant database was performed and the duplicates removed, 18,378 annotated sequences matched known sequences, 3078 were hypothetical and 9002 were uncharacterized sequences. Fifty percent and 41% of known sequences match sequences from Mollusca and Gastropoda respectively. Among the bivalvia, 33%, 17%, 17% and 15% of the contigs match sequences from Ostreoida, Veneroida, Pectinoida and Mytiloida respectively. Gene ontology analysis showed that metabolic, cellular, transport, cell communication and cell cycle represent 33%, 15%, 9%, 8.
It was hypothesized that the proto-oncogenes were regulated by the presence of transposase whose gene expression was increased in tetraploid hemocytes  [ 16 ]. Briefly, although several studies have been initiated, the molecular mechanisms by which hemocytes become neoplastic are still to be unravelled. Unfortunately, little is known on the transcriptome of soft shell clams. Only few sequences are available in GenBank represented mainly by Map53 (Acc# AF253323. 1 ), Map73 (Acc# AF253324. 1 ), and mortalin (Acc # EF576660 ). The development of the new generation of sequencing technologies represents a great opportunity to increase the number of transcript sequences and would provide a basis platform for molecular mechanisms studies involved in DN in soft shell clams. Thus, this study aims at increasing the numbers of transcript sequences in hemocytes of soft shell clams affected by DN.
Sequence analysis and bioinformatics Reads generated from Illumina HiSeq2000 sequencing were assembled using the CLC Genomics Workbench software v5. 5. Adaptors and primer sequences were trimmed as well as low quality and duplicates removed. De novo sequence assembly was performed using de Bruijn graphs as described in  [ 19 -21 ]. The generated contigs and isotigs were blasted against NCBI Non-Redundant database including Swissprot, Metazoan Refseq and UniprotKB / Trembl protein databases using the GenomeQuest bioinformatic platform (US) with a cut-off of 10 -6. Gene ontology searches were performed using the Panther Pathway  [ 22 ]. Sequences were submitted to BLAST comparison against the KEGG GENES database to obtain KO (KEGG Orthology) assignments and to generate KEGG pathways. The threshold > 60 was applied to BLAST bit scores.
De novo assembly The tetraploid status of hemocytes has been screened using flow cytometry. Three groups of hemocytes were determined: Group C, a healthy group with less than 10% of tetraploid cells; Group D, an intermediate group with tetraploid hemocytes ranging between 10% and 50% and group E, a diseased group with more than 50% of tetraploid cells. More than 95,399,159 reads count were generated from the three groups with an average length of 45 bp. The bioinformatic analysis of the sequences was performed using the CLC Genomics Workbench software v5. 5. The adaptors and primers were trimmed; in addition, duplicates and low quality sequences were removed from the data set. Upon cleaning, de novo assembly was performed on the sequences using de Bruijn graphs. More than 73,696 contigs were generated with a mean contig length estimated at 585 bp ranging from 189 bp to 14,773 bp.
More than 90. 3% of the contigs (66,612 sequences) had a length ranging from 189 to 1268 bp and less than 9. 7% were longer than 1268 bp ( Fig. 1  ). The emergence of the next generation of sequencing has dramatically increased the knowledge and information on bacteria, invertebrate and vertebrate organisms' transcriptome. Although the number of Expressed Sequence Tags (ESTs) has increased during the last decade, the knowledge on mollusk bivalvia in particular M. arenaria is still limited. GenBank database contains only 248,489 nucleotides and 373,300 ESTs related to Bivalvia (4 / 15 / 2013). Ostreoida and Mytiloida represent the most representative groups with 223,017 (59. 7%) and 71,328 (19. 1%) ESTs respectively. Among the Ostreoida, Crassostrea is the main representative group with 222,785 (99.
9%) ESTs and Mytilus have been mainly sequenced in the Mytiloida family with 67,990 (95. 3%). Unfortunately, the number of ESTs related to M. arenaria is very poor with 100 entries represented mainly by cytochrome oxidase, microsatellite and ribosomal RNA. Among the 100 entries, only 10 transcripts have been recorded in GenBank (4 / 15 / 2013) represented by M. arenaria p53 tumor suppressor homolog (Myap53) mRNA, partial cds ( U45237. 1 ); M. arenaria voltage-dependent sodium channel mRNA, partial cds ( AY847740. 1 ); M. arenaria p73-like protein mRNA, complete cds ( AF253324. 1 ); M. arenaria E3 ubiquitinprotein ligase mRNA, complete cds ( AF154109. 2 ); M. arenaria aryl hydrocarbon receptor-like protein mRNA, complete cds ( AF261769. 1 ); M. arenaria p53 tumor suppressor-like protein mRNA, complete cds ( AF253323.
Annotation A Blastx search was performed against NCBI Non Redundant database including Swissprot, Metazoan Refseq and UniprotKB / Trembl protein databases. The GenomeQuest bioinformatic platform was used for the Blastx search and a cut-off of 10 -6 was applied for the analysis. Once the duplicates were removed, 18,378 annotated sequences matched known sequences, 3078 were hypothetical and 9002 were uncharacterized sequences. Eighty-five percent of the annotated sequences are among eukaryote identities ( Fig. 2 A ) with 18% and 5% linked to arthropoda and mollusca phylla ( Fig. 2 B ). Data showed that 50% and 41% of known sequences match with sequences from Mollusca and Gastropoda respectively ( Fig. 3 A ). Among the bivalvia, 33%, 17%, 17% and 15% of the contigs match sequences from Ostreoida, Veneroida, Pectinoida and Mytiloida respectively ( Fig.
Transcripts involved in G1-S phase of cell cycle At the G1 phase also known as the growth phase which corresponds to a high rate of biosynthesis, the CDK4,6 like proteins were identified in our database. CDK4,6 linked to cyclin D is the first serinethreonine kinases activated during the cell cycle. CDK4,6-cyclin D complex under proliferative signal activation allow the cell to enter the cell cycle at its first G1 phase  [ 27 ]. Once activated, CDK4,6-Cyclin D initiates a sequential activation of downstream of cyclin E-CDK2, which regulates the G1-S transition and centrosome duplication. In our study, cyclin D2 and cyclin E transcripts were 4. 6 and 3. 8 times respectively higher than the control during the development phase of the disease ( Fig. 6  ). Once the disease was established, the expression level of cyclin D2 and E was 2.
6  ). It was shown that cyclin B1 is a c-myc target whose overexpression induces chromosomal activity and tetraploidy  [ 45 ]. In the M phase, the anaphase promoting complex / cyclosome (APC / C) is an E3 ubiquitin ligase complex that targets the degradation of protein involved in the cell cycle during the M phase. APC / C's activation depends on two WD-40 domain proteins, CDC20 and CDH1. In our study, APC / C family members identified in our database and in particular APC / C sub-unit 7 showed a high expression level in hemocyte with tetraploid status ranging between 10% and 50% as well as in diseased organisms with more than 50% tetraploid hemocytes ( Fig. 8  ). Similarly, Cdh1 / Cdc20 is also higher in both groups D and E ( Fig. 8  ). In yeast mitosis, CDC20 and CDH1 bind to the APC / C, which is activated during the mitosis process  [ 46 ].
Cell cycle molecular pathway in hemocytes of M. arenaria Cell cycle progression is mainly regulated by the complex cyclin-CDK (cyclin-dependent kinase). These kinases are under control of mitogenic signals and play a central role in cell proliferation  [ 27 ]. Pathways were generated once the sequences were blasted against KEGG Genes database. Focusing on pathways related to cell cycle, 77 transcripts were identified from our sequence database. Based on the KEGG pathways, these sequences are involved at different phases of the cell cycle: G1-S-G2-M ( Fig. 9  ). In this study, individual variability was not taken into account because individuals were pooled in three different pools based on their tetraploidy status. However, sequences and data generated from this study provided a snapshot of molecular mechanisms involved in cell cycle in hemocytes of soft-shell clams M.