dataesr/scientific-paragraphs-categorization huggingface dataset:
FTIR spectroscopy mFTIR measurements were carried out on IN10 experimental device and also performed on an IN10MX microscope (Thermo Scientific) to allow recording of large maps. All spectra were collected in ultrafast mode using a 50 mm × 50 mm aperture. The spectra were collected in the 4000-800 cm -1 mid-IR range at a resolution of 16 cm -1 with one spectrum per pixel. Data analysis of IR spectra and chemical images was performed using OMNIC software (Thermo Scientific). In order to estimate the overall extent of mineralized matrix over the samples as well as its chemical nature, a first set of maps was performed (2000 mm x 4500 mm), then large maps were collected to allow an extended overview of the different conditions (3700 mm x 7700 mm). Due to the extended acquisition times to picture the maps, several maps were divided for convenience in 2 or 4 areas depending on the initial map size.
In order to gather information regarding the spatial repartition of Ca 2+ and Mg 2+ cations as well as Pi anions, EDX experiments were performed. In Fig. 3B , purple (for Pi) and red (for Ca 2+ ) maps perfectly matched, revealing a co-localization of Pi and Ca 2+ in the same structure. Observations were similar regardless of the assessed Mg 2+ concentration or the calcifying condition (data not shown for PiCa with or without supplemental Mg 2+ ). Moreover, a supplemental deposit of Mg 2+ apart from the one incorporated in the support was not detected by EDX avouching its absence from calcium phosphate deposits (data not shown). FE-SEM pictured clearly the presence of calcification preferentially positioned on cells (Fig. 3A  and 3B ) regardless of the assessed Mg 2+ concentration or the calcifying condition (data not shown for PiCa with or without supplemental Mg 2+ ).
Effect of Mg 2+ on crystal formation As detailed above, mFTIR maps were performed to reveal where CPA deposition was preferentially occurring (Fig. 2 ). Looking closely at these maps, it appeared that raising Mg 2+ up to 5 mM during 18 days seemed to reduce the number and intensity of CPA peaks compared to the calcifying conditions alone (Pi4 or PiCa). At day 14, such influence of Mg 2+ was not noticeable (data not shown). Larger maps were then performed for the Pi4, Pi4 Mg2 and Pi4 Mg5 samples at day 18 to confirm this finding. In Fig. 4 , the expanded mFTIR maps show a heterogeneous spatial repartition of CPA. Calcifications are present on all samples although the map corresponding to the condition containing 5 mM of Mg 2+ is showing less numerous spots and is exhibiting CPA peaks of weaker intensities.
With respect to the tested conditions, the deposits were more pronounced than their respective cellular counterpart and were far more prominent in conditions with increasing concentrations of Mg 2+ (data not shown). This observation rules out the possibility of a direct physicochemical inhibition of Mg 2+ on nucleation or growth of CPA in our model. Concerning the Mg 2+ influence on the crystal structure and composition, several publications show that the incorporation of foreign ions into hydroxyapatite structure can affect its crystallinity, morphology, lattice parameters, and stability  [36, 37, 38]. Among them, Mg 2+ is known to inhibit the synthesis of hydroxyapatite and promote the formation of whitlockite in acellular systems  [39, 40]. In the presence of calcifying HAVSMC, regardless of the tested conditions, only CPA was detected using mFTIR in our samples even when 5 mM of Mg 2+ was added.
The passive deposition on MirrIR slides without cells did not yield the formation of withlockite even in presence of Mg 2+ (data not shown). Succinctly, Mg 2+ was not able to modify the crystal structure in our experimental setup. Our data are strongly reinforcing recent findings from De Schutter et al. that assessed a rat model of uremia treated with a magnesium-based phosphate binder  [48]. VC was analysed in aortas as well as in femoral and carotid arteries using synchrotron X-ray m-fluorescence and X-ray m-diffraction. Uremic animals developed severe VC that was reduced in the aortas of animals of the Mg 2+ -containing phosphate binder group. Yet, the synchrotron analysis of VC indicated that mineral precipitates exclusively consisted of calcium hydroxyapatite. None of the samples contained whitlockite or any other type of calcium phosphate deposits in uremic rats regardless of the treatment.
These findings strongly support a previous report by Massy et al. that analyzed VC in atheromatous lesions of ApoE -/-uremic mice with FTIR. In their animal model, VC was composed of calcite and hydroxyapatite  [49]. Shortly, supplemental Mg 2+ was not able to alter the crystal structure neither in cellular nor in animal models. Taken together, our results suggest that the Mg 2+ beneficial effects on VC are bound to cellular activities rather than physicochemical modifications of the calcium phosphate crystal. The spatial distribution of the CPA crystals was investigated using mFTIR maps as well as FE-SEM combined with EDX spectrometry observations. The complete set of data led us to conclude that calcification occurs mainly as CPA spots located close to or directly on the HAVSMC bodies. In our experimental setup, CPA deposition was massive and the various crystal sizes start at the nm scale to largely exceed the mm scale.
Specifically for infants born at 30-31 and at 32-33 weeks of gestation, the questionnaire assessed the following variables: whether written nutrition guidelines were available in the unit, whether parenteral nutrition (PN) was considered since the day of birth, the type of venous access chosen in case of PN, postnatal day on which parenteral AA and lipid intake was started, AA starting dose, postnatal day on which enteral feeding was started, enteral feeding advancement and fortification strategy. PN was defined as "intravenous nutrition given through a central or peripheral line and containing at least both dextrose and nitrogen", full enteral feeding as "enteral feed given as sole nutritional source". Day of life (DOL) 1 was defined as the day of birth. In each centre, respondents were asked to record data from the last consecutive 12 patients on the electronic file (3 patients for each GA, born from 30 to 33 weeks of gestation) being at 36 weeks postconceptional age (PCA) or discharged from the unit.
Data collection and management The identity of the respondent to the questionnaire and that of the centre's electronic file were both blinded for the analysis to all authors. Patients' records were anonymous. Data recording for this study was approved by the National Committee for data protection (Commission Nationale de l'Informatique et des Libertés, registration number 1687438). This study was approved by the institutional medical research ethics committee (Comité de Protection des Personnes Sud-Ouest et Outre Mer III, authorization number 2013/76). According to French legislation, written parental consent was not needed for this study. Demographic features and in-hospital morbidities were collected. The following data were recorded on DOL1, 3, 7, 14 and at 36 weeks PCA or at discharge (DC) (when before 36 weeks PCA): weight, parenteral (g/Kg/d of dextrose, AA and lipids) and enteral intake (ml/kg/d of human or given formula milk), whether a central or peripheral venous line was inserted.
Questionnaire responses and study population A total of 29 units were surveyed. Four units were secondary excluded as they only provided responses to the questionnaire without feedback of patients' data. So, finally, 25 units were included in the analysis (23 III level NICUs and 2 IIB level nurseries). Data of 276 patients were analysed. Population characteristics are presented in Table  1. Table  2  shows the questionnaires responses (intended practice) according to groups of GA.
Acknowledgements With thanks to  Madame Isabelle Germain , executive secretary at  Centre d'Études Périnatales de l'Océan Indien  ( CHU La Réunion ) who played a crucial role in this study. All the medical doctors collaborating on the NUTRIQUAL French group:  Tasmine Akbaraly ,  CH Perpignan ;  Dominique Astruc ,  CHU Strasbourg; Brigitte Auburtin, CH Epinal ;  Isabelle Bauvin ,  CH Pau ;  Antoine Bedu ,  CHU Limoges ;  Faouzi Benababdelmalek ,  CH Nevers ;  Amandine Blasquez ,  CH Libourne ;  Farid Boubred ,  AP-HP Marseille ;  Henri Bruel ,  CH Le Havre ;  Gilles Cambonie ,  CHRU Montpellier ;  Magali Carbonnier ,  CHU La Réunion (Saint-Pierre );  Daniele De Luca ,  Antoine Béclère -GH Paris Sud ;  Celine Dillenseger ,  CHU Strasbourg ;  Benoît Dumont , CHU Saint Etienne; Michel Françoise, CH Chalon sur Saône ;  Julie Guerreiro ,  CHR Orléans ;  Joel Hodonou CH Périgueux ;  Khaled Husseini ,  CHU Poitiers; Pierre-Henry Jarraud, Port-Royal -Hôpital Cochin AP-PH Paris ;  Philippe Jouvencel ,  CHIC Bayonne ;  Serge Klosowski ,  CH Lens ;  Laura Kollen ,  CH Perpignan ;  Davi Komlan ,  CH Cayenne ;  Aurélie Labaste, CH Chalon sur Saône ;  Doriane Madelenau ,  Port-Royal -Hôpital Cochin AP-PH Paris ;  Florence Masson ,  CHRU Montpellier ;  Anne-Claude Menguy ,  CH Perpignan ;  Myriam Mirc ,  CHI André-Gregoire, Montreuil ;  Fadilha Mokraoui ,  Antoine Béclère -GH Paris Sud ;  Julien Moursie ,  CH Le Havre ;  Jean-René Nelson ,  CH Libourne ;  Laurence Pognon ,  CHRU Lille ;  Duksha Ramful ,  CHU La Réunion (Saint Denis );  Olivier Romain ,  Antoine Béclère -GH Paris Sud ;  Sylvaine Rousseau ,  CH Roubaix ;  Denis Semama ,  CHU Dijon ;  Laurent Storme ,  CHRU Lille ;  Amélie Vintéjoux ,  CH Macon ;  Carlos Varela ,  CHU Guadeloupe.
General Genome Features We have sequenced the genome of the marine-derived S. brevicaulis using three different genome sequencing methods namely Roche 454, Illumina HiSeq 2000 and ion-torrent. Using Roche 454 pyrosequencing, we achieved a 32. 2. Mb genome with N50 equals to 88 kb and 935 contigs, which further joined to form 699 scaffolds with N50 of 116. 7 kb. Using short reads of Illumina and Ion-torrent, we achieved smaller N50 (and large numbers of scaffolds) as 67. 5 kb (2605) and 26. 3 kb (12119), respectively. We performed a hybrid assembly using all these three types of reads, this yielded N50 of 131. 8 kb with 623 scaffolds. This corroborates that Roche 454 alone is good performer for fungal genome assembly and combining more than one method is the better choice. This is also reflected by data from a recent genome assembly of the white-rot fungus Pycnoporus cinnabarinus  [19].
Genome Annotation and Phylogenetic Analysis Functional annotation is critical for understanding the genomic data of new species and is supported by Gene Ontology (GO)  [25]. GO helps in characterization of genes, transcripts and proteins of many organisms in terms of biological processes (BP), cellular components (CC), and molecular functions (MF)  [25]. We have used this method for the functional annotation of S. brevicaulis proteins using the Blast2GO suite  [25]. The derived S. brevicaulis proteins were assigned to three functional groups based on GO terminology: BP, CC and MF (S2 Table ). We traced 5,159 proteins to BP terms (Fig 2 ) with the following five top categories: 761 related to oxidation-reduction processes, 485 related to trans-membrane transport, 423 related to regulation of transcription, 318 related to mycelium development, and 187 related to methylation.
Protein Domains of S. brevicaulis Protein domains are biochemically independently foldable structural units, which depicting evolutionary conservation with the presence of at least one protein motif. This implies that proteins carrying common domains may have similar functions. Hence, this is an important source for scanning new genomes for putative proteins with similar functions. There are two state of the art databases namely the Pfam  [28]  and the Interpro  [29] , both used for protein domain analysis. This analysis is helpful for better annotation of new genomes. We found a total of 10,458 deduced protein sequences of S. brevicaulis associated with all eukaryotic protein domains (S3 Table ) and top 20 Pfam domains, which are summarized in Fig 4. Additionally, we found two transporter domains in Pfam with 221 proteins harboring a major facilitator superfamily/MSF_1 domain (PF07690.
11), and 107 proteins containing a sugar (and other) transporter/sugar_tr domain (PF00083. 19 ). These transporters are generally single-polypeptide secondary carriers involved in transportation of sugars and other small solutes in response to chemiosmotic ion gradients  [30, 31]. Two transcription factor domains are also in this list with 205 fungal specific transcription factor domain/ Fungal_trans (PF04082. 13) and 112 fungal Zn(2)-Cys(6) binuclear cluster domain/Zn_clus (PF00172. 13). These proteins serve as transcription regulatory elements. We compared all transcription factor domains, which suggested that these two fungal transcription factor domains are highly expanded in selected ascomycetes (S4 Table) as shown previously  [32]. We detected 112 G-beta repeat/WD40 (PF00400. 27) domains, which may be involved in signal transduction.
Plant Biomass Associated Metabolism Evident from Comparative Analyses of Carbohydrate Active Enzymes The type of association between sponges and fungi and the corresponding ecological function remain unclear and little evidence is available on fungal adaptation to sponges (if any). Studying the carbohydrate-active enzymes (CAZy) profile could provide interesting information on the main families represented in S. brevicaulis genome and perhaps reveal its substrate preference and its nutritional relationship with the sponge. Using specialized homology detections and annotation from CAZy database, (www. cazy. org) we identified 478 CAZy genes in S. brevicaulis genome (S6 and S7 Tables). These enzymes are divided into six classes, i. e. 71 auxiliary activities (AAs), 34 carbohydrate esterases (CEs), 50 carbohydrate binding modules (CBMs), 227 glycoside hydrolases (GHs), 81 glycosyl transferases (GTs) and 15 polysaccharide lyases (PLs).
Analyses of MFS-Type and Sugar Transporters Also Support Plant Biomass Associated Metabolism Taking into account the entire CAZyme repertoire, it is clear that S. brevicaulis has a metabolism capable of break down plant biomass. The same picture emerges when S. brevicaulis proteins predicted to harbor either a MFS domain (PF07690. 11), or a sugar (and other) transporter domain (PF00083. 19 ) are compared to the corresponding transporter complement of N. crassa, a representative plant biomass saprophyte. N. crassa has only about half as many transporters encoded in its genome compared to S. brevicaulis (159 vs. 328 with the same PFam annotations). Yet an overall similar distribution of the transporters can be observed across the categories as defined by the Transport Classification database (TCDB;  [40]   ).
Class 2. A. 1. 12 (the Sialate:H + Symporter family; dark green), is greatly overrepresented in terms of transcript abundance (only 2 genes, but with 5. 9% of total transporter-specific transcript) due to g12790. t1 being the second most highly expressed transporter in the genome (Table  4 ). Homology search by BLAST  [42]  suggests that g12790. t1 encodes for a carboxylic acid transporter, such as for lactate or pyruvate uptake, which should have been abundant in the rich medium S. brevicaulis was grown in. An analysis of the remaining genes in the list of top 10 transcribed transporters suggests that these collectively help to satisfy some of the major nutritional requirements of the fungus, such as for carbon and nitrogen as well as vitamins. Sources for these are carbohydrates (hexoses such as glucose, pentoses and other polyols; g14394.
The resulting product is then released by the NRPS by cyclization. The pks6 gene (g13622) on the other hand has a non-reducing PKS protein product and BLASTP analysis against GenBank showed that it is shares similarities with the mycelium pigment synthase and shares 71% identity to a PKS (VDAG_00190) that has been proposed to be involved in the biosynthesis of melanin in Verticillium dahlia  [58]. Hence, PKS6 could be involved in pigment biosynthesis in S. brevicaulis. These pks genes are type I PKS genes and are localized in 5 different clusters (Fig  7   At current the secondary metabolite products produced by many of these proteins are unknown as it is typical for many fungi studied. As genome sequencing of fungi has become affordable we expect more and more fungal genomes being available in the public databases, which will lead into a better picture of homologous gene clusters and their final products.
However, a BLASTP search with these two ORFs gave no significant hit in the databases. Upon scanning expression profiling based on RNA-seq data, we found that all of the mating type genes of S. brevicaulis are expressed. The MAT1-1-1 gene has highest expression among three mating genes, which is followed by MAT1-1-3 and MAT1-1-2 (Fig  9B ). The flanking gene SLA2 gene has a particular high expression, which is 10-fold higher in comparison to the by scaffold and positions on the scaffold and different colors are illustrating different types of clusters. Biosynthetic genes are key gene (like either nrps or pks and so on) and main supporting genes such as a cytochrome P450 gene as per antiSMASH  [48]  guidelines. Similarly, other genes are any other gene in the cluster, which are not key genes, regulatory (such as transcription factor or suppressor) and transporters (such as ABC transporter) and are marked in grey shade.
doi:10. 1371/journal. pone. 0140398. g007 APN2 gene. Overall, we report that conserved genes of the mating type loci of S. brevicaulis are expressed. Overall, the presence of three MAT1-1 genes and absence of MAT1-2 gene in the S. brevicaulis genome corroborate that S. brevicaulis LF580 is a MAT1-1 strain. Additionally, all three MAT1-1 genes appear to be functional genes, because these genes shown expression profiles in the RNA-Seq datasets.
Genome Sequencing Using Three Different Methods Roche 454 sequencing was performed with 20 μg genomic DNA at Macrogen (Korea). This provided 631 Mb 454 reads with an average read length of 432. 5 bp (S3 Fig). Illumina sequencing was performed using Illumina HiSeq™ 2000 with 20 μg genomic DNA at the Macrogen (Korea). This yielded in 2. 5 Ã 10 8 Illumina reads with an average length of 101 bp (S10 Table ). Ion-torrent sequencing was carried out with 20 μg genomic DNA at Genotypic Technology (Bangalore, India) and 630 Mb of Ion-torrent reads were generated with average length of 119 bp (S11 Table ). The whole genome sequencing and RNA-Seq data for S. brevicaulis is publically available using BioSample accession ID: SAMN03764504 and corresponding BioProject accession ID: PRJNA288424.
Genome Assembly, Repeat Detection, Gene Prediction and Annotation Analyses Roche 454 reads were assembled into contigs using Newbler assembler  [68]. Several Genome assemblies were performed using de Brujin graph based method by de novo assembler in the CLCBio Genomic workbench  [69]  using generated reads of Illumina, and Ion-Torrent and all reads for hybrid assembly. Scaffolding of contigs generated by respective assemblies was carried out using genome finishing module of CLCBio Genomic workbench  [69]. The Repeat elements were predicted using RepeatMasker and RepeatProteinMasker software programs (Smit, AFA, Hubley, R & Green, P. RepeatMasker Open-4. 0. 0 1996-2013 http://www. repeatmasker. org) using the fungal transposon species library (database version 20120418) as input. Gene prediction was performed using Augustus gene prediction tool using Asperigillus niger as training dataset.
This prediction was compared with other genome prediction tools. Predict genes were annotated using BLAST homology searches  [42]  with an E-value cutoff of 1e -3 , supported by BLAST2GO tool  [25]. Predicted coding regions were annotated using BLAST  [42]  with comparing the Kyoto Encyclopedia of Genes and Genomes (KEGG)  [70] , Swiss-Prot, TrEMBL, Gene Ontology (GO), and non-redundant (NR) databases.
Genome-Wide Phylogenetic Relationship In order to confirm the phylogenetic position of species under study we reconstructed a phylogenetic tree using the CVtree  [27]. CVtree is an alignment free composition vector tree based method and hence does not require selection of specific genes for phylogeny reconstruction. The only parameter required by the method is k, that was set to 7  [71]. We used the fully predicted proteomes of 67 fungi, and the choanoflagellate Monosiga brevicollis as an outgroup  [72]. Bootstrap scores for phylogeny were calculated as in  [73]  by randomly sampling the proteome of each species, with replacement, to create a novel perturbed proteome for each of the 100 bootstrap runs. A representative subset of the 68 species was plotted using APE package  [74]  within the R computing environment  [75].
Protein Domain Estimation Predicted proteins of this genome were scanned to all known Pfam (version 27)  [28]  and Interpro (version 43)  [29]  protein domains collections, respectively. Pfam domains were predicted using HMMER 3. 0  [76] , removing overlapping clans. In order to compare protein coding gene content across fungal species we constructed a python script to carry out the following tasks. Interpro database  [29]  was searched for Pfam  [28]  identifiers corresponding to Interpro identifiers of interest. For each Pfam  [28]  identifier pfam_scan. pl (ftp://ftp. sanger. ac. uk/pub/ databases/Pfam/Tools/), a wrapper for HMMER 3. 0  [76] , was run to find the matching proteins in the genomes of interest. To analyse subfamily structure of each Pfam family's member proteins in the genomes, the corresponding protein sequences were collected and mcl clustered  [77] based on the E-value matrix of all-vs-all BLASTP  [42].
Identifications and Classifications of CAZyme Domains All putative proteins were compared to the entries in the CAZy database  [80, 81]  using BLASTP  [42]. The proteins with E-values smaller than 0. 1 were further screened by a combination of BLAST searches against individual protein modules belonging to the following classes auxiliary activities (AA), glycoside hydrolases (GH), glycosyltransferases (GT), polysaccharide lyases (PL), carbohydrate esterases (CE) and carbohydrate-binding modules (CBM) in the CAZy database (http://www. cazy. org/). HMMER 3. 0  [76]  was used to query a collection of custommade hidden Markov model (HMM) profiles constructed for each CAZy family. All identified proteins were then manually curated and whenever possible, assigned to a subfamily within a family.
Classification of MFS-Type and Sugar Transporters For a more precise classification of the S. brevicaulis genes annotated according to Pfam as MFS-type or sugar transporters (328 genes total), the Transporter Classification Database (TCDB) was used  [40]. In addition, the 159 transporter genes of N. crassa with the same Pfam annotations were also classified using TCDB  [40]. To this end, sequence similarity searches were performed against the TCDB for each gene using BLASTP  [42]  with default parameters. To ensure a certain level of stringency, only E-value of 1e -10 and below were considered as reliable hits. If a BLAST  [42]  search met these preconditions, the corresponding gene was classified into the same category as the TCDB homolog with the best e-value. When the E-value threshold was exceeded for all TCDB results, the gene was not categorized.
Detection of Bioactive Encoding Genes and Their Clusters Initially, putative genes that encoding for proteins which produce bioactive compounds are identified using BLAST  [42]  with an E-value < 1e -3. Subsequently, this genome was analysed using SMURF  [82]  and antiSMASH  [48]  for putative clusters and further examined by manually coupled with RNA-Seq data. The functional domains of PKSs and NRPSs were identified as previously described  [83] , using a combinations of tools namely antiSMASH  [48] , NCBI Conserved Domain Database  [84] , InterPro  [29]  and the PKS/NRPS Analysis Web-site  [85].