dataesr/scientific-paragraphs-categorization huggingface dataset:
01). In contrast, at the OTU level (and also Family level, data not shown), the bacterial communities were clearly discriminated according to the cyanobacteria genus (Anabaena or Microcystis). As shown in Fig  4 , the Sphingomonadales (Kruskal-Wallis; p-value < 0. 01) and Nitrosomonadales (Kruskal-Wallis; p-value < 0. 01) were notably abundant during the Microcystis bloom, while the Xanthomonadales (Kruskal-Wallis; p-value < 0. 01) and Chthoniobacterales (Kruskal-Wallis; p-value < 0. 05) were more abundant during the Anabaena bloom. A low number of OTUs were shared by at least three fractions but these OTUs contained a very high number of reads (Fig  5 ). In contrast, a large majority of OTUs were found in only one fraction (ranged from 215 OTUs to 779 OTUs), however, they represented a very low number of reads (Fig  5 ).
The number of OTUs shared by both free-living bacterial communities (117 OTUs) was more than five-fold higher than those shared by both associated bacterial communities (14 OTUs). This was also observed for the number of reads they contained (2. 7 versus 0. 2%). The dominant OTUs (> 1%, 40 OTUs) accounted for 55. 6% and 58. 3% of the reads for associated and free-living fractions of Anabaena bloom respectively and for 73. 1% and 40% of the reads for the associated and free-living fractions of Microcystis bloom respectively. The representative sequences of abundant OTUs were blasted to GeneBank1 database (S3 Table ) and around 10% of these OTUs displayed a sequence identity value < 98% with sequences from GeneBank1. Among the other OTUs displaying 98% sequence identity with sequences from GeneBank1, 37,5% of the OTUs sequences were found associated with cyanobacterial blooms and numerous sequences were retrieved in organic-matter-rich ecosystems worldwide (S3 Table ).
The estimation of the composition of BCs depends on, for a substantial part, the choice of the sequencing strategy and of the targeted DNA region (e. g. [22] ). But, when comparing data obtained by both primer sets, although they don't target the same 16S rDNA regions, the same dominant phyla were retrieved and no major differences were found in the global structure of the communities and in the dominant OTUs. The NC-Pr2 primer set therefore can be used to compare BCs associated with bloom-forming cyanobacteria.
5-85 ms, and ten echoes. To measure the longitudinal relaxation times (T 1 ), MSME sequence was used with the following parameters: FOV =5 cm ×5 cm, matrix =128×96, TR =90 ms, 150 ms, 300 ms, 500 ms, 800 ms, 1,200 ms, 2,000 ms, and 3,000 ms, and TE =8. 5 ms. The T 1 for each sample was calculated in MATLAB (The Mathworks, R2012b) by using the equation of f(x)=a+c×(1-exp(-1×x/b)).
Then, sections were re-incubated at 37°C for 1 hour and rinsed. Freshly prepared DAB was used for color developing, while hematoxylin was used for counterstaining. All sections were dehydrated in a gradient ethanol and mounted with neutral gums eventually. The analysis of stained sections was done under a microscope, and quantitative analysis was done using Image Pro Plus software (version 6. 0). The measurement parameter was density mean, calculated by integrated optical density divided by area sum, and the intensity was averaged from five FOVs for ten tissue sections.
Results are shown in Figure  6. It can be seen that there is more blue deposition in cancer cells incubated with M-HFn nanoparticles with larger core size. We also assessed the iron content in cancer cells by ICP-MS and found that cancer cells accumulated 0. 16 pg cell -1 , 0. 29 pg cell -1 , 0. 80 pg cell -1 , and 1. 23 pg cell -1 of Fe after being incubated with equal amount of M-HFn 1000 , M-HFn 3000 , M-HFn 5000 , and M-HFn 7000 for 24 hours, respectively (Figure  6F ). Tumor tissues incubated with M-HFn nanoparticles showed brown color, which is in contrast to purple color of the normal tissues counterstained by hematoxylin. Quantitative analysis of effect on staining with M-HFn nanoparticles was performed using Image Pro Plus software, which shows that M-HFn nanoparticles with large core size generate high value of density mean.
Figure7shows the M-HFn-based peroxidase staining performed on xenografted MDA-MB-231 tumor tissues. Tumor tissues incubated with M-HFn nanoparticles showed brown color, which is in contrast to purple color of the normal tissues counterstained by hematoxylin. Quantitative analysis of effect on staining with M-HFn nanoparticles was performed using Image Pro Plus software, which shows that M-HFn nanoparticles with large core size generate high value of density mean.
Acknowledgments This work was supported by the  CAS/SAFEA International Partnership Program for Creative Research Teams  ( KZCX2-YW-T10 ), the  National Natural Science Foundation of China  (numbers 41330104 and  41204053 ), and the  R&D of Key Instruments and Technologies for Deep Resources Prospecting  (the  National R&D Projects for Key Scientific Instruments , number  ZDYZ2012-1-01-02 ). We thank  Drs F Fang  and  H Lei  of  Wuhan Institute of Physics and Mathematics, CAS , for selfless help in the MRI experiment. We are grateful to three anonymous reviewers for their constructive comments that significantly improved the manuscript.
Between 8 and 20 clones were amplified by PCR (electronic supplementary material, table  S2 ) and sequenced using M13 primers. Allelic identity was confirmed when the corresponding DNA sequence was found in at least two clones. Only one or two alleles were recovered from any of our samples, confirming that our primers targeted one single MHC-II locus in all species. Sequences obtained were aligned with MHC-II b1 sequences of 17 amphibian species from around the world that vary in susceptibility to Bd  [19] [20] [21] [22] [23] [24] [25]  (length of sequences: 37-81 amino acids; complete list in electronic supplementary material, figure  S1 ; GenBank accession numbers KJ679288-KJ679331) using CLUSTAL W  [26]. Sequences then were translated into amino acids using BIOEDIT  [27]. We examined the amino acid composition at 15 codon positions known to affect the properties of the P4 (seven sites), P6 (four sites) and P9 (four sites) pockets of the MHC-II peptide-binding groove in humans  [11, 12].
Codon b9 of pocket P9 was not evaluated because it was missing from more than half of our dataset. The most frequent amino acid across MHC-II b1 sequences of Bd-resistant amphibians was recorded for each of the 15 positions. We hypothesized that these most frequent amino acid compositions represent pocket conformations associated with Bd resistance. Allelic frequencies within populations could not be considered because such data are not available for most amphibian species. Nevertheless, if Bd induced strong selection for particular MHC-II conformations, we would expect to find a trend. Failure to find a relationship, however, would not allow us to draw any conclusion. For each MHC-II binding pocket, the proportion of b1 sequences containing all the amino acids most frequent in resistant amphibians was compared with that characteristic of susceptible species.
(c) Microsatellite genotyping and data analysis A panel of nine microsatellite markers, including two markers isolated from the Litoria ewingii complex  [30]  and seven from a L. v. alpina partial genomic DNA library (see the electronic supplementary material), was organized into two fluorescently labelled multiplexes, and multiplex PCR was performed with Qiagen multiplex PCR master mix following the method described in electronic supplementary material, table  S3   [31]. Details of microsatellite primers, GenBank accession numbers and PCR protocols are given in electronic supplementary material, table  S3. Allele sizes were assigned using an ABI3730 DNA analyser at NICEM (Seoul National University, South Korea) and PEAK SCANNER v. 1. 0 (Applied Biosystems, Carlsbad, CA, USA). Conformity to Hardy-Weinberg equilibrium and linkage disequilibrium was determined with GENEPOP v.
4. 0  [32]. Heterozygosity values and frequency of null alleles were estimated with CERVUS  [33]. Frequency of null alleles was high (F. 0. 10) for four markers (Livea-GT1, Livea-AG3, Le2 and Le4) in the three populations genotyped. Therefore, we statistically adjusted allele frequencies assuming a single new allele size by generating a new genotyping dataset corrected for null alleles in FREENA  [34]. Subsequent rspb. royalsocietypublishing. org Proc. R. Soc. B 282: 20143127 analyses were run both with the five-marker dataset and the full nine-marker dataset corrected for null alleles.
Numbers of frogs available for treatments were subject to actual clutch sizes and natural attrition during growth and development. Frogs were maintained in a quarantine room at temperatures between 18 and 208C under a 12 L : 12 D regimen. Subjects were housed individually in small plastic tubs on an angled rack with drainage holes, a loose pebble floor and a gauze-covered top. They were fed twice weekly with vitamin-dusted (calcium and herptivite alternately) crickets, and tubs were cleaned daily by flushing with fresh filtered water. Subjects were monitored daily for clinical signs of infection (dullness, lethargy, peripheral erythema and increased skin shedding). Bd infection intensity data were collected weekly by swabbing all subjects, each with fresh gloves and a new sterile dry swab (MW100; Medical Wire and Equipment, Corsham, UK).
The significance of each variable's effect on hazard risk was evaluated with Wald z statistics. Analyses were conducted with the 'survival' package in R v. 3. 0. 2. (f ) Detection of selection pressure Genetic variation among populations (F ST ) at MHC and microsatellite markers was calculated and compared with simulated expected F ST values in wild L. v. alpina populations using Fdist  [37]  implemented in LOSITAN  [38]. Markers with F ST values significantly higher than the simulated distribution (posterior probability more than 0. 95) were considered to be under positive selection. Analyses were done on the full dataset including the three populations, and on pairs of populations, to identify population-specific differences in selection pressure. Balancing or directional selection affecting MHC-II in wild L.
Funding statement. The research was supported by the  National Research Foundation of Korea (NRF) , funded by the  Government of the Republic of Korea (MSIP)  (grant nos. 2010-0002767 ,  2012R1A1A2044449  and  2012K1A2B1A03000496  to B. W. ), by  Seoul National University (Brain Fusion Program ,  Brain Korea 21 Program  and  New Faculty Resettlement Fund  grants to B. W. ) and by the  Australian Biosecurity CRC for Emerging Infectious Diseases  and the  Australian Research Council  (grant nos. FT100100375 ,  LP110200240  and  DP120100811  to L. F. S. and L. B. ).
Cells with MAB-like properties have been isolated from human adult skeletal muscle pericytes  9  and expanded under clinical-grade conditions, providing the basis for a Phase I/II clinical trial for Duchenne muscular dystrophy (EudraCT no. 2011-000176-33; Cossu et al. in preparation). Since the initial identification of MABs in mouse embryos  1  , all MABs thus far isolated from different species (mouse, dog and human) and developmental stages have been shown to contribute to muscle regeneration in vivo. Although alkaline phosphatase expression can be used to identify adult human MABs in skeletal muscle, no single unequivocal marker has been identified that denotes MAB identity across species  1, 4, 6, 9. As a result, MABs are defined predominantly by their isolation method and functional properties.
Overall, these data highlight a fundamental role of PW1 for the other key feature of MABs: absence of PW1 impairs MAB ability to cross the vessel wall and reach the muscle through a mechanism that leads to the upregulation of JAM-A. PW1 regulates JAM-A by a direct binding to its promoter. PW1 has recently been shown to function as a transcription factor with a DNA-binding motif AGTnnCnnnTGGCT  20. Our work suggests a mechanism in which PW1 regulates cycE and JAM-A. Using the Genomatix Matinspector software, we identified two different regions on the minus strand of the cycE promoter containing the core sequences necessary for PW1 binding. However, due to a 480% GC content, we were unable to obtain reproducible data confirming that PW1 directly binds to these sites. Nevertheless, we measured the luciferase activity in NIH3T3 cells co-transfected with pLuciferase-cycE À 94/ þ 263 promoter  28  (pCE), pE2F-2 (a well-known cycE-activator) and pGL4.
Quality control (QC) of the RNA samples was performed using an Agilent Bioanalyzer 2100 (Agilent Technologies). Two different RNA extractions were processed for each of the cell lines under analysis, and each sample was labelled and hybridized to a Mouse Gene 1. 0 ST Genechip array according to the manufacturer's specifications (Affymetrix). Data were analysed using Partek Genomics Suite v6. 3 software (RMA algorithm). Differentially expressed genes were identified through analysis of variance, using a fold change cut-off 41. 2 and a P value of 0. 05. Microarray data have been deposited in Gene Expression Omnibus (GEO) under accession code GSE64334. Quantitative PCR with reverse transcription. Total RNA was isolated using NucleoSpin RNA XS Kit (Macheray-Nagel) and was retro-transcribed to cDNA with the iScript Reverse Transcription Supermix (Bio-Rad), according to the manufacturer's instructions.
33 mM 6-CFDA. Cells were then added to the upper chamber and allowed to migrate for 8 h. Migrated hMABs on the lower side of the filters were fixed and counted. Quantification of migrated hMABs per area is shown. Data are presented as means ( ± s. d. ) from five independent experiments, each of these was run in triplicate. **Po0. 005, *Po0. 5, unpaired one-way t-test.
Acknowledgements We thank  G. Maroli  for helpful discussion. We also are grateful to  S. Monteverde ,  L. Perani ,  E. Vitucci  and  L. Formicola  for technical assistance,  L. Ferrarini  and  G. Pavesi  for his help in the Microarray analysis and  A. Oldani  for imaging support. This work received funding from the  EC FP7VII projects Optimization of Stem Cell Therapy for Degenerative Epithelial and Muscle Diseases (OPTISTEM ;  Health-F5-2009-223098 ) and ENDOSTEM (Activation of vasculature-associated stem cells and muscle stem cells for the repair and maintenance of muscle tissue; Agreement 241440). The team of D. S. and G. Ma. is a beneficiary of  Laboratoire d'Excellence Revive (Investissement d'Avenir ;  ANR-10-LABX-73 ) G. Me. also thanks the  ERC StG2011  ( RegeneratioNfix 280611 ) and the  Italian Ministry of University and Research  ( MIUR-Futuro in Ricerca 2010 ) for their support.
Recently, the use of experimental proteomic data with proteogenomics has emerged as an interesting approach for improving genome annotation and for dealing with non-model organisms  [7]. Interpretation of proteomic data requires a comprehensive protein sequence database. For a non-model organism, it is worthwhile to first establish the genome sequence that can then be translated into the six reading frames. The resulting protein database can be queried with experimental tandem mass spectrometry results in order to quickly establish the list of key cellular or extracellular players. Proteins may be quantified with either a labeling or non-labeling approach  [6]. Although non-labeling approaches based on spectral counts are by far the most frequently used as they are simple to perform and reliable even for the analysis of extracellular components  [8, 9] , labeling methodology is also adequate for this purpose  [10].
The analysis of variance of the replicates for each salinity evaluated allows a determination that smaller variations occur in the total spectral counts when the cells are in the optimal growth salinity, 0. 5% NaCl, (12%), than when they are in salinities of 0. 0% and 4. 0% NaCl in which there were variations of 14% and 18%, respectively (S1 Table ). A total of 30,130 MS/MS spectra were assigned to 2,321 tryptic peptides (S2 Table ). This was done with a stop-to-stop ORF database that had been constructed by six frame translation of its chimeric genome in an earlier study  [7]. These peptides allowed the identification of 249 non-redundant proteins in which at least two peptides were validated by tandem mass spectrometry (S3 Table ). Fig  1  shows a Venn diagram of the extracellular proteins detected within the different growth conditions.
A total of 196 proteins were identified at 0. 0% NaCl, 175 proteins at 0. 5% NaCl and 199 proteins at 4. 0% NaCl. As indicated in  Fig 1, 131  proteins were common to the three conditions, which were mostly related to central metabolism processes. On the other hand, 24 proteins were common only to 0. 0% and 0. 5% NaCl conditions while 15 proteins were common to only 4. 0% and 0. 5% NaCl conditions. In both cases the majority of the proteins were again related to central metabolism. In the case of proteins common to 0. 0% and 4. 0% NaCl, 20 of the proteins identified were mainly involved in translation processes. The distribution of the proteins detected in the three salinities based on functional categories according to the KEGG database is summarized in Fig 2. A total of 265 proteins out of the 315 proteins identified could be assigned to 40 pathways involved in T.
Full-scan mass spectra were measured from m/z 300 to 1,700 with the LTQ-Orbitrap XL mass spectrometer in data-dependent mode using the TOP7 strategy. In brief, a scan cycle was initiated with a full scan of high mass accuracy in the Orbitrap. This was followed by MS/MS scans in the linear ion trap of the seven most abundant precursor ions, with dynamic exclusion of previously selected ions. Genome sequencing of T. consotensis and 6-frame ORF database and is available at the European Nucleotide Archive (http://www. ebi. ac. uk/ena/data/view/ CBKU010000001-CBKU010002377). The 2377 contigs sequences were concatenated end to end (from the largest to the shortest) to create a virtual continuous genome sequence. This artificial chimeric sequence was translated into the six reading frames using Bioedit version 7.
1. 3 software which resulted in ORF polypeptide sequences (from stop to stop). The resulting ORF database comprised 52,246 putative polypeptide sequences, totaling 9,292,134 amino acids with an average of 178 amino acids per putative polypeptide. Proteomic data and proteogenomic procedures were then used to discriminate between false, correct but undetected, and correct and detected protein sequences as described earlier  [48].
MS/MS database search The recorded MS/MS spectra of one fraction of each replicate were merged before a further search against our home-made ORF database was done. First, peak lists were generated with MASCOT DAEMON version 2. 3. 2 from Matrix Science using the extract_msn. exe data import filter from the Xcalibur FT package (version 2. 0. 7) proposed by ThermoFisher. Data import filter options were set as previously described at 400 (minimum mass), 5,000 (maximum mass), 0 (grouping tolerance), 0 (intermediate scans), and 1,000 (threshold)  [50]. We performed a search for the MS/MS spectra in the ORF database with the following parameters: tryptic peptides with a maximum of 2 missed cleavages during proteolytic digestion, a mass tolerance of 5 ppm on the parent ion, and MS/MS of 0. 5 Da; fixed modification for carbamidomethylated Cys (+57.
0215); and variable modification for oxidized Met (+15. 9949). All peptide matches with the ORF database with a peptide score above the query threshold of p< 0. 05 and rank 1 were parsed using the IRMa 1. 28. 0  [51]. Using a decoy database the false-positive rate for peptide identification with these parameters was estimated at below 0. 5%. MS/MS spectra assigned to several loci were systematically removed. A total of 80,542 MS/MS spectra were recorded during the 24 nanoLC-MS/MS runs. Four biological repeats were done for each of the three growth media and the two analytical replicates. A protein was considered validated when at least two different peptides of that protein were detected in the same experiment. Using a reverse decoy database false-positive identification of proteins with these parameters was estimated at below 0.
Comparison of protein abundance with PatternLab The number of MS/MS spectra per protein (spectral counts) was determined for the different replicates under each growth condition. A unique biological replicate, 0. 5% NaCl, was considered to be an outlier because of its significantly low number of assigned spectra. The salinity of 0. 5%NaCl was used as a control condition for the comparative analysis of the abundance of the detected proteins. Protein abundances were first compared between 0. 0% NaCl medium (8 replicates) and the reference medium of 0. 5% NaCl (6 replicates), and between 4. 0% NaCl medium (8 replicates) and the reference medium of 0. 5% NaCl (6 replicates). A list of non-redundant proteins detected among the corresponding datasets was established for each of these two comparisons.
The total spectral count of each polypeptide was used to rank the proteins detected from highest to lowest. The statistical variation of proteins among the replicates under the two specific growth conditions compared was calculated using the T-Fold option of PatternLab 2. 0  [52]. This module allows normalization of spectral count datasets, calculating average fold changes with the t-test, and estimating the resulting theoretical false discovery rate. Stringent parameters were used for this analysis: minimum fold change of 1. 5, minimum p-value of 0. 05 and BH-FDR Alfa of 0. 15. The normalized spectral abundance factor (NSAF) for each protein was calculated as described  [50].
Protein and nucleic sequence analysis A BLASTp search was performed at the NCBI website facilities (www. blast. ncbi. nlm. nih. gov) using the non-redundant protein sequences and default parameters. The functional annotations of all proteins identified in this study were further confirmed using the KEGG database (www. genome. jp/kegg/). The genomic contexts of specific loci were inspected using the Geno-Mapper tool  [53]. For the predictions of signal peptides, proteins identified exclusively in the exoproteome of T. consotensis, i. e. which were not present in the cellular proteome were manually re-annotated in terms of sequence structure through inspection of the corresponding stopto-stop open reading frame and blast results. The sequences obtained were exported into a FASTA file for evaluation by the MetaLocGramN facilities (http://genesilico.
pl/ MetaLocGramN/)  [54] , SecretomeP 2. 0 with settings for Gram-negative bacteria (http://www. cbs. dtu. dk/services/SecretomeP/) [55] and PRED-TAT (http://www. compgen. org/tools/ PRED-TAT)  [56]. On the basis of the NSAF percentage, a ratio was calculated for each protein identified in the proteomic dataset. This was used to compare their abundance in the secretome with their abundance in the previously analyzed global cellular proteome  [7]. Proteins with a ratio (%NSAF secretome/%NSAF cellular proteome) above 1. 0 were considered to be secretome specific.
DNA extraction and sequencing of T. consotensis cells was performed as described by Rubiano-Labrador et al. (2014). Briefly, the DNA was fragmented and a 454-library with an average 8-kb insert size was constructed and sequenced on the Roche 454 GS FLX+ System (Titanium XL+ sequencing chemistry) by the GATC company. A total of 171,055 sequencing reads were recorded which resulted in 59,754,518 bases read. De novo assembling with the 454 Newbler assembler tool resulted in 2377 contigs (5,701,113 nt, 161,098 reads used) for the T. consotensis genome (10. 4× coverage). This Whole Genome Shotgun project has been deposited at DDBJ/EMBL/GenBank under the accession numbers CBKU010000001-CBKU010002377.