dataesr/scientific-paragraphs-categorization huggingface dataset:
The method of identification included the m/z from 3,000 to 15,000 Da. For every spectrum, a maximum of 100 peaks 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 only at the genus level; and a score < 1. 7 did not enable any identification. For strain JC13 T , no significant score was obtained, suggesting that our isolate was not a member of any known species or genus in the Biotyper database. We incremented our database with the spectrum from strain JC13 T (Figure  4 ). The gel view allowed us to highlight the spectra differences with other species of Erysipelothrichaceae family members (Figure  5 ).
Genome project history The organism was selected for sequencing on the basis of its phylogenetic position and 16S rRNA similarity to members of the family Erysipelotrichaceae and is part of a study of the human digestive flora aiming at isolating all bacterial species within human feces  [1]. It was the seventh genome from the Erysipelotrichaceae family and the first genome of Dielma fastidiosa gen. nov. , sp. nov. The Genbank accession number is CAEN00000000 and consists of 82 contigs. Table  3  shows the project information and its association with MIGS version 2. 0 compliance  [52]  Growth conditions and DNA isolation Dielma fastidiosa sp. nov. , strain JC13 T (= CSUR P149 = DSM 26099) was grown on 5% sheep blood-enriched Columbia agar at 30°C in anaerobic atmosphere. Seven petri dishes were spread and the cultivated bacteria were resuspended in 3×100µl of G2 buffer (EZ1 DNA Tissue kit, Qiagen).
Genome annotation Open reading frames (ORFs) were predicted using Prodigal  [53]  with default parameters. However, the predicted ORFs were excluded if they spanned a sequencing gap region. The predicted bacterial protein sequences were searched against the GenBank  [54]  and Clusters of Orthologous Groups (COG) databases using BLASTP. The tRNAs and rRNAs were predicted using the tRNAScanSE  [55]  and RNAmmer  [56]  tools, respectively. Lipoprotein signal peptides and numbers of transmembrane helices were predicted using SignalP  [57]  and TMHMM  [58] , respectively. ORFans were identified if their BLASTP E-value was lower than 1e-03 for alignment length greater than 80 amino acids. If alignment lengths were smaller than 80 amino acids, we use an E-value of 1e-05. Such parameter thresholds have already been used in previous works to define ORFans.
Genome properties The genome is 3,574,031 bp long (one chromosome of 3,556,241 bp and one plasmid of 17,790 bp) with a GC content of 40. 00% (Figure  6  and Table  5 ). Of the 3,491 predicted chromosomal genes, 3,441 were protein-coding genes and 50 were RNAs. A total of 2,534 genes (72. 58%) were assigned a putative function. ORFans accounted for 269 genes (7. 81%) and the remaining genes were annotated as hypothetical proteins. The properties and statistics of the genome are summarized in Tables  5  and 6. The distribution of genes into COGs functional categories is presented in Table  6. The 17,790bp-long plasmid contains 17 protein-coding genes. A BLASTN search showed its closest match to be the DO plasmid from Enterococcus faecium (GenBank Accession number: NC017961).
This sequence was not present in the current Zv. 9 assembly. When we aligned the cDNA clone with all other zebrafish cabps cDNA sequences it displayed the highest degree of conservation to cabp4a (data not shown). Using specific primers against the identified cDNA clone (IMAGE:4145466) sequence, we were able to amplify a 530 bp fragment from wild type Tupfel long fin cDNA. The online protein domain prediction tool Prosite from ExPasy assigned two EF-Hand domains to the unknown gene (Fig. 1C ). Based on these results, we decided to call this cDNA clone cabp4b. We subsequently calculated a phylogenetic tree based on the protein sequences of all H. sapiens and D. rerio Calcium binding proteins (for details see Material and Methods). As previously described  [10]  cabp7s and cabp8s (calneurons) form a separate subfamily (Fig.
Vibratome sections and confocal microscopy After staining, whole-mount embryos were washed twice in 0,1% Tween in PBS 16. Afterwards, the samples were embedded in gelatin/albumin with 4% of Glutaraldehyde and sectioned (20 mm) on a VT1000 S vibrating blade microtome (Leica). The sections were analyzed on a Leica Upright Widefield epifluorescence microscope and a Zeiss LSM710 confocal microscope (Zeiss). Images were processed using ImageJ, Adobe Photoshop and Adobe Illustrator software.
Acknowledgments We thank  E. Restrepo  for sharing preliminary results and  W. Norton ,  Ch. Gebhardt  and  S. Weiss  for their advice and comments on the manuscript. A special thank to  L. Poggi  and  J. Wittbrodt  that kindly provided the Tg(Vsx2:GFP) [18] and Tg(Ptf1A:GFP) [17] zebrafish transgenic lines and  H. Baier  for the Tg(Brn3C:memGFP) line. We thank  Olivier and Armelle  for excellent fish husbandry.
Sequence comparison We obtained protein sequences thanks to Genebank database: Drosophila melanogaster CG11188 (AAF52427), Homo sapiens Che-1 (AAH00591), Mus musculus AATF (NP_062790), Rattus norvegicus AATF (AAH78769), and Xenopus laevis AATF (NP_001167477). Similarities between CG11188 and Che-1/AATF related proteins were analyzed using Clustal W and Mac Vector.
ACKNOWLEDGMENTS We are grateful to  Isabelle Bécam  and  Lénaig Défachelles  for their participation in the screen and  Sabine Ritzenthaler  for sequencing class III alleles. We would like to thank the following for fly stocks: Bloomington, Szeged, and Harvard stock centers;  Spyros Artavanis-Tsakonas ;  Allison Bardin ;  Nick Brown ;  Antoine Guichet ;  Michael Mann ;  Mattias Mannervik ;  Anne Plessis ; and  François Schweisguth. We are also grateful to the imaging facilities of the  Institut Jacques Monod and the Plateforme d'Imagerie Cellulaire et Tissulaire IBiSA Genetics and Developmental Biology Imaging facility at Institut Curie  for their excellent technical help. J. R. H. is funded by  Centre National de Recherche Scientifique, Association pour la Recherche sur le Cancer (ARC)  # 3802 , and  Agence Nationale de la Recherche  # 06-JCJC-0092-01 ; M.
Introduction The identification of unknown bodies is crucial for ethical, medico-legal and civil reasons. Police and forensic investigators worldwide spend considerable time every year attempting to solve such cases. Typically, unidentified bodies or human remains are eventually identified by fingerprint comparisons, comparison of ante-and postmortem dental or medical radiographs, or by DNA analysis of tissue from the dead body and from possible relatives. However, in cases where there are no clues as to the identity, a characterization of the body can limit and focus the search for possible matches and help to exclude impossible or unlikely alternatives. The Doe Network Database (http://www. doenetwork. org) is extensively used in North America and includes both reported missing persons and unidentified bodies.
This database contains information on about 3,800 unidentified deceased individuals, the majority from the United States. A careful review of this database (Table  1 ) showed that the estimated age for adult individuals displayed an average uncertainty range of 15612 years. Such a wide range is not very helpful in the efforts to limit the search for possible matches. Furthermore, the sex was unknown or uncertain in some of the cases, and the geographic origin of the person rarely known, apart from information about the place where the victim was found. Hence, a more detailed characterization of the subjects in terms of age, sex and geographical origin is expected to improve the success rate in dead victim identification work. The most common procedure to estimate the age of an unidentified body is to perform an anthropological examination, which regarding skeletonized bodies focuses on age-related changes in teeth and bones.
In general, C4 plants tend to grow in hotter or drier climates than C3 plants. This in turn means that animals, including humans, having a diet based mainly of C4 plants and/or on animals that eat C4 plants, will incorporate more 13 C than those mainly living off C3 plant based diets. 18 O is another stable isotope that shows geographic variation. The incorporation of 18 O in animal tissues is correlated to the levels in drinking water and these levels vary with latitude because of differences in the evaporation and condensation propensity between 16 O and 18 O  [18]. In the United States, reports indicate that the highest tap water 18 O concentrations are in the south and southeast and the lowest in the northwest  [19]. These data are based on tap water samples collected from 2002-2003. Due to differences in precipitation and variable ground water supplies to specific areas, these levels may differ somewhat from year to year.
DNA analyses are very swift and can be performed at short notice by many laboratories worldwide. The consistent results using two different methods for sex determination in select cases support the notion that these analyses are robust. In addition, since both the Identifiler TM kit and the PowerplexH Y System provide a specific profile of the individual, such an analysis will often be needed anyway if antemortem radiographs cannot be retrieved and it seems practical and more economical to perform this analysis sooner than later. The Doe network database includes a large number of unidentified persons and different identification methods may be used to compare the characteristics of the deceased with antemortem material from the deceased or with samples from relatives. The review of this database (Table  1 ) revealed that the estimates of age of the subject show a great variation and that the sex was sometimes unknown.
29160. 003 (1 SD), in agreement with the certified value of 1. 29360. 001. 14 C-free calcite serves as background material for processing the enamel samples. The enamel samples are organized in groups of 10-14 unknowns bracketed by primary standards with one primary standard in the middle of the group. The secondary standards, primary standards and group of unknowns are measured consecutively as a cycle. Upon completion of a cycle the set of primary standards, secondary standards and unknown samples are measured again until desired precision is achieved. A typical group of 14 enamel samples is measured completely in 2-3 h. The measurement error is determined for each sample and generally ranges between 60. 2-0. 8% (1 SD). All 14 C data are reported using the F 14 C fraction modern nomenclature developed for post-bomb data  [39].
Western Blot Analysis Protein samples from the left ventricle were prepared in lysis buffer as described previously  [40]. The proteins (40-50 mg)   resolved by SDS-PAGE and transferred to a PVDF membrane (GE Healthcare). The membrane was then incubated with a primary antibody and followed by a HRP-conjugated secondary antibody. Specific proteins were detected by chemiluminescent methods using the Lumigen TMA-6 kit (Lumigen, Southfield, Michigan). Protein abundance on western blots was quantified by densitometry using Quantity One software (Bio-Rad, Hercules, CA).
C. CR induced the phosphorylation of ULK1 at ser555 in WT mice, but not in AMPKa2 KO mice. Data in A and B were expressed as mean 6 SE and analyzed by two-way ANOVA. Sample sizes were indicated in the bar graphs. doi:10. 1371/journal. pone. 0059682. g004 autophagy induction in WT mice was impaired by diminished AMPK signaling in KO mice. To ascertain that the changes in LC3-II levels were caused by altered formation of autophagosomes rather than the clearance of autophagic vacuoles, we determined autophagic flux, an index that reflects the number of autophagic vacuoles delivered to and degraded in the lysosome  [56]. This was assessed by the difference of LC3-II protein levels in the absence and presence of bafilomycin A1 (BFA, 3 mmole/kg), an inhibitor of autophagic degradation. BFA was delivered by i.
Calculation of endocytic time intervals. The differentiated data highlight intensity peaks marking sequences of endocytic events. In contrast to nonpolarized cells, polarized WT cells displayed a constant amplitude of dI/dt, marking internalization of a constant fraction of Abp1 molecules during each endocytic event. To analyze the frequency of these events with constant amplitude, a threshold of 50% of the maximum intensity of each endocytic sequence was set. Only the peaks with amplitude higher than the threshold were selected and the time interval between two consecutive events was calculated and presented as a scatter dot plot. An F-test was used to verify that the variance of distributions between the strains was significantly different (Figs. 3 C and 4 D; GraphPad Prism 5; GraphPad Software).
, 2012). In the (uniform) steady-state, the system of equations for Cdc42 autoamplification reduces to the following: Cdc k k GEF k GEF Cdc GEF N V k k k Cdc k k k k k k Cdc m GEF c m m = + + + + +     - - - 1 42 42 1 1 7 4 4 7 1 1 7 * * η η            Cdc m 42 * and GEF N V k k k k k k Cdc Cdc k k k C m GEF c m m * * * = + +       + - - - 1 42 42 4 4 7 1 1 7 1 1 7 d dc k k k k k k Cdc Cdc m m m 42 42 42 4 4 7 1 1 7 * * *. + + + +               - - η η We solved this system numerically using Matlab (Mathworks; see Matlab script in online supplemental material). Each equation defines a curve in the plane ( Cdc42 m * and Cdc42 m ), and uniform steady-states are defined by the intersections of these two curves. Under adequate parameter regimes (in silico WT cells; Table  1 ), the system shows multiple solutions.
Successful polarization of the autoamplification module with fast Cdc42-GTP diffusion (Fig. S1, A  [i] and B  [iv] ) supports multistability as a potential mechanism for symmetry breaking and polarity establishment. Remarkably, the autoamplification module approaches multiple uniform steady-states using previously published parameters. However, reaching the multistable regimen using 3,000 Cdc42 molecules (based on the expression levels of other Rho GTPases in the Saccharomyces Genome Database) required subtle adjustments of parameter values (Table  1 ). In the presence of Cdc42 fluxes to and from the plasma membrane caused by exo-and endocytosis, respectively, steady-state equations are only quantitatively modified, and the autoamplification module remains multistable within comparable ranges of parameter values.
Video 2 shows the reorganization of trafficking domains during polarity establishment in in silico WT cells. Video 3 is of a polarizing WT cell in vivo displaying endocytic corralling of the exocytic zone. Video 4 is of a sla2 cell in silico showing perturbed endocytic corralling. Video 5 is of a polarizing sla2 cell in vivo showing perturbed endocytic corralling and multiple exocytic poles. The Matlab script calculating the concentration of Cdc42-GTP solves the steady-state equations of the autoamplification module. Online supplemental material is available at http://www. jcb. org/cgi/content/ full/jcb. 201206081/DC1. Additional data are available in the JCB Data-Viewer at http://dx. doi. org/10. 1083/jcb. 201206081. dv. that exocytic vesicles carry sufficient endocytic coat proteins to form a single coat.
Duration of coat and actomyosin module recruitment phases were set in agreement with measured Abp1-RFP residency times (Fig. 4 B ) and recent observations  (Liu et al. , 2009; Carroll et al. , 2012). Protein populations were estimated from the Saccharomyces Genome Database. The number of Bem1-Cdc24-GEF complexes was limited to the Cdc24 copy number (see Table  1 ). Owing to a limited number of early coat proteins (e. g. , clathrin), the maximal number of early endocytic patches that may simultaneously develop was estimated by dividing the total number of clathrin molecules in a cell by the typical number of clathrin molecules in a coat  (Agrawal et al. , 2010). The number of Cdc42 molecules in a cell was set to 3,000, in agreement with amount of other Rho GTPases in yeast. Modeling sla2, sla1 bbc1, and rvs167 rvs161 mutants Sla2 is thought to enable binding of the actin cytoskeleton to clathrin coats  (Weinberg and Drubin, 2012).
Simulation data formatting and presentation We used the Surface Evolver binary image export tool to produce the images of the simulated cell (Figs. 2 A and 4 A) and to produce Videos 1, 2, and 4 at one frame per second. Movies were converted to the. avi format using screen capture with the software VirtualDub, and then to the. mov format using h. 264 compression in QuickTime. The kymographs were obtained by creating a contour of the cell along the equator crossing the pole with the highest Cdc42-GTP concentration, similar to kymograph construction for in vivo data. The Cdc42-GTP concentration and endocytic/exocytic events along the cell contour (y axis) were plotted as a function of time (x axis) using ImageJ.
We thank  D. Drubin ,  Y. Sun , and  R. Collins  for reagents and advice. We also thank the  McCusker lab  and  A. Royou  for discussion. Work in the McCusker lab is funded by  Seventh Framework Programme  ( FP7) Marie Curie  grant  IRG249298 ,  Agence Nationale de la Recherche  grant  2010 JCJC 1210 01 ,  Fondation pour la Recherche Medicale  (FRM; grant  INE20100518678 ),  Agence pour la Recherche sur le Cancer (ARC ; grant  PDF20120605172 ),  Centre National de la Recherche Scientifique (CNRS) ,  University of Bordeaux Segalen (UBS) , and  Conseil Régional d'Aquitaine Volet Recherche 20091301015. M. Jose ,  S. Tollis , and  D. Nair  are funded by  FRM ,  ARC ,  UBS ,  Region Aquitaine ,  CNRS , and  FP7 Marie Curie IEF Fellowships. Submitted: 19 June 2012 Accepted: 14 January 2013.
Data Complete genome sequences and annotations were downloaded from NCBI GenBank (ftp://ftp. ncbi. nih. gov, last accessed November 20, 2013; supplementary table S1, Supplementary Material online). We excluded pseudogenes and genes with internal in-frame stop codons. All the predicted operons for these organisms were downloaded from the Prokaryotic Operon DataBase (ProOpDB; http://operons. ibt. unam. mx/OperonPredictor/, last accessed November 20, 2013), which claims to be the most accurate method available  (Taboada et al. 2012). As different operon predictions may differ in a number of cases  (Brouwer et al. 2008) , we also calculated all results using the operons predicted in the Database of prOkaryotic OpeRons (DOOR) at http://csbl1. bmb. uga. edu/OperonDB (last accessed November 20, 2013;  Mao et al.
2009 ; supplementary text S1, Supplementary Material online). We analyzed Escherichia coli K-12 MG1655, 102 a-Proteobacteria, 63 b-Proteobacteria, and 124 Firmicutes. To avoid overrepresentation of highly similar organisms, those above 97% in 16SrRNA identity were clustered and the largest genome was selected for this study. We did not include Tenericutes, the basal branch of Firmicutes, in our study because their genomes are always small and evolve fast. Their inclusion would lower the accuracy of the method to detect homology and might affect our results. For the three clades, we included in our study all species with complete public annotated genome sequences for which there were whole-genome operon predictions in both databases.
Operon Gene Pairs The operon structure of a given genome was analyzed as a succession of intraoperon gene pairs (OGP). Starting from the operon prediction data of a given genome, the OGP were constructed for each pair of adjacent genes within the operon (there are [k À 1] adjacent gene pairs for a k-gene operon). For example, a set of adjacent genes ABC will be decomposed in two pairs: AB and BC. Under a null model of neutral evolution of operons, the individual OGPs are statistically independent, because disruption of the adjacency between B and C will not affect the adjacency between A and B. Deletion of B leads to exclusion of the two pairs from further analysis. We made a test to check that counting a gene twice-its two pairs-is not affecting our results under a selection model where disruption of an operon between AB might lead also to decrease selection for BC.
Analysis of Transcription Factors Information for the predicted transcription factors for each genome was downloaded from the DBD transcription factor database  (Charoensawan et al. 2013). We analyzed all organisms in our study for which there were predictions available of transcription factors: 49 a-proteobacteria, 35 b-proteobacteria, and 59 Firmicutes. We included in the analysis the nonredundant transcription factor protein families using UCLUST with a threshold of 80%  (Edgar 2010).
Phylogenetic-Independent Contrasts For each clade (plus E. coli K-12 MG1655), we built a supermatrix concatenating the aligned protein sequences of the core genome (described earlier for the persistence analysis). The phylogenetic trees of the three clades were inferred from this supermatrix by maximum likelihood algorithms using PHYML  (Guindon and Gascuel 2003)  with the model LG + À(8) and default parameters. The trees were rooted using E. coli K-12 MG1655 as an outgroup. For each variable of interest, we carried out the phylogenetic-independent contrast (PIC) analysis  (Felsenstein 1985)  using the package ape  (Paradis et al. 2004 ) for R software (R Development Core Team 2011). The analysis of contrasts showed in some clades some systematic outliers, caused by long internal branches in the tree.
Associations between General Features of Operon Organization and Genome Features We used two independent databases of operon predictions, ProOpDB and DOOR, to class pairs of adjacent genes as intraoperonic or interoperonic (see Materials and Methods). These analyses were done for 124 genomes of Firmicutes, 102 of aand 63 of b-Proteobacteria (one genome per species). The analysis of both operon databases gave concordant results and we only present in the main text the results concerning ProOpDB, which reports the highest accuracy  (Taboada et al. 2012 ; see supplementary text S1 [Supplementary Material online] for a comparison). Species in our data set are not independent statistical instances because they are related by a common evolutionary history. To correct for this effect, we retested all correlation analyses using PICs (see  Materials and Methods; Felsenstein 1985 ; supplementary tables S3 and S4, Supplementary Material online).
Acknowledgments This work was supported by the  Agencia Nacional de Promocion Cientı ´fica y Tecnica de Argentina (AGENCIA)  grant  PICT-2008-0832  to M. F. , a postdoctoral fellowship from the  Consejo Nacional de Investigaciones Cientı ´ficas y Tecnicas (CONICET)  to P. N. , the  Agencia Nacional de Investigacion e Innovacion (ANII ,  MOV_CA_2012 ) grant to H. R. , and  European Research Council  grant  EVOMOBILOME grant   281605  to E. P. C. R. M. F. is a member of  CONICET Researcher's Career. The authors are grateful to  Enrique Merino  for providing access to the database and helpful Perl scripts.
Nox4 Mediates IL-1ß-effects on MMP-1 Secretion and DNA Fragmentation in C-20/A4 Chondrocyte Cells Our previous studies showed that Nox4 is involved in MMP-1 expression in C-20/A4 human chondrocyte cells  [22]. To assess the role of Nox4 in chondrocytes, we generated a C-20/A4 chondrocyte cell line that provided a stable expression of Nox4A (Genbank No. AF254621), or Nox4B (Genbank No. AY288918) (Figure  1A ). Nox4A correspond to the commonly described wild type Nox4. Nox4B is a splice variant in which the first NADPH binding site is missing and corresponds to a non functional enzyme. It has been described as a dominant negative variant in A549 cells  [31]. Results showed a significant production of ROS by luminescence in Nox4A transfected cells compared with the cells that overexpress Nox4B (Figure  1B ).