dataesr/scientific-paragraphs-categorization huggingface dataset:
This plasmid, or one very similar to it, has been found in the 03BB87 strain  [13]. Furthermore, an operon, hasACB, located on pBCXO1 and encoding a hyaluronic acid capsule, is functional in the G9241 strain, in contrast to B. anthracis in which the hasA gene is mutated  [18, 19]. The G9241 strain is therefore able to synthesize two polysaccharide capsules  [18]. Emerging B. cereus strains have been isolated from great apes that died from an anthrax-like disease in Cameroon (CA) and Côte d'Ivoire (CI)  [20, 21, 22, 23]. These unusual strains are unlike any other isolated before and were originally designated as "Bacillus cereus variety anthracis", but were later renamed B. cereus biovar (bv) anthracis to comply with database requirements. Their genomic characterization showed that they belong to the B.
Sequence analysis For sequencing of the has operon and the atxA gene, PCR fragments were generated from genomic DNA of the CAR, CAR-P and derivative strains (S1 Table ), were processed by standard procedures  [37]  and were then sequenced with an AB3100 DNA sequencer (Applied Biosystems, Foster City, USA). Sequences were compiled and analysed with the Gap4 software (The Staden package, 1998-PMID: 10547834).
Bioluminescence imaging Cutaneous infection was performed by injecting 10 μl of spore suspension in PBS into the dermis of the right ear pinna as described previously, or by depositing 20 μl of spore suspension onto the nostril  [30]. Images were acquired with an IVIS 100 system (Xenogen) according to instructions from the manufacturer. Analysis and acquisition were performed with Living Image 2. 5 software (Xenogen). Unless otherwise noted, mice were anaesthetised with a constant flow of 2. 5% isofluorane mixed with oxygen. The XGI-8 Gas Anaesthesia System (Xenogen) was used, which enabled control of the duration of anaesthesia. Images were acquired with a binning of 16. Luminescent signals from the exterior of mice were acquired for 1 min. All other photographic parameters were kept constant.
We confirmed the presence of capsular material surrounding the CAR bacteria by India ink staining (Fig. 1A ). We isolated a spontaneous rough colony of the CAR strain (CAR-R strain) on capsule-inducing agar plates; the lack of any capsule was confirmed by India ink staining of CAR-R bacteria. Multiplex PCR analysis of this rough clone showed that pBCXO1 was lost, suggesting that the expression of the capsule in the CAR strain was linked to the presence of pBCXO1 (S1A Fig. ). We then investigated whether this capsule may be the pBCXO1-encoded hyaluronic acid capsule (has operon), as recently reported for the pathogenic B. cereus G9241 strain  [18]. DNA sequencing of the hasACB operon of the CAR strain showed that, in contrast to B. anthracis  [8] , the hasA gene is non-mutated and the deduced sequence of the HasA protein is identical to the sequences available in the databases for the CI and G9241 strains.
The HasC and HasB protein sequences were also identical to those of the CI and G9241 strains, with only one mismatch for HasB at position 209 (Ala!Thr) compared with the sequence from G9241. We examined the role of the hasACB operon in the capsule produced by the CAR strain by inactivating the hasA gene encoding the hyaluronate synthase. The resulting CAR-H(ΔhasA) strain gave rough colonies on capsule-inducing agar and showed no capsule by India ink staining, suggesting that it was unable to synthesise a capsule (Fig. 1A ). Hyaluronidase enzymatic digestion of encapsulated bacteria confirmed the hyaluronic acid nature of this has operon- encoded capsule in the CAR strain; this treatment led to a complete absence of the capsule as visualised in Fig. 1A. The CA strain, and the CI (through database sequence analysis  [24] ), thus harbour genetic determinants encoding a PDGA capsule on pBCXO2 and a HA capsule on pBCXO1.
4A  & B ). Our data thus show that HA-capsule expression in the B. cereus bv anthracis CA strain is regulated by AtxA. We consistently observed that rough mutants formed at the edges of smooth colonies after 48h of growth on capsule-inducing solid medium under 5% CO 2. We screened fifteen spontaneous rough mutants of the CAR and CAR-P strains for LF production; none produced LF. Multiplex PCR analysis showed that two mutants had lost pBCXO1. We determined the sequence of the atxA gene in the remaining thirteen non-encapsulated mutants. All thirteen strains carried mutations in the atxA gene (Table  5  and S3   Fig. ). Two mutants carried one base change leading to an amino acid substitution: either Ser to Pro (CAR2) or Pro to Thr (CAR4). These two mutations were located in the winged helix-turn-helix WH region in the N-terminal part of AtxA  [49, 50].
Acknowledgments We thank the Ivorian authorities for long-term support, especially the Ministry of the Environment and Forests as well as the  Ministry of Research , the directorship of the  Taï National Park , the  Laboratoire National d'Appui au Développement Agricole (LANADA)  and  Laboratoire Central de Pathologie Animale (LCPA), Bingerville, Côte d'Ivoire  and the  Swiss Research Center in Abidjan. From Cameroon , we thank the  MINFoF, MINRESI , the  Service de la Conservation de la Réserve du Dja  and various organisations, especially " Last Great Ape ", the " Limbe Wildlife Center " and " Projet Grand Singe " as well as the  John Hopkins University, Bloomberg School of Public Health, Department of Epidemiology, Cameroon Project. We warmly thank  Sylviane Derzelle  and  Guillaume Girault  for access to the Anses' B.
Due to the high variability of the N-terminal domain, it is often excluded from phylogenetic analysis  11  , and rather the C-terminal of the protein comprising the zinc-finger domains (generally starting from amino acid 120) is more suitable. Snail family members all possess at least four zinc-finger domains (Znf II-V), and often a fifth zinc-finger domain (Znf I) is found N-terminally to Znf II. The four zinc-finger domains at the C-terminus are reported as essential for DNA binding and also comprise a nuclear localisation signal  22, 25. In order to carefully group snail family proteins, we constructed a tree based on 69 snail super-family proteins comprising 49 snail and 20 scratch proteins (Fig. 2A ) using the alignment of the region that covers the five zinc-finger domains (see supplementary dataset 2,3 for accession numbers and sequence alignment).
The first zinc-finger of NvSNAILB (orange) is weakly recognized (E-value 0. 25; see supplementary dataset 4 for SMART predictions). This analysis shows that the number of zinc fingers among snail proteins is variable across species and indicates multiple duplication events, zinc-finger domain loss and gene loss. Phylogenetic analysis. C2H2 zinc-finger domains where predicted using the Simple Modular Architecture Research; Multiple sequence alignment was performed with Muscle 3. 8. 31 software 58 and were subsequently manually improved (in MacVector 11. 0. 2). Handling of the multiple sequence alignment was done using jalview 2. 7 software59. Tree reconstruction was performed with MR. BAYES3  60  , the consensus tree shown was based on 2,000,000 generations. Trichoplax adhaerens (Ta) SNAIL (XP_002108251) has been raced out from Trichoplax adhaerens coding DNA for this study (see primer sequences in supplementary information).
Once fluorescence was apparent in the fertilized embryos live images were taken. As shown in Fig. 6 , the full length NvSNAILA fused to the fluorescent protein mCherry specifically localizes into the nucleus and exhibits enrichment in regions with a similar size and shape that are excluded in embryos stained with Hoechst, a DNA marker that is excluded from nucleoli  36  (Fig. 6A , inset). NvSNAILB fused to the fluorescent protein mCherry also specifically localizes to the nucleus, but with reduced levels in nucleoli-like regions compared to NvSNAILA (Fig. 6B ). The cellular distribution of NvSNAILA-Δ Znf , NvSNAILB-Δ Znf fused to mVenus was also similar as observed in HeLa cells, exhibiting a marked increase in cytoplasmic levels as well as a marked reduction in nucleoli (Fig. 6C, D ). We also injected NvSNAILA-Δ 5SNAG and Δ 20pNLS mutants fused to mVenus, which also specifically localized into the nucleus and in a subset of nuclei exhibited reduced but more variable fluorescence distribution with respect to the nucleoli (data not shown).
Methods Plasmids used for HeLa cells analysis. cDNA for Nematostella vectensis SNAILA and B as well as the respective truncated variants were RT-PCR-amplified from Nematostella vectensis and cloned in pmTurquoise2, psYFP2, pmCherry (clontech-like) vectors providing a C-terminal mTurquoise2  28  , sYFP2 and mCherry tag. cDNA for human (Hs) SNAIL1 and 2 were RT-PCR-amplified from HeLa cells and cloned in pmTurquoise2 N1 (clontech-like) vectors providing a C-terminal mTurquoise2 tag. Coding DNA for human FIBRILLARIN (HsFIB) was PCR-amplified from HeLa cells cDNA and cloned in psYFP2 C1 (clontech-like) vector providing an N-terminal sYFP2 tag. See supplementary dataset 1 all primer sequences. A plasmid pmCherry (clontech-like) vector was used for quantification analysis. Hybrid genes were obtained by PCR-driven overlap extension as previously described  51  , and cloned in pmTurquoise2 N1 (clontech-like) vector providing an C-terminal mTurquoise2 tag.
The photon arrival times were recorded by a Picoharp 300 time-correlated single-photon counting system (Picoquant). Samples were measured at room temperature (21 °C). The photon arrival times were recorded during 120 seconds by the SymPhoTime 5. 23 (Picoquant) software. The size and shape of the observation volume was determined from FCS calibration measurements using purified mTurquoise2 in PBS as previously outlined  56  , and the estimated volume structure parameter was 8. The diffusion time of the fusion proteins was analysed in FFS Data Processor 2. 3 software (SSTC). Sections of raw data, lacking significant photobleaching and aggregation spikes, were autocorrelated and analysed using a one-component 3D diffusion model with correction for triplet/blinking kinetics  56   were D denotes the diffusion coefficient found for a free diffusing FP and is equal to 90 μ m 2 /s 57.
Acknowledgments We thank  Mark Q. Martindale  for laboratory and scientific support. This research was supported by the  Netherlands Research Organization  ( NWO-ALW VIDI 864. 09. 015MP  and AAD), by individual short-term fellowships received by  A. A. D  ( ASTF184-2011 ) and T. Q. D. ( ASTF509-2012 ) from the  European Molecular Biology Organization (EMBO)  and Middelgroot investment grants ( 834. 09. 003  and  834. 07. 003 ).
The labeling was revealed in brown by the chromogen 3,3'-diaminobenzidine (DAB) and the sections were counterstained with Mayer's hematoxylin. Two methods of negative control were performed: the first one was by omitting the primary antibody to test the secondary antibody's specificity. The second one consisted in testing primary antibody's specificity by saturation with a homologous antigen; the b-endorphin antibody was pre-absorbed with an excess of rat b-endorphin recombinant protein (E1142, Sigma-Aldrich) at 37°C for 1 h. Morphometry and labeling quantification. The diameter of seminiferous tubules was measured by photonic microscopy (Zeiss, Jena, Germany) at objective magnification ×40, with a number of 20 seminiferous tubules per section per slide for each animal. A quantitative study of immunoreactivity was carried out using Fiji Win 32, a distribution of Image J software (NIH, Bethesda, USA) that measures the average darkness of the image due to DAB signal.
Genechip and data analysis from neurospheres Total RNA extracted from transduced cells was tested on disposable RNA chips (Agilent RNA 6000 Nano LabChip kit) to determine the concentration and purity/integrity of RNA samples using Agilent 2100 bioanalyser. cDNA synthesis, biotin-labeled target synthesis, hybridization to HG-U133 plus 2. 0 GeneChip (Affymetrix) arrays, staining and scanning were performed according to the standard protocol supplied by Affymetrix. For each probe set on each array, a detection call of Present, Absent or Marginal was made. Detection calls were made using the affy R/Bioconductor package  [33]. Background corrected raw data were Log2-transformed and quantilenormalized following the Robust Multichip Average (RMA) procedure using R (Bioconductor)  [34]. Differentially expressed genes were obtained with limma package  [35] , performing pairwise comparison between the mock and vector transduced hmNPCs and picking up probe sets showing a present call and a fold change > ± 1.
5. A moderated t-test was performed between transduced and untreated groups selecting probe sets with a p-value 0. 05. The data set containing the Affymetrix probe identifiers, selected as differentially expressed in transduced hmNPCs, and the corresponding fold changes, were uploaded into g:Profiler (updated version 23/7/2013). gGOSt Gene Group Functional Profiling was set with the following parameters: i) significant only, ii) hierarchical sorting, and iii) as specified in the results section either no filtering or hierarchical filtering best per parent group (strong). Heat maps of differentially expressed genes and belonging to selected enriched functions were constructed by using Excel 2007 (Microsoft Office package). Genes were categorized based on the annotations on g:Profiler  [36].
Sample normalization was carried out on the basis of GAPDH expression (Applied Biosystems, TaqMan Gene Expression Assay, batch IDs Hs99999905_m1). GAPDH was unchanged in transduced as compared to mock samples. Reactions were performed using the Applied Biosystems PRISM 7300 Real Time PCR System. To obtain relative quantification with respect to the undifferentiated mock cells, quantification cycle values (Cq,  [37] ) were exported directly into an EXCEL worksheet for analysis, and the data were calculated with the 2 -ΔΔCq method  [38].
Transcriptome analysis of HD-CAV-2 transduced neurospheres To characterize the toxicogenomic signature and the biological properties of HD-CAV-2-neural cells interaction, human differentiated neurospheres, derived from the BNA hmNPC batch, were incubated with the vector at an MOI of 1000 vg/cell. RNA was extracted at 2 h and 5 days postincubation to analyze both early and mid-late events following vector effects. RNA was tested on HG-U133 plus 2. 0 Affymetrix genechips, which included greater than 47,000 transcripts. Mas5. 0 and RMA were used for raw data elaboration, R Bioconductor limma package was then applied for statistical evaluation of modified genes. Three independently transduced and mock samples, at the two time points, were tested. A p-value 0. 05 and a fold change > ±1. 5 were used as threshold values (Fig  2A ).
These parameters were chosen to identify statistically significant variations (p-value 0. 05), and include small effects (fold change > ±1. 5), that could be relevant to define the "full" picture of the potential molecular toxicity of HD-CAV-2 on human cells. The global impact of the vector was limited, indicating modest potential toxicity at this MOI. But a significant response was detected at 5 days postincubation ( To interpret the biological significance of global gene modulation, the full list of probes modulated by HD-CAV-2 was uploaded into the bioinformatic online software g:Profiler. By g: GOSt filtering we identified groups including biological processes, cellular components and molecular functions  (Fig 3 and S1 Table). Among the biological processes in silico analysis identified cell cycle, mitosis, DNA damage, microtubule and centromere-related processes.
Comparative analyses of the response to HD-CAV-2 of 2D and 3D cultures Transcriptome data related to the effect of LV and of HD-CAV-2 in 2D cultures of human neurons  [22]  (raw data are available at the GEO site http://www. ncbi. nlm. nih. gov/geo/query/acc. cgi?acc=GSE47130) was used to compare the 2D and neurosphere responses to HD-CAV-2. We found that 46 probes were modulated both in the 2D and 3D conditions (Fig  5 ). These results obtained in different cell batches (BNA and 3821 for 2D and BNA for 3D samples) and two different culture conditions (2D and 3D) strengthened the reliability of the analyses reported on Fig  2 , and allowed us to identify the transcriptome alterations specifically related to human neural cells transduced by HD-CAV-2. The g:GOSt analysis of the 46 probes commonly modulated by HD-CAV-2 in the 2D and 3D neurospheres, highlighted cell cycle, DNA metabolism, the centromeric pathway, and the microtubule related processes as being the stringent transcriptional signature of HD-CAV-2 transduction.
Acknowledgments This work was supported by  EU   FP7 grants BrainCAV  (n. 222992) and BrainVectors (n. 286071) and by  PTD/EBBBIO/119243/2010 , funded by Fundacao para a Ciencia eTecnologia (FCT), Portugal. DS was the recipient of a PhD fellowship from  FCT ,  Portugal  ( SFRH/BD/ 78308/2011 ).
This work was supported by  EU   FP7 grants BrainCAV  (n. 222992) and BrainVectors (n. 286071) and by  PTD/EBBBIO/119243/2010 , funded by Fundacao para a Ciencia eTecnologia (FCT), Portugal. DS was the recipient of a PhD fellowship from  FCT ,  Portugal  ( SFRH/BD/78308/2011 ).
The entire microarray data set was submitted to the Gene Expression Omnibus repository with the accession number GSE62687 (http://www. ncbi. nlm. nih. gov/geo/query/ acc. cgi?acc=GSE62687). Comparative analyses were performed on data reported here and data submitted to the Gene Expression Omnibus repository with the accession number GSE47130 applying the same statistical approach described above. All relevant data are within the paper and its Supporting Information files.
RNA extraction and real-time quantitative RT-PCR Thirty milligrams of seeds (three biological replicates) were ground in liquid nitrogen and total RNA was extracted by a hot phenol procedure according to  Verwoerd et al. (1989). Reverse transcription was performed with 1 µg total RNA as described by  Leymarie et al. (2012). The relative expressions were calculated according to  Hellemans et al. (2007)  with two reference genes, Ubiquitin 5 and AT4G12590, and expressed in arbitrary units with a value of 100 to the dry dormant seeds after harvest, which was used as control sample for normalization  (Pfaffl, 2001). Primer sequences are presented in Supplementary Table  S1  (available at JXB online). The statistical analysis was performed with StatBox 6. 40 software (Grimmer logiciels, France).
Patients and treatment Adult patients with resected pancreatic adenocarcinoma (R0: resection for cure or R1: microscopic residual tumor) were included from 31 French clinical centers in this study. Main noninclusion criteria were metastatic or locally advanced disease, presence of infectious syndrome, and previous chemotherapy (within the ten years before inclusion). All patients were eligible for adjuvant gemcitabine-monotherapy as follows: 30-minutes IV-infusion of 1000 mg/m 2 every week for 3 consecutive weeks followed by one week off for 6 courses. Demographic (e. g age, sex weight, body surface area), clinical (e. g. tumor size, localization, and tumor classification using TNM, disease grade, World Health Organization (WHO) status, resection margin) and biological data (e. g. data about liver, renal and cardiac functions, whole blood count) were collected prior and during treatment.
1%, formic acid) as aqueous phase and an organic phase composed of acetonitrile. A 5 μl-volume sample was injected and eluted with a gradient of aqueous and organic phases at a constant flow rate of 0. 250 ml/min for a total run time of 6 minutes. A Waters tandem quadrupole detection system with an electrospray ionization (ESI) source operating in positive mode for gemcitabine and ABC and negative mode for dFdU was used to obtain mass and product ion spectra The resulting pharmacokinetics data were analyzed using pharmacokinetics software Kine-ticPro (WGroup, France). Bayesian estimation was used to estimate individual pharmacokinetics parameters and to simulate plasma exposure of patients, based on previously published pharmacokinetic parameters  [20].
Statistical analysis The main objective of the trial was to evaluate the capability of CDA to predict the occurrence of early severe hematological toxicity upon gemcitabine. In order to bring out a positive likelihood ratio of CDA more than 3. 5 (H 1 ), objective reached when sensitivity is more than 70% and specificity is more than 80% with an α risk of 5% and a power of 80%, 107 patients had to be included. With an estimated 10% of lost-to-follow-up patients or patients not treated, 120 patients were finally included. The probability of severe hematological toxicity without CDA knowledge was estimated at 12. 5%, based on retrospective published data  [8]. Primary criterion, safety secondary endpoints (i. e. , overall toxicities and non-hematological ones) and exploratory analyses were done on the set of patients receiving at least one dose of gemcitabine and with a CDA fully evaluable status.
The activity of the genes in the figure is measured by fusion of their promoters to a gfp reporter gene on a low-copy plasmid. Genes are shown in grey or green and their promoter regions in red. As illustrated in Fig. 2 , and explained in more detail in the Methods and materials and Text S3, the primary absorbance and fluorescence signals can be transformed into promoter activities using kinetic models of gene expression. More precisely, the reporter gene data can be used to deduce protein synthesis rates  [23, 25]. Under certain conditions, the latter are proportional to mRNA concentrations and promoter activities, and thus reflect the transcriptional activity of the gene (Text S2). Following established terminology, we will refer to the measured protein synthesis rates as promoter activities, or more generally, activities of genes.
A region is colored red if none of the returned sign patterns is consistent with the data only. Two examples of inconsistent sign patterns are shown. Note that, for every combination of half-lives, the analysis of the pooled data (results reported as "Intersection") is generally more constraining than the pooling of the results from individual analyses: The expected pattern may be consistent (yellow) with all individual datasets but not minimal (green) for any of them, and turn out to be consistent and minimal (green) when all datasets are analyzed at once (see also Text S5). doi:10. 1371/journal. pcbi. 1004028. g011 that using the promoter activity of flgM for the fitting of the same quantity may render the regression problem degenerate. Still, these results raise a more general question: When is it important to take into account protein half-lives and global physiological effects? To answer this question we performed an in-silico analysis where the regulation model of Eqs.
For instance, Gerosa et al. have developed quantitative models to dissect global and specific regulation of E. coli genes involved in arginine biosynthesis  [18]. To our knowledge, however, the work presented here is the first systematic study of how the integration of information on both global physiological effects and protein concentrations can improve the inference of regulatory interactions and the identification of regulation functions from time-series gene expression data. It is important to emphasize that the proposed approach is orthogonal to existing inference methods and that the models and analysis procedures proposed in this study can be directly combined with many of the methods described in the literature  [1, [3] [4] [5] [6] [7]. The models and analysis procedures we have used are explicitly detailed and can be easily integrated into available methods, as illustrated for the MATLAB implementation of the minimal sign pattern algorithm  [42].