dataesr/scientific-paragraphs-categorization huggingface dataset:
The training sets of genes used to first construct the recognition profiles for s F , s E , s G and s K were highlighted in yellow. For each promoter the score was obtained as defined in materials and methods. Using the same profiles, we searched the intergenic regions (positions (2100 +10) relative to start codons) of six closely related Clostridium species, C. saccharolyticum, C. thermocellum, C. tetani, C. cellulolyticum, C. ljungdahlii, C. kluyveri. We also analyzed the B. subtilis promoters using the DBTBS database  [96]. The absence of an orthologous gene is indicated by 0. When an orthologous gene is present the score and the locus-tag are indicated. (PDF) Table  S9  Complementation of the mutants inactivated for the sigma factors of sporulation. qRT-PCR experiments were performed on two different RNA preparations for each mutant and each complemented strain.
PCR Primer Design Primers Probio_Uni/Probio_Rev (Table  1 ) were assessed for specificity using the ARB software package  [25]  and the SILVA 108 SSU Reference 16S rRNA gene database release  [26]. In order to validate the designed primers, we used an in silico approach based on BLASTN matches with corresponding 16S rRNA gene sequences from various bacteria that are commonly found in the gut as well as those that are not expected in this environment, which provided allowed us to evaluate if these primers may also be used to examine the biodiversity of different microbial ecosystems. In order to increase the number of microbial taxa recognized by the primers designed in this study we introduced a certain level of nucleotide degeneracy.
Se-quencing of the amplicon libraries was carried out on a 314 chip using the Ion Torrent PGM system and employing the Ion Sequencing 200 kit (Life Technologies) according to the supplier's instructions. After sequencing, the individual sequence reads were filtered by the PGM software to remove low quality and polyclonal sequences. Sequences matching the PGM 39 adaptor were also automatically trimmed. All PGM quality-approved, trimmed and filtered data were exported as sff files.
Sequence-based Microbiota Analysis The sff files were processed using QIIME  [29]. Quality control retained sequences with a length between 150 and 200 bp, mean sequence quality score. 25, with truncation of a sequence at the first base if a low quality rolling 10 bp window was found. Presence of homopolymers. 6 bp, and sequences with mismatched primers were omitted. In order to calculate downstream diversity measures (alpha and beta diversity indices, Unifrac analysis), 16S rRNA Operational Taxonomic Units (OTUs) were defined at $97% sequence homology. All reads were classified to the lowest possible taxonomic rank using QIIME and a reference dataset from the Ribosomal Database Project  [30]. OTUs were assigned using uclust  [31]. The hierarchical clustering based on population profiles of most common and abundant taxa was performed using UPGMA clustering (Unweighted Pair Group Method with Arithmetic mean, also known as average linkage) on the distance matrix of OTU abundance.
Compared to other primer pairs mentioned above, the Probio_Uni/Probio_Rev primer pair perfectly matches with a higher number of human gut microbiota components as detected by an in silico analysis against Ribosomal Database Project's (RDP) sequences. As displayed in Figure  1 , the Probio_Uni/Probio_Rev primer pair theoretically targets all 16S rRNA gene sequences of the gut microbiota bacterial orders we selected with an average similarity of 94. 4% and generating Figure  1. Heat map showing the order classification rates for optimal choice of primers. Cells are colored on a gradient from 0% to 100% matches of the primer with the 16S rRNA gene target sequences of the indicated microbial order. The size of the amplicons generated by the various primer pairs are indicated. Furthermore, the percentage of the amplification rate from each primer pair on the various microbial taxa here described is indicated at the top of the heat map.
As previously shown, the evaluation of the abundance of members of the gut microbiota based on 16S rRNA gene profiling might be influenced by the copy number of 16S rRNA gene sequences  [40]. Thus, we decided to normalize the number of reads linked to microbial taxon for the copy number of 16S rRNA gene loci present in their genome sequences (Table  2  and Figure  S1 ). The detected difference, expressed in log units, between the number of microorganisms added and the number of sequences, either normalized for the copy number of 16S rRNA gene loci or not normalized, was calculated for each microorganism. The Bray-Curtis dissimilarity indexes were then calculated between the experimental data obtained for each bacterial mix (P1, P2 and P3) and the true levels of added microbes present in these mixes.
The decrease in the rate of phylotype detection and the plateauing of various diversity indices for this set of PCR primers demonstrated that a large part of the diversity in these libraries had been detected, even though a higher number of phylotypes was identified for the primer pair Probio_Uni/Probio_Rev as compared to the other PCR primer sets (Fig. 3 ). The significance test in UniFrac  [44]  reported P-Values (Bonferroni corrected) equal to 1e-02 for every pair of samples of both mother and infant sets, meaning that the results are highly significant (if P-values #0. 05 are considered to be statistical significant). This method was used to evaluate if the cluster distribution of the sequences achieved with the different PCR primers differs from random expectations. Principal Coordinate Analysis (PCoA), applied using the UniFrac program, showed that, while the datasets obtained with the P1/P2 and Probio_uni/ Probio_rev primer pairs cluster together, the dataset achieved with the 520F/802R primer pair is rather different (Fig.
3 ). This suggests that the microbial composition assessed by this latter primer set is different than those detected by either P1/P2 or Probio_uni/Probio_rev. Clustering of de-noised high quality reads generated 18,910 and 2,361 OTUs for the mother and infant samples, respectively. As expected the microbial composition of the two fecal samples displayed a much simpler OTU organization in the infant stool sample as compared to that of the mother. At genus level, sequencing reads could be assigned to 83 main individual taxons, of which 30 were present in all the three PCR-primer dataset in at least one of the two samples (Fig. 4 ). Furthermore, we analyzed the similarities and differences in the composition of the fecal sample assayed using the three PCR primer sets by hierarchical clustering based on population profiles of the most common and abundant taxa (Fig.
The authors thank  GenProbio srl for the financial support of the Laboratory of Probiogenomics. This work was financially supported by  Fondazione Cariparma  to MV and by a  FEMS  Advanced Fellowship 2011 and an  IRCSET Embark postdoctoral fellowship  to FT. This work was also financially supported by a Ph. D. fellowship (Spinner 2013,  Regione Emilia Romagna)  to  S. D. DvS  is a member of The Alimentary Pharmabiotic Centre, which is a  Centre for Science and Technology (CSET)  funded by the  Science Foundation Ireland (SFI) , through the  Irish Government's National Development Plan  (Grant no. 02/CE/B124  and  07/CE/ B1368 ). The authors also acknowledge the support of the  Spanish Plan Nacional de I+D  (grant  AGL2010-14952 ). Arancha Hevia  was the recipient of an  FPI grant , and  Borja Sa  ´nchez was the recipient of a Juan de la Cierva postdoctoral contract.
Acknowledgements MB and AJC are supported by the  CNRS  ( Centre National de la Recherche Scientifique ) and the  ANR (Agence Nationale de la Recherche : grants  BLAN08-1_329396  and  ANR-10-PDOC-019-01 ). KJB is supported by a  BBSRC  studentship, and KJB and BFL are supported by the  Wellcome Trust.
The results were analyzed with SOS2. 1 software (Applied Biosystems). Expression of the genes was calculated from the accurate threshold cycle (Ct), which is the PCR cycle at which an increase in fluorescence from SYBR Green probes above the baseline signal can first be detected. The Ct values for GAPDH were compared with those from Mi-2, HARS, DNA-PKcs, U1-70, TLR3 and TLR7, and in each well to calculate ΔCt. Data of the treated conditions were expressed relative to the signal obtained for the average of the untreated controls by the ΔΔCt calculation. The triplicate ΔΔCt values for each sample were averaged.
Strain increases the expression of characteristic proteins involved in the response to mechanical stretch in C2C12 myoblasts We next evaluated whether straining C2C12 myoblasts in vitro can induce the up-regulation of the characteristic key molecules that have been linked to the mechanical-stretch pathway. For that, C2C12 cells were stretched during 2 days using the 10%, 0. 25Hz protocol and protein extracts were then analyzed by Western blots to evaluate the levels of calmodulin, nNOS, MMP-2, HGF and c-Met proteins. Results demonstrated that mechanical-stretch induces a significant elevation of calmodulin, nNOS, MMP-2, HGF and c-Met protein levels by a factor of, respectively, 2. 4-, 1. 6-, 1. 5-, 1. 9-, and 1. 5-fold, relative to their levels in unstretched cells (Figure  2 ). Of notes, our results did not show substantial difference in the levels of these proteins as compare to unstretched controls when mechanical strain was apply during 4 days (data not shown).
LAE sequence identification and alignment The genomic sequences homologous to the D. melanogaster LAE were recovered by Blat analysis at the UCSC Genome Browser website (http://genome. ucsc. edu/cgi-bin/hgBlat?command = start) and aligned with MAFFT (http://mafft. cbrc. jp/alignment/server/). The multiple alignment was then shaded with Boxshade (http:// www. ch. embnet. org/software/BOX_form. html).
Immunofluorescence and image quantification Third-instar larval imaginal discs were prepared and stained using standard procedures. Confocal analyses were done with a LEICA TCS SP5 microscope. Rat anti-Bab2  [17]  and rabbit anti-Dll  [50]  antibodies were used at 1/2000 and 1/200, respectively. For each reporter construct, GFP fluorescence quantification was obtained from 10 distinct T2 leg and eye-antennal discs (i) dissected from late third-instar larvae grown in the same environmental conditions (temperature and larval density), and then (ii) fixed in the same conditions. Confocal images were analyzed with ImageJ software, using the same area (centered on the distalmost ring of cells), laser excitation settings (75% maximal detection) and brightness/contrast image acquisition.
Acknowledgments We thank  T. Kojima ,  G. Campbell ,  G. Boekhoff-Falk ,  S. Cohen ,  N. Gompel ,  T. M. Williams ,  S. Carroll ,  P. Couso ,  M. Suzanne ,  A. Vincent ,  F. Laski  and the  Bloomington Stock Center  for fly stocks and reagents, and the  Developmental Studies Hybridoma Bank (DSHB)  at the  University of Iowa  for antibodies. We are grateful to  A. Vincent ,  S. Plaza ,  M. Crozatier  and  C. Immarigeon  for discussions and helpful suggestions on the manuscript or during the course of this work. We thank  S. Bernat-Fabre  and  J. Favier  for technical assistance, as well as  C. Faucher  and  O. Bardot  for their contributions to this project. Lastly, we acknowledge the Toulouse RIO Imaging platform.
Data Integration To investigate the correlations between the transcriptome and metabolome data, the two datasets were plotted on a single graph using the visualization tool developed by Enjalbert et al. [26]. A time series of maps representing changes in metabolites and transcripts related to central carbon metabolism was generated to analyze the fine tuning of molecular events that occurred during the glucose-acetate transition (Figure  5A ). As expected, these representations emphasized the metabolic quasi-steady-state during the exponential growth on glucose, since very few modifications were observed during this phase. The few noticeable changes concerned the metabolome, especially in the TCA cycle. After GE, drastic changes occurred at both the metabolome and transcriptome levels, indicating fast and profound molecular adaptation to the new environmental conditions.
In conclusion, the present work emphasized the rapid massive reshuffling of both gene expression and metabolism just after glucose exhaustion. Detailed information is provided regarding the order, time and extent of the molecular and physiological events that occur during the glucose-acetate transition in E. coli, which will be of particular interest in the development of dynamic models of metabolism. The datasets generated in this study are available to the scientific community on the MIAME-compliant EBI database  [34]. They are of particular interest in light of recent progress toward comprehensive understanding of metabolism dynamics  [8, 15].
RT-PCR Analysis Gene expression of selected genes was also monitored by RT-PCR using the same three independent triplicates. A volume equivalent to 2 mg of cell dry weight was harvested by centrifugation (1 min, 13,000 × g) and flash frozen in liquid nitrogen. Total RNA extractions were performed using a Qiagen RNeasy Midi extraction kit. Samples were treated with DNase to eliminate genomic DNA; the samples were subjected to a reverse transcription using the Super Script II Reverse transcriptase (Life Technology). RT-PCR was performed using the SYBR-Green based detection protocol (Life Technology), with an ICycler realtime PCR detection system (Bio-Rad) and using "MyIQ" software (Bio-Rad). Primers (Table  1 ) were designed with "primer3" online freeware  [36]. Data were normalized versus two controls (16S and ihfB genes) and versus the mid-exponential phase level of expression.
Conclusions Knowledge of the molecular mechanisms underlying metabolic adaptations in E. coli is still sparse. The regulation, sequence and timing of the events underlying these phases are still poorly understood, as datasets describing the fine timing of metabolic transitions are still rare, even for a classical workhorse like E. coli. The main reason for this knowledge gap is the complexity of the regulatory network that controls metabolism, with interwoven genetic and metabolic regulations  [8, 26, 37] ; hence the need to combine several omics approaches to address this complexity  [38]. Here, we demonstrated the value of multi-omic approaches to further our understanding of metabolic adaptation. Due to the complexity of metabolism and its many layered regulation, this work focused on central carbon metabolism as the first target, but the approach now needs to be extended to the entire metabolic network to get the full picture of adaptation mechanisms.
Acknowledgments This work was supported by the  French Agence Nationale de la Recherche  ( ANR, Project  n  ANR-06-BYOS-0003-03 ) from which B. E. received a post-doctoral fellowship. The metabolome data were collected using the MS and NMR MetaToul equipment [39] at the  Toulouse Metabolomics and Fluxomics facilities. Continuous support from the  Institut National de la Recherche Agronomique (Department "Microbiology of the Food Chain") , the  Région Midi-Pyrénées , the  Ministère de l'Education Nationale et de la Recherche , the  European Regional Development Fund (ERDF)  and SICOVAL is gratefully acknowledged.
v. most often as a standalone therapeutic intervention, in subjects bearing hepatocellular carcinoma (NCT01171651; NCT01387555; NCT01636284), CRC (NCT01380600, NCT01394939; NCT01469611) or chemorefractory solid tumors (NCT00625456; NCT01169584). The highly attenuated oncolytic vaccinia virus GL-ONC1 (developed by Genelux, also known as GLV-1h68)  187  is being tested in combination with chemoradiotherapy for the treatment of HNC patients (NCT01584284), as a standalone therapeutic intervention administered intrapleurally in lung cancer patients (NCT01766739), and upon intravenous or intraperitoneal delivery in subjects affected by advanced solid tumors or peritoneal carcinomatosis, respectively (NCT00794131; NCT01443260). In addition, clinical trials are currently ongoing for investigating the safety and antineoplastic activity of: (1) talimogene laherparepvec,  62  administered i.
t. -as a standalone intervention or combined with systemic ipilimumab  188, 189  -to melanoma patients (NCT00769704; NCT01368276; NCT01740297); (2) naturally occurring coxsackievirus A21 (developed by Viralytics as Cavatak™),  190  administered i. t. as a single agent to melanoma patients (NCT01227551; NCT01636882); (3) CGTG-102 (an oncolytic adenovirus engineered to drive the local expression of GM-GSF, developed by Oncos),  191  administered i. t. or i. v. -alone or in combination with metronomic cyclophosphamide-to patients affected by advanced solid tumors (NCT01437280; NCT01598129); (4) DNX-2401 (a genetically manipulated replication-competent adenovirus developed by DNAtrix),  192, 193  given i. t. as a standalone agent to glioblastoma and glioma patients (NCT00805376; NCT01582516); (5) HSV1716 (a γ34.
5-deficient variant of HSV developed by Virttu as Seprehvir ® ),  169  administered intrapleurally or intratumorally to individuals affected by mesothelioma or solid tumors (NCT01721018; NCT00931931); (6) Toca511 ® (a retrovirus engineered to express cytosine deaminase, developed by Tocagen), given alone or in combination with 5-fluorocytosine to subjects affected by astrocytoma, glioblastoma, oligoastrocytoma and oligodendrocytoma (NCT01156584; NCT01470794); (7) the Seneca Valley virus (a replication-competent oncolytic picornavirus also known as NTX-010),  194  administered i. v. as a single agent or combined with metronomic cyclophosphamide to patients with lung cancer or neuroendocrine tumors, respectively (NCT01017601; NCT01048892); (  8 ) PVSRIPO (an nonpathogenic recombinant poliovirus),  195  given i.
t. as a standalone intervention to glioblastoma patients (NCT01491893); (  9 ) the attenuated measles virus commonly used as a prophylactic vaccine,  75, 196  given intrapleurally as a single therapeutic agent to mesothelioma patients (NCT01503177); (10) CG0070 (a conditionally replicating GM-CSF-armed oncolytic adenovirus),  61, 197  instilled intravesically as a single agent to subjects with bladder carcinoma (NCT01438112); (  11 ) HF10 (a spontaneous attenuated variant of HSV1),  198, 199  administered i. t. as a standalone intervention to individuals affected by refractory HNC or other solid tumors (NCT01017185); (12) an attenuated lentogenic isolate of the Newcastle disease virus (known as NDV-HUJ),  174, 200  given i. v. as a single agent to glioblastoma, neuroblastoma and sarcoma adenoviral strains, most often lacking the genes coding for E3 or the anti-apoptotic protein E1B55K,  43  have already been used in patients affected by glioma,  140  sarcoma,  141  head and neck cancer (HNC),  97, [142] [143] [144] [145]  pancreatic cancer,  146, 147  colorectal carcinoma (CRC),  [147] [148] [149]  prostate carcinoma,  [150] [151] [152]  ovarian cancer,  153, 154  bladder carcinoma  61  and multiple solid tumors.
One third (17) of these studies are investigating the activity of a wild-type reovirus (serotype 3 Dearing, developed by Oncolytics Biotech under the name of Reolysin ® )  186  administered i. v. or (rarely) i. p. , often in combination with conventional therapeutic regimens, to patients affected by multiple myeloma (NCT01533194), HNC (NCT00753038; NCT01166542), breast carcinoma (NCT01656538), melanoma (NCT00651157; NCT00984464), lung cancer (NCT00861627; NCT00998192; NCT01708993), pancreatic carcinoma (NCT00998322; NCT01280058), CRC (NCT01274624; NCT01622543), prostate cancer (NCT01619813), reproductive tract neoplasms (NCT00602277; NCT01199263) or pediatric solid tumors (NCT01240538). Eight clinical trials are assessing the safety a single agent to subjects affected by hepatocellular carcinoma (NCT01628640).
The large majority of these studies are Phase I/II clinical trials, with the notable exceptions of NCT01438112 (assessing the antineoplastic activity of CG0070 in bladder carcinoma patients), NCT01166542 (evaluating the efficacy of Reolysin ® in HNC patients) as well as NCT00769704 and patients (NCT01174537); (13) parvovirus H1 (a naturally occurring parvoviral variant developed by Oryx Verwaltungs as ParvOryx ® ),  177, 201  administered i. v. or i. t. as a standalone therapeutic intervention to glioblastoma patients (NCT01301430); and (  14 ) a variant of the vesicular stomatitis virus engineered to drive the expression of interferon β (IFNβ),  202, 203  given i. t. as.
Concluding Remarks During the last two decades, great efforts have been dedicated at the development of viruses that would selectively and efficiently kill malignant cells while sparing their normal counterparts. Accumulating clinical evidence indicates that oncolytic virotherapy is generally well tolerated and, at least under specific circumstances, exerts durable antineoplastic effects. Importantly, although some degree of immunosuppression initially favors NCT01368276 (both investigating the antineoplastic potential of talimogene laherparepvec in melanoma patients). Of note, Amgen representatives have very recently declared that NCT00769704 met its primary endpoint of durable response rate, defined as the rate of complete or partial response lasting continuously for at least six months (source www.
Acknowledgments Authors are supported by the  Ligue Nationale contre le Cancer (équipe labellisée) ,  Agence Nationale de la Recherche ,  AXA Chair for Longevity Research, Association pour la Recherche sur le Cancer ,  Cancéropôle Ile-de-France ,  Institut National du Cancer (INCa) ,  Fondation Bettencourt-Schueller ,  Fondation de France ,  Fondation pour la Recherche Médicale , the  European Commission (ArtForce) , the  European Research Council , the  LabEx Immuno-Oncology , the  SIRIC Stratified Oncology Cell DNA Repair and Tumor Immune Elimination (Socrate) , the  Cancer Research and Personalized Medicine (Carpem)  consortium, and the  Paris Alliance of Cancer Research Institutes (Pacri).
v. As single agent NCT00794131 HF10 HNC Solid tumors I recruiting i. t. As single agent NCT01017185 Mesothelioma I/II recruiting Intrapleural As single agent NCT01721018 HSv1716 Non-CNS solid tumors I recruiting i. t. As single agent NCT00931931 HCC II recruiting i. v. n. a. As single agent Combined with BSC NCT01636284 NCT01387555 Active not recruiting i. v. and i. t. Followed by sorafenib NCT01171651 JX594 CrC I Active not recruiting recruiting i. v. i. v. As single agent As single agent NCT01380600 NCT01469611 I/II recruiting i. v. and i. t. Combined with irinotecan NCT01394939 Solid tumors I Active not recruiting i. t. i. v. As single agent As single agent NCT01169584 NCT00625456 Measles virus Mesothelioma I recruiting Intrapleural As single agent NCT01503177 GBM NDv-HUJ NB I/II Not yet recruiting i.
v. As single agent NCT01174537 Sarcoma Lung cancer II recruiting i. v. As single agent NCT01017601 NTX-010 Neuroendocrine tumors I recruiting i. v. Combined with cyclophosphamide NCT01048892 ParvOryx GBM I/II recruiting i. t. or i. v. As single agent NCT01301430 PvSrIPO GBM I recruiting i. t. As single agent NCT01491893 Abbreviations: BSC, best supportive care; CeD, convection enhanced delivery; CNS, central nervous system; CrC, colorectal cancer; GBM, glioblas- toma multiforme; HCC, hepatocellular carcinoma; HNC, head and neck cancer; HSv, herpes simplex virus; i. p. , intra peritoneum; i. t. , intra tumorem; i. v. , intra venam; n. a. , not available; NB, neuroblastoma; NDv, Newcastle disease virus; rT, radiotherapy. *Started after January 1, 2008, and not with- drawn, terminated or completed on the day of submission.