dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2004). Illumina reads (GA II; PE library, ∼ 160 mio reads) were used to correct 454 base calling base errors. This provided 197× coverage of the chromosome and 311× coverage of the plasmid, with an error rate of less than 1:100 000. Sequences have been deposited at the European Nucleotide Archive with the accession numbers HF571520-HF571521.
Gene prediction and annotation Gene prediction and annotation of protein-coding genes was done as described elsewhere  (Mann et al. , 2013). Ribosomal RNA genes were identified via BLAST searches  (Altschul et al. , 1997)  against public nucleotide databases and transfer RNA genes using TRNASCAN-SE v. 1. 21 (Lowe and Eddy,  1997). CRISPRs were identified with CRISPRFINDER  (Grissa et al. , 2007). Selected CAZymes from multi-functional CAZyme families were subjected to in-depth phylogenetic analyses to uncover their substrate specificities. For each family, a set of experimentally characterized proteins was selected and aligned with their H. tiamatea homologues using MAFFT  (Katoh et al. , 2002)  with iterative refinement and the Blosum62 matrix. Phylogenetic trees were computed from these alignments using PHYML  (Guindon and Gascuel, 2003)  with 100 replicates for bootstrapping and annotations derived based on proximities to experimentally characterized proteins.
1 mm, 5 μm (Fortis Technologies, Marl, Germany). In brief, a MALDI TOF/TOF 4800 mass spectrometer (AB SCIEX) was used for acquisition and processing of the peptides. The resulting raw peak lists of precursors and fragment ions were filtered and exported with ABI-Extractor (Peaks-Bioinformatics Solutions, Waterloo, ON, Canada). Protein identification and quantitation were done with MASCOT v. 2. 3. 01 (Matrix Science, London, UK) and PHENYX v. 2. 6 (GeneBio, Geneva, Switzerland). The search was performed against the predicted protein sequences of H. tiamatea. The concatenated target-decoy database search strategy was used to estimate the false positive rate (below 1%) to improve reliability of the data (P-value < 0. 01). A minimum of two unique peptides and three sets of spectra obtained in triplicated RP-LC-MALDI TOF/TOF MS data was required for protein identification and further quantification.
Acknowledgments We thank the crew of the  R/V Urania  for sampling of the Medee DHAL,  Jörg Wulf  for catalysed reporter deposition fluorescence in situ hybridization analyses,  Rafael Bargiela  for helping with figures and  Rudolf Amann  for critical reading of the manuscript. This study was supported by the  EU   FP7  project  MAMBA ('Marine Metagenomics for New Biotechnological Applications ',  FP7-KBBE-2008-226977 ; http://mamba. bangor. ac. uk/), the  Spanish Ministry of Economy and Competitiveness  (grant  BIO2011-25012 ) and the  Max Planck Society. H. T. , O. V. G. and P. N. G. acknowledge the support of  EU   FP7  for the project  MicroB3  ( OCEAN-2011-287589 ).
94Rev1): Consideration of aliphatic amines and amides evaluated in an addendum to the group of aliphatic and aromatic amines and amides evaluated by JECFA (68 th meeting). The Panel concluded that: "For one substance. 090] additional toxicity data are still needed before the evaluation can be finalised. Besides the safety assessment of these flavouring substances, the specifications for the materials of commerce have also been consiered and for one substance,  [FLno: 16. 090], the composition of the stereoisomeric mixture has to be specified". The requested data on 3-  (3,4-dimethoxyphenyl) -N-  [2-(3,4-dimethoxyphenyl) -ethyl]-acrylamide  [FLno: 16. 090 ] have now been submitted by the applicant. The Commission requests EFSA to finalise its safety assessment on. 090] within nine months from the receipt of this letter.
Each test group consisted of 10 animals per sex. Recovery groups were included for the control and high dose groups as well. Clinical observations, functional observation battery and motor activity were recorded. The feed homogeneity was checked by dietary chemical analysis. Data on body weight and individual food consumption were collected throughout the in-life phase of the study. Blood samples were taken for complete haematological, clinical chemical and serological analyses. At study termination, body weight, organ and tissue weights were recorded after macroscopical examination and complete histopathology was performed on the animals of the control and highest dose groups. No substancerelated effects were found implying that the highest dose group is the NOAEL of 1100 mg/kg diet which is equal to approximately 73 mg N-3,7-dimethyl-2,6-octadienyl cyclopropylcarboxamide/kg bw/day in male rats.
Data analysis Paternity analysis: identification of potential crop-pollinated offspring To assess the extent of crop-to-weed pollen flow, we first used a simple exclusion approach. We used the genotype of the variety cultivated in 2009 and of the weedy mother plants to exclude (or not) the cultivated variety as a father for each offspring  (Jones and Ardren 2003)   [-8,0) [3,6) [9,12) [15,18) [21,24) [27,30) [33,36) [39,42) [45,48)  Date of flowering onset T 0 the variety could contribute to false exclusions, we allowed one mismatch between the variety and its potential offspring. The outcome of this procedure was used to compute, for each sampled mother, the proportion P c of offspring that could result from pollination by the cultivated variety. To relate weed phenology to the level of pollination by the crop, we grouped the mother plants into 9 discrete classes according to their date of flowering onset and computed within each class the mean value of P c.
Goodness of fit The mean predicted crop pollination rate of sampled mothers was 10. 4%. It decreased from approx. 30% in the earlier flowering groups of mothers to 0% in the latest ones Table  1. Quality of the fit of models with different combinations of alternative hypotheses, evaluated through L, the log-likelihood of the data set. In the different models, the dispersal of cultivated pollen was described using either a constant density function (null model) or the family of exponential power functions (exponential, normal, or exponential power function); the temporal distribution of weedy pollen was described by a constant function or as proportional to the weeds flowering area (dispersal of weedy pollen: cst or var, respectively); an effect of local density on weedy male fecundity was included (yes) or not (no), and allelic frequencies in the pollen cloud were computed as either constant or variable over the season (AF: cst or var, respectively).
2012). Last but not least, our model yielded estimates of cropweed hybridization rates very close to the hybridization rates estimated by a simple exclusion approach (Fig. 2B ). By contrast, we did not detect a significant effect of phenological assortative mating within the weedy population (i. e. no effect of the inclusion of its temporal genetic structure into the model). Although surprising, this negative result may be due to a low precision in the estimation of allele frequencies in the temporal subsets of the data (i. e. allelic frequencies were estimated from <50 individuals in approx. 20% of the data subsamples). Despite a crop flowering period extending over 19 days, we modelled the temporal pattern of crop pollen emission by a single date: T cult. This simplification proved useful regarding our objectives but was biologically unrealistic: the temporal distribution of cultivated pollen included in the model (eqn 1) accounts for the combined effects of its temporal dispersal ability (i.
Acknowledgements The authors are very grateful to  Camille Noilhan ,  Muriel Tavaud  and  Aline Rocher  for technical assistance. We also thank  Jacques David  and  Sylvain Gl  emin for insightful discussions,  Alex Widmer  and  Laur ene Gay  for critical review of the manuscript and anonymous reviewers for their valuable comments on previous versions. This work was funded by  CETIOM. Marie Roumet  was supported by a fellowship from the  French Ministry of Research.
Ngf-modulated miRs Affect Neuronal Signaling Pathways The transcription factor Creb is a key mediator of neurotrophin signaling  (Kaplan and Miller 2000; Annibali and Nasi 2007). To assess its involvement in controlling the expression of Ngf-modulated miRs, we investigated the presence of Creb binding sites at their promoters. We employed the JASPAR web site (JASPAR 2013) to interrogate the database of microRNA promoters validated by chromatin immunoprecipitation  (Marson et al. 2008). We found a statistically significant enrichment of Creb binding sites at promoters of microRNAs modulated at 3, 6, and 24 h of Ngf treatment, compared with a random promoter population (data not shown). This supports the hypothesis that Ngf may control the expression of early-modulated miRs, at least in part, via Creb.
To get an insight into the possible function of the miRs modulated by Ngf, we made use of DIANA LAB-DNA Intelligent Analysis software (DIANA LAB 2013) to retrieve their predicted targets, and we identified the pathways affected by their expression by means of the KEGG PATHWAY database (KEGG PATHWAY 2013). We retained only pathways with p values B0. 05, calculated by the hypergeometric distribution. Targets of miRs modulated at 1 h were mainly involved in signaling pathways concerning differentiation, proliferation, survival, cell adhesion, TGF-beta signaling, neurotrophin signaling, JAK-STAT signaling, and extracellular matrix (ECM)-receptor interaction (Table  1 ). Predicted targets of microRNAs modulated by Ngf at 3 and 6 h were preferentially enriched in signaling pathways-MAPK, TGF-beta, p-53 signaling, ECM-receptor interaction-long-term depression, focal adhesion, adherens junction, axon guidance, and glioma.
Validation of Array Data by Real-Time PCR To validate by quantitative real-time PCR (RT-PCR) miR differential expression upon Ngf treatment, we focused on a set of ten microRNAs, chosen for expression pattern, experimentally proven targets, and literature data. were picked from the list in Fig. 1. The remaining three microRNAs-miR-103, miR-212, and miR-132-are not listed in Fig. 1  since they presented a subthreshold modulation by Ngf in the array experiments (data not shown), but were selected for the following reasons. Expression of the miR-212/132 cluster in cortical and hippocampal neurons is induced by Bdnf through Creb and their promoter is bound by Creb in PC12 cells  (Vo et al. 2005; Remenyi et al. 2010). The two microRNAs are implicated in synaptic plasticity, mental diseases, and drug dependence  (Impey et al.
Real-Time PCR Quantitative real-time PCR (RT-PCR) was performed using the miScript SYBR Green PCR Kit in 96-well plates according to the manufacturer's instructions. Each 20 ll reaction contained 2. 5 ng template cDNA, 2 ll universal primer, and 2 ll miR specific primer (from Qiagen) or U6 snoRNA primer as control. Real-time PCR reactions were performed by an Applied Biosystem 7500 apparatus. Expression data were calculated by 7500 software v2. 0. 5 (Applied Biosystems) according to the DDCt method and expressed as relative quantities after normalization to U6 level.
Microarray Analysis Before proceeding with microarray profiling, the efficacy of Ngf was checked by RT-PCR expression analysis of PC3, a known Ngf immediate-early responsive gene (data not shown). RNA was extracted with TRIzol and 5 lg RNA from each sample were labeled with Hy5 TM and Hy3 TM fluorescent labels using the miRCURY TM LNA Array power labeling kit (Exiqon, Denmark), according to the procedure described by the manufacturer. Hy5 TMlabeled samples and Hy3 TM -labeled reference RNA sample were mixed pair-wise and hybridized to the miRCURY TM LNA Array version 11. 0 (Exiqon, Denmark), which contains capture probes targeting 514 unique miRs from human, mouse, and rat registered in miRBASE version 12. 0, and spike-in controls. The hybridization was carried out as recommended by the vendor.
After hybridization, the microarray slides were scanned using a Perkin-Elmer Scan Array and images analyzed by the GenePix Pro 6. 0 program. Analysis of the scanned slides indicated successful labeling of RNAs as evidenced by the signal intensities of all capture probes for the control spike-in oligonucleotides. For each slide, spots with signal to background ratio below 1. 5 and flagged spots were filtered out. Systematic bias in the data was removed by applying the LOWESS normalization. To establish the significance of observed regulation for each miR, Student's t test was used and the p values were corrected for multiple comparisons. Finally, miRs with a p value less than 0. 05 and a FC greater than 1. 7 or less than -1. 7 (FC at least 1. 7 in absolute value) were considered. Heat maps were generated by two-way hierarchical clustering.
Bioinformatics Analysis TargetScan (6. 2; http://targetscan. org/) and DIANA mi-croT (http://diana. cslab. ece. ntua. gr/microT/) software was used to predict microRNA targets. Targets were investigated through DIANA mir-Path (http://diana. cslab. ece. ntua. gr/) and KEGG Pathway, containing over 20,900 annotated human genes (www. genome. jp/kegg/pathway. html). Creb binding sites were investigated via JASPAR (http://jaspar. genereg. net/).
Immunoblotting and Immunohistochemistry Whole-cell protein extracts were prepared from cells lysed in RIPA buffer. Samples were separated through SDS PAGE gels, transferred to Hybond ECL membranes (GE Healthcare), and treated with appropriate antibodies. Staining was performed by the SuperSignal Chemiluminescent Substrate from Pierce. ImageJ software (http://rsbweb. nih. gov/ij/) was used for densitometric analysis; western blot quantification was normalized against loading controls. Immunohistochemical detection was performed as described  (Annibali et al. 2012). Antibodies used: phospho-Akt(Ser473) and phospho-p44/42 MAPK (ERK1/2) (Thr202/Tyr204) antibodies were from Cell Signaling, Vgf antibody  [24]  was kindly provided by A. Levi, monoclonal anti-b-Actin-peroxidase clone Ac-15 (A3854) and anti-a-Tubulin (T6199) were from Sigma, beta III tubulin antibody was from Abcam, and mouse monoclonal anti-App (22C11) from Millipore.
Acknowledgments We thank  Bioway Company, China , for generously providing mouse salivary gland ß-Ngf. Funding was provided by grants from  ASI ,  Fondazione G. Berlucchi , and the  EPIGEN  project to S. N;  Fondazione Roma  and  MIUR FIRB  to P. C. EM and NM were supported by  MIUR FIRB  fellowships. We thank  Maria Teresa Ciotti  for her invaluable support for DRG cultures,  Marco Scarno  `( CASPUR, Rome ) for his generous advice on statistical data analysis, and  Andrea Levi  for reagents and advice.
01 89 Axon guidance \0. 01 74 Neurotrophin signaling pathway \0. 01 72 Focal adhesion \0. 01 103 Long-term potentiation \0. 01 42 ErbB signaling pathway \0. 01 48 MAPK signaling pathway 0. 02 125 Predicted targets of all microRNAs modulated by Ngf at each time point-from 1 to 240 h-were retrieved and mapped into the KEGG Pathway database through DIANA miR-Path software; only pathways with p value B 0. 05 were retained. Pathways relevant to nervous system and neurons are shown; the number of Ngf-modulated miRs targeting a given pathway and the numbers of genes that are targeted in that pathway are also indicated.
04 MAPK signaling pathway 259 26 7. 4e-03 Regulation of actin cytoskeleton 214 25 1. 5e-03 Axon guidance 131 23 6. 7e-06 Focal adhesion 206 19 0. 03 Neurotrophin signaling pathway 120 19 1. 6e-04 Wnt signaling pathway 143 16 0. 01 Dopaminergic synapse 130 16 5. 3e-03 were collectively retrieved and mapped into the KEGG Pathway database through DIANA miR-Path software. B KEGG Pathways affected by each of the ten select miRs. Predicted targets of each miR were retrieved by TargetScan and mapped into the KEGG Pathway database; only pathways with p value B 0. 05 were retained. Pathways relevant to nervous system and neurons were considered; mir-207 did not show nervous system relevant pathways with statistical significance. The number of Ngf-modulated miRs targeting a given pathway and the numbers of genes targeted in that pathway are indicated Ngf-modulated miRs.
The photons are detected in the photon tagger located at z = -103 m. An electron tagger is placed at z = -5. 4 m adjacent to the beampipe. It is used to provide information on ep → eX events at very low Q 2 (photoproduction) where the electron scatters through a small angle (π -θ < 5 mrad). At HERA transverse polarisation of the lepton beam arises naturally through synchrotron radiation via the Sokolov-Ternov effect  [20]. Spin rotators installed in the beamline on either side of the H1 detector allow transversely polarised leptons to be rotated into longitudinally polarised states and back again. Two independent polarimeters LPOL  [21]  and TPOL  [22]  monitor the polarisation. Only data where a TPOL or LPOL measurement is available is used. When both measurements are available they are averaged  [23].
Data samples The data sets used in the measurement of the reduced cross sections correspond to two short dedicated data taking periods in 2007 in which the proton beam energy was reduced to 460 GeV and 575 GeV, and the scattered lepton was detected in the LAr calorimeter. The positron beam was longitudinally polarised with polarisation P e = (N R -N L )/(N R + N L ), where N R (N L ) is the number of right (left) handed leptons in the beam. The integrated luminosity and longitudinal lepton beam polarisation for each data set are given in Table  1. The lepton beam polarisation plays no significant role in this analysis. The extraction of the F L structure function in Sect. 5. 2 uses the cross section measurements presented here and e + p measurements with P e = 0 at E p = 920 GeV in which the scattered positron is detected in the LAr calorimeter (Tables  22  and 26  of  [5]  scaled by a normalisation factor of 1.
018  [33]  which arises from an error in the determination of the integrated luminosity used for this data set). In addition the F L extraction also uses cross section measurements from H1 at E p = 460, 575 and 920 GeV with the positron detected in the SpaCal as it is described in  [3]. The two detectors provide access to different kinematic regions and the corresponding measurements are referred to as the LAr and SpaCal data for each of the three values of E p.
Polar angle measurement and energy calibration The detector calibration and alignment procedures adopted for this analysis rely on the methods discussed in detail in  [5]  which uses the high statistics E p = 920 GeV data recorded just prior to the 460 and 575 GeV runs. The detector was not moved or opened between these run periods. The alignment and calibration constants obtained at E p = 920 GeV are verified using the same methods  [5]  for the data presented here. In this analysis the scattered lepton is detected in the LAr calorimeter by searching for a compact and isolated electromagnetic energy deposition. The polar angle of the scattered lepton, θ e , is determined using the position of its energy deposit (cluster) in the LAr calorimeter, and the event vertex reconstructed with tracks from charged particles.
The relative alignment of the calorimeter and tracking chambers is verified using a sample of events with a well measured lepton track  [49]  in which the COZ chamber provides an accurate z reconstruction of the particle trajectory. The residual difference between the track and cluster polar angles in data and simulation is found to be less than 1 mrad, and this value is used as the systematic uncertainty of the scattered lepton polar angle. An in situ energy calibration of electromagnetic energy depositions in the LAr calorimeter is performed for both data and simulation. Briefly, a sample of NC events in which the HFS is well contained in the detector is used with the Double Angle reconstruction method  [50, 51]  to predict the scattered lepton energy (E D A ) which is then compared to the measured electromagnetic energy response allowing local calibration factors to be determined in a finely segmented grid in z and φ.
The remaining background is estimated from the number of data events with opposite charge. This background is statistically subtracted from the positively charged sample. However, a charge asymmetry in photoproduction can arise due to the different detector response to particles compared to antiparticles  [58, 59]. The charge asymmetry has been determined by measuring the ratio of wrongly charged scattered lepton candidates in e + p to e -p scattering at E p = 920 GeV data and was found to be 1. 03 ± 0. 05  [5]. This is cross checked in the E p = 460 and 575 GeV data using photoproduction events in which the scattered electron is detected in the electron tagger. In this sample fake scattered electron candidates passing all selection criteria are detected in the LAr calorimeter with both positively and negatively charged tracks associ- ated to the electromagnetic cluster.
Cross section measurement The simulation is used to correct the selected event samples for detector acceptance, efficiencies, migrations and QED radiation effects. The simulation provides a good description of the data and therefore is expected to give a reliable determination of the detector acceptance. The accessible kinematic ranges of the measurements depend on the resolution of the reconstructed kinematic variables. The ranges are determined by requiring the purity and stability of any measurement bin to be larger than 30 % as determined from signal MC. The purity is defined as the fraction of events generated and reconstructed in a measurement bin (N g+r ) from the total number of events reconstructed in the bin (N r ). The stability is the ratio of the number of events generated and reconstructed in a bin to the number of events generated in that bin (N g ).
The purity and stability are typically found to be above 60 %. The detector acceptance, A = N r /N g , corrects the measured signal event yields for detector effects including resolution smearing and selection efficiency. The measured differential cross sections σ (x, Q 2 ) are then determined using the relation σ (x, Q 2 ) = N -B L • A • C • 1 + QED , ( 4 ) where N and B are the selected number of data events and the estimated number of background events respectively, L is the integrated luminosity, C is the bin centre correction, and (1 + QED ) are the QED radiative corrections. These corrections are defined in  [60, 61]  and are calculated to first order in α using the program Heracles  [35]  as implemented in Djangoh  [34]  and verified with the numerical analysis programs Hector  [62]  and Eprc  [63].
Noise subtraction: Energy classified as noise in the LAr calorimeter is excluded from the HFS. For y < 0. 19 the calorimetric energy not contained within hadronic jets is classified as noise. The uncertainty on the subtracted noise is estimated to be 5 % of the noise contribution as determined from the analysis of the HERA II E p = 920 GeV data  [5]. For y > 0. 19 the noise contribution is restricted to the sum of isolated low energy calorimetric depositions. Here the residual noise contribution is assigned an uncertainty of 20 %, to accomodate differences between data and simulation. Nominal trigger efficiency: The uncertainty on the trigger efficiency in the nominal analysis is determined separately for both E p = 460 and 575 GeV data taking periods. Three trigger requirements are employed: the global timing, the event timing and the calorimeter energy.