dataesr/scientific-paragraphs-categorization huggingface dataset:
Methylome analysis by SMRT PacBio sequencing Genomic DNA from various deletions and the complemented strains was prepared by CTAB reagent followed by QIAGEN genomic-tip 100/G. SMRTbell template libraries were prepared from total H. pylori genomic DNA following the 10 kb Template Preparation Procedure (Pacific Biosciences, Menlo Park, CA, USA). One SMRT cell was run on an RSII sequencer using P6/C4 chemistry, producing between 800 and 1100 Mb of raw sequence (two SMRT cells for the dR dM1 dM2 strain). The genome sequence was assembled for each strain using Pacific Biosciences SMRT Analysis 2. 3 program 'RS HGAP Assembly. 3 , with coverage between 411X and 513X, and the assembly was closed to a single circular genome manually. SMRT sequencing and methylation detection was performed as described earlier in  (8, 18).
AGS cells apoptosis assay Apoptosis analysis of AGS cells (3 × 10 6 ) co-cultured with H. pylori strains at an MOI of 1:100 for 24 h was detected by the appearance of a typical sub-Go/G1 fraction of fragmented nuclei. Apoptosis analysis was carried out as described in  (20). Briefly, cells were scraped and resuspended in PBS followed by centrifugation at 200 × g. The cells were washed with PBS and fixed by the drop wise addition of 70% chilled ethanol. Fixed cells were stored in 4 • C overnight before analysis. The fixed cells were washed thrice with PBS and stained with propidium iodide (50 g ml -1 in PBS) solution containing, 1 mg ml -1 RNase and 0. 05% Triton X-100. A minimum of 10 000 events per sample was measured. Acquisition and analysis were conducted using FACS Diva software (Becton Dickinson, USA).
Mass spectrometry and protein identification In gel trypsin of protein bands were performed as described  (24). Digested peptides were reconstituted in 15 l of the 0. 1% formic acid and 1 l of the same was injected on column. Digested peptides were subjected to 70 min RPLC gradient, followed by acquisition of the data on LTQ-Orbitrap-MS. Generated data was searched for the identity on MASCOT as search engine and using Swiss-Prot, TrEMBL and H. pylori databases. Proteins with >20% coverage were used for further analysis.
SMRT sequencing DNA modification Genome-wide detection of modified bases, and analysis of DNA motifs for those modified bases, was performed using SMRT Analysis 2. 3 program 'RS Modification and Motif Analysis. 1'. Coverage for the motifs identified was high, ranging from 195X to 240X per DNA strand. Modification of the 3-prime adenine in the 5 -GAAGA-3 motif was observed in all five strains, with nearly 100% of the sites called by the program as modified, while m4C modification of the complement strand motif, 5 -TCTTC-3 , was called at nearly 100% of the sites in the three strains containing the M2. HpyAII MTase (R. hpyAII, dR M1 and R. hpyAII-M2. hpyAII::M2. hpyAII kan), but was completely absent in the two M2. HpyAII deletion strains (R. hpyAII-M2. hpyAII and R. hpyAII-M1. hpyAII-M2. hpyAII) having a deletion of the M2.
DISCUSSION H. pylori is a genetically diverse bacteria and to date 80 different clinical isolates have been sequenced (NCBI database). Methylome analysis of H. pylori isolates revealed strain-specific methylation patterns on the genome  (7). Interestingly, H. pylori codes for a large number of N 6 -adenine MTases (8) and many of these have been shown to be involved in the epigenetic regulation of gene expression  (30, 31). Unlike eukaryotic cells, bacterial epigenetic regulation is centered on the modification of adenine residues at the N 6 -position. We have previously shown that the deletion of a solitary C 5 -cytosine MTase in H. pylori leads to altered gene expression affecting the transcription of genes involved in motility, adherence, and virulence  (10). Prior to our study the existence of C 5 -cytosine methylation in the bacterial genome was mainly associated with restriction protection.
ACKNOWLEDGEMENTS We thank  Prof. Utpal Tatu  and his lab members for their help in 2D gel electrophoresis. Members of D. N. R. laboratory are acknowledged for their support and valuable suggestions for the study. We thank  Dr Ritesh Kumar ,  Dr Prashant Damke ,  Dr Gajendra Dwiwedi ,  Semanti Ray ,  Yedu Prasad  and  Sushant Bangru  for crucial discussions and critical reading of the manuscript. Dr Avijit Sarkar  and  Dr Raghavan  are acknowledged for their support during the study in NICED. We thank the  FACS facility at IISc  and  NICED. D. N. R. acknowledges  DST  for J. C. Bose Fellowship. We thank  Dr Pablo Radicella  for providing plasmid P1175 and for critical suggestions.
The contamination removal step had been performed using bowtie2 (version 2. 2. 2), in-house Perl scripts and picard tools (version 1. 119). The pre-processed reads were aligned to the Helicobacter pylori 26695 reference genome and gene model downloaded from ENSEMBL (ftp://ftp. ensemblgenomes. org/pub/bacteria/release32/ gtf/bacteria 0 collection/helicobacter pylori 26695/ Helicobacter pylori 26695. ASM852v1. 32. gtf. gz). The alignment was performed using Tophat program (version 2. 1. 1) with default parameters. After aligning the reads with reference gene model, the aligned reads were used for estimating expression of the genes and transcripts using cufflinks program (version 2. 2. 1). Raw data are publicly available at NCBI GEO accession number GSE94268.
4 mm lead and 1. 7 mm polystyrene scintillators. The EMCal is a fairly high granularity detector. It has a cell area of ∆η × ∆φ = 0. 0143 × 0. 0143 rad and an energy resolution of σ E(GeV) /E = 4. 8%/E ⊕ 11. 3/ √ E ⊕ 1. 7%  [40]. In year 2011, it covered |η| < 0. 7 and ∆ϕ = 100 degrees. The main detectors used for triggering and characterization of the collision are the V0  [41]  and the Zero Degree Calorimeters (ZDC)  [42]. The V0 consists of two scintillator arrays located on opposite sides of the Interaction Point (IP) at 340 and 90 cm covering 2. 8 < η < 5. 1 and -3. 7 < η < -1. 7, respectively. The ZDC detectors are located at a distance of 114 m on both sides of the IP and detect spectator nucleons. The Pb-Pb data sample used for this analysis was collected in the 2011 LHC run. During that period, about 358 ion bunches circulated in each LHC beam, with collisions delivering a peak luminosity of 4.
We present the analysis of five joint XMM-Newton/NuSTAR observations, 20 ks each and separated by 12 days, of the broad-line radio galaxy 3C 382. The data were obtained as part of a campaign performed in September-October 2016 simultaneously with VLBA. The radio data and their relation with the X-ray ones will be discussed in a following paper. The source exhibits a moderate flux variability in the UV/X-ray bands, and a limited spectral variability especially in the soft X-ray band. In agreement with past observations, we find the presence of a warm absorber, an iron Kα line with no associated Compton reflection hump, and a variable soft excess well described by a thermal Comptonization component. The data are consistent with a "two-corona" scenario, in which the UV emission and soft excess are produced by a warm (kT 0.
1994). The jet inclination and velocity are estimated to be < 45 deg and > 0. 6c respectively, from the jet to counterjet brightness ratio  (Giovannini et al. 2001). From the high-energy properties, however, the jet contribution to the Xray continuum is likely small (see also  Grandi & Palumbo 2007). 3C 382 is also not detected in gamma-rays with Fermi  (Kataoka et al. 2011; Hooper et al. 2016). This paper is organized as follows. In Section 2, we describe the UV/X-ray observations and data reduction. In Section 3 we discuss the timing properties. In Section 4 we present the analysis of the XMM-Newton and NuSTAR spectra. In Section 5 we discuss the results and summarize our conclusions.
OBSERVATIONS AND DATA REDUCTION 3C 382 was observed five times by XMM-Newton  (Jansen et al. 2001)  and NuSTAR  (Harrison et al. 2013 ) between 2016 August 29 and 2016 October 17. Each pointing had a net exposure of ∼20 ks. The log of the data sets is reported in Table  1. XMM-Newton observed the source with the optical monitor (OM;  Mason et al. 2001) , the EPIC cameras  (Strüder et al. 2001; Turner et al. 2001 ) and the Reflection Grating Spectrometer (RGS; den  Herder et al. 2001). The data were processed using the XMM-Newton Science Analysis System (sas v16. 1). The OM photometric filters were operated in the Science User Defined image/fast mode. The images were taken with the U, UVW1, UVM2, and UVW2 filters, with an exposure time of 4. 4 ks for each image. The OM data were processed with the sas pipeline omichain, and prepared for the spectral analysis using the sas task om2pha.
The EPIC-pn spectra were grouped such that each spectral bin contained at least 30 counts, and not oversampling the spectral resolution by a factor greater than 3. Finally, the RGS data were extracted using the standard sas task rgsproc. The NuSTAR data were reduced using the standard pipeline (nupipeline) in the NuSTAR Data Analysis Software (nustardas, v1. 9. 3), using calibration files from NuSTAR caldb v20171002. Spectra and light curves were extracted using the standard tool nuproducts for each of the two hard X-ray detectors aboard NuS-TAR, sitting inside the corresponding focal plane modules A and B (FPMA and FPMB). The source data were extracted from circular regions with a radius of 75 arcsec, and background was extracted from a blank area close to the source. The spectra were binned to have a signal-to-noise ratio greater than 5 in each spectral channel, and not oversampling the instrumental resolution by a factor greater than 2.
SPECTRAL ANALYSIS We performed the spectral analysis with the xspec 12. 9 package  (Arnaud 1996). The RGS spectra were not binned and were analysed using the C-statistic  (Cash 1979) , to exploit the high spectral resolution of the gratings in the 0. 3-2 keV band. Broad-band (UV to X-ray, 0. 3-80 keV) fits were instead performed on the binned pn and NuSTAR spectra plus the OM photometric data, using the χ 2 minimisation technique. All errors are quoted at the 90% confidence level (∆C = 2. 71 or ∆χ 2 = 2. 71) for one interesting parameter. In our fits we always included neutral absorption (phabs model in xspec) from Galactic hydrogen with column density N H = 6. 98 × 10 20 cm -2  (Kalberla et al. 2005). We assumed the element abundances of  Anders & Grevesse (1989)  and the photoelectric absorption cross-sections of  Verner et al.
A reflection component? We investigated the presence of a reflection component associated with the Fe Kα line fitting the pn and NuSTAR data in the 3-79 keV energy band. Fitting the spectra above 3 keV allows us to focus on the putative Compton hump avoiding the complexities in the soft band (soft excess and warm absorber). First, we fitted the five pn+NuSTAR data sets with a simple model including a power law with an exponential cut-off plus a Gaussian line (see Sect. 4. 2). We left the photon index, cut-off energy and normalization of the power law free to vary between the different observations. Concerning the Gaussian line, we left the width and flux free to vary between the different observations. We found a good fit (χ 2  /dof = 1925/1921), and only lower limits to the high-energy cut-off of 130-150 keV, consistent with the measurements reported by  Grandi et al.
(2001)  and  Ballantyne et al. (2014). Then, to test for the presence of a reflection continuum, we replaced the cut-off power law with the pexrav model in xspec, which includes Compton reflection from a neutral medium of infinite column density in a slab geometry  (Magdziarz & Zdziarski 1995) , such as a standard neutral accretion disc. We fixed the inclination angle at 30 deg, since the fit was not sensitive to this parameter. We found no improvement, and only an upper limit to the reflection fraction R = Ω/2π, where Ω is the solid angle subtended by the reflector, of ∼0. 1. To further test the robustness of this result, we performed the same fit to NuSTAR data alone, thus avoiding cross-calibration issues. We found the same upper limit to the reflection fraction. Next, we tested a model including relxill, version 1.
The broad-band fits As the final step of the high-energy spectral analysis, we fitted the pn and NuSTAR data in the whole X-ray energy band (0. 3-79 keV) including the optical/UV data from the OM. First, we note that the extrapolation of the best-fitting model above 3 keV to lower energies clearly reveals a soft excess, even in the case of the ionized reflection model with relxill (see Fig. 9 ). Even refitting the data in the 0. 3-79 keV with relxill, and including the warm absorber (Sect. 4. 1), we obtained a poor fit (χ 2 /dof = 2712/2249) with significant residuals below 2 keV. The broad-band (UV to hard X-rays) data allow us to test physical Comptonization models. The different components are described below.
DISCUSSION We reported on the broad-band high-energy (UV to hard X-rays) view of the radio/X-ray monitoring of the BLRG 3C 382 based on five joint XMM-Newton and NuSTAR observations. 3C 382 appears to be weakly variable both in the UV and Xray bands, at least on the time-scale of our campaign. Most of the flux variability is found in the soft X-ray band, whereas the flux and spectral variability at hard X-rays is small. Even if a significant correlation cannot be established, the data suggest a trend of a stronger soft X-ray flux corresponding to a larger UV flux. This is consistent with a Comptonization origin for the X-ray emission. The lack of spectral variability at hard X-rays (the photon index being always consistent with 1. 78-1. 79) would in turn suggest that the source is not undergoing significant geometrical or physical variations.
The corona/jet connection will be investigated in a forthcoming paper, in which we will present the radio data of the campaign. In agreement with previous observations, we find the presence of a significant soft X-ray excess below 2 keV. Ionized reflection is not able to self-consistently explain the soft excess, the Fe Kα line and the lack of a Compton hump in this source. On the other hand, a warm Comptonization model is found to well describe the soft excess. Its photon index is found to be around 2. 4-2. 5, while the temperature is consistent with 0. 6 keV, corresponding to an optical depth of around 20. Interestingly, these parameters are in agreement with those generally found in radio-quiet Seyferts, although most radio-quiet sources tend to show lower temperatures between 0. 1 and 0.
Concerning the hot corona, we derive only lower limits to the temperature of 20-40 keV. This corresponds to an upper limit to the optical depth of around 4. We also estimate the amplification factor A h of the hot corona to be around 20 (only weakly depending on the temperature; see  Petrucci et al. 2018). This large value indicates a compact or patchy corona, intercepting only a fraction of the seed soft photons. Indeed, the geometrical parameter g describing the compactness or "patchiness" of the corona can be estimated as ∼ 2/A h  (Petrucci et al. 2018 ). We thus find g 0. 1, in ) Energy (keV) Figure  10. Broad-band UV/X-ray data and best-fitting model (see Table  5 ). Upper panel: XMM-Newton/OM, pn and NuSTAR data (rebinned for plotting purposes) with folded model. Middle panel: contribution to χ 2.
2016). This has been the first XMM-Newton/NuSTAR campaign explicitly aimed at studying the high-energy emission of an AGN by probing its variability on time-scales of days. NGC 4593 is an X-ray bright Seyfert 1 galaxy hosting a supermassive black hole of ∼ 10 7 solar masses  (Denney et al. 2006) , i. e. two orders of magnitude smaller than 3C 382. The campaign on NGC 4593 has shown the source to be remarkably variable, both in flux and spectral shape, on time-scales as short as a few ks, with a softerwhen-brighter behaviour. From the X-ray spectral analysis, the primary power law was found to have a photon index varying between 1. 6 and 1. 8 and a high-energy cut-off varying from 90 +20 -40 keV to > 700 keV. Moreover, the high-energy data are consistent with the presence of two distinct reflection components producing a significant Fe Kα line with a broad component, and a moderate Compton hump.
ACKNOWLEDGEMENTS We are grateful to the referee for helpful comments that improved the manuscript. This work is based on observations obtained with: the NuSTAR mission, a project led by the  California Institute of Technology , managed by the  Jet Propulsion Laboratory  and funded by  NASA ;  XMM-Newton , an  ESA  science mission with instruments and contributions directly funded by  ESA Member States  and the  USA (NASA). This research has made use of data, software and/or web tools obtained from  NASA's High Energy Astrophysics Science Archive Research Center (HEASARC) , a service of  Goddard Space Flight Center  and the  Smithsonian Astrophysical Observatory. The research leading to these results has received funding from the  European Union 's  Horizon 2020 Programme un- der the  AHEAD  project (grant agreement n.
654215). FU acknowledges financial support from the  Italian Space Agency (ASI)  under contract  ASI/INAF 2013-025-R01. SB and MC acknowledge financial support from  ASI  under grant  ASI-INAF I/037/12/0 , while GM, AM and AT from  ASI/INAF I/037/12/0-011/13. SB, GM, AM, RM and AT acknowledge financial support from the  European Union Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement no. 312789. FU, GM, SB, MC, MD, PG, ET, ADR, MG, AM, RM and AT acknowledge financial contribution from the agreement ASI-INAF n. 2017-14-H. O. BDM acknowledges support from the  Polish National Science Center  grant  Polonez 2016/21/P/ST9/04025. GP ackowledges support by the  Bundesministerium für Wirtschaft und Technologie/Deutsches Zentrum für Luft und Raumfahrt (BMWI/DLR ,  FKZ 50 OR 1408 ) and the  Max Planck Society.
The FDG PET/CT fixing per-treatment can also be a volume of interest. Per-radiotherapy FDG PET/CT can be performed without artefacts (lung inflammation) and the persistence of 42Gy fixation is very pejorative  [11, 12]. As a result, we proposed a French multicenter study with dose increase on per-radiotherapy FDG volume (RTEP7, NCT02473133). Another study is also underway in the USA by the RTOG (RTOG 1106) and encouragingpreliminary results have been published by Kongs et al. in a phase 2  [13]. The definition of BTV (Biologic Target Volume) is a crucial step of treatment planning in radiation therapy. Many methods of pre-treatment segmentation have been defined but there is no segmentation method in the process of radiotherapy. For Until now, manual delineation of FDG PET positive tissues is the gold standard, despite poor reproducibility  [14].
Patient population and treatment Data were extracted from 4 prospective studies corresponding to a total of 67 patients, respectively S1, S2, S3 and S4, where S1-3 correspond to monocentric clinical trials (Centre Henri Becquerel, Rouen, France)  [11, 12, 31]  (NCT01261598, NCT01261585) and S4 (NCT01576796) an ongoing multicentre clinical trial study  [31] , in which patients had given written and informed consent. All patients were treated with radiation therapy alone or concomitant chemoradiotherapy for inoperable stage II or III NSCLC. Patients were treated by conformational radiation therapy. The dose prescription corresponded to 66 Gy in 33 fractions, with 2 Gy per fraction given daily, 5 days a week. The mean age was 59 years. There were 13 women and 54 men presenting stage II (10%) or stage III (90%) NSCLC.
PET/CT imaging For patients treated at the Centre Henri Becquerel, the per-therapeutic PET/CT was performed on a Biograph Sensation 16 Hi-Rez device (Siemens Medical Solutions, Erlangen, Germany), without time of flight system or image reconstruction algorithm incorporating point-spread function. Forty-six patients underwent their PET/CT on this device. They were unrolled in S1-3 monocentric clinical trials (39 patients), and in S4 (7 patients). As the PET/CT device corresponded to an old generation model, these patients were grouped into a database called S old. Patients who underwent their FDG PET/CT on a new generation of positron-emission tomograph came from S4 study. All the image reconstruction algorithms incorporated a point-spread function, while some of them used a time of flight system (ToF).
Data analysis Regression function of perPET-RT For primary tumours and nodes, the couples of values (Th opt , SUV max ) were defined, as well as the associated couple of constants (i. e. (A pr , B pr ) and (A no , B no )) of the linear regression (Eq. 2). The fits were obtained by minimizing the residuals by computing their coefficient of determination (R 2 ). The robustness of the adaptive threshold calibration procedure was evaluated by testing whether the slopes and the intercepts of the two datasets issued from the two PET models (old vs. new) were significantly different  [33]. First, slopes were compared. If this first p-value was less than 0. 05, it could be concluded that the lines were significantly different. In that case, there was no point in comparing the intercepts. Otherwise, intercepts were compared.
Agreement of segmented volumes The performance of perPET-RT method was evaluated using the Dice similarity coefficient (DSC) according to the following expression: DSC ¼ 2ðX∩Y Þ ðX∪Y Þ Eq. 3. Where X corresponds to the gold standard volume and Y the volume segmented by perPET-RT. The agreement between the segmented volumes using other segmentation methods was also performed using DSC. As two adaptive thresholding methods (ADT and COA) were calibrated only on the Biograph Sensation 16 Hi-Rez device, the segmentation was only done on S old data for these 2 methods. At, first a descriptive analysis of DSC was performed for each segmentation method by computing median (DSC med ), minimum (DSC min ) and maximum (DSC max ) of DSC. For this analysis, first/third quartiles and first/ ninth deciles of DSC-values were also extracted leading to the estimation of the inter-quartile range (difference between third and first quartiles, i.
It requires knowing the type of lesion (primary or node) and the measurement of SUV max , which is, in practice, easier and more reproducible than thresholding methods based on contrast (COA and ADT) or a mean SUV measurement (AOV). Another advantage of perPET-RT is that there is no need to calibrate the method on PET/CT models, unlike many adaptive thresholding methods. In our database, the method was not sensitive to the generation of PET models. This result has to be confirmed on other databases. Nevertheless, the concept of using such an approach in clinical routine or in mono or multicentre clinical trials is possible and easy to implement. As gold standard, a consensus threshold value was used. Palie et al. showed that there was an excellent reproducibility in delineation of MTVs by the physicians  [39].
Acetylene reduction measurements Nitrogenase activity was determined by gas chromatography measuring the enzymatic conversion of acetylene gas to ethylene as previously described  (Trinick et al. , 1976). Infected plants at 28 dpi, placed in a 50-mL plastic vial and sealed with a rubber lid. Acetylene gas (BOC, Manchester, UK) was injected into the vials with 2% (v/v) final concentration, incubated for 1 h at 23°C and 1 mL sample taken for analysis. Conversion of acetylene to ethylene by rhizobial nitrogenase was recorded on a Clarus 480 (Perkin Elmer) gas chromatograph with N 2 as the carrier gas set to a flow rate of 25 mL min -1 , a HayeSep N 80/100 mesh column, connected to a flame ionisation detector at 100°C. Acetylene was applied in excess and peak areas of ethylene were quantified using TotalChrom Workstation software (Perkin Elmer) and displayed as relative units.