dataesr/scientific-paragraphs-categorization huggingface dataset:
Structure of the bacterial communities present in oilseed rape and wheat residues visualized by incorporating phylogenetic distances using the UniFrac distance matrix. MDS were performed on the overall dataset and faceted according to the sampling period. Each point represents one sample corresponding to a cropping season (shape: 2015-2016; 2016-2017; 2017-2018) and crop within a rotation (colour: oilseed rape in rotation, i. e. in WOW and OWO; wheat monoculture, i. e. in WWW; wheat in rotation, i. e. in WOW and OWO). Figure S2 - Jul. Oct. Dec. Feb. May 0. 2 Cropping season 0. 1 2015-2016 Axis. 2 [13. 1%] -0. 1 0. 0 2016-2017 July 2017 Crop within a rotation Oilseed rape in rotation Wheat in monoculture -0. 2 Wheat in rotation -0. 2 0. 0 0. 2 0. 4 -0. 2 0. 0 0. 2 0. 4 -0. 2 0. 0 0. 2 0. 4 -0.
B Cell Subset Phenotyping PBMCs were isolated using Ficoll-Histopaque density gradient centrifugation and were stained ex vivo using the following antibodies: CD19 Alexa Fluor 488 (clone HIB19), FcRL4 PE (clone 413D12), CD27 APC/Cy7 (clone O323), CD138 BV421 (clone MI15), IgM PerCp/Cy5. 5 (clone MHM-88), CD24 PE/Cy7 (clone ML5), CD38 APC (clone HB7) (all from BioLegend), and IgG BV510 (clone G18-145) (BD Biosciences). Samples were acquired on FACS Canto II (BD Biosciences) and analyzed by FlowJo v10. 0 software.
Cytometry Bead Assay for Measuring B Cell Cytokines Concentrations of cytokines IL-6 were quantified in the supernatants from B cells cultured for cytokine production using a LEGENDplex Human B Effector 1/2 Panel immunoassay (BioLegend) as per the manufacturer's instructions. For the detection of cytokines APRIL and CD40L in the plasma of healthy donors and DENV-positive patients, a LEGENDplex Human B cell Activator Panel immunoassay (BioLegend) was used as per the manufacturer's instructions. Samples were acquired using BD FACS Canto II and analyzed using LEGENDplex v7. 0 (Vigene Tech, USA) software.
Statistical Analysis Statistical analyses were done using GraphPad Prism 7. 00 software (GraphPad Software, Inc. , La Jolla, CA, USA). Since the data did not pass the criteria for normality using D'Agostino & Pearson normality test, the non-parametric Mann-Whitney Utest was used to compare data between two groups or by nonparametric paired Wilcoxon matched pairs signed rank test for paired data. Statistical analysis of data with more than two groups was done using the Kruskal-Wallis test followed by Dunn's posttest for multiple comparisons. For comparing paired samples between three conditions, Friedman's test was used. Correlations were calculated by Spearman analysis. For all analyses, P < 0. 05 was considered significant.
A decrease of CD19 + CD24 hi CD38 hi B cells within the total of single cells is not observed; however, this is a small subset and the percentages are very low. Frequencies of circulating immune cell subsets might change day to day during the acute phase of DENV infection. Therefore, we included only patients presenting at the hospital at day 4 of fever for a sub-analysis, which yielded similar differences in B cell subset frequencies as observed in our total cohort (data not shown). As there were more patients in the DHF/DSS group undergoing secondary infection, this could skew our results. Analyzing the different B cell subsets in secondary infected patients only yielded the same results, with significant decreased percentages of CD19 + CD24 hi CD38 hi B cells (median, 2. 9 vs. 5. 4%; P < 0.
Results Selected characteristics of the study participants are presented in Table  1. In total, 298 thyroid cancer cases and 1934 controls were included in the study from two regions of Belarus (Gomel, Mogilev) and four regions of the RF (Bryansk, Kaluga, Orel, Tula). One case, confirmed as follicular adenoma by the study international pathologist panel, was excluded from the data analysis, together with the respective controls. Approximately 77% of all cases (228 out of 298) were from Belarus, with 192 out of 228 cases from Gomel region (84%). Approximately 63% of thyroid cancers were in women, and 58% of the cases were less than 5 years old at the time of the accident. 131 I thyroid doses (arithmetic means of 1000 individual stochastic doses) in the study subjects had a log-normal distribution, with 937 subjects having a 131 I dose <0.
Discussion We report a significant positive association between 131 I thyroid dose and thyroid cancer risk after exposure at ages below 18 years at the time of the Chernobyl fallout using improved thyroid dosimetry and an expanded dataset, following up on the earlier case-control study  [1]. 131 I thyroid dose estimates were revised based on more precise age-specific thyroid mass values in Belarusian and Russian children, updated reduction factors for different types of milk and dairy products, and reclassified shared and unshared dose errors. This resulted in somewhat lower estimates of 131 I thyroid dose in the study subjects with 131 I median dose of 0. 29 Gy compared to the previously reported median of 0. 36 Gy in Belarus, and of 0. 02 Gy as compared to the earlier reported median of 0.
For data analysis, we placed study subjects' BMI estimates into two categories ("normal" versus "overweight") using sex-and age-specific reference cut-off values, defined by the World Health Organization (WHO) growth curves for school-aged children and adolescents (5-19 years old)  [30]. The number of underweight and obese subjects in the study was very small, so we combined underweight with the normal category, and obese with the overweight category. We used the PECAN module of the EPICURE version 1. 81 statistical software for matched case-control data to fit the models  [31]. All statistical tests were two-sided, with p-values of ≤0. 05 considered as statistically significant. The 95% CIs were calculated using the maximum likelihood method, except for the linear quadratic EOR model and the log-linear model, where Wald bounds were calculated.
Acknowledgments: We especially thank  Irina Malakhova ,  Nina Shabeka , and  Semyon Polyakov  ( Belarusian Center for Medical Technologies, Computer Systems, Administration, and Management of Health, Minsk, Belarus ),  Yoshisada Shibata  ( Nagasaki University, Nagasaki, Japan ),  Valeryi Khrouch (deceased)  ( State Research Center, Institute of Biophysics, Moscow, the Russian Federation ),  Evaldas Maceika  ( Institute of Physics, Vilnius, Lithuania ),  Irina Zvonova  ( Research Institute of Radiation Hygiene, St. Petersburg, the Russian Federation ),  Oleg Vlassov ,  Sergey Chekin ,  Vladimir Parshin ,  Alexander Abrosimov ,  Evgenyi Lushnikov ,  Marat Maksioutov ,  Evgenyi Parshkov , and  Anatoli Tsyb (deceased) (Medical Radiological Research Center RAMS, Obninsk , the  Russian Federation) ,  André Bouville  ( National Cancer Institute, Bethesda ),  Guennadi Goulko  ( Clinic and Policlinic for Nuclear Medicine, Bayerische Julius-Maximilians University of Würzburg, Germany ),  Masaharu Hoshi  ( Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan ),  Jadvyga Anoshko  ( Institute of Geological Sciences of the National Academy of Sciences of Belarus, Minsk, Belarus ),  Larisa Astakhova  (deceased) (Center of  Laser Medicine, Childhood Polyclinic No.
Purpose of the study In ABO-incompatible bone marrow transplantation, an efficient depletion of red blood cells (RBC) within the graft is mandatory to avoid adverse events in transplanted patients. Using non therapeutic products, we evaluated the substitution of the standard density gradient-based separation (DGBS) over Ficoll-Paque with the use of an automated procedure intended for buffy coat only (SmartRedux software) introducing modifications within the settings to achieve a drastic reduction of the initial volume of the product. Both methods were conducted on the Sepax-2 device.
The newly available BMP kit (Bone Marrow Program) available with the Spectra Optia device achieved results in a similar range as those reported for Optia's predecessor technology, the COBE Spectra  [10] [11] [12] [13]. The Sepax-2 device (Biosafe SA, a brand of GE Healthcare, Geneva, Switzerland) is commonly used for cord blood banking  [14] , HPC concentration before cryopreservation  [15]  or HPC washing after thawing  [16, 17]. Due to the low capacity of the Sepax-2 spinning chamber (210 mL at each cycle), processing of bone marrow (BM) collection for adult HPC transplantation processing requires several centrifugation cycles thus limiting the use of Sepax-2 to mononuclear cells (MNC) isolation from low volumes bone marrow aspirates for regenerative medicine  [18, 19]. Up to now, density-free separations onto Sepax-2 device were performed using Generic Volume Reduction (GVR) software and CS-490 disposable kits.
The GVR protocol allowed initial product volumes between 50 mL and 880 mL. Several procedures were required for larger BM volumes requiring BM splitting and extensive manipulation. The recent introduction of the SmartRedux software only available with the Sepax-2 device provided the ability to process an input volume of up to 3300 mL in a single raw extending the use of the Sepax-2 device for preparations of BM for hematopoietic transplantations in adults. The procedure is adaptive and various settings can be settled to enhance cell recovery or deplete RBC contamination in the final product. Its performances for the processing (volume reduction or RBC depletion) of bone marrow with volumes higher than 880 mL are currently under evaluation. Increasing regulations in cell therapy field requires that process validations shall be performed prior to their application to therapeutic products for HPC transplantation  [20] [21] [22].
Consequently, biological parameters studied to validate the process are white blood cells (WBC) or mononuclear cells (MNC) and not CD34+ HPC. Here, we report the capability to generate representative non-therapeutic products (NTP) close to BM harvest characteristics, significantly enriched with CD34+ HPC, by mixing several products issued from the preparation of random platelet concentrates (RPC) and disqualified BC. Using these products, we settled optimal settings for SmartRedux (method A or SmartRedux-ABOi) to achieve in a raw extremely low residual RBC volumes together with high mononuclear (MNC) and hematopoietic progenitor cells (HPC, CD34 positive cells) recoveries. To validate its performance, we compare it with the automated method based on a density gradient based-separation (DGBS) over Ficoll-Paque using the NeatCell software (method B).
Separation device and protocols Sepax-2 uses fully automatic walk-away software for volume reduction (SmartRedux) and RBC depletion (NeatCell) with the tubing sets CS490. 1 and CS900. 2 respectively (Biosafe SA), as described elsewhere  [14] [15] [16] [17]. Others reagents required for RBC depletion are Ficoll-Paque™ PLUS density gradient media (GE Healthcare, USA), 0,9% sodium chloride (B. Braun Medical Inc. , USA) and 4% human serum albumin (HSA, LFB, Les Ulis, France). The characteristics of the final product (total volume, optional additional volume of donor plasma) can be selected in SmartRedux software so as to better adapt the graft composition to the ABO compatibility status between donor and recipient, for instance the total depletion of donor residual plasma in case of ABO-minor incompatibility and to allow a safe and easy infusion to the patient.
Before starting the procedure, several settings must be adjusted by the operator. One major option is the capability to proceed using either a "fixed final volume" or a "proportional volume"method. Briefly, the former, the final volume can be selected by the user between 1 mL and 1500 mL, the latter, the final volume will be calculated as a percentage of the initial quantity of nucleated cells (between 1% and 100%) (see operating manual). Taken together, these parameters estimate a factor of volume reduction (Rf) for the SmartRedux procedure calculated as follows : = ( - ) Previously, we validated SmartRedux software and applied our settings in BM processing for ABO-compatible (ABOc) transplantation, referred further as to SmartRedux-ABOc (data not shown). In all these procedures, we used the "fixed final volume" option and set a final volume below the widespread limit of 10 mL/recipient body weight.
This translated in a Rf for BM volume (ratio between the final and the initial volumes after BM filtration and dilution with anticoagulant additives) of 4,0 ± 0,9 fold. However, RBC residual volume was to 158 ± 82 mL which would prevent its use for major ABOi BM transplantation. For major ABOi BM transplantation, following manufacturer's advice we enhanced RBC depletion using SmartRedux software targeting a drastic reduction of the BC volume up to 7,5% of the volume of the initial product (method A, also referred as to SmartRedux-ABOi). Method A was validated on eight NTP. We proceeded using the "fixed final volume" option, and set additional plasma to 1% of initial product volume. Hematocrits of initial products were adjusted between 35% and 50% before processing if necessary. Median Rf of NTP volume was to 14,8 ± 2,3 fold (12,0 -18,3) corresponding to 6,7% ± 1,1% of initial product volume.
We compared the efficiency of SmartRedux-ABOi (method A) with results from RBC depletion using an automated DGBS over Ficoll-Paque considered as the "gold standard" using NeatCell software on the same device (method B). Method B was conducted on four NTP as follows: in a first step, the volumes of NTP were exactly decreased to 120 mL using previously validated and described SmartRedux-ABOc procedure. Then, we applied to this intermediate BC the NeatCell software to deplete RBC. At the end, the mononuclear cells (MNC) were collected in a small volume (about 45 mL). In both approaches, either saline, HSA or autologous plasma can be added to the product in order to decrease the product density before use.
Processing time For method A, processing time was calculated as the time from CS600. 1 tubing set installation onto the Sepax-2 device (hands-on) to the completion of the "in-house" optimized settings of SmartRedux software (walk-away). For method B, processing time started with CS600. 1 tubing set installation onto the Sepax-2 device, application of standard SmartRedux software and then followed with CS900. 2 kit installation and application of NeatCell program. During automatic process steps none operator was mandatory (walk away).
We confirmed in this study that BC are suitable for qualifications and that enrichment with residues from RPC containing HPC allows the qualification of the method by monitoring in non-therapeutic products, the relevant target cell for BMT instead of WBC or MNC. Sepax-2 device is used in cord blood banking  [17] , BM cell concentration and MNC isolation for regenerative medicine  [18, 19]. In the past few years, volume reduction of HPC before cryopreservation  [15] , HPC washing after thawing  [16, 17]  have been evaluated using Sepax-2. Few data were published on the processing of high volume of products enriched in MNC and CD34+ HPC such as those aimed for BMT in adults. Our work demonstrated the capability of Sepax-2 and SmartRedux software for high RBCs depletion of high volume products in a raw and without the use of a density gradient separation.
CONCLUSIONS We showed that "in-house" SmartRedux-ABOi with a drastic volume reduction factor (method A) as well as "gold standard" automated DGBS over Ficoll-Paque using NeatCell software (method B) achieved satisfactory RBC depletion and CD34+ recovery. We demonstrated that the use of Sepax-2 device should not be restricted to small-volume BM cell processing and in association with SmartRedux software can be used for RBC depletion in large-volume BM in a raw without the need to proceed to a DGBS. The choice between one option or the other should be guided by the need to reach very low amount of residual RBC or to promote the highest progenitor CD34+ recovery. Further validations using BM of our "in-house" SmartRedux-ABOi protocol are needed to confirm our data but we suggest to use it for BM processing in major ABO-incompatible BMT in adult recipients rather than DGBS over Ficoll-Paque which is time consuming and costly.
ACKNOWLEDGMENTS This work was partially funded by grants from the  General Council of Alpes-Maritimes  (Appel à Projets Recherche 2011) and the  General Council of the Region PACA  (Appel à Projets Recherche Finalisée 2014, Projet POSITIVE). Authors thanks  Mrs. Jessica REMY MARTIN  from  Biosafe SA  (a brand of  GE Healthcare, Geneva, Switzerland ) for her collaboration.
The DNA was suspended in TE overnight at 4 °C. Sequencing of the Marinitoga lauensis genome was carried out at the Yale Center for Genome Analysis (YCGA) using the PacBio RS II. Pre-assembly, assembly and final genome curation were performed at the YCGA using the Hierarchical Genome Assembly Process (HGAP) with the SMRT analysis v. 2. 3. 0 software suite, which utilized the P_PreAssemblerDagcon module for pre-assembly, the P_AssembleUnitig module for initial assembly, the P_Mapping module to map reads back to assembled contigs and the P_AssemblyPolishing A C C E P T E D M A N U S C R I P T module to generate final consensus sequence contigs. Completion and contamination were assessed using CheckM  [25]. Open reading frames were predicted in Prokka  [31]  and annotated using the Rapid Annotation using Subsystem Technology web server (RAST)  [4, 6, 24] , with additional annotation using the Clusters of Orthologous Groups of proteins database  [27].
The NCBI Conserved Domain database was also used for manual annotation as needed  [17, 18]. Transfer RNAs were identified using the tRNAscan-SE 2. 0 web server  [15] , CRISPR regions were predicted with CRISPRCasFinder  [8]  and ribosomal RNAs were identified with Rfam v. 12. 0 and Infernal v. 1. 1. 2 [21, 22]. Whole genome synteny plots were constructed using Circos  [13]. 16S rRNA gene sequence similarity was assessed using EZBioCloud, supplemented with alignments in Geneious v. 10. 0. 2  [12]. 16S rRNA genes were aligned using the Geneious aligner, and regions with >50% sequence variability were manually masked. Maximum-likelihood phylogenetic analysis was performed using RAxML v. 8. 2. 4  [33]  with 1000 replicate bootstrap trees. Concatenated protein trees were built using a set of 16 ribosomal proteins  [3]  individually aligned using Muscle  [10].
A region ~47. 6 kb in length was identified, showing similar structure to other described Marinitoga-associated viral sequences (Fig. S3C-D ). Two putative proviral regions were also identified in the genome of Marinitoga sp. 1137 (Genbank NZ_CP009471. 1), which have not been previously described. In this analysis, these two regions were treated as a single provirus. Of the 80 ORFs predicted in the proviral sequence (Table  S2 ), 53 have homologues (E ≤ 0. 00001) in one of the other Marinitoga-associated proviral regions, based on BlastP  [2]. Twenty-two of the remaining ORFs without predicted Marinitoga viral homologues could not be assigned a putative function with RAST, COG or the NCBI Conserved Domain (CD) Database. The strain LG1 T proviral sequence include a putative CRISPR/Cas system-associated cas4 gene, which was also identified in the proviral region of Marinitoga sp.
Sulfur, cystine and thiosulfate were reduced to sulfide, and cells yield was improved in the presence of cystine. Optimal growth occurs at 55-60°C, pH 6. 5 and 3% (w/v) NaCl. The type strain LG1 T (=DSM 106824=JCM 32613) was isolated from a deep-sea hydrothermal chimney located at the deep-sea hydrothermal vent field Mariner (20° 10' S; 176° 36' W) at 1913 m deep. The DNA G+C content of this strain is 27. 9 mol%. The EMBL 16S rRNA gene sequence accession number of strain LG1 T is MH457605. This Whole Genome Shotgun project has been deposited at DDBJ/ENA/GenBank under the accession QHLX00000000. The version described in this paper is version QHLX01000000. The formal proposal of the new species "Marinitoga lauensis sp. nov. ," is given in Table  1. The digital protologue under the Taxonumbers TA00749.
Acknowledgements This study was funded by the  European Union program MaCuMBA  (grant agreement  311975 ) to  Stéphane L'Haridon  and by the  US-National Science Foundation  ( OCE1235432  and  OCE 1558795 ) to  Anna-Louise Reysenbach. Research was supported by  UBO ,  CNRS  and Ifremer. We thank the captain and crew members of the  RV Thomas Thompson  and the  ROV Jason team  for assistance in collecting samples. We thank  Claire Geslin  for helpful discussion and advices, and  Philippe Helies  for the transmission electron microscopy pictures.
Receding side southwest References: 1 NASA/IPAC Extragalactic Database (NED, https://ned. ipac. caltech. edu) 2  Wiegert et al. (2015)  3 estimated in this work 4 Mathewson et al. (1992)  5  Mathewson & Ford (1996)  6 SFR and SFR density (SFRD) from Wiegert et al. (2015) 7  Irwin et al. (2012a)  Here, we investigate the radio properties of NGC 4666 and its central source. We present the first flux measurements of the central source from the high-resolution radio continuum data of CHANG-ES. We further analyze the data on the radio halo, scale heights, and the linear polarization. Additional archival VLA C- band data of NGC 4666 complement the polarization data. With supplementary X-ray data from XMM-Newton we are able to support the AGN classification of the central source and analyze the far-extended X-ray halo, which seems to be correlated to the radio halo.
XMM data To study the nature of the possible central source, as well as of the galactic energy budget via analysis of the emission from the hot gas, XMM-Newton archive data for NGC 4666 were used (see Table  4  for the parameters of the observations). The data were processed using the SAS 15. 0. 0 package  (Gabriel et al. 2004)  with standard reduction procedures. The tasks epchain and emchain helped to obtain event lists for two EPIC-MOS cameras  (Turner et al. 2001 ) and the EPIC-pn camera  (Strüder et al. 2001). The event lists were then carefully filtered for periods of intense background radiation. From the output data an image in the soft energy range of 0. 2-1 keV was produced, along with the exposure map (without vignetting correction) masked for the acceptable detector area using the images script 3  , modified by the authors to allow adaptive smoothing.
Furthermore, a spectral analysis was performed. The spectra of each region were created using all three EPIC cameras. The background spectra were obtained using blank sky-event lists (see  Carter & Read 2007) , filtered using the same procedures as for the source-event lists. For each spectrum, response matrices and effective area files were produced. Next, including A&A proofs: manuscript no. N4666_Stein these ancillary files, spectra from all three EPIC cameras and the corresponding background blank sky spectra were merged using the SAS task epicspeccombine into a final background subtracted source spectrum. Finally, the spectra were fitted using XSPEC 12  (Arnaud 1996).
Due to the wavelength dependence, this effect is not as strong in C-band. Notes: -Channel width: δλ 2 , width of the λ 2 distribution: ∆λ 2 , shortest wavelength squared: λ 2 min -FWHM of the resolution (RMSF) in Φ space: δφ (rad m -2 ) -Largest scale in Φ space to which the observation is sensitive: max-scale (rad m -2 ) -Maximum observable RM (resp. Φ): RM max (rad m -2 ). (from  Brentjens & de Bruyn (2005) ). From the data in  Xu & Han (2014) , the Galactic foreground RM in the direction to NGC 4666 was determined. This value (RM foreground = -5. 8 ± 1. 3 rad m -2 ) was subtracted from the final RM cube. To adopt RM synthesis, Stokes Q and Stokes U images for each spw were produced. These have to be convolved to the largest beam in the frequency range (the beam size being dependent on frequency).