dataesr/scientific-paragraphs-categorization huggingface dataset:
GC-MS Analysis Mass spectrometry was performed on an Agilent gas chromatograph-mass spectrometer (GC-MS) Model 7890/5975, equipped with HP-5MS capillary column (25 m x 0. 25 mm, film thickness 0. 25 µm) programmed with the same conditions as for GC-FID. The mass spectrometer (MS) ionization was set in positive electron impact mode at 70 eV and electron multiplier was set at 2200 V. Ion source and MS quadrupole temperatures were 230 °C and 180 °C, respectively. Mass spectral data were acquired in the scan mode in the m/z range 33-450. The essential oils constituents were identified by matching their mass spectra and retention indices (RI) with those of reference compounds from libraries  (Adams 1995; Mc Lafferty and Stauffer, 1991). The proportions of the identified compounds were calculated by internal normalization.
The instrument was under the control of Empower 2 software, build 2145 (Waters). Plasma N-glycans were separated on a Waters bridged ethylene hybrid (BEH) Glycan column, 150 × 2. 1 mm, 1. 7 m BEH particles, with 100 mmol/l ammonium formate, pH 4. 4, as solvent A and acetonitrile as solvent B. The separation method used a linear gradient of 70-53% acetonitrile (vol. /vol. ) at flow rate of 0. 561 ml/min in a 25 min analytical run. Data were processed using an automated integration method and the chromatograms were all separated in the same manner into 31 peaks (GP1-GP31), where the content of glycans in each peak was expressed as a percentage of the total integrated area. All glycan structures were annotated with MS/MS analysis by HILIC-UPLC coupled with a Synapt G2-Si ESI-QTOF-MS system (Waters).
Total protein concentration was determined with BCA Protein Assay Kit (Santa Cruz Biotechnology, Dallas, TX, USA) according to the manufacturer's protocol and 40 g of protein extract was used for standard immunoblotting with ␤-tubulin as a loading control. Rabbit anti-SaCas9 1:5000 (ab203943, Abcam, Cambridge, UK), mouse anti-SpCas9 1:1000 (ab191468, Abcam), rabbit anti-␤-Tubulin 1:2000 (ab6046, Abcam), goat anti-Rabbit IgG H&L (HRP) 1:200 000 (ab6721, Abcam) and goat Anti-Mouse IgG H&L (HRP) 1:200 000 (ab205719, Abcam) antibodies were used. The antibody-tagged protein bands were visualized by Immobilon Western Chemiluminescent HRP Substrate (Milipore, Burlington, MA, USA) according to the manufacturer's protocol. ECL signals captured on Alliance Q9 Advanced Chemiluminescence Imager (Clever Scientific, Warwickshire, UK) were quantified using the ImageJ software  (32).
Statistical analysis and data representation Changes in CpG methylation and expression levels, as well as changes in glycan structure ratios, were analyzed using the Mann-Whitney test. All data were visualized using the R Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, Austria). Images from western blotting experiments were processed and quantitated using the ImageJ program  (32). Pre-processing and normalization of whole methylome data were done using the 'minfi' Bioconductor package  (33). PCA analysis followed by Wilcoxon Rank Sum Tests was conducted to identify possible confounding variables. SVA was performed to correct for potential batch effects. We converted ␤-values converted to M-values, and a linear regression model with adjustments for Sentrix ID was used to identify differentially methylated probes (DMPs) using the Bioconductor 'limma' package  (34).
Statistically significant DMPs were defined as those with false discovery rate (FDR)-adjusted P-values of < 0. 05, and delta-beta values of > 0. 05 or < -0. 05. The 'IlluminaHumanMethylationEPICanno. ilm10b2. hg 19' annotation package was used to map DMPs to CpG annotations, i. e. CpG islands, CpG shores, CpG shelves or open sea regions. The 'annotatr' Bioconductor package was used to map the DMP regions to chromatin states based on annotations defined by chromHMM in Hmec cells. Fold enrichment of each category based on relationship to CpG islands and regulatory regions were calculated by dividing the fraction of DMPs in each annotation category with the fraction of all filtered probes mapped to the respective category, correcting for differences in representation of each annotation category on the Infinium MethylationEPIC array.
It should be noted that to allow clearer visualization, Figure  8C  and E  was plotted using methylation (␤) values that were adjusted by Surrogate Variable Analysis (SVA) and log-transformed into M-values, which do not directly reflect the real biological % DNA methylation. Similar graphs depicting actual methylation values (unadjusted betas normalized by the R package 'funnorm') are included in Supplementary Figure  S11.
FUNDING Croatian National Science Foundation Project EpiGly-coIgG [Epigenetic regulation of IgG glycosylation; contract # 3361 ];  IRI grant  from the  European Structural and Investment Funds  [contract # KK. 01. 2. 1. 01. 0003 ]; Croatian National Centre of Research Excellence in Personalized Healthcare  [contract # KK. 01. 1. 1. 01. 0010 ]; ICGEB   CRP grant  [ Comprehensive Toolbox for Epigenetic Modulation of Gene Expression ; Contract no. CRP/17/006 ;  ICGEB Ref. No. CRP/ HRV17-03 ]; European  Horizon2020  project  SYSCID ,  SC1-2016-2017  [A systems medicine approach to chronic inflammatory disease; contract # 733100 ]. Funding for open access charge: All funders/projects declared above can be used to cover page charges; there is enough funding from each of them. The work carried out at IARC was partially supported by:  Institut National du Cancer (INCa, France) ,  Foundation ARC pour la Recherche sur le Cancer (France) ,  INCa-DGOS-Inserm  (grant # 12563 ),  EC FP7 Marie Curie Actions -People -Co -funding of regional, national and international programmes (COFUND).
Data from smokers, however, have suggested intensified consolidation of clones in the airways of smokers  16  , potentially carrying a high burden of persistent mutagenic alterations. Similarly, hyperplasia of airway epithelial cells has been reported to be a typical feature in the early COPD pathogenesis  17. Therefore, we leveraged medium-coverage WGS data of lower lobe epithelial lung tissue, isolated from airway brushings, and blood as reference tissue from 12 elderly individuals to identify somatic single-nucleotide mutations (SSMs) and compared the total mutational load with respect to smoking status (ex-smokers vs. never smokers) and presence of COPD (within ex-smokers). For a subset of ex-smokers, upper lobe brushings were also analysed in order to reveal temporal information of mutational development.
Calculation of sensitivity (recall) and precision (positive predictive value) of different SMC procedures was solely based on the predicted position (without considering mutation type). We further assessed the impact of a filtering script to the calls of VarScan 2 as recommended by the authors  31. As the combination of the mapping software and the SMC tool had sometimes proven crucial for the overall accuracy of a pipeline  30  , we also carried out sensitivity analyses with GEM3, a meanwhile updated version of GEM2, as well as with the popular aligner BWA-mem  32. We finally included MuTect 2, a completely revised version, which had in the meantime been integrated in GATK v. 4. x and had performed well in a benchmark study  33. Recall-Precision scatter plots were built with the function "scatterplot" in the package "car" in R 3.
Experimental verification of mutation calls. From each confidence segment, sets of 30 positions were selected randomly, but with the fix inclusion of all calls pointing either to non-synonymous SSMs or effecting a splice site (based on ENSEMBL, N = 4) and the requirement of at least one call from each individual being present. Calls lying on the Y-chromosome (N = 9) were not considered. Details about the primer design, the polymerase chain reactions (PCR) for amplifying the 90 selected positions, the concatenation with subsequent sequencing and data processing are given in Supplementary Methods. Four PCRs failed and successful concatenation of products of the remaining 86 reactions was confirmed by gel electrophoresis for each sample (length above 2 kb). After sequencing the concatenated products, SAMtools v.
Validation of the applied strategy in cancer. In order to validate the applied strategy to call SSMs, we carried out the same procedure with two cancer cases (one CLL and one MB case) from which we had fully verified somatic mutation call sets  30. The strategy of taking the intersection of the individual results of the three callers proved accurate (Supplementary Fig. S4A ). Compared to intersections of only two tools, the loss in recall was marginal and clearly compensated by a material gain in precision. Replacing the aligner GEM2 with the newer version GEM3 improved results for Strelka and respective intersections in the MB data set, but no such effect was found in the CLL data set. Further sensitivity analyses with BWA-mem confirmed that the intersection strategy of three tools led to higher precision than alternative strategies, while the recall remained high (Supplementary Fig.
S4B ). Improvements from MuTect to MuTect 2 were clearly visible in the individual results, but were not essential in intersections. Therefore, we did not consider applying these updated mapping or calling tools to the sequencing data of the brushings (EvA data set). critical appraisal of the somatic mutation calls. Despite the successful validation of our SMC strategy in cancer cases, we further assessed some characteristics of the 1651 suggested SSMs in lower lobe brushings across all subjects and compared them with those of the (true and false positive) calls in the two cancer cases when applying the same tools. Calls did not show material differences in terms of chromosomal distribution, structural annotation, overlap with DHS or repetitive regions, as well as mutation type (Fig. 2 ). As 9 of the 12 individuals in the EvA data set were former smokers, a higher proportion of C > A substitutions in lung epithelial tissue (as compared to malignant brain or blood tissue) could have been anticipated  34  , but sample size was obviously too limited to draw conclusions from the absence of such an association.
There were other features of the calls in the EvA data set that deviated considerably. Variant alleles peaked at markedly lower frequencies (median VAF ranged from 0. 22 for subject 12 to 0. 35 for subject 2) than in MB (0. 45) or CLL (0. 44). This is not unexpected since clonal heterogeneity is likely much higher in non-cancerous samples. However, results from the two cancer cases suggested that the reliability of calls with decreased VAF was reduced. The false positive proportion of the SSM calls shared between the three callers showed median VAFs of 0. 23 (MB) and 0. 29 (CLL), whereas the true positive calls barely deviated from 0. than for calls from the MB (13. 5%) and CLL sample (11. 7%), and the latter proportions even decreased further when including only the confirmed calls (to 5.
Acknowledgements We thank  Yohannes Tesfaigzi ,  Lovelace Respiratory Research Institute, Albuquerque, NM, USA , for helpful discussions. We are grateful to  Raul Tonda  for providing the script for the Rainfall-plots. The EvA study is an  EU -funded project (# 200506 ) under the  Seventh Framework Programme  ( FP7 ). We acknowledge the support of the  Spanish Ministry of Economy, Industry and Competitiveness (MEIC)  through the  Instituto de Salud Carlos III  and the 2014-2020 Smart Growth Operating Program to the EMBL partnership. We also acknowledge the support of the  Centro de Excelencia Severo Ochoa , and the  Generalitat de Catalunya  through the  Departament de Salut, Departament d'Empresa i Coneixement  and the  CERCA Programme.
Introduction Recent progress in direct electron detector technology, the provision of intense and coherent electron beams using field emission guns (FEGs and X-FEGs) in cryo-electron microscopes and advances in image-processing algorithms and sample preparation have led to the so-called 'resolution revolution'  (Ku ¨hlbrandt, 2014; Mitra, 2019)  in cryo-electron microscopy (cryo-EM). Indeed, two thirds of the more than 6000 entries currently in the Electron Microscopy Data Bank (EMDB;  Patwardhan, 2017)  have been deposited within the last five years. However, an average resolution for singleparticle cryo-EM structures of between 5 and 6 A ˚for the 3DEM density maps deposited suggests that there is still some way to go before cryo-EM becomes a routine technique for the production of high-resolution structural information.
Nevertheless, with this aim in mind, and coupled with significant advances in sample preparation and data processing, many national and international centres for cryo-EM have opened during the last few years (see, for example,  Alewijnse et al. , 2017, and references therein; Stuart et al. , 2016; Clare et al. , 2017). In 2015, the European Synchrotron Radiation Facility (ESRF) took the decision to complement its portfolio of cutting-edge X-ray-based facilities for structural biology  (Pernot et al. , 2013; von Stetten et al. , 2015; Linden et al. , 2014; Mueller-Dieckmann et al. , 2015)  by acquiring, installing and commissioning a cryo-EM facility (CM01; http://www. esrf. eu/ home/UsersAndScience/Experiments/MX/About_our_beamlines/ CM01. html) based around a Titan Krios microscope and making it available to its structural biology user community.
2a ). Images or movies recorded by the detector are directly transferred to the ESRF central storage system (NICE, Networked Interactive Computing Environment; https://www. esrf. eu/Infrastructure/Computing/ NICE) using a dedicated fibre-optic connection (10 Gb s À1 ). This facilitates not only fast data transfer but also allows both on-the-fly data backup onto an external hard drive and image pre-processing. In general, raw data are maintained on disk for up to 50 days from the experiment date and are then archived on tape and stored without time limit. Data backup to external hard disk drives is usually carried out by the users using the same easy-to-use interface that is available on all ESRF beamlines for structural biology. Alternatively, users can also download and transfer data to their home storage system via an rsync command.
CM01 implements the ESRF data policy (http://www. esrf. fr/datapolicy). Parallelized image pre-processing (Fig. 2b ) using several GPU-equipped computing clusters is automatically launched on the collected movies using the SCIPION wrapper  (Conesa Mingo et al. , 2018; Gomez-Blanco et al. , 2018). The imported movies are drift-corrected using MotionCor2  (Zheng et al. , 2017)  and contrast-transfer function (CTF) parameters are estimated using Gctf  (Zhang, 2016). With the current GPU infrastructure, which is subject to constant upgrades, and for an incoming rate of up to 80 movies per hour, pre-processing results are calculated with almost no delay. The output of MotionCor2 and Gctf are uploaded into the ISPyB database (Delageniere et al. , 2011) and are displayed, along with other metadata, as snapshots in EXI (Fig.
mitegen. com/product/mitegen-cryoem-pucks-generation-2-0/) in a dedicated storage area. As for experiments on the ESRF's X-ray-based structural biology beamlines, samples must be registered using the ISPyB sampletracking module (Delageniere et al. , 2011). In the case that more data need to be collected from a set of grids, samples can be stored for up to six months, a period that can be prolonged upon request. Again, as for the ESRF's X-ray-based structural biology beamlines, if users do not come to the ESRF for their experiment then the costs of sample transport to and from Grenoble are met by the ESRF (see https://www. esrf. eu/ UsersAndScience/Experiments/MX/How_to_use_our_beamlines/ Prepare_Your_Experiment/Dewar_sending).
The last plot indicates the average motion per frame in micrometres from the alignment of the acquired movies. onto Quantifoil 1. 2/1. 3 400 mesh grids (https://www. quantifoil. com/); excess liquid was blotted off for 2 s. The K2 detector was used in counting mode for automatic data collection using the EPU software. Movies were collected as gain-normalized and unpacked MRC files at a magnification of 130 000, yielding a calibrated pixel size of 1. 067 A ˚. Drift correction was carried out using MotionCor2  (Zheng et al. , 2017)  and CTF estimation was performed by Gctf  (Zhang, 2016). Further image-processing steps were performed using RELION 2. 1  (Kimanius et al. , 2016; Scheres, 2012). Segments were automatically picked and extracted with about 90% overlap between segments. 2D reference-free classification was performed and class averages showing high-resolution features were selected and included for 3D refinement.
As a final step, local refinement of the CTF parameters was performed using Gctf  (Zhang, 2016). The map was further post-processed by automatically applying a B factor of À83 A ˚2, yielding a gold-standard FSC  (Henderson et al. , 2012)  resolution of 2. 3 A ˚(Fig. 5 ), one of the highest resolutions for the TMV structure to be published  (Weis et al. , 2019). Even though the resolution of the TMV structure presented here is not the highest to be reported  (Song et al. , 2019) , the result obtained clearly shows the very high quality of data that can be obtained using CM01. The final helical parameters are 1. 408 A ˚for the helical rise and 22. 03 for the helical twist. One TMV protomer (PDB entry 4udv;  Fromm et al. , 2015)  was rigid-body fitted into the density map using UCSF Chimera  (Pettersen et al.
Perspectives With the rapid growth of the cryo-EM community in the last few years, the demand for data collection at high-end microscopes such as the Titan Krios installed at CM01 has skyrocketed. Since its installation, CM01 has proved to be a highly successful facility, acting Laboratory access is provided to users for cryo-EM sample preparation. The laboratory includes a Vitrobot positioned in the fume hood, as can be seen on the left side. in concert with the ESRF's X-ray-based beamlines for structural biology as a source of primary or complementary structural information in a wide range of projects. One of the major driving forces for the creation of CM01 was to provide a facility that can be accessed by all of the ESRF's international structural biology user community. However, a lack of infrastructure for sample preparation and screening remains a bottleneck, particularly for researchers in smaller laboratories.
Acknowledgements We would like to thank all of the ESRF support groups, such as the technical infrastructure division, safety, communication and data-analysis units and computing and network services, for their invaluable support during the construction, setup and commissioning of the microscope. The support of  Francesco Sette  (Director General of the ESRF),  Harald Reichert  (Director of Research of the ESRF),  Winfried Weissenhorn  (Director of the IBS) and  Stephen Cusack  (Head of EMBL Outstation Grenoble) was crucial for this project. We would also like to mention  FEI, Gatan  and particularly their application support teams for continuous training and support, specifically  Pierre-Yves Mille ,  Remi Boucher ,  Bruno Barlassina ,  Ana Alarcon ,  Wim Woorhut ,  Eric Bathelt ,  Felix de Haas ,  Thomas Hoffmann  and  Evgeniya Pechnikova.
Canakinumab, a selective, human anti-IL-1β monoclonal antibody, has been proven to be efficacious in patients with CAPS ≥2 years of age  (21) (22) (23)  but long-term follow-up data for this age group have not previously been published. Canakinumab has also been reported to not affect the induction or persistence of anti-body responses after immunization with unadjuvanted influenza or alum-adjuvanted meningococcal vaccines in healthy subjects ages 18-45 years  (24). Recently and unexpectedly, pneumococcal vaccines were reported to trigger severe local and systemic inflammation in some patients with CAPS  (25). This report summarizes the long-term efficacy and safety of canakinumab in pediatric patients with CAPS ≤5 years of age, including 6 patients ≤2 years of age, with follow-up of 3 years, including the core study (ClinicalTrials.
Statistical analysis. No inferential analyses were performed, and categorical variables are presented as absolute frequencies and percentages. Continuous variables are presented as the mean ± SD; median, minimum, maximum; and number of nonmissing data points. Tests were nonparametric. "End of study" refers to the end of the extension study. AEs were coded using the MedDRA version 17. 1. The number and percentage of patients with AEs were summarized, regardless of relationship to the study drug. Patients who experienced multiple events for a given term were counted once. Data are presented as rounded values.
RESULTS Patient disposition and baseline clinical characteristics. Seventeen patients (with a median age of 31 months [range 1-59 months]) with CAPS were enrolled in the core study. Six of the patients were younger than 2 years of age. All enrolled patients completed the core study and entered the extension study. Most patients (14 of 17 [82%]) completed the extension study; of the 3 patients who discontinued during the extension study, 2 discontinued owing to unsatisfactory therapeutic effect (and were thus managed outside the clinical protocol as per local standard of care) and 1 had no reason for discontinuation recorded (and data were also subsequently unavailable). Screening for NLRP3 mutations was performed by routine genetic sequencing as part of regular clinical care for all patients.
The mean time from diagnosis to study entry was 2. 6 years. All 17 patients had at least 1 confirmed pathologic NLRP3 mutation (Supplementary Table  1 , available on the Arthritis & Rheumatology web site at http://onlin elibr ary. wiley. com/doi/10. 1002/art. 41004/ abstract). An additional TNFRS1 variant (p. R121Q, also referred to as the R92Q variant) was observed in 1 MWS patient. Of the 17 patients enrolled, 12 (71%) had MWS, 4 (24%) had NOMID (based on neurologic involvement in 4, on papilledema in 3, and overall severity of the phenotype in all 4 as judged by the local investigator), and 1 (6%) had FCAS (Table  2 ). Median baseline CRP and SAA levels were abnormal (7. 0 mg/liter for CRP and 9. 1 mg/liter for SAA). 1 ). Pharmacokinetics/pharmacodynamics. Data relating to pharmacokinetics and pharmacodynamics evaluation were analyzed and will be reported separately.
NCT01302860 and  NCT01576367. The views expressed are those of the author(s) and not necessarily those of the  NHS , the  NIHR , or the Department of Health. Supported by  Novartis Pharma AG, Switzerland. Research at Great Ormond was supported by the research support from  Novartis ,  Sobi ,  NovImmune , and  Roche. Dr. Hofer  support from  Novartis. Dr. Koné-Paut  has received consulting fees from  Novartis ,  Sobi ,  AbbVie ,  NovImmune ,  Pfizer , LFB, and  Chugai  (less than $10, Novartis ,  Roche ,  Sobi , and  CSL Behring. Dr. Horneff  has received research support from  AbbVie ,  Chugai ,  MSD/Janssen ,  Novartis ,  Pfizer , and  Roche. Dr. Calvo Penadés  has received research support from  Novartis ,  AbbVie ,  Roche ,  Pfizer ,  MSD ,  GlaxoSmithKline , and  Bristol-Myers Squibb. Dr.
16S rRNA Gene Amplicon Sequencing 16S rRNA gene amplicon sequencing of effluent samples of colonic model 1 was carried out at DNAVision (Gosselies, Belgium) on a 454 Life Sciences Genome Sequencer FLX instrument (Roche Applied Science, Vilvoorde, Belgium). Amplification of the V5-V6 hypervariable 16S rRNA region 1 https://rrndb. umms. med. umich. edu/about/ was performed using primers 784F and 1061R  (42). Data was analyzed using the open source software package Quantitative Insights Into Microbial Ecology (QIIME), v1. 9 (43) as described before  (35).