dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2010). More than half of the terpene synthase genes have been functionally characterized  (Martin et al. , 2010)  and were found to produce a large number of different mono-and sesquiterpene backbones in vitro. Interestingly, this variability is not reflected in the volatile profiles of grapes and wines in our selected studies. Sesquiterpenes do not appear in our dataset of 141 validated volatiles. However, a labeling study revealed production of 14 sesquiterpenes in grape skins of two different varieties, suggesting the sesquiterpene metabolism in grapes is nonetheless active  (May et al. , 2013). The concentrations of sesquiterpenes in grapes and wines are probably too low to be detected in non-targeted profiling experiments, but they do contribute to wine aroma of at least some varieties: rotundone, an oxygenated sesquiterpene, is responsible for the peppery aroma of Shiraz wines  (Wood et al.
FUNDING The authors acknowledge the support of the  Agence Nationale de la Recherche  to the  InteGrape  project ( ANR-13-BSV6-0010 ). The research leading to these results has received funding from the  People Programme  ( Marie Curie Actions ) of the European Union's  7th Framework Programme  (FP7/2007-2013) to TI under  REA Grant Agreement 289217.
Determination of quinol peroxidation rates was conducted inside a Coy anaerobic chamber equipped with an Avantes DH-2000 spectrophotometer. Due to the high 278-nm absorbance at high quinol/quinone concentrations, the reaction progress was monitored at 260 nm rather than 278 nm. The extinction coefficient ε 260nm = 6. 23 mM -1 cm -1 was determined from the UV spectrum of decylubiquinone based on ε 278nm = 12. 7 mM -1 cm -1. The reactions were performed in the standard buffer: 50 mM MOPS, 100 mM NaCl, 0. 1% LM, pH 7 unless otherwise noted. Aliquots of nitric oxide (NO) were added from a NO-saturated (2 mM) aqueous solution. Igor Pro version 6. 1 (Wavemetrics) was used for data analysis and creating graphs. Analysis of the steady-state kinetics. Initial QPO rates were determined for varying H 2 O 2 concentrations while keeping the decylubiquinol (dQH 2 ) concentration constant and vice versa.
Polarographic test for catalase activity after achieving anoxia through cytochrome bd oxidase turnover as in  70. (A) Oxidase turnover was started, by consecutively adding 10 mM DTT, 50 μ M UQ-0 and 100 nM enzyme to the standard buffer. 90 seconds after reaching anoxia, 1 mM of H 2 O 2 was added to the reaction and no increase in oxygen could be observed. 150 seconds after peroxide addition, 20 nM catalase were added and formation of oxygen was observed. (B) Identical reaction parameters as in (A) were used. The reaction mixture was incubated for 2. 5 (black), 5 (gray) and 10 minutes (light gray) after addition of 1 mM H 2 O 2. After incubation, 100 nM of catalase were added and formation of different quantities of oxygen was observed. in a separate experiment (22 nM s -1 NO at 100 μ M NO and 100 μ M dQH 2 , data not shown).
3). → + H O H O O 2 2 (4) 2 2 2 2 We hypothesized that the catalase activity detected by the authors in ref. 70 might be due to impurities in their enzyme preparation. Therefore, isolated membranes from E. coli that overexpress cytochrome bd were assayed for catalase activity. Interestingly, the membranes did show a weak catalase activity (Fig. 7 ). It is notable that the relation between activity and H 2 O 2 concentration (Fig. 7A ) is very similar to that presented in the inset of Fig. 1  in ref. 70. The catalase activity profile is biphasic and non-hyperbolic, showing quite a sharp increase below ~0. 2 mM H 2 O 2 and levelling off at higher H 2 O 2 concentrations unlike canonical catalases that show a linear relation at millimolar H 2 O 2 concentrations  [79] [80] [81]. These data suggest that the catalase activity reported in ref.
Acknowledgements The authors want to dedicate this paper to professor  Simon de Vries , who unexpectedly passed away in the autumn of 2015 during the process of manuscript preparation. This work was supported by an  ECHO grant  ( 711. 011. 004 ) from the  Netherlands Organization for Scientific Research (NWO)  to  Simon de Vries  and an  AFR grant  ( 3945775 ) from the  Fonds National de la Recherche Luxembourg  to  Jo Hoeser. We thank  Shalini Sahebdin ,  Marc Strampraad  and  Gaël Brasseur  for their technical assistance.
In 1981, Richardson  [Ric81]  introduced the cartoon representation for proteins, which depicts the secondary structure as ribbons and arrows. Since then, a variety of cartoon renderings have been developed that vary the graphical appearance, e. g. using straight cylinders for helices (see Figure  6 ). One of the earliest implementations of the cartoon model was the Ribbons program  [CB86] , which was influential to subsequent work. Its successor Ribbons 2. 0  [Car91]  provided interactive visualization. A current challenge is to improve the efficiency for the interactive visualization of large, dynamic proteins. This can for example be achieved by mesh-refinement techniques at the software level  [HOF04]  or by moving to GPUs at the hardware level. TexMol by Bajaj et al. helix ray casting by using impostor-based GPU shaders instead of tessellated geometry.
Later on, Le Muzic et al. [LMAPV15]  presented a system, cellVIEW, to interactively visualize large molecular datasets using the Unity3D game engine (see Figure  7 ). The exploited techniques further advanced the performance of atomistic visualization by means of a real-time LOD selection technique implemented in the tessellation shader. The proposed approach allows to render datasets containing 15 billion atoms at 60 fps. In 2012, Lindow et al. [LBH12]  presented an approach similar to those of Le Muzic et al. [LMPSV14, LMAPV15] , where the atomic data is stored in a 3D voxel grid on the GPU. During ray casting, a fast ray-voxel traversal is used and only spheres in the current voxel are tested for intersection. For very large data sets, the rendering is much faster than direct ray casting  [RE05, SWBG06]  or even the two-stage culling approach by Grottel et al.
Volumetric representations and aggregation Besides the tailored representations discussed in Section 4, visualization methods developed for other application fields can also be utilized to depict molecular data sets. Especially vector field c 2016 The Authors Computer Graphics Forum published by John Wiley & Sons Ltd. visualization methods can be useful for dynamic molecular data. These methods, however, require a continuous representation of the raw particle data. Such representations can be obtained by sampling points to a 3D grid. Similar to the convolution surfaces, a kernel function is often used to define the influence radius of the sampled particles. Cohen et al. [CKK*05] used volumetric maps to study accessibility. Scharnowski et al. [SKS*13] sampled dipole moments derived from the atomic positions to a grid and subsequently used the curl operator to separate similar regions in the resulting vector field.
Especially in the context of steered simulations, haptic feedback using specialized interaction devices becomes interesting since it can be used to convey forces. Another application area that uses methods for direct manipulation of molecular data is interactive molecular modelling. Intuitive haptic exploration using specialized hardware was implemented  [SGSG01]  and applied to a 4000 atom membrane channel. The performance requirement for haptic rendering is even more stringent than for graphics rendering, as it imposes refresh rates of about 1000 Hz. by CellBlender  [BDF15] , which is a plug-in for the 3D modelling tool Blender. The visualization module eases generation of MCell models and shows the resulting simulation, where the molecules, represented as glyphs, are embedded into 3D meshes of cellular structures.
Their proper visual representation can provide important insight into bonding and other relationships. The molecular orbitals (see Figure  16 ) can be computed and visualized for dynamic data using GPU-accelerated algorithms [SHLK11]. Tools like VMD, Chimera, and PyMOL furthermore enable users to load field data stored on regular grids, which can then be visualized by mesh extraction, isocontours, or volume rendering. They also offer field line visualiza-tions, which can be useful for electrostatics data. There is also a variety of specialized stand-alone tools for molecular visualization of such physico-chemical properties, such as Molden package systems partially incorporate the abovementioned state-of-the-art techniques. Amira, for example, provides all the classical representations like ball-and-stick, space-filling, and cartoon representations.
Furthermore, molecular surfaces like vdW surface, SAS, SES, and MSS can be rendered using GPU-based ray casting  [LBPH10]. Amira also provides alignment and grid-based sampling tools to effectively visualize the flexibility of molecules using iso-surfaces or volume rendering. In general, however, it is often difficult to assess the commercial tools technically due to their closed source. The last category contains web-based solutions for molecular rendering. Although such tools usually cannot integrate the latest stateof-the-art techniques covered by this report due to technical limitations, it is worthwhile to mention them because they are nowadays capable of interactive visualization of large molecular complexes. They can be embedded into web sites to provide specialized visualizations of entries in structural databases or results of structurerelated calculations.
One of the still most widely used web-based tools is the Java-applet Jmol  [jmo09]. It supports loading many file formats, rendering molecular surfaces, orbitals, schematic cartoons, and other features. OpenAstexViewer  [Har02]  is another Java-based program which aims to assist in structure-based drug design. It can be used both as applet and as a standalone application. Among other functions, it offers shaded molecular surfaces with transparency and property mapping. JSmol [HPR*13], an extension of Jmol that uses only HTML5 and JavaScript instead of Java, is currently under development. NGL viewer  [RH15]  and iview  [LLNW14].
Second, dealing with larger molecular systems; for this, new visual representations c 2016 The Authors Computer Graphics Forum published by John Wiley & Sons Ltd. of the data will be required and, in consequence, a complete visual language for biomolecular systems needs to be established. This includes abstractions that go far beyond the level of single molecules. Today atomistic representations are available for viruses; soon small bacterial organisms will be modelled in atomic detail. When zooming out from a molecule to see the entire structure at some point, all the molecules in the model create a salt-and-pepper noise pattern without any strong informative insight. Currently there is no abstraction mechanism that would meaningfully convey these levels, as for example cartoon representations do for secondary structures.
Acknowledgements This work was supported through grants from the  German Research Foundation (DFG)  as part of SFB  716 , the  Senate Department for Economics, Technology and Research in Berlin , the  Excellence Center at Linköping and Lund in Information Technology (ELLIIT) , the  French Agency for Research grants ExaViz  ( ANR-11-MONU-003 ) and  Dynamo  ( ANR-11-LABX-0011 ), the  Vienna Science and Technology Fund (WWTF)  through project  VRG11-010 , the  OeAD ICM  through project  CZ 17/2015 , the  Norway  grants project  NF-CZ07-MOP-2-086-2014  and the PhysioIllustration research project  218023  funded by the  Norwegian Research Council.
Each HREM image stack comprised up to1300 short axis images, produce by successive removal of 2 μ m (E14. 5-E16. 5) or 3 μ m (E18. 5-P0) sections. Mice were staged according to gestational age (Embryonic days) such that E0-0. 9 refers to the one-cell embryo stage, E14. 5 (Carnegie stage 22 in the human) marks the time when ventricular septation is complete and a dense trabecular meshwork is established within the ventricular cavities, E18. 5 is immediately before birth and P0, the neonatal mouse. Image processing and analysis of murine data. After optimization of grayscale mapping, HREM datasets were subscaled to 250 Mb for 3D volume-rendered reconstructions in OsiriX (an open source software package that permits interactive 3D visualisation; 64bit version) and scored by a single reader, blinded to murine group and stage, for the presence or absence of crypts on short-axis HREM stacks and cross-checked on 3D volumetric models of the lumens.
AMVL and PMVL length was measured using the open-poly region of interest tool while basal leaflet thickness was measured using linear calipers in OsiriX. Intra-observer variability was estimated for AMVL length and basal leaflet thickness (n = 35) in randomly-selected mouse embryo datasets by HREM. Intra-and inter-observer variability was estimated for myocardial crypt rulings (n = 40) in randomly-selected mouse embryo datasets by HREM using two readers blinded to each other's rulings (GC and CO).
Statistical analysis. Statistical analysis was performed in R programming language (version 3. 0. 1, The R Foundation for Statistical Computing) and illustrations reporting bullseye plots constructed in MATLAB ® (The MathWorks Inc. , Natick, MA, USA, R2012b). Descriptive data are expressed as mean ± standard deviation (s. d. ) except where otherwise stated. Distribution of data was assessed on histograms and using Shapiro-Wilk test. Categorical variables were compared by Fisher's exact tests. Normally distributed continuous variables pertaining to wildtype, HO and HET KO were compared using analysis of variance (ANOVA) with Tukey's post-hoc test. Intra-and inter-observer variability for crypt rulings was evaluated by the Cohen's Kappa statistic. Intraclass correlation coefficient was used to compare variability of repeated mitral leaflet measurements.
Acknowledgements The authors are indebted to the staff of the  Biological Services Division  of the former  MRC National Institute for Medical Research  (now The  Francis Crick Institute, Mill Hill laboratory ) and their counterparts at the  University Medical Center Hamburg-Eppendorf (Hamburg, Germany ) for care and maintenance of animals used in this study. HREM work is funded by the  Wellcome Trust  (# WT100160 ) supporting the strategic award programme 'Deciphering the  Mechanisms of Developmental Disorders ' , 2013-2018. G. C. is supported by the  National Institute for Health Research Rare Diseases Translational Research Collaboration  ( NIHR RD-TRC #532772 ), by the  European Society of Cardiology (ESC, EACVI)  and by  NIHR University College London Hospitals Biomedical Research Centre.
5 h. Fractions were precipitated in methanol and resuspended in gel loading buffer containing SDS. Proteins were detected by Western blot using the Odyssey imaging system (Li-cor Biosciences), with IRDye 800CW-and 680CW-conjugated secondary antibodies (Invitrogen). ␥-Tubulin levels were quantified using the Odyssey 2. 1 software: the Odyssey fluorescence system provides a linear relationship between signal intensity and antigen loading. Band intensities were measured with background subtraction, and the values were normalized relative to the total ␥-tubulin amount, corresponding to the sum of the intensities of all the fractions. For immunoprecipitation, gradient fractions were incubated with anti-GCP4 FL antibody for 2 h at 4 °C and with protein A magnetic beads (Dynal) for an additional 2 h.
Immunofluorescence-Cells grown on coverslips were fixed in Ϫ20 °C methanol and processed for immunofluorescence following conventional protocols. For detection, secondary antibodies conjugated to Alexa 488 or 568 (Invitrogen) were used. Fluorescence microscopy was performed on a widefield microscope (Axiovert 200 M; Carl Zeiss MicroImaging, Inc. ) equipped with a Z motor using a 40ϫ (Plan Neofluar, 1. 3 NA) or 63ϫ (Plan Apo, 1. 4 NA) objective. Images were acquired with a MRm camera and Axiovision software (Carl Zeiss MicroImaging, Inc. ). Image processing was done using Adobe Photoshop. Quantification of fluorescence was done using Axiovision; intensities at centrosomes and along spindle microtubules were measured on images acquired under constant exposure, within circular areas of 2 m Ø.
Fluorescence decays were recorded during a time interval of 20 ns. A 4 ϫ 4 binning was used to reduce the acquisition time. The MCP-PMT gain and the exposure time of the CCD were adjusted to avoid overexposure of the CCD. For each image, average fluorescence decay profiles were calculated, and the lifetimes were estimated by fitting these data with a mono-or bi-exponential function using the Levenberg-Marquart non-linear least squares estimation procedure. FRET efficiency was calculated by E ϭ 1 Ϫ ( DA )/( D ), with DA and D the mean lifetime of the donor in the presence or absence of the acceptor, respectively. Statistical comparisons were performed by Student's t test. The relation between the FRET efficiency and the distance r between the donor and the acceptor is given by equation E ϭ 1/ (r/R 0 ) 6 , with R 0 the Förster distance to obtain 50% of FRET.
Abstract. The enhancement of the stratospheric aerosol layer by volcanic eruptions induces a complex set of responses causing global and regional climate effects on a broad range of timescales. Uncertainties exist regarding the climatic response to strong volcanic forcing identified in coupled climate simulations that contributed to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). In order to better understand the sources of these model diversities, the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) has defined a coordinated set of idealized volcanic perturbation experiments to be carried out in alignment with the CMIP6 protocol. VolMIP provides a common stratospheric aerosol data set for each experiment to minimize differences in the applied volcanic forcing.
It defines a set of initial conditions to assess how internal climate variability contributes to determining the response. VolMIP will assess to what extent volcanically forced responses of the coupled ocean-atmosphere system are robustly simulated Published by Copernicus Publications on behalf of the European Geosciences Union. by state-of-the-art coupled climate models and identify the causes that limit robust simulated behavior, especially differences in the treatment of physical processes. This paper illustrates the design of the idealized volcanic perturbation experiments in the VolMIP protocol and describes the common aerosol forcing input data sets to be used.
Ensemble simulations sampling appropriate initial conditions and using the same volcanic forcing data set accounting for aerosol microphysical processes can help assess the signal-to-noise ratio and reduce uncertainties regarding the magnitude of post-eruption surface cooling  (Stoffel et al. , 2015). Careful sampling of initial climate conditions and the opportunity to consider volcanic eruptions of different strengths will allow VolMIP to better assess the relative role of internally generated and externally forced climate variability during periods of strong volcanic activity. VolMIP also contributes toward more reliable climate models by helping to identify the origins and consequences of systematic model biases affecting the dynamical climatic response to volcanic forcing. As a consequence, VolMIP will improve our confidence in the attribution and dynamical interpretation of reconstructed post-eruption regional features and provide insights into regional climate predictability during periods of strong volcanic forcing.
First, in Sect. 2 we provide a general description of the individual experiments included in the VolMIP protocol. Then, Sect. 3 provides details about the volcanic forcing for each experiment, including implementation and the forcing input data to be employed, for which this paper also serves as a reference. We discuss the limitations of VolMIP and potential follow-up research in Sect. 4, before summarizing the most relevant aspects of this initiative in Sect. 5.
Therefore, if, for instance, year Y of the control integration matches the desired conditions for the sampling, then the corresponding VolMIP simulation should start with restart data from year Y-1 of the control, for the day of the year specified for the experiment. Restart files from piControl must be accordingly selected and documented in the metadata of each simulation. If no restart data are available for the day of the year when the experiment starts, the control simulation must be re-run based on the first (backward in time) available restart file until the start date of the VolMIP experiment. All experiments except the decadal prediction experiment (Sect. 2. 1. 4) and the millennium cluster experiment (Sect. 2. 4. 4) maintain the same constant boundary forcing as the piControl integration, except for the volcanic forcing.
Implementation: general aspects VolMIP identifies a volcanic forcing data set for each experiment included in the protocol. The forcing parameters either are provided in terms of aerosol optical properties and distributions in time and space, as for the case when available data were identified as consensus reference, or can be calculated based on the tool and guidelines described in the protocol. The latter is the case for the volc-long and volc-cluster experiments that use forcing input data specifically generated for VolMIP. In addition, the implementation of the forcing (e. g. , spectral interpolation) is constrained to ensure that the imposed radiative forcing is consistent across the participating models. Surface albedo changes due to tephra deposition and indirect cloud radiative effects are neglected in all the experiments.
Therefore, VolMIP proposes for the volc-long and volccluster experiments forcing data sets constructed with the Easy Volcanic Aerosol (EVA) module version 1. 0  (Toohey et al. , 2016a). EVA provides an analytic representation of volcanic stratospheric aerosol forcing, prescribing the aerosol's radiative properties and primary modes of spatial and temporal variability. It creates volcanic forcing from a given eruption sulfur injection and latitude with an idealized spatial and temporal structure, constructed so as to produce good agreement with observations of the aerosol evolution following the 1991 Pinatubo eruption. Scaling to larger eruption magnitudes is performed in a manner similar to the forcing reconstruction of  Crowley and Unterman (2013). EVA is also used to construct the volcanic forcing data set used for the PMIP-past1000 experiment  (Kageyama et al.
, 2016). This augments the comparability between PMIP and VolMIP results concerning those eruptions that are featured by both MIPs. The EVA module outputs data resolved for given latitudes, heights, and wavelength bands. It therefore is an improvement compared to previously available volcanic forcing data sets for the pre-observational period. The forcing sets produced with EVA have the same format as the CMIP6 standard forcing files, i. e. , aerosol extinction, single scattering albedo, and asymmetry factor, all as a function of latitude, height, and the spectral bands of the model. The aerosol forcing produced by EVA decays to 0 around the tropopause. Therefore, differently from the forcing used in the volc-pinatubo experiments, no clipping of the forcing is necessary at the tropopause for experiments using EVA forcing.