309 research outputs found

    Spectral Characterization of Analog Samples in Anticipation of OSIRIS-REx\u27s Arrival at Bennu

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    NASA\u27s Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer hide (OSIRIS-REx) mission successfully launched on September 8th, 2016. During its rendezvous with near-Earth asteroid (101955) Bennu beginning in 2018, OSIRIS-REx will characterize the asteroid\u27s physical, mineralogical, and chemical properties in an effort to globally map the properties of Bennu, a primitive carbonaceous asteroid, and choose a sampling location]. In preparation for these observations, analog samples were spectrally characterized across visible, near- and thermal-infrared wavelengths and were used in initial tests on mineral-phase-detection and abundance-determination software algorithms

    Spectral Characterization of Analog Samples in Anticipation of OSIRIS-REx's Arrival at Bennu

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    NASA's Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx) mission successfully launched on September 8th, 2016. During its rendezvous with near-Earth asteroid (101955) Bennu beginning in 2018, OSIRIS-REx will characterize the asteroid's physical, mineralogical, and chemical properties in an effort to globally map the properties of Bennu, a primitive carbonaceous asteroid, and choose a sampling location [e.g. 1]. In preparation for these observations, we spectrally characterized a suite of analog samples across visible, near- and thermal-infrared wavelengths and used these in initial tests of phase detection and abundance determination software algorithms. Here we present the thermal infrared laboratory measurements of the analog sample suite measured under asteroidlike conditions, which are relevant to the interpretation of spectroscopic observations by the OSIRIS-REx Thermal Emission Spectrometer (OTES) [2, 3]. This suite of laboratory measurements of asteroid analogs under asteroid-like conditions is the first of their kind

    Lessons Learned from Preparing OSIRIS-REx Spectral Analog Samples for Bennu

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    NASA\u27s OSIRIS-REx sample return mission launched on September 8th, 2016 to rendezvous with B-type hide asteroid (101955) Bennu in 2018. Type C and B asteroids have been linked to carbonaceous chondrites because of their similar visible - to - near infrared (VIS-NIR) spectral properties [e.g., 1,2]. The OSIRIS-REx Visible and Infrared Spectrometer (OVIRS) and the Thermal Emission Spectrometer (OTES) will make spectroscopic observations of Bennu during the encounter. Constraining the presence or absence of hydrous minerals (e.g., Ca-carbonate, phyllosilicates) and organic molecules will be key to characterizing Bennu [3] prior to sample site selection. The goal of this study was to develop a suite of analog and meteorite samples and obtain their spectral properties over the wavelength ranges of OVIRS (0.4- 4.3 micrometer) and OTES (5.0-50 micrometer). These spectral data were used to validate the mission science-data processing system. We discuss the reasoning behind the study and share lessons learne

    Critical Exponents, Hyperscaling and Universal Amplitude Ratios for Two- and Three-Dimensional Self-Avoiding Walks

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    We make a high-precision Monte Carlo study of two- and three-dimensional self-avoiding walks (SAWs) of length up to 80000 steps, using the pivot algorithm and the Karp-Luby algorithm. We study the critical exponents ν\nu and 2Δ4γ2\Delta_4 -\gamma as well as several universal amplitude ratios; in particular, we make an extremely sensitive test of the hyperscaling relation dν=2Δ4γd\nu = 2\Delta_4 -\gamma. In two dimensions, we confirm the predicted exponent ν=3/4\nu = 3/4 and the hyperscaling relation; we estimate the universal ratios  / =0.14026±0.00007\ / \ = 0.14026 \pm 0.00007,  / =0.43961±0.00034\ / \ = 0.43961 \pm 0.00034 and Ψ=0.66296±0.00043\Psi^* = 0.66296 \pm 0.00043 (68\% confidence limits). In three dimensions, we estimate ν=0.5877±0.0006\nu = 0.5877 \pm 0.0006 with a correction-to-scaling exponent Δ1=0.56±0.03\Delta_1 = 0.56 \pm 0.03 (subjective 68\% confidence limits). This value for ν\nu agrees excellently with the field-theoretic renormalization-group prediction, but there is some discrepancy for Δ1\Delta_1. Earlier Monte Carlo estimates of ν\nu, which were  ⁣0.592\approx\! 0.592, are now seen to be biased by corrections to scaling. We estimate the universal ratios  / =0.1599±0.0002\ / \ = 0.1599 \pm 0.0002 and Ψ=0.2471±0.0003\Psi^* = 0.2471 \pm 0.0003; since Ψ>0\Psi^* > 0, hyperscaling holds. The approach to Ψ\Psi^* is from above, contrary to the prediction of the two-parameter renormalization-group theory. We critically reexamine this theory, and explain where the error lies.Comment: 87 pages including 12 figures, 1029558 bytes Postscript (NYU-TH-94/09/01

    Renormalized couplings and scaling correction amplitudes in the N-vector spin models on the sc and the bcc lattices

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    For the classical N-vector model, with arbitrary N, we have computed through order \beta^{17} the high temperature expansions of the second field derivative of the susceptibility \chi_4(N,\beta) on the simple cubic and on the body centered cubic lattices. (The N-vector model is also known as the O(N) symmetric classical spin Heisenberg model or, in quantum field theory, as the lattice O(N) nonlinear sigma model.) By analyzing the expansion of \chi_4(N,\beta) on the two lattices, and by carefully allowing for the corrections to scaling, we obtain updated estimates of the critical parameters and more accurate tests of the hyperscaling relation d\nu(N) +\gamma(N) -2\Delta_4(N)=0 for a range of values of the spin dimensionality N, including N=0 [the self-avoiding walk model], N=1 [the Ising spin 1/2 model], N=2 [the XY model], N=3 [the classical Heisenberg model]. Using the recently extended series for the susceptibility and for the second correlation moment, we also compute the dimensionless renormalized four point coupling constants and some universal ratios of scaling correction amplitudes in fair agreement with recent renormalization group estimates.Comment: 23 pages, latex, no figure

    Co-regulation map of the human proteome enables identification of protein functions

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    This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData availability: All mass spectrometry raw files generated in-house have been deposited in the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository36 with the dataset identifier PXD008888. The co-regulation map is hosted on our website at www.proteomeHD.net, and pair-wise co-regulation scores are available through STRING (https://string-db.org). A network of the top 0.5% co-regulated protein pairs can be explored interactively on NDEx (https://doi.org/10.18119/N9N30Q).Code availability: Data analysis was performed in R 3.5.1. R scripts and input files required to reproduce the results of this manuscript are available in the following GitHub repository: https://github.com/Rappsilber-Laboratory/ProteomeHD. R scripts related specifically to the benchmarking of the treeClust algorithm using synthetic data are available in the following GitHub repository: https://github.com/Rappsilber-Laboratory/treeClust-benchmarking. The R package data.table was used for fast data processing. Figures were prepared using ggplot2, gridExtra, cowplot and viridis.Note that the title of the AAM is different from the published versionThe annotation of protein function is a longstanding challenge of cell biology that suffers from the sheer magnitude of the task. Here we present ProteomeHD, which documents the response of 10,323 human proteins to 294 biological perturbations, measured by isotope-labelling mass spectrometry. We reveal functional associations between human proteins using the treeClust machine learning algorithm, which we show to improve protein co-regulation analysis due to robust selectivity for close linear relationships. Our co-regulation map identifies a functional context for many uncharacterized proteins, including microproteins that are difficult to study with traditional methods. Co-regulation also captures relationships between proteins which do not physically interact or co-localize. For example, co-regulation of the peroxisomal membrane protein PEX11β with mitochondrial respiration factors led us to discover a novel organelle interface between peroxisomes and mitochondria in mammalian cells. The co-regulation map can be explored at www.proteomeHD.net .Biotechnology & Biological Sciences Research Council (BBSRC)European Commissio

    TRY plant trait database - enhanced coverage and open access

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    Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    Influence of bevacizumab, sunitinib and sorafenib as single agents or in combination on the inhibitory effects of VEGF on human dendritic cell differentiation from monocytes

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    Vascular endothelial growth factor (VEGF) inhibits differentiation and maturation of dendritic cells (DC), suggesting a potential immunosuppressive role for this proangiogenic factor. Bevacizumab, sorafenib and sunitinib target VEGF-mediated angiogenesis and are active against several types of cancer, but their effects on the immune system are poorly understood. In this study, VEGF and supernatants of renal carcinoma cell lines cultured under hypoxia were found to alter the differentiation of human monocytes to DC. Resulting DC showed impaired activity, as assessed by the alloreactive mixed T-lymphocyte reaction. Bevacizumab and sorafenib, but not sunitinib, reversed the inhibitory effects of VEGF, but not of those mediated by tumour supernatants. Dendritic cells matured under the influence of VEGF expressed less human leukocyte antigen-DR (HLA-DR) and CD86, and this effect was restored by bevacizumab and sorafenib. Finally, tumour-cell supernatants decreased interleukin-12 (IL-12) production by mature DC, and such inhibition was not restored by any of the tested drugs, delivered either as single agents or in combination. The deleterious effects of tumour-cell supernatants were mainly mediated by thermostable molecules distinct from VEGF. These results indicate that inhibition of the differentiation of monocytes to DC is a multifactorial effect, and that they support the development of combinations of angiogenesis inhibitors with immunological modulators

    No common denominator for breast cancer lymph node metastasis

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    The axillary lymph node status is the most powerful prognostic factor for breast cancer patients to date. The molecular mechanisms that control lymph node metastasis, however, remain poorly understood. To define patterns of genes or gene regulatory pathways that drive breast cancer lymph node metastasis, we compared the gene expression profiles of 15 primary breast carcinomas and their matching lymph node metastases using microarrays. In general, primary breast carcinomas and lymph node metastases do not differ at the transcriptional level by a common subset of genes. No classifier or single gene discriminating the group of primary tumours from those of the lymph node metastases could be identified. Also, in a series of 295 breast tumours, no classifier predicting lymph node metastasis could be developed. However, subtle differences in the expression of genes involved in extracellular-matrix organisation and growth factor signalling are detected in individual pairs of matching primary and metastatic tumours. Surprisingly, however, different sets of these genes are either up- or downregulated in lymph node metastases. Our data suggest that breast carcinomas do not use a shared gene set to accomplish lymph node metastasis

    Limits of JT gravity

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    We construct various limits of JT gravity, including Newton-Cartan and Carrollian versions of dilaton gravity in two dimensions as well as a theory on the three-dimensional light cone. In the BF formulation our boundary conditions relate boundary connection with boundary scalar, yielding as boundary action the particle action on a group manifold or some Hamiltonian reduction thereof. After recovering in our formulation the Schwarzian for JT, we show that AdS-Carroll gravity yields a twisted warped boundary action. We comment on numerous applications and generalizations.Comment: 41 pages, 3 figures, 1 table; v2: Matches published version + Footnote 11; v3: Corrected typo in Carrollian/Galilean generalized dilaton potentia
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