232 research outputs found

    Quantitative Multi-Parametric Evaluation of Centrosome Declustering Drugs: Centrosome Amplification, Mitotic Phenotype, Cell Cycle and Death

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    Unlike normal cells, cancer cells contain amplified centrosomes and rely on centrosome clustering mechanisms to form a pseudobipolar spindle that circumvents potentially fatal spindle multipolarity (MP). Centrosome clustering also promotes lowgrade chromosome missegregation, which can drive malignant transformation and tumor progression. Putative ‘centrosome declustering drugs’ represent a cancer cell-specific class of chemotherapeutics that produces a common phenotype of centrosome declustering and spindle MP. However, differences between individual agents in terms of efficacy and phenotypic nuances remain unexplored. Herein, we have developed a conceptual framework for the quantitative evaluation of centrosome declustering drugs by investigating their impact on centrosomes, clustering, spindle polarity, cell cycle arrest, and death in various cancer cell lines at multiple drug concentrations over time. Surprisingly, all centrosome declustering drugs evaluated in our study were also centrosome-amplifying drugs to varying extents. Notably, all declustering drugs induced spindle MP, and the peak extent of MP positively correlated with the induction of hypodiploid DNA-containing cells. Our data suggest acentriolar spindle pole amplification as a hitherto undescribed activity of some declustering drugs, resulting in spindle MP in cells that may not have amplified centrosomes. In general, declustering drugs were more toxic to cancer cell lines than non-transformed ones, with some exceptions. Through a comprehensive description and quantitative analysis of numerous phenotypes induced by declustering drugs, we propose a novel framework for the assessm

    A Method for Upscaling In Situ Soil Moisture Measurements to Satellite Footprint Scale Using Random Forests

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    Geophysical products generated from remotely sensed data require validation to evaluate their accuracy. Typically in situ measurements are used for validation, as is the case for satellite-derived soil moisture products. However, a large disparity in scales often exists between in situ measurements (covering meters to 10 s of meters) and satellite footprints (often hundreds of meters to several kilometers), making direct comparison difficult. Before using in situ measurements for validation, they must be “upscaled” to provide the mean soil moisture within the satellite footprint. There are a number of existing upscaling methods previously applied to soil moisture measurements, but many place strict requirements on the number and spatial distribution of soil moisture sensors difficult to achieve with permanent/semipermanent ground networks necessary for long-term validation efforts. A new method for upscaling is presented here, using Random Forests to fit a model between in situ measurements and a number of landscape parameters and variables impacting the spatial and temporal distributions of soil moisture. The method is specifically intended for validation of the NASA soil moisture active passive (SMAP) products at 36-, 9-, and 3-km scales. The method was applied to in situ data from the SoilSCAPE network in California, validated with data from the SMAPVEX12 campaign in Manitoba, Canada with additional verification from the TxSON network in Texas. For the SMAPVEX12 site, the proposed method was compared to extensive field measurements and was able to predict mean soil moisture over a large area more accurately than other upscaling approaches

    Reconciling the contribution of environmental and stochastic structuring of tropical forest diversity through the lens of imaging spectroscopy.

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    Both niche and stochastic dispersal processes structure the extraordinary diversity of tropical plants, but determining their relative contributions has proven challenging. We address this question using airborne imaging spectroscopy to estimate canopy β-diversity for an extensive region of a Bornean rainforest and challenge these data with models incorporating niches and dispersal. We show that remotely sensed and field-derived estimates of pairwise dissimilarity in community composition are closely matched, proving the applicability of imaging spectroscopy to provide β-diversity data for entire landscapes of over 1000 ha containing contrasting forest types. Our model reproduces the empirical data well and shows that the ecological processes maintaining tropical forest diversity are scale dependent. Patterns of β-diversity are shaped by stochastic dispersal processes acting locally whilst environmental processes act over a wider range of scales

    Timing and Reconstruction of the Most Recent Common Ancestor of the Subtype C Clade of Human Immunodeficiency Virus Type 1

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    Human immunodeficiency virus type 1 (HIV-1) subtype C is responsible for more than 55% of HIV-1 infections worldwide. When this subtype first emerged is unknown. We have analyzed all available gag (p17 and p24) and env (C2-V3) subtype C sequences with known sampling dates, which ranged from 1983 to 2000. The majority of these sequences come from the Karonga District in Malawi and include some of the earliest known subtype C sequences. Linear regression analyses of sequence divergence estimates (with four different approaches)were plotted against sample year to estimate the year in which there was zero divergence from the reconstructed ancestral sequence. Here we suggest that the most recent common ancestor of subtype C appeared in the mid- to late 1960s. Sensitivity analyses, by which possible biases due to oversampling from one district were explored, gave very similar estimates

    Maps of active layer thickness in northern Alaska by upscaling P-band polarimetric synthetic aperture radar retrievals

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    Extensive, detailed information on the spatial distribution of active layer thickness (ALT) in northern Alaska and how it evolves over time could greatly aid efforts to assess the effects of climate change on the region and also help to quantify greenhouse gas emissions generated due to permafrost thaw. For this reason, we have been developing high-resolution maps of ALT throughout northern Alaska. The maps are produced by upscaling from high-resolution swaths of estimated ALT retrieved from airborne P-band synthetic aperture radar (SAR) images collected for three different years. The upscaling was accomplished by using hundreds of thousands of randomly selected samples from the SAR-derived swaths of ALT to train a machine learning regression algorithm supported by numerous spatial data layers. In order to validate the maps, thousands of randomly selected samples of SAR-derived ALT were excluded from the training in order to serve as validation pixels; error performance calculations relative to these samples yielded root-mean-square errors (RMSEs) of 7.5–9.1 cm, with bias errors of magnitude under 0.1 cm. The maps were also compared to ALT measurements collected at a number of in situ test sites; error performance relative to the site measurements yielded RMSEs of approximately 11–12 cm and bias of 2.7–6.5 cm. These data are being used to investigate regional patterns and underlying physical controls affecting permafrost degradation in the tundra biome

    The stellar content of the Hamburg/ESO survey. III. Field horizontal-branch stars in the Galaxy

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    We present a sample of 8321 candidate Field Horizontal-Branch (FHB) stars selected by automatic spectral classification in the digital data base of the Hamburg/ESO objective-prism survey. The stars are distributed over 8225 square degrees of the southern sky, at |b| > 30 deg. The average distance of the sample, assuming that they are all FHB stars, is 9.8 kpc, and distances of up to ~30 kpc are reached. Moderate-resolution spectroscopic follow-up observations and UBV photometry of 125 test sample stars demonstrate that the contamination of the full candidate sample with main-sequence A-type stars is < 16%, while it would be up to 50% in a flux-limited sample at high galactic latitudes. Hence more than ~6800 of our FHB candidates are expected to be genuine FHB stars. The candidates are being used as distance probes for high-velocity clouds and for studies of the structure and kinematics of the Galactic halo.Comment: A&A, in pres
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