A Heterogeneous Spatial Model for Soil Carbon Mapping of the Contiguous United States Using VNIR Spectra

The Rapid Carbon Assessment, conducted by the U.S. Department of Agriculture, was implemented in order to obtain a representative sample of soil organic carbon across the contiguous United States. In conjunction with a statistical model, the dataset allows for mapping of soil carbon prediction across the U.S., however there are two primary challenges to such an effort. First, there exists a large degree of heterogeneity in the data, whereby both the first and second moments of the data generating process seem to vary both spatially and for different land-use categories. Second, the majority of the sampled locations do not actually have lab measured values for soil organic carbon. Rather, visible and near-infrared (VNIR) spectra were measured at most locations, which act as a proxy to help predict carbon content. Thus, we develop a heterogeneous model to analyze this data that allows both the mean and the variance to vary as a function of space as well as land-use category, while incorporating VNIR spectra as covariates. After a cross-validation study that establishes the effectiveness of the model, we construct a complete map of soil organic carbon for the contiguous U.S. along with uncertainty quantification

Nonparametric Dark Energy Reconstruction from Supernova Data

Understanding the origin of the accelerated expansion of the Universe poses one of the greatest challenges in physics today. Lacking a compelling fundamental theory to test, observational efforts are targeted at a better characterization of the underlying cause. If a new form of mass-energy, dark energy, is driving the acceleration, the redshift evolution of the equation of state parameter w(z) will hold essential clues as to its origin. To best exploit data from observations it is necessary to develop a robust and accurate reconstruction approach, with controlled errors, for w(z). We introduce a new, nonparametric method for solving the associated statistical inverse problem based on Gaussian Process modeling and Markov chain Monte Carlo sampling. Applying this method to recent supernova measurements, we reconstruct the continuous history of w out to redshift z=1.5.Comment: 4 pages, 2 figures, accepted for publication in Physical Review Letter

Nonparametric Reconstruction of the Dark Energy Equation of State

A basic aim of ongoing and upcoming cosmological surveys is to unravel the mystery of dark energy. In the absence of a compelling theory to test, a natural approach is to better characterize the properties of dark energy in search of clues that can lead to a more fundamental understanding. One way to view this characterization is the improved determination of the redshift-dependence of the dark energy equation of state parameter, w(z). To do this requires a robust and bias-free method for reconstructing w(z) from data that does not rely on restrictive expansion schemes or assumed functional forms for w(z). We present a new nonparametric reconstruction method that solves for w(z) as a statistical inverse problem, based on a Gaussian Process representation. This method reliably captures nontrivial behavior of w(z) and provides controlled error bounds. We demonstrate the power of the method on different sets of simulated supernova data; the approach can be easily extended to include diverse cosmological probes.Comment: 16 pages, 11 figures, accepted for publication in Physical Review

Nonparametric Reconstruction of the Dark Energy Equation of State from Diverse Data Sets

The cause of the accelerated expansion of the Universe poses one of the most fundamental questions in physics today. In the absence of a compelling theory to explain the observations, a first task is to develop a robust phenomenology. If the acceleration is driven by some form of dark energy, then, the phenomenology is determined by the dark energy equation of state w. A major aim of ongoing and upcoming cosmological surveys is to measure w and its time dependence at high accuracy. Since w(z) is not directly accessible to measurement, powerful reconstruction methods are needed to extract it reliably from observations. We have recently introduced a new reconstruction method for w(z) based on Gaussian process modeling. This method can capture nontrivial time-dependences in w(z) and, most importantly, it yields controlled and unbaised error estimates. In this paper we extend the method to include a diverse set of measurements: baryon acoustic oscillations, cosmic microwave background measurements, and supernova data. We analyze currently available data sets and present the resulting constraints on w(z), finding that current observations are in very good agreement with a cosmological constant. In addition we explore how well our method captures nontrivial behavior of w(z) by analyzing simulated data assuming high-quality observations from future surveys. We find that the baryon acoustic oscillation measurements by themselves already lead to remarkably good reconstruction results and that the combination of different high-quality probes allows us to reconstruct w(z) very reliably with small error bounds.Comment: 14 pages, 9 figures, 3 table

The transcription factors Pap1 and Prr1 collaborate to activate antioxidant, but not drug tolerance, genes in response to H2O2

In response to hydrogen peroxide (H2O2), the transcription factor Pap1 from Schizosaccharomyces pombe regulates transcription of genes required for adaptation to oxidative stress and for tolerance to toxic drugs. H2O2 induces oxidation of Pap1, its nuclear accumulation and expression of more than fifty Pap1-dependent genes. Oxidation and nuclear accumulation of Pap1 can also be accomplished by genetic inhibition of thioredoxin reductase. Furthermore, genetic alteration of the nuclear export pathway, or mutations in Pap1 nuclear export signal trigger nuclear accumulation of reduced Pap1. We show here that a subset of Pap1-dependent genes, such as those coding for the efflux pump Caf5, the ubiquitin-like protein Obr1 or the dehydrogenase SPCC663.08c, only require nuclear Pap1 for activation, whereas another subset of genes, those coding for the antioxidants catalase, sulfiredoxin or thioredoxin reductase, do need oxidized Pap1 to form a heterodimer with the constitutively nuclear transcription factor Prr1. The ability of Pap1 to bind and activate drug tolerance promoters is independent on Prr1, whereas its affinity for the antioxidant promoters is significantly enhanced upon association with Prr1. This finding suggests that the activation of both antioxidant and drug resistance genes in response to oxidative stress share a common inducer, H2O2, but alternative effectors

Clinical value of next generation sequencing of plasma cell-free DNA in gastrointestinal stromal tumors

[Background] Gastrointestinal stromal tumor (GIST) initiation and evolution is commonly framed by KIT/PDGFRA oncogenic activation, and in later stages by the polyclonal expansion of resistant subpopulations harboring KIT secondary mutations after the onset of imatinib resistance. Thus, circulating tumor (ct)DNA determination is expected to be an informative non-invasive dynamic biomarker in GIST patients.[Methods] We performed amplicon-based next-generation sequencing (NGS) across 60 clinically relevant genes in 37 plasma samples from 18 GIST patients collected prospectively. ctDNA alterations were compared with NGS of matched tumor tissue samples (obtained either simultaneously or at the time of diagnosis) and cross-validated with droplet digital PCR (ddPCR).[Results] We were able to identify cfDNA mutations in five out of 18 patients had detectable in at least one timepoint. Overall, NGS sensitivity for detection of cell-free (cf)DNA mutations in plasma was 28.6%, showing high concordance with ddPCR confirmation. We found that GIST had relatively low ctDNA shedding, and mutations were at low allele frequencies. ctDNA was detected only in GIST patients with advanced disease after imatinib failure, predicting tumor dynamics in serial monitoring. KIT secondary mutations were the only mechanism of resistance found across 10 imatinib-resistant GIST patients progressing to sunitinib or regorafenib.[Conclusions] ctDNA evaluation with amplicon-based NGS detects KIT primary and secondary mutations in metastatic GIST patients, particularly after imatinib progression. GIST exhibits low ctDNA shedding, but ctDNA monitoring, when positive, reflects tumor dynamics.This research is supported by a Fero Fellowship Award (C.S.), Asociación Española Contra el Cáncer (J.P. Barcelona) (C.S.), and ISCIII PI16/01371 (C.S.). C.S. and A.V. acknowledge to the Cellex Foundation for providing facilities and equipment

Genome-Wide Screen of Genes Required for Caffeine Tolerance in Fission Yeast

Isabel A. Calvo et al...Background An excess of caffeine is cytotoxic to all eukaryotic cell types. We aim to study how cells become tolerant to a toxic dose of this drug, and the relationship between caffeine and oxidative stress pathways. Methodology/Principal Findings We searched for Schizosaccharomyces pombe mutants with inhibited growth on caffeine-containing plates. We screened a collection of 2,700 haploid mutant cells, of which 98 were sensitive to caffeine. The genes mutated in these sensitive clones were involved in a number of cellular roles including the H2O2-induced Pap1 and Sty1 stress pathways, the integrity and calcineurin pathways, cell morphology and chromatin remodeling. We have investigated the role of the oxidative stress pathways in sensing and promoting survival to caffeine. The Pap1 and the Sty1 pathways are both required for normal tolerance to caffeine, but only the Sty1 pathway is activated by the drug. Cells lacking Pap1 are sensitive to caffeine due to the decreased expression of the efflux pump Hba2. Indeed, ?hba2 cells are sensitive to caffeine, and constitutive activation of the Pap1 pathway enhances resistance to caffeine in an Hba2-dependent manner. Conclusions/Significance With our caffeine-sensitive, genome-wide screen of an S. pombe deletion collection, we have demonstrated the importance of some oxidative stress pathway components on wild-type tolerance to the drug.This work was supported by Direccion General de Investigacion of Spain Grant BFU2006-02610, and by the Spanish program Consolider-Ingenio 2010 Grant CSD 2007-0020, to E.H.Peer reviewe

Towards a typology for constrained climate model forecasts

In recent years several methodologies have been developed to combine and interpret ensembles of climate models with the aim of quantifying uncertainties in climate projections. Constrained climate model forecasts have been generated by combining various choices of metrics used to weight individual ensemble members, with diverse approaches to sampling the ensemble. The forecasts obtained are often significantly different, even when based on the same model output. Therefore, a climate model forecast classification system can serve two roles: to provide a way for forecast producers to self-classify their forecasts; and to provide information on the methodological assumptions underlying the forecast generation and its uncertainty when forecasts are used for impacts studies. In this review we propose a possible classification system based on choices of metrics and sampling strategies. We illustrate the impact of some of the possible choices in the uncertainty quantification of large scale projections of temperature and precipitation changes, and briefly discuss possible connections between climate forecast uncertainty quantification and decision making approaches in the climate change context

Targeting transcription regulation in cancer with a covalent CDK7 inhibitor

Tumour oncogenes include transcription factors that co-opt the general transcriptional machinery to sustain the oncogenic state, but direct pharmacological inhibition of transcription factors has so far proven difficult. However, the transcriptional machinery contains various enzymatic cofactors that can be targeted for the development of new therapeutic candidates, including cyclin-dependent kinases (CDKs). Here we present the discovery and characterization of a covalent CDK7 inhibitor, THZ1, which has the unprecedented ability to target a remote cysteine residue located outside of the canonical kinase domain, providing an unanticipated means of achieving selectivity for CDK7. Cancer cell-line profiling indicates that a subset of cancer cell lines, including human T-cell acute lymphoblastic leukaemia (T-ALL), have exceptional sensitivity to THZ1. Genome-wide analysis in Jurkat T-ALL cells shows that THZ1 disproportionally affects transcription of RUNX1 and suggests that sensitivity to THZ1 may be due to vulnerability conferred by the RUNX1 super-enhancer and the key role of RUNX1 in the core transcriptional regulatory circuitry of these tumour cells. Pharmacological modulation of CDK7 kinase activity may thus provide an approach to identify and treat tumour types that are dependent on transcription for maintenance of the oncogenic state.National Institutes of Health (U.S.) (Grant HG002668)National Institutes of Health (U.S.) (Grant CA109901

Beyond equilibrium climate sensitivity

ISSN:1752-0908ISSN:1752-089