Observations of Outflowing UV Absorbers in NGC 4051 with the Cosmic Origins Spectrograph

We present new Hubble Space Telescope (HST)/Cosmic Origins Spectrograph observations of the Narrow-Line Seyfert 1 galaxy NGC 4051. These data were obtained as part of a coordinated observing program including X-ray observations with the Chandra/High Energy Transmission Grating (HETG) Spectrometer and Suzaku. We detected nine kinematic components of UV absorption, which were previously identified using the HST/Space Telescope Imaging Spectrograph. None of the absorption components showed evidence for changes in column density or profile within the \sim 10 yr between the STIS and COS observations, which we interpret as evidence of 1) saturation, for the stronger components, or 2) very low densities, i.e., n_H < 1 cm^-3, for the weaker components. After applying a +200 km s^-1 offset to the HETG spectrum, we found that the radial velocities of the UV absorbers lay within the O VII profile. Based on photoionization models, we suggest that, while UV components 2, 5 and 7 produce significant O VII absorption, the bulk of the X-ray absorption detected in the HETG analysis occurs in more highly ionized gas. Moreover, the mass loss rate is dominated by high ionization gas which lacks a significant UV footprint.Comment: 41 pages, 10 Figures; accepted for publication in the Astrophysical Journa

Diffuse-Charge Dynamics in Electrochemical Systems

The response of a model micro-electrochemical system to a time-dependent applied voltage is analyzed. The article begins with a fresh historical review including electrochemistry, colloidal science, and microfluidics. The model problem consists of a symmetric binary electrolyte between parallel-plate, blocking electrodes which suddenly apply a voltage. Compact Stern layers on the electrodes are also taken into account. The Nernst-Planck-Poisson equations are first linearized and solved by Laplace transforms for small voltages, and numerical solutions are obtained for large voltages. The ``weakly nonlinear'' limit of thin double layers is then analyzed by matched asymptotic expansions in the small parameter $\epsilon = \lambda_D/L$, where $\lambda_D$ is the screening length and $L$ the electrode separation. At leading order, the system initially behaves like an RC circuit with a response time of $\lambda_D L / D$ (not $\lambda_D^2/D$), where $D$ is the ionic diffusivity, but nonlinearity violates this common picture and introduce multiple time scales. The charging process slows down, and neutral-salt adsorption by the diffuse part of the double layer couples to bulk diffusion at the time scale, $L^2/D$. In the ``strongly nonlinear'' regime (controlled by a dimensionless parameter resembling the Dukhin number), this effect produces bulk concentration gradients, and, at very large voltages, transient space charge. The article concludes with an overview of more general situations involving surface conduction, multi-component electrolytes, and Faradaic processes.Comment: 10 figs, 26 pages (double-column), 141 reference

Priority setting for new technologies in medicine: A transdisciplinary study

BACKGROUND: Decision makers in health care organizations struggle with how to set priorities for new technologies in medicine. Traditional approaches to priority setting for new technologies in medicine are insufficient and there is no widely accepted model that can guide decision makers. DISCUSSION: Daniels and Sabin have developed an ethically based account about how priority setting decisions should be made. We have developed an empirically based account of how priority setting decisions are made. In this paper, we integrate these two accounts into a transdisciplinary model of priority setting for new technologies in medicine that is both ethically and empirically based. SUMMARY: We have developed a transdisciplinary model of priority setting that provides guidance to decision makers that they can operationalize to help address priority setting problems in their institution

Children's Divergent Thinking Improves When They Understand False Beliefs

This research utilized longitudinal and cross sectional methods to investigate the relation between the development of a representational theory of mind and children's growing ability to search their own minds for appropriate problem solutions. In the first experiment 59 pre-school children were given three false-belief tasks and a divergent thinking task. Those children who passed false-belief tasks produced significantly more items, as well as more original items, in response to divergent thinking questions than those children who failed. This significant association persisted even when chronological age, verbal and nonverbal general ability were partialed out. In a second study 20 children who failed the false-belief tasks in the first experiment were re-tested three months later. Again, those who now passed the false-belief tasks were significantly better at the divergent thinking task than those who continued to fail. The associations between measures of divergent thinking and understanding false-beliefs remained significant when controlling for the covariates. Earlier divergent thinking scores did not predict false-belief understanding three months later. Instead, children who passed false-belief tasks on the second measure improved significantly in relation to their own earlier performance and improved significantly more than children who continued to fail. False-belief task performance was significantly correlated to the amount of intra-individual improvement in divergent thinking even when age, verbal and nonverbal skills were partialed out. These findings suggest that developments in common underlying skills are responsible for the improvement in understanding other minds and searching one's own. Changes in representational and executive skills are discussed as potential causes for the improvement

Reduction in carbon uptake during turn of the century drought in western North America

Fossil fuel emissions aside, temperate North America is a net sink of carbon dioxide at present¹⁻³. Year-to-year variations in this carbon sink are linked to variations in hydroclimate that affect net ecosystem productivity³,⁴. The severity and incidence of climatic extremes, including drought, have increased as a result of climate warming⁵⁻⁸. Here, we examine the effect of the turn of the century drought in western North America on carbon uptake in the region, using reanalysis data, remote sensing observations and data from global monitoring networks. We show that the area-integrated strength of the western North American carbon sink declined by 30–298 Tg C  yr⁻¹ during the 2000–2004 drought. We further document a pronounced drying of the terrestrial biosphere during this period, together with a reduction in river discharge and a loss of cropland productivity. We compare our findings with previous palaeoclimate reconstructions⁷ and show that the last drought of this magnitude occurred more than 800 years ago. Based on projected changes in precipitation and drought severity, we estimate that the present mid-latitude carbon sink of 177–623 Tg C yr⁻¹ in western North America could disappear by the end of the century.KEYWORDS: Hydrology, hydrogeology and limnology, Biogeochemistry, Climate scienc

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment