The Spectra of Red Quasars

We measure the spectral properties of a representative sub-sample of 187 quasars, drawn from the Parkes Half-Jansky, Flat-radio-spectrum Sample (PHFS). Quasars with a wide range of rest-frame optical/UV continuum slopes are included in the analysis: their colours range from 2 < B-K < 7. The median H-beta and [O III] emission-line equivalent widths of the red quasar sub-sample are a factor of ten weaker than those of the blue quasar sub-sample. Both the colours and the emission-line equivalent widths of the red quasars can be explained by the addition of a featureless red synchrotron continuum component to an otherwise normal blue quasar spectrum. The relative strengths of the blue and red components span two orders of magnitude at rest-frame 500nm. The blue component is weaker relative to the red component in low optical luminosity sources. This suggests that the fraction of accretion energy going into optical emission from the jet is greater in low luminosity quasars. This synchrotron model does not, however, fit around 10% of the quasars, which have both red colours and high equivalent width emission-lines. We hypothesise that these red, strong-lined quasars have intrinsically weak Big Blue Bumps. There is no discontinuity in spectral properties between the BL Lac objects in our sample and the other quasars. The synchrotron emission component only dominates the spectrum at longer wavelengths, so existing BL Lac surveys will be biassed against high redshift objects.Comment: 22 pages, 12 figures, accepted for publication in PASA. Data tables and composite spectra from the paper can be found at http://msowww.anu.edu.au/~pfrancis

Radio-Excess IRAS Galaxies: PMN/FSC Sample Selection

A sample of 178 extragalactic objects is defined by correlating the 60 micron IRAS FSC with the 5 GHz PMN catalog. Of these, 98 objects lie above the radio/far-infrared relation for radio-quiet objects. These radio-excess galaxies and quasars have a uniform distribution of radio excesses and appear to be a new population of active galaxies not present in previous radio/far-infrared samples. The radio-excess objects extend over the full range of far-infrared luminosities seen in extragalactic objects. Objects with small radio excesses are more likely to have far-infrared colors similar to starbursts, while objects with large radio excesses have far-infrared colors typical of pure AGN. Some of the most far-infrared luminous radio-excess objects have the highest far-infrared optical depths. These are good candidates to search for hidden broad line regions in polarized light or via near-infrared spectroscopy. Some low far-infrared luminosity radio-excess objects appear to derive a dominant fraction of their far-infrared emission from star formation, despite the dominance of the AGN at radio wavelengths. Many of the radio-excess objects have sizes likely to be smaller than the optical host, but show optically thin radio emission. We draw parallels between these objects and high radio luminosity Compact Steep-Spectrum (CSS) and GigaHertz Peaked-Spectrum (GPS) objects. Radio sources with these characteristics may be young AGN in which the radio activity has begun only recently. Alternatively, high central densities in the host galaxies may be confining the radio sources to compact sizes. We discuss future observations required to distinguish between these possibilities and determine the nature of radio-excess objects.Comment: Submitted to AJ. 44 pages, 11 figures. A version of the paper with higher quality figures is available from http://www.mso.anu.edu.au/~cdrake/PMNFSC/paperI

A role for nickel-iron cofactors in biological carbon monoxide and carbon dioxide utilization

Ni–Fe containing enzymes are involved in the biological utilization of carbon monoxide, carbon dioxide, and hydrogen. Interest in these enzymes has increased in recent years due to hydrogen fuel initiatives and concerns over development of new methods for CO2 sequestration. One Ni–Fe enzyme called carbon monoxide dehydrogenase (CODH) is a key player in the global carbon cycle and carries out the interconversion of the environmental pollutant CO and the greenhouse gas CO[subscript 2]. The Ni–Fe center responsible for this important chemistry, the C-cluster, has been the source of much controversy, but several recent structural studies have helped to direct the field toward a unifying mechanism. Here we summarize the current state of understanding of this fascinating metallocluster.National Institutes of Health (U.S.) (GM69857)Massachusetts Institute of Technology. Energy InitiativeHoward Hughes Medical Institute. Investigato

The global distribution and burden of dengue

Dengue is a systemic viral infection transmitted between humans by Aedes mosquitoes1. For some patients dengue is a life-threatening illness2. There are currently no licensed vaccines or specific therapeutics, and substantial vector control efforts have not stopped its rapid emergence and global spread3. The contemporary worldwide distribution of the risk of dengue virus infection4 and its public health burden are poorly known2,5. Here we undertake an exhaustive assembly of known records of dengue occurrence worldwide, and use a formal modelling framework to map the global distribution of dengue risk. We then pair the resulting risk map with detailed longitudinal information from dengue cohort studies and population surfaces to infer the public health burden of dengue in 2010. We predict dengue to be ubiquitous throughout the tropics, with local spatial variations in risk influenced strongly by rainfall, temperature and the degree of urbanisation. Using cartographic approaches, we estimate there to be 390 million (95 percent credible interval 284-528) dengue infections per year, of which 96 million (67-136) manifest apparently (any level of clinical or sub-clinical severity). This infection total is more than three times the dengue burden estimate of the World Health Organization2. Stratification of our estimates by country allows comparison with national dengue reporting, after taking into account the probability of an apparent infection being formally reported. The most notable differences are discussed. These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue. We anticipate that they will provide a starting point for a wider discussion about the global impact of this disease and will help guide improvements in disease control strategies using vaccine, drug and vector control methods and in their economic evaluation. [285

Asteroseismology and Spectropolarimetry of the Exoplanet Host Star λ Serpentis

The bright star lambda Ser hosts a hot Neptune with a minimum mass of 13.6 M &amp; OPLUS; and a 15.5 day orbit. It also appears to be a solar analog, with a mean rotation period of 25.8 days and surface differential rotation very similar to the Sun. We aim to characterize the fundamental properties of this system and constrain the evolutionary pathway that led to its present configuration. We detect solar-like oscillations in time series photometry from the Transiting Exoplanet Survey Satellite, and we derive precise asteroseismic properties from detailed modeling. We obtain new spectropolarimetric data, and we use them to reconstruct the large-scale magnetic field morphology. We reanalyze the complete time series of chromospheric activity measurements from the Mount Wilson Observatory, and we present new X-ray and ultraviolet observations from the Chandra and Hubble space telescopes. Finally, we use the updated observational constraints to assess the rotational history of the star and estimate the wind braking torque. We conclude that the remaining uncertainty on the stellar age currently prevents an unambiguous interpretation of the properties of lambda Ser, and that the rate of angular momentum loss appears to be higher than for other stars with a similar Rossby number. Future asteroseismic observations may help to improve the precision of the stellar age

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

Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score.

OBJECTIVE: To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). DESIGN: Prospective observational cohort study. SETTING: International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium-ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020. PARTICIPANTS: Adults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction. MAIN OUTCOME MEASURE: In-hospital mortality. RESULTS: 35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). CONCLUSIONS: An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations. STUDY REGISTRATION: ISRCTN66726260