126 research outputs found
Feasibility of omega-3 fatty acid supplementation as an adjunct therapy for people with chronic obstructive pulmonary disease: study protocol for a randomized controlled trial
There is evidence to support the use of supplementation with long-chain omega-3 polyunsaturated fatty acids (LCn-3PUFA) from oily fish or fish oil for the treatment of various inflammatory diseases such as rheumatoid arthritis. Chronic obstructive pulmonary disease (COPD) is a progressive, terminal disease characterized by persistent airflow limitation, lung and systemic inflammation. To date, one randomized controlled trial has been published that assessed the efficacy of LCn-3PUFA in people with this condition. The aim of this article is to discuss the feasibility of conducting a trial to evaluate fish oil supplementation as adjunct therapy in people with COPD.The study is supported by a University of South Australia, Division of Health Sciences grant (DRDG 2011 (round 2))
Investigating the Atmospheric Mass Loss of the Kepler-105 Planets Straddling the Radius Gap
An intriguing pattern among exoplanets is the lack of detected planets
between approximately R and R. One proposed
explanation for this "radius gap" is the photoevaporation of planetary
atmospheres, a theory that can be tested by studying individual planetary
systems. Kepler-105 is an ideal system for such testing due to the ordering and
sizes of its planets. Kepler-105 is a sun-like star that hosts two planets
straddling the radius gap in a rare architecture with the larger planet closer
to the host star ( R, days, R, days). If photoevaporation sculpted the
atmospheres of these planets, then Kepler-105b would need to be much more
massive than Kepler-105c to retain its atmosphere, given its closer proximity
to the host star. To test this hypothesis, we simultaneously analyzed radial
velocities (RVs) and transit timing variations (TTVs) of the Kepler-105 system,
measuring disparate masses of M ( g cm) and M ( g cm). Based on these masses, the difference in gas
envelope content of the Kepler-105 planets could be entirely due to
photoevaporation (in 76\% of scenarios), although other mechanisms like
core-powered mass loss could have played a role for some planet albedos.Comment: 14 pages, 3 figures, 2 table
Towards \u3csup\u3e26\u3c/sup\u3eNa via (d,p) with SHARC and TIGRESS and a novel zero-degree detector
Nucleon transfer experiments have in recent years begun to be exploited in the study of nuclei far from stability, using radioactive beams in inverse kinematics. New techniques are still being developed in order to perform these experiments. The present experiment is designed to study the odd-odd nucleus 26Na which has a high density of states and therefore requires gamma-ray detection to distinguish between them. The experiment employed an intense beam of up to 3×107 pps of 25Na at 5.0 MeV/nucleon from the ISAC-II facility at triumf. The new silicon array SHARC was used for the first time and was coupled to the segmented clover gamma-ray array TIGRESS. A novel thin plastic scintillator detector was employed at zero degrees to identify and reject reactions occurring on the carbon component of the (CD)2 target. The efficiency of the background rejection using this detector is described with respect to the proton and gamma-ray spectra from the (d,p) reaction. © Published under licence by IOP Publishing Ltd
The TESS-Keck Survey: Science Goals and Target Selection
Space-based transit missions such as Kepler and TESS have demonstrated that
planets are ubiquitous. However, the success of these missions heavily depends
on ground-based radial velocity (RV) surveys, which combined with transit
photometry can yield bulk densities and orbital properties. While most Kepler
host stars are too faint for detailed follow-up observations, TESS is detecting
planets orbiting nearby bright stars that are more amenable to RV
characterization. Here we introduce the TESS-Keck Survey (TKS), an RV program
using ~100 nights on Keck/HIRES to study exoplanets identified by TESS. The
primary survey aims are investigating the link between stellar properties and
the compositions of small planets; studying how the diversity of system
architectures depends on dynamical configurations or planet multiplicity;
identifying prime candidates for atmospheric studies with JWST; and
understanding the role of stellar evolution in shaping planetary systems. We
present a fully-automated target selection algorithm, which yielded 103 planets
in 86 systems for the final TKS sample. Most TKS hosts are inactive,
solar-like, main-sequence stars (4500 K < Teff < 6000 K) at a wide range of
metallicities. The selected TKS sample contains 71 small planets (Rp < 4 Re),
11 systems with multiple transiting candidates, 6 sub-day period planets and 3
planets that are in or near the habitable zone of their host star. The target
selection described here will facilitate the comparison of measured planet
masses, densities, and eccentricities to predictions from planet population
models. Our target selection software is publicly available (at
https://github.com/ashleychontos/sort-a-survey) and can be adapted for any
survey which requires a balance of multiple science interests within a given
telescope allocation.Comment: 23 pages, 10 figures, 5 table
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
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