146 research outputs found
Precipitation sensitivity to autoconversion rate in a numerical weather-prediction model
Aerosols are known to significantly affect cloud and precipitation patterns and intensity, but these interactions are ignored or very simplistically handled in climate and numerical weather-prediction (NWP) models. A suite of one-way nested Met Office Unified Model (UM) runs, with a single-moment bulk microphysics scheme was used to study two convective cases with contrasting characteristics observed in southern England. The autoconversion process that converts cloud water to rain is directly controlled by the assumed droplet number. The impact of changing cloud droplet number concentration (CDNC) on cloud and precipitation evolution can be inferred through changes to the autoconversion rate. This was done for a range of resolutions ranging from regional NWP (1 km) to high resolution (up to 100 m grid spacing) to evaluate the uncertainties due to changing CDNC as a function of horizontal grid resolution. The first case is characterised by moderately intense convective showers forming below an upper-level potential vorticity anomaly, with a low freezing level. The second case, characterised by one persistent stronger storm, is warmer with a deeper boundary layer. The colder case is almost insensitive to even large changes in CDNC, while in the warmer case a change of a factor of 3 in assumed CDNC affects total surface rain rate by ~17%. In both cases the sensitivity to CDNC is similar at all grid spacings <1 km. The contrasting sensitivities of these cases are induced by their contrasting ice-phase proportion. The ice processes in this model damp the precipitation sensitivity to CDNC. For this model the convection is sensitive to CDNC when the accretion process is more significant than the melting process and vice versa
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
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
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
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
Plasma steroid concentrations reflect acute disease severity and normalise during recovery in people hospitalised with COVID-19
Objective: Endocrine systems are disrupted in acute illness, and symptoms reported following coronavirus disease 2019 (COVID-19) are similar to those found with clinical hormone deficiencies. We hypothesised that people with severe acute COVID-19 and with post-COVID symptoms have glucocorticoid and sex hormone deficiencies.
Design/Patients: Samples were obtained for analysis from two UK multicentre cohorts during hospitalisation with COVID-19 (International Severe Acute Respiratory Infection Consortium/World Health Organisation [WHO] Clinical Characterization Protocol for Severe Emerging Infections in the UK study), and at follow-up 5 months after hospitalisation (Post-hospitalisation COVID-19 study).
Measurements: Plasma steroids were quantified by liquid chromatography–mass spectrometry. Steroid concentrations were compared against disease severity (WHO ordinal scale) and validated symptom scores. Data are presented as geometric mean (SD).
Results: In the acute cohort (n = 239, 66.5% male), plasma cortisol concentration increased with disease severity (cortisol 753.3 [1.6] vs. 429.2 [1.7] nmol/L in fatal vs. least severe, p < .001). In males, testosterone concentrations decreased with severity (testosterone 1.2 [2.2] vs. 6.9 [1.9] nmol/L in fatal vs. least severe, p < .001). In the follow-up cohort (n = 198, 62.1% male, 68.9% ongoing symptoms, 165 [121–192] days postdischarge), plasma cortisol concentrations (275.6 [1.5] nmol/L) did not differ with in-hospital severity, perception of recovery, or patient-reported symptoms. Male testosterone concentrations (12.6 [1.5] nmol/L) were not related to in-hospital severity, perception of recovery or symptom scores.
Conclusions: Circulating glucocorticoids in patients hospitalised with COVID-19 reflect acute illness, with a marked rise in cortisol and fall in male testosterone. These findings are not observed 5 months from discharge. The lack of association between hormone concentrations and common post-COVID symptoms suggests steroid insufficiency does not play a causal role in this condition
γCOP Is Required for Apical Protein Secretion and Epithelial Morphogenesis in Drosophila melanogaster
Background: There is increasing evidence that tissue-specific modifications of basic cellular functions play an important role in development and disease. To identify the functions of COPI coatomer-mediated membrane trafficking in Drosophila development, we were aiming to create loss-of-function mutations in the γCOP gene, which encodes a subunit of the COPI coatomer complex.
Principal Findings: We found that γCOP is essential for the viability of the Drosophila embryo. In the absence of zygotic γCOP activity, embryos die late in embryogenesis and display pronounced defects in morphogenesis of the embryonic epidermis and of tracheal tubes. The coordinated cell rearrangements and cell shape changes during tracheal tube morphogenesis critically depend on apical secretion of certain proteins. Investigation of tracheal morphogenesis in γCOP loss-of-function mutants revealed that several key proteins required for tracheal morphogenesis are not properly secreted into the apical lumen. As a consequence, γCOP mutants show defects in cell rearrangements during branch elongation, in tube dilation, as well as in tube fusion. We present genetic evidence that a specific subset of the tracheal defects in γCOP mutants is due to the reduced secretion of the Zona Pellucida protein Piopio. Thus, we identified a critical target protein of COPI-dependent secretion in epithelial tube morphogenesis.
Conclusions/Significance: These studies highlight the role of COPI coatomer-mediated vesicle trafficking in both general and tissue-specific secretion in a multicellular organism. Although COPI coatomer is generally required for protein secretion, we show that the phenotypic effect of γCOP mutations is surprisingly specific. Importantly, we attribute a distinct aspect of the γCOP phenotype to the effect on a specific key target protein
Recommended practices for computerized clinical decision support and knowledge management in community settings: a qualitative study
<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to identify recommended practices for computerized clinical decision support (CDS) development and implementation and for knowledge management (KM) processes in ambulatory clinics and community hospitals using commercial or locally developed systems in the U.S.</p> <p>Methods</p> <p>Guided by the Multiple Perspectives Framework, the authors conducted ethnographic field studies at two community hospitals and five ambulatory clinic organizations across the U.S. Using a Rapid Assessment Process, a multidisciplinary research team: gathered preliminary assessment data; conducted on-site interviews, observations, and field surveys; analyzed data using both template and grounded methods; and developed universal themes. A panel of experts produced recommended practices.</p> <p>Results</p> <p>The team identified ten themes related to CDS and KM. These include: 1) workflow; 2) knowledge management; 3) data as a foundation for CDS; 4) user computer interaction; 5) measurement and metrics; 6) governance; 7) translation for collaboration; 8) the meaning of CDS; 9) roles of special, essential people; and 10) communication, training, and support. Experts developed recommendations about each theme. The original Multiple Perspectives framework was modified to make explicit a new theoretical construct, that of Translational Interaction.</p> <p>Conclusions</p> <p>These ten themes represent areas that need attention if a clinic or community hospital plans to implement and successfully utilize CDS. In addition, they have implications for workforce education, research, and national-level policy development. The Translational Interaction construct could guide future applied informatics research endeavors.</p
Genome-wide imputation study identifies novel HLA locus for pulmonary fibrosis and potential role for auto-immunity in fibrotic idiopathic interstitial pneumonia.
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This article is open access.Fibrotic idiopathic interstitial pneumonias (fIIP) are a group of fatal lung diseases with largely unknown etiology and without definitive treatment other than lung transplant to prolong life. There is strong evidence for the importance of both rare and common genetic risk alleles in familial and sporadic disease. We have previously used genome-wide single nucleotide polymorphism data to identify 10 risk loci for fIIP. Here we extend that work to imputed genome-wide genotypes and conduct new RNA sequencing studies of lung tissue to identify and characterize new fIIP risk loci.We performed genome-wide genotype imputation association analyses in 1616 non-Hispanic white (NHW) cases and 4683 NHW controls followed by validation and replication (878 cases, 2017 controls) genotyping and targeted gene expression in lung tissue. Following meta-analysis of the discovery and replication populations, we identified a novel fIIP locus in the HLA region of chromosome 6 (rs7887 P meta = 3.7 × 10(-09)). Imputation of classic HLA alleles identified two in high linkage disequilibrium that are associated with fIIP (DRB1*15:01 P = 1.3 × 10(-7) and DQB1*06:02 P = 6.1 × 10(-8)). Targeted RNA-sequencing of the HLA locus identified 21 genes differentially expressed between fibrotic and control lung tissue (Q < 0.001), many of which are involved in immune and inflammatory response regulation. In addition, the putative risk alleles, DRB1*15:01 and DQB1*06:02, are associated with expression of the DQB1 gene among fIIP cases (Q < 1 × 10(-16)).We have identified a genome-wide significant association between the HLA region and fIIP. Two HLA alleles are associated with fIIP and affect expression of HLA genes in lung tissue, indicating that the potential genetic risk due to HLA alleles may involve gene regulation in addition to altered protein structure. These studies reveal the importance of the HLA region for risk of fIIP and a basis for the potential etiologic role of auto-immunity in fIIP.National Heart, Lung and Blood Institute
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Insight into volatile behavior at Nyamuragira volcano (D.R. Congo, Africa) through olivine-hosted melt inclusions
Author Posting. © American Geophysical Union, 2011. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry Geophysics Geosystems 12 (2011): Q0AB11, doi:10.1029/2011GC003699.We present new olivine-hosted melt inclusion volatile (H2O, CO2, S, Cl, F) and major element data from five historic eruptions of Nyamuragira volcano (1912, 1938, 1948, 1986, 2006). Host-olivine Mg#'s range from 71 to 84, with the exception of the 1912 sample (Mg# = 90). Inclusion compositions extend from alkali basalts to basanite-tephrites. Our results indicate inclusion entrapment over depths ranging from 3 to 5 km, which agree with independent estimates of magma storage depths (3–7 km) based on geophysical methods. Melt compositions derived from the 1986 and 2006 Nyamuragira tephra samples best represent pre-eruptive volatile compositions because these samples contain naturally glassy inclusions that underwent less post-entrapment modification than crystallized inclusions. Volatile concentrations of the 1986 and 2006 samples are as follows: H2O ranged from 0.6 to 1.4 wt %, CO2 from 350 to 1900 ppm, S from 1300 to 2400 ppm, Cl from 720 to 990 ppm, and F from 1500 to 2200 ppm. Based on FeOT and S data, we suggest that Nyamuragira magmas have higher fO2 (>NNO) than MORB. We estimate the total amount of sulfur dioxide (SO2) released from the 1986 (0.04 Mt) and 2006 (0.06 Mt) Nyamuragira eruptions using the petrologic method, whereby S contents in melt inclusions are scaled to erupted lava volumes. These amounts are significantly less than satellite-based SO2 emissions for the same eruptions (1986 = ∼1 Mt; 2006 = ∼2 Mt). Potential explanations for this observation are: (1) accumulation of a vapor phase within the magmatic system that is only released during eruptions, and/or (2) syn-eruptive gas release from unerupted magma.Funding for this
work was provided by NSF (grant EAR 0910795 (to SAC)
and grant EAR 0646694 (to AMS)), as well as the National
Geographic Society (grant 7698-04 (to SAC))
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