Impact of weather types on UK ambient particulate matter concentrations

Each year more than 29,000 premature deaths in the UK are linked to long term-exposure to ambient particulate matter (PM) with a diameter less than 2.5 μm (PM2.5). Many studies have focused on the long-term impacts of exposure to PM, but short-term increases in pollution can also exacerbate health effects, leading to deaths brought forward within exposed populations. This study investigates the impact of different atmospheric circulation patterns on UK PM2.5 concentrations and the relative contribution of local and transboundary pollutants to variations in PM2.5 concentrations. Daily mean PM2.5 observations from 42 UK background sites indicate that easterly, south-easterly and southerly wind directions and anticyclonic circulation patterns enhance background concentrations of PM2.5 at all UK sites by up to 12 μg m-3. Results from back trajectory analysis and the European Monitoring and Evaluation Programme for UK model (EMEP4UK) show this is due to the transboundary transport of pollutants from continental Europe. While back trajectories indicate under easterly, south-easterly and southerly flow 25–50% of the total accumulated primary PM2.5 emissions originate outside of the UK, with a very polluted footprint (0.25–0.35 μg m-2). Anticyclonic conditions, which occur frequently (21%), also lead to increases in PM2.5 concentrations (UK multi-annual mean 14.7 μg m-3). EMEP4UK results indicate this is likely due the build-up of local emissions due to slack winds. Under westerly and north-westerly flow 15–30% of the total accumulated primary PM2.5 emissions originate outside of the UK, and are much less polluted (0.1 μg m-2) with model results indicating transport of clean maritime air masses from the Atlantic. Results indicate that both wind-direction and stability under anticyclonic conditions are important in controlling ambient PM2.5 concentrations across the UK. There is also a strong dependence of high PM2.5 Daily Air Quality Index (DAQI) values on easterly, south-easterly and southerly wind-directions, with >70% of occurrences of observed 48–71+ μg m-3 concentrations occurring under these wind directions. While north-westerly and cyclonic conditions reduce PM2.5 concentrations at all sites by up to 8 μg m-3. PM2.5 DAQI values are also lowest under these conditions, with >80% of 0–11 μg m-3 concentrations and >50% of 12–23 μg m-3 concentrations observed during westerly, north-westerly and northerly wind directions. Indicating that these conditions are likely to be associated with a reduction in the potential health effects from exposure to ambient levels of PM2.5

Allele-Specific HLA Loss and Immune Escape in Lung Cancer Evolution

Immune evasion is a hallmark of cancer. Losing the ability to present neoantigens through human leukocyte antigen (HLA) loss may facilitate immune evasion. However, the polymorphic nature of the locus has precluded accurate HLA copy-number analysis. Here, we present loss of heterozygosity in human leukocyte antigen (LOHHLA), a computational tool to determine HLA allele-specific copy number from sequencing data. Using LOHHLA, we find that HLA LOH occurs in 40% of non-small-cell lung cancers (NSCLCs) and is associated with a high subclonal neoantigen burden, APOBEC-mediated mutagenesis, upregulation of cytolytic activity, and PD-L1 positivity. The focal nature of HLA LOH alterations, their subclonal frequencies, enrichment in metastatic sites, and occurrence as parallel events suggests that HLA LOH is an immune escape mechanism that is subject to strong microenvironmental selection pressures later in tumor evolution. Characterizing HLA LOH with LOHHLA refines neoantigen prediction and may have implications for our understanding of resistance mechanisms and immunotherapeutic approaches targeting neoantigens. Video Abstract [Figure presented] Development of the bioinformatics tool LOHHLA allows precise measurement of allele-specific HLA copy number, improves the accuracy in neoantigen prediction, and uncovers insights into how immune escape contributes to tumor evolution in non-small-cell lung cancer

Assessing costs of Indonesian fires and the benefits of restoring peatland

Deforestation and drainage has made Indonesian peatlands susceptible to burning. Large fires occur regularly, destroying agricultural crops and forest, emitting large amounts of CO2 and air pollutants, resulting in adverse health effects. In order to reduce fire, the Indonesian government has committed to restore 2.49 Mha of degraded peatland, with an estimated cost of US$3.2-7 billion. Here we combine fire emissions and land cover data to estimate the 2015 fires, the largest in recent years, resulted in economic losses totalling US$28 billion, whilst the six largest fire events between 2004 and 2015 caused a total of US$93.9 billion in economic losses. We estimate that if restoration had already been completed, the area burned in 2015 would have been reduced by 6$8.4 billion for 2004–2015, making it a cost-effective strategy for reducing the impacts of peatland fires to the environment, climate and human health

Large air quality and human health impacts due to Amazon forest and vegetation fires

Vegetation fires across the tropics emit fine particulate matter (PM2.5) to the atmosphere, degrading regional air quality and impacting human health. Extensive vegetation fires occur regularly across the Amazon basin, but there have been no detailed assessments of the impacts on air quality or human health. We used updated exposure-response relationships and a regional climate-chemistry model, evaluated against a comprehensive set of observational data, to provide the first in-depth assessment of the potential public health benefits due to fire prevention across the Amazon Basin. We focused on 2012, a year with emissions similar to the 11-year average (2008 to 2018). Vegetation fires contributed >80% of simulated dry season mean surface PM2.5 in the western Amazon region particularly in Bolivia and Brazilian states of Rondônia, Acre, and Mato Grosso. We estimate that the prevention of vegetation fires would have averted 16 800 (95UI: 16 300–17 400) premature deaths and 641 000 (95UI: 551 900–741 300) disability adjusted life years (DALYs) across South America, with 26% of the avoided health burden located within the Amazon Basin. The health benefits of fire prevention in the Amazon are comparable to those found in Equatorial Asia

Regulators of yeast endocytosis identified by systematic quantitative analysis

Endocytosis of receptors at the plasma membrane is controlled by a complex mechanism that includes clathrin, adaptors, and actin regulators. Many of these proteins are conserved in yeast yet lack observable mutant phenotypes, which suggests that yeast endocytosis may be subject to different regulatory mechanisms. Here, we have systematically defined genes required for internalization using a quantitative genome-wide screen that monitors localization of the yeast vesicle-associated membrane protein (VAMP)/synaptobrevin homologue Snc1. Genetic interaction mapping was used to place these genes into functional modules containing known and novel endocytic regulators, and cargo selectivity was evaluated by an array-based comparative analysis. We demonstrate that clathrin and the yeast AP180 clathrin adaptor proteins have a cargo-specific role in Snc1 internalization. We additionally identify low dye binding 17 (LDB17) as a novel conserved component of the endocytic machinery. Ldb17 is recruited to cortical actin patches before actin polymerization and regulates normal coat dynamics and actin assembly. Our findings highlight the conserved machinery and reveal novel mechanisms that underlie endocytic internalization

Discovery and Expansion of Gene Modules by Seeking Isolated Groups in a Random Graph Process

BACKGROUND: A central problem in systems biology research is the identification and extension of biological modules-groups of genes or proteins participating in a common cellular process or physical complex. As a result, there is a persistent need for practical, principled methods to infer the modular organization of genes from genome-scale data. RESULTS: We introduce a novel approach for the identification of modules based on the persistence of isolated gene groups within an evolving graph process. First, the underlying genomic data is summarized in the form of ranked gene-gene relationships, thereby accommodating studies that quantify the relevant biological relationship directly or indirectly. Then, the observed gene-gene relationship ranks are viewed as the outcome of a random graph process and candidate modules are given by the identifiable subgraphs that arise during this process. An isolation index is computed for each module, which quantifies the statistical significance of its survival time. CONCLUSIONS: The Miso (module isolation) method predicts gene modules from genomic data and the associated isolation index provides a module-specific measure of confidence. Improving on existing alternative, such as graph clustering and the global pruning of dendrograms, this index offers two intuitively appealing features: (1) the score is module-specific; and (2) different choices of threshold correlate logically with the resulting performance, i.e. a stringent cutoff yields high quality predictions, but low sensitivity. Through the analysis of yeast phenotype data, the Miso method is shown to outperform existing alternatives, in terms of the specificity and sensitivity of its predictions

Calculation of the relative metastabilities of proteins in subcellular compartments of Saccharomyces cerevisiae

[abridged] Background: The distribution of chemical species in an open system at metastable equilibrium can be expressed as a function of environmental variables which can include temperature, oxidation-reduction potential and others. Calculations of metastable equilibrium for various model systems were used to characterize chemical transformations among proteins and groups of proteins found in different compartments of yeast cells. Results: With increasing oxygen fugacity, the relative metastability fields of model proteins for major subcellular compartments go as mitochondrion, endoplasmic reticulum, cytoplasm, nucleus. In a metastable equilibrium setting at relatively high oxygen fugacity, proteins making up actin are predominant, but those constituting the microtubule occur with a low chemical activity. A reaction sequence involving the microtubule and spindle pole proteins was predicted by combining the known intercompartmental interactions with a hypothetical program of oxygen fugacity changes in the local environment. In further calculations, the most-abundant proteins within compartments generally occur in relative abundances that only weakly correspond to a metastable equilibrium distribution. However, physiological populations of proteins that form complexes often show an overall positive or negative correlation with the relative abundances of proteins in metastable assemblages. Conclusions: This study explored the outlines of a thermodynamic description of chemical transformations among interacting proteins in yeast cells. The results suggest that these methods can be used to measure the degree of departure of a natural biochemical process or population from a local minimum in Gibbs energy.Comment: 32 pages, 7 figures; supporting information is available at http://www.chnosz.net/yeas