Emulation of a chemical transport model to assess air quality under future emission scenarios for the southwest of Western Australia

Simulation outputs from chemical transport models (CTMs) are essential to plan effective air quality policies. A key strength of these models is their ability to separate out source-specific components which facilitate the simulation of the potential impact of policy on future air quality. However, configuring and running these models is complex and computationally intensive, making the evaluation of multiple scenarios less accessible to many researchers and policy experts. The aim of this work is to present how Gaussian process emulation can provide a top-down approach to interrogating and interpreting the outputs from CTMs at minimal computational cost. A case study is presented (based on fine particle sources in the southwest of Western Australia) to illustrate how an emulator can be constructed to simultaneously evaluate changes in emissions from on-road transport and electricity sectors. This study demonstrates how emulation provides a flexible way of exploring local impacts of electric vehicles and wider regional effects of emissions from electricity generation. The potential for emulators to be applied to other settings involving air quality research is discussed

Characterising the impact of heatwaves on work-related injuries and illnesses in three Australian cities using a standard heatwave definition- Excess Heat Factor (EHF)

BACKGROUND AND AIMS:Heatwaves have potential health and safety implications for many workers, and heatwaves are predicted to increase in frequency and intensity with climate change. There is currently a lack of comparative evidence for the effects of heatwaves on workers' health and safety in different climates (sub-tropical and temperate). This study examined the relationship between heatwave severity (as defined by the Excess Heat Factor) and workers' compensation claims, to define impacts and identify workers at higher risk. METHODS:Workers' compensation claims data from Australian cities with temperate (Melbourne and Perth) and subtropical (Brisbane) climates for the years 2006-2016 were analysed in relation to heatwave severity categories (low and moderate/high severity) using time-stratified case-crossover models. RESULTS:Consistent impacts of heatwaves were observed in each city with either a protective or null effect during heatwaves of low-intensity while claims increased during moderate/high-severity heatwaves compared with non-heatwave days. The highest effect during moderate/high-severity heatwaves was in Brisbane (RR 1.45, 95% CI: 1.42-1.48). Vulnerable worker subgroups identified across the three cities included: males, workers aged under 34 years, apprentice/trainee workers, labour hire workers, those employed in medium and heavy strength occupations, and workers from outdoor and indoor industrial sectors. CONCLUSION:These findings show that work-related injuries and illnesses increase during moderate/high-severity heatwaves in both sub-tropical and temperate climates. Heatwave forecasts should signal the need for heightened heat awareness and preventive measures to minimise the risks to workers.Blesson M. Varghese, Adrian G. Barnett, Alana L. Hansen, Peng Bi, John Nairn, Shelley Rowett, Monika Nitschke, Scott Hanson-Easey, Jane S. Heyworth, Malcolm R. Sim, Dino L. Pisaniell

Breast cancer risk factors and survival by tumor subtype: pooled analyses from the breast cancer association consortium

Background: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype.Methods: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype.Results: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (P-adj > 0.30). The strongest associations were between all-cause mortality and BMI >= 30 versus 18.5-25 kg/m(2) [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age >= 30 years versus 0-= 10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking.Conclusions: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype.Impact: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.Surgical oncolog

The association of circadian parameters and the clustering of fatigue, depression, and sleep problems in breast cancer survivors:a latent class analysis

PurposeCircadian rhythms control a wide range of physiological processes and may be associated with fatigue, depression, and sleep problems. We aimed to identify subgroups of breast cancer survivors based on symptoms of fatigue, insomnia, and depression; and assess whether circadian parameters (i.e., chronotype, amplitude, and stability) were associated with these subgroups over time.MethodsAmong breast cancer survivors, usual circadian parameters were assessed at 3–4 months after diagnosis (T0), and symptoms of fatigue, depression, and insomnia were assessed after 2–3 years (T1, N = 265) and 6–8 years (T2, N = 169). We applied latent class analysis to classify survivors in unobserved groups (“classes”) based on symptoms at T1. The impact of each of the circadian parameters on class allocation was assessed using multinomial logistic regression analysis, and changes in class allocation from T1 to T2 using latent transition models.ResultsWe identified 3 latent classes of symptom burden: low (38%), moderate (41%), and high (21%). Survivors with a late chronotype (“evening types”) or low circadian amplitude (“languid types”) were more likely to have moderate or high symptom burden compared to “morning types” and “vigorous types,” respectively. The majority of survivors with moderate (59%) or high (64%) symptom burden at T1 had persistent symptom burden at T2.Implications for Cancer SurvivorsA late chronotype and lower circadian amplitude after breast cancer diagnosis were associated with greater symptoms of fatigue, depression, and insomnia at follow-up. These circadian parameters may potentially be novel targets in interventions aimed at alleviating symptom burden among breast cancer survivors

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes

International audienceGenome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes