Cycling for transport and recreation : associations with socio-economic position, environmental perceptions, and psychological disposition

OBJECTIVE Interest is growing in promoting utility cycling (i.e., for transport) as a means of incorporating daily physical activity (PA) into people’s lives, but little is known about correlates of utility cycling. Our primary aim was to examine cross-sectional relationships between socio-economic characteristics, neighborhood environment perceptions and psychological disposition with utility cycling (with or without additional recreational cycling). A secondary aim was to compare these relationships with those for recreation-only cycling. METHOD Baseline survey data (2007) from 10,233 participants in HABITAT, a multilevel longitudinal study of PA, sedentary behavior, and health in Brisbane adults aged 40-65 years, were analysed using multinomial regression modelling. RESULTS Greater income, habitual PA, and positive beliefs about PA were associated with utility and recreation-only cycling (p<0.05). Always having vehicle access and not in the labor force were associated with recreation-only cycling (p<0.05). Some or no vehicle access, part-time employment, and perceived environmental factors (little crime, few cul-de-sacs, nearby transport and recreational destinations) were associated with utility cycling (p<0.05). CONCLUSION Our findings suggest differences in associations between socio-economic, neighborhood perceptions and psychological factors and utility and recreation-only cycling in Brisbane residents aged 40-65 years. Tailored approaches appear to be required to promote utility and recreational cycling.

A multiscale road map of cancer spheroids : incorporating experimental and mathematical modelling to understand cancer progression

Computational models represent a highly suitable framework, not only for testing biological hypotheses and generating new ones but also for optimising experimental strategies. As one surveys the literature devoted to cancer modelling, it is obvious that immense progress has been made in applying simulation techniques to the study of cancer biology, although the full impact has yet to be realised. For example, there are excellent models to describe cancer incidence rates or factors for early disease detection, but these predictions are unable to explain the functional and molecular changes that are associated with tumour progression. In addition, it is crucial that interactions between mechanical effects, and intracellular and intercellular signalling are incorporated in order to understand cancer growth, its interaction with the extracellular microenvironment and invasion of secondary sites. There is a compelling need to tailor new, physiologically relevant in silico models that are specialised for particular types of cancer, such as ovarian cancer owing to its unique route of metastasis, which are capable of investigating anti-cancer therapies, and generating both qualitative and quantitative predictions. This Commentary will focus on how computational simulation approaches can advance our understanding of ovarian cancer progression and treatment, in particular, with the help of multicellular cancer spheroids, and thus, can inform biological hypothesis and experimental design.

Mathematical relationships for metal build-up on urban road surfaces based on traffic and land use characteristics

The study investigated the influence of traffic and land use parameters on metal build-up on urban road surfaces. Mathematical relationships were developed to predict metals originating from fuel combustion and vehicle wear. The analysis undertaken found that nickel and chromium originate from exhaust emissions, lead, copper and zinc from vehicle wear, cadmium from both exhaust and wear and manganese from geogenic sources. Land use does not demonstrate a clear pattern in relation to the metal build-up process, though its inherent characteristics such as traffic activities exert influence. The equation derived for fuel related metal load has high cross-validated coefficient of determination (Q2) and low Standard Error of Cross-Validation (SECV) values indicates that the model is reliable, while the equation derived for wear-related metal load has low Q2 and high SECV values suggesting its use only in preliminary investigations. Relative Prediction Error values for both equations are considered to be well within the error limits for a complex system such as an urban road surface. These equations will be beneficial for developing reliable stormwater treatment strategies in urban areas which specifically focus on mitigation of metal pollution.