Bayesian estimation of small effects in exercise and sports science

The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.

Selecting rainfall events for effective Water Sensitive Urban Design: A case study in Gold Coast City, Australia

The current approach for protecting the receiving water environment from urban stormwater pollution is the adoption of structural measures commonly referred to as Water Sensitive Urban Design (WSUD). The treatment efficiency of WSUD measures closely depends on the design of the specific treatment units. As stormwater quality is influenced by rainfall characteristics, the selection of appropriate rainfall events for treatment design is essential to ensure the effectiveness of WSUD systems. Based on extensive field investigations in four urban residential catchments based at Gold Coast, Australia, and computer modelling, this paper details a technically robust approach for the selection of rainfall events for stormwater treatment design using a three-component model. The modelling results confirmed that high intensity-short duration events produce 58.0% of TS load while they only generated 29.1% of total runoff volume. Additionally, rainfall events smaller than 6-month average recurrence interval (ARI) generates a greater cumulative runoff volume (68.4% of the total annual runoff volume) and TS load (68.6% of the TS load exported) than the rainfall events larger than 6-month ARI. The results suggest that for the study catchments, stormwater treatment design could be based on the rainfall which had a mean value of 31 mm/h average intensity and 0.4 h duration. These outcomes also confirmed that selecting smaller ARI rainfall events with high intensity-short duration as the threshold for treatment system design is the most feasible approach since these events cumulatively generate a major portion of the annual pollutant load compared to the other types of events, despite producing a relatively smaller runoff volume. This implies that designs based on small and more frequent rainfall events rather than larger rainfall events would be appropriate in the context of efficiency in treatment performance, cost-effectiveness and possible savings in land area needed.

Proteomics and mass spectrometric studies reveal planktonic growth of Mycobacterium smegmatis in biofilm cultures in the absence of rpoZ

Mycobacterium smegmatis is known to form biofilms and many cell surface molecules like core glycopeptidolipids and short-chain mycolates appear to play important role in the process. However, the involvement of the cell surface molecules in mycobacteria towards complete maturation of biofilms is still not clear. This work demonstrates the importance of the glycopeptidolipid species with hydroxylated alkyl chain and the epoxylated mycolic acids, during the process of biofilm development. In our previous study, we reported the impairment of biofilm formation in rpoZ-deleted M. smegmatis, where rpoZ codes for the ω subunit of RNA polymerase (R. Mathew, R. Mukherjee, R. Balachandar, D. Chatterji, Microbiology 152 (2006) 1741). Here we report the occurrence of planktonic growth in a mc2155 strain which is devoid of rpoZ gene. This strain is deficient in selective incorporation of the hydroxylated glycopeptidolipids and the epoxy mycolates to their respective locations in the cell wall. Hence it forms a mutant biofilm defective in maturation, wherein the cells undertake various alternative metabolic pathways to survive in an environment where oxygen, the terminal electron acceptor, is limiting.