Mirror, mirror on the wall, who is the happiest of them all?

This paper turns Snow-White's magic mirror onto recent economics Nobel Prize winners, top economists and happiness researchers, and through the eyes of the 'man in the street' seeks to determine who the happiest academic is. The study not only provides a clear answer to this question but also unveils who is the ladies' man and who is the sweetheart of the aged. It also explores the extent to which information matters and whether individuals' self-reported happiness affects their perceptions about the happiness of these superstars in economics.

Comparison of three expert elicitation methods for logistic regression on predicting the presence of the threatened brush-tailed rock-wallaby petrogale penicillata

Numerous expert elicitation methods have been suggested for generalised linear models (GLMs). This paper compares three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression. These methods were trialled on two experts in order to model the habitat suitability of the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The first elicitation approach is a geographically assisted indirect predictive method with a geographic information system (GIS) interface. The second approach is a predictive indirect method which uses an interactive graphical tool. The third method uses a questionnaire to elicit expert knowledge directly about the impact of a habitat variable on the response. Two variables (slope and aspect) are used to examine prior and posterior distributions of the three methods. The results indicate that there are some similarities and dissimilarities between the expert informed priors of the two experts formulated from the different approaches. The choice of elicitation method depends on the statistical knowledge of the expert, their mapping skills, time constraints, accessibility to experts and funding available. This trial reveals that expert knowledge can be important when modelling rare event data, such as threatened species, because experts can provide additional information that may not be represented in the dataset. However care must be taken with the way in which this information is elicited and formulated.

The effect of unlocking RGD-motifs in collagen I on pre-osteoblast adhesion and differentiation

Denaturation of extracellular matrix proteins exposes cryptic binding sites. It is hypothesized that binding of cell adhesion receptors to these cryptic binding sites regulates cellular behaviour during tissue repair and regeneration. To test this hypothesis, we quantify the adhesion of pre-osteoblastic cells to native (Col) and partially-denatured (pdCol) collagen I using single-cell force spectroscopy. During early stages of cell attachment (≤180 s) pre-osteoblasts (MC3T3-E1) adhered significantly stronger to pdCol compared to Col. RGD (Arg-Gly-Asp)-containing peptides suppressed this elevated cell adhesion. We show that the RGD-binding α5β1- and αv-integrins mediated pre-osteoblast adhesion to pdCol, but not to Col. On pdCol pre-osteoblasts had a higher focal adhesion kinase tyrosine-phosphorylation level that correlated with enhanced spreading and motility. Moreover, pre-osteoblasts cultured on pdCol showed a pronounced matrix mineralization activity. Our data suggest that partially-denatured collagen exposes RGD-motifs that trigger binding of α5β1- and αv-integrins. These integrins initiate cellular processes that stimulate osteoblast adhesion, spreading, motility and differentiation. Taken together, these quantitative insights reveal an approach for the development of alternative collagen I- based surfaces for tissue engineering applications.