Living long and ageing well: is epigenomics the missing link between nature and nurture?

Human longevity is a complex trait and increasingly we understand that both genes and lifestyle interact in the longevity phenotype. Non-genetic factors, including diet, physical activity, health habits, and psychosocial factors contribute approximately 50 % of the variability in human lifespan with another 25 % explained by genetic differences. Family clusters of nonagenarian and centenarian siblings, who show both exceptional age-span and health-span, are likely to have inherited facilitatory gene groups, but also have nine decades of life experiences and behaviours which have interacted with their genetic profiles. Identification of their shared genes is just one small step in the link from genes to their physical and psychological profiles. Behavioural genomics is beginning to demonstrate links to biological mechanisms through regulation of gene expression, which directs the proteome and influences the personal phenotype. Epigenetics has been considered the missing link between nature and nurture. Although there is much that remains to be discovered, this article will discuss some of genetic and environmental factors which appear important in good quality longevity and link known epigenetic mechanisms to themes identified by nonagenarians themselves related to their longevity. Here we suggest that exceptional 90-year old siblings have adopted a range of behaviours and life-styles which have contributed to their ageing-well-phenotype and which link with important public health messages.

An invasive-native mammalian species replacement process captured by camera trap survey random encounter models

Camera traps are used to estimate densities or abundances using capture-recapture and, more recently, random encounter models (REMs). We deploy REMs to describe an invasive-native species replacement process, and to demonstrate their wider application beyond abundance estimation. The Irish hare Lepus timidus hibernicus is a high priority endemic of conservation concern. It is threatened by an expanding population of non-native, European hares L. europaeus, an invasive species of global importance. Camera traps were deployed in thirteen 1 km squares, wherein the ratio of invader to native densities were corroborated by night-driven line transect distance sampling throughout the study area of 1652 km2. Spatial patterns of invasive and native densities between the invader’s core and peripheral ranges, and native allopatry, were comparable between methods. Native densities in the peripheral range were comparable to those in native allopatry using REM, or marginally depressed using Distance Sampling. Numbers of the invader were substantially higher than the native in the core range, irrespective of method, with a 5:1 invader-to-native ratio indicating species replacement. We also describe a post hoc optimization protocol for REM which will inform subsequent (re-)surveys, allowing survey effort (camera hours) to be reduced by up to 57% without compromising the width of confidence intervals associated with density estimates. This approach will form the basis of a more cost-effective means of surveillance and monitoring for both the endemic and invasive species. The European hare undoubtedly represents a significant threat to the endemic Irish hare.

A frontal view gait recognition based on 3D imaging using a time of flight camera

Studies have been carried out to recognize individuals from a frontal view using their gait patterns. In previous work, gait sequences were captured using either single or stereo RGB camera systems or the Kinect 1.0 camera system. In this research, we used a new frontal view gait recognition method using a laser based Time of Flight (ToF) camera. In addition to the new gait data set, other contributions include enhancement of the silhouette segmentation, gait cycle estimation and gait image representations. We propose four new gait image representations namely Gait Depth Energy Image (GDE), Partial GDE (PGDE), Discrete Cosine Transform GDE (DGDE) and Partial DGDE (PDGDE). The experimental results show that all the proposed gait image representations produce better accuracy than the previous methods. In addition, we have also developed Fusion GDEs (FGDEs) which achieve better overall accuracy and outperform the previous methods.