Strong population structure in a species manipulated by humans since the Neolithic: the European fallow deer (Dama dama dama).

Species that have been translocated and otherwise manipulated by humans may show patterns of population structure that reflect those interactions. At the same time, natural processes shape populations, including behavioural characteristics like dispersal potential and breeding system. In Europe, a key factor is the geography and history of climate change through the Pleistocene. During glacial maxima throughout that period, species in Europe with temperate distributions were forced south, becoming distributed among the isolated peninsulas represented by Anatolia, Italy and Iberia. Understanding modern patterns of diversity depends on understanding these historical population dynamics. Traditionally, European fallow deer (Dama dama dama) are thought to have been restricted to refugia in Anatolia and possibly Sicily and the Balkans. However, the distribution of this species was also greatly influenced by human-mediated translocations. We focus on fallow deer to better understand the relative influence of these natural and anthropogenic processes. We compared modern fallow deer putative populations across a broad geographic range using microsatellite and mitochondrial DNA loci. The results revealed highly insular populations, depauperate of genetic variation and significantly differentiated from each other. This is consistent with the expectations of drift acting on populations founded by small numbers of individuals, and reflects known founder populations in the north. However, there was also evidence for differentiation among (but not within) physically isolated regions in the south, including Iberia. In those regions we find evidence for a stronger influence from natural processes than may be expected for a species with such strong, known anthropogenic influence.

Digitally adjusting chromogenic dye proportions in brightfield microscopy images.

We present an algorithm to adjust the contrast of individual dyes from colour (red-green-blue) images of dye mixtures. Our technique is based on first decomposing the colour image into individual dye components, then adjusting each of the dye components and finally mixing the individual dyes to generate colour images. Specifically in this paper, we digitally adjust the staining proportions of hematoxylin and eosin (H&E) chromogenic dyes in tissue images. We formulate the physical dye absorption process as a non-negative mixing equation, and solve the individual components using non-negative matrix factorisation (NMF). Our NMF formulation includes camera dark current in addition to the mixing proportions and the individual H and E components. The novelty of our approach is to adjust the dye proportions while preserving the color of nonlinear dye interactions, such as pigments and red blood cells. In this paper we present results for only H&E images, our technique can easily be extended to other staining techniques.

Quantification of spatial parameters in 3D cellular constructs using graph theory.

Multispectral three-dimensional (3D) imaging provides spatial information for biological structures that cannot be measured by traditional methods. This work presents a method of tracking 3D biological structures to quantify changes over time using graph theory. Cell-graphs were generated based on the pairwise distances, in 3D-Euclidean space, between nuclei during collagen I gel compaction. From these graphs quantitative features are extracted that measure both the global topography and the frequently occurring local structures of the "tissue constructs." The feature trends can be controlled by manipulating compaction through cell density and are significant when compared to random graphs. This work presents a novel methodology to track a simple 3D biological event and quantitatively analyze the underlying structural change. Further application of this method will allow for the study of complex biological problems that require the quantification of temporal-spatial information in 3D and establish a new paradigm in understanding structure-function relationships.