Therefore, we were able to partition variation as a result of selection and phenotypic plasticity. Within-individual variation in body condition increased in

early life until SBC-115076 chemical structure middle age (i.e. 34 years of age) in the two sexes followed by only a slight decrease in body condition during senescence in males but not in females. After accounting for age-dependent variation, condition could be partitioned into a within-individual plastic response to environmental conditions during migration and a nonplastic response (i.e. a between-individual difference) to environmental conditions experienced in the African winter quarters. Specifically, there was a within-individual increase in body condition as environmental conditions during migration improved in both males and females, independent of age. There was a between-individual effect of condition found in the winter quarter in body condition of PLX3397 in vivo females, but not in males, which was attributed to the disappearance of females in poor body condition from the study population as a result of the higher natal dispersal of low-quality females compared to high-quality ones during years with favourable environmental conditions in the African winter quarters. Males and females also tended to be

in better body condition during the warmer springs upon arrival at the breeding grounds. There was a temporal decline in female body condition during 19912007, whereas no significant trend was detected in males. Therefore, both intrinsic (e.g. age and sex) and extrinsic factors (e.g. climate) affected body condition.

(C) 2011 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, 105, 420434.”
“Enabled by novel molecular learn more markers, fluorescence microscopy enables the monitoring of multiple cellular functions using live cell assays. Automated image analysis is necessary to monitor such model systems in a high-throughput and high-content environment. Here, we demonstrate the ability to simultaneously track cell cycle phase and cell motion at the single cell level. Using a recently introduced cell cycle marker, we present a set of image analysis tools for automated cell phase analysis of live cells over extended time periods. Our model-based approach enables the characterization of the four phases of the cell cycle G1, S, G2, and M, which enables the study of the effect of inhibitor compounds that are designed to block the replication of cancerous cells in any of the phases. We approach the tracking problem as a spatio-temporal volume segmentation task, where the 2D slices are stacked into a volume with time as the z dimension. The segmentation of the G2 and S phases is accomplished using level sets, and we designed a model-based shape/size constraint to control the evolution of the level set.