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BackgroundDespite advances in imaging techniques, real-time visualization of the structure and dynamics of tissues and organs inside small living animals has remained elusive. Recently, we have been using synchrotron x-rays to visualize the internal anatomy of millimeter-sized opaque, living animals. This technique takes advantage of partially-coherent x-rays and diffraction to enable clear visualization of internal soft tissue not viewable via conventional absorption radiography. However, because higher quality images require greater x-ray fluxes, there exists an inherent tradeoff between image quality and tissue damage.ResultsWe evaluated the tradeoff between image quality and harm to the animal by determining the impact of targeted synchrotron x-rays on insect physiology, behavior and survival. Using 25 keV x-rays at a flux density of 80 μW/mm-2, high quality video-rate images can be obtained without major detrimental effects on the insects for multiple minutes, a duration sufficient for many physiological studies. At this setting, insects do not heat up. Additionally, we demonstrate the range of uses of synchrotron phase-contrast imaging by showing high-resolution images of internal anatomy and observations of labeled food movement during ingestion and digestion.ConclusionSynchrotron x-ray phase contrast imaging has the potential to revolutionize the study of physiology and internal biomechanics in small animals. This is the only generally applicable technique that has the necessary spatial and temporal resolutions, penetrating power, and sensitivity to soft tissue that is required to visualize the internal physiology of living animals on the scale from millimeters to microns.

We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as “uphill/downhill” flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.

The negative allometric scaling of metabolic rate with body size is among the most striking patterns in biology. We investigated whether this pattern extends to physically independent eusocial systems by measuring the metabolic rates of whole functioning colonies of the seed-harvester ant Pogonomyrmex californicus. These intraspecific scaling data were compared to the predictions of an additive model developed to estimate collective metabolic rates. Contrary to the prediction of the additive model, colony metabolic rate allometry resembled the pattern commonly observed interspecifically for individual organisms, scaling with colony mass(0.75). Among the same-aged colonies, net growth rate varied by up to sevenfold, with larger colonies exhibiting higher net growth efficiency than smaller colonies. Isolated worker groups exhibited isometric metabolic rate scaling, suggesting that the social environment of the colony is critical to regulating individual patterns of work output. Within the social environment, individual worker locomotor velocities exhibited power-law distributions that scaled with colony size so that larger colonies exhibited a greater disparity between active and inactive ants than did smaller colonies. These results demonstrate that behavioral organization within colonies may have a major influence on colony-level metabolism and in generating intraspecific variation in growth trajectories.

Investigating local-scale interactions within a network makes it possible to test hypotheses about the mechanisms of global network connectivity and to ask whether there are general rules underlying network function across systems. Here we use motif analysis to determine whether the interactions within social insect colonies resemble the patterns exhibited by other animal associations or if they exhibit characteristics of biological regulatory systems. Colonies exhibit a predominance of feed-forward interaction motifs, in contrast to the densely interconnected clique patterns that characterize human interaction and animal social networks. The regulatory motif signature supports the hypothesis that social insect colonies are shaped by selection for network patterns that integrate colony functionality at the group rather than individual level, and demonstrates the utility of this approach for analysis of selection effects on complex systems across biological levels of organization.