Adaptation to hard-object feeding in sea otters and hominins

The large, bunodont postcanine teeth in living sea otters (Enhydra lutris) have been likened to those of certain fossil hominins, particularly the ’robust’ australopiths (genus Paranthropus). We examine this evolutionary convergence by conducting fracture experiments on extracted molar teeth of sea otters and modern humans (Homo sapiens) to determine how load-bearing capacity relates to tooth morphology and enamel material properties. In situ optical microscopy and x-ray imaging during simulated occlusal loading reveal the nature of the fracture patterns. Explicit fracture relations are used to analyze the data and to extrapolate the results from humans to earlier hominins. It is shown that the molar teeth of sea otters have considerably thinner enamel than those of humans, making sea otter molars more susceptible to certain kinds of fractures. At the same time, the base diameter of sea otter first molars is larger, diminishing the fracture susceptibility in a compensatory manner. We also conduct nanoindentation tests to map out elastic modulus and hardness of sea otter and human molars through a section thickness, and microindentation tests to measure toughness. We find that while sea otter enamel is just as stiff elastically as human enamel, it is a little softer and tougher. The role of these material factors in the capacity of dentition to resist fracture and deformation is considered. From such comparisons, we argue that early hominin species like Paranthropus most likely consumed hard food objects with substantially higher biting forces than those exerted by modern humans.

A Faster Circular Binary Segmentation Algorithm for the Analysis of Array CGH Data

Motivation: Array CGH technologies enable the simultaneous measurement of DNA copy number for thousands of sites on a genome. We developed the circular binary segmentation (CBS) algorithm to divide the genome into regions of equal copy number (Olshen {\it et~al}, 2004). The algorithm tests for change-points using a maximal $t$-statistic with a permutation reference distribution to obtain the corresponding $p$-value. The number of computations required for the maximal test statistic is $O(N^2),$ where $N$ is the number of markers. This makes the full permutation approach computationally prohibitive for the newer arrays that contain tens of thousands markers and highlights the need for a faster. algorithm. Results: We present a hybrid approach to obtain the $p$-value of the test statistic in linear time. We also introduce a rule for stopping early when there is strong evidence for the presence of a change. We show through simulations that the hybrid approach provides a substantial gain in speed with only a negligible loss in accuracy and that the stopping rule further increases speed. We also present the analysis of array CGH data from a breast cancer cell line to show the impact of the new approaches on the analysis of real data. Availability: An R (R Development Core Team, 2006) version of the CBS algorithm has been implemented in the ``DNAcopy'' package of the Bioconductor project (Gentleman {\it et~al}, 2004). The proposed hybrid method for the $p$-value is available in version 1.2.1 or higher and the stopping rule for declaring a change early is available in version 1.5.1 or higher.