Search PubMed⌕ Search

Biomedical subjects

Dean C Adams

Publications and source records attributed to Dean C Adams.

4 recordsLinked to original sources

Quantifying biomechanical motion using Procrustes motion analysis.

The ability to quantify and compare the movements of organisms is a central focus of many studies in biology, anthropology, biomechanics, and ergonomics. However, while the importance of functional motion analysis has long been acknowledged, quantitative methods for identifying differences in motion have not been widely developed. In this article, we present an approach to the functional analysis of motion and quantification of motion types. Our approach, Procrustes Motion Analysis (PMA) can be used to distinguish differences in cyclical, repeated, or goal-directed motions. PMA exploits the fact that any motion can be represented by an ordered sequence of postures exhibited throughout the course of a motion. Changes in posture from time step to time step form a trajectory through a multivariate data space, representing a specific motion. By evaluating the size, shape, and orientation of these motion trajectories, it is possible to examine variation in motion type within and among groups or even with respect to continuous variables. This represents a significant analytical advance over current approaches. Using simulated and digitized data representing cyclical, repeated and goal-directed motions, we show that PMA correctly identifies distinct motion tasks in these data sets.

Animals↗

Quantitative genetics of plastron shape in slider turtles (Trachemys scripta).

Shape variation is widespread in nature and embodies both a response to and a source for evolution and natural selection. To detect patterns of shape evolution, one must assess the quantitative genetic underpinnings of shape variation as well as the selective environment that the organisms have experienced. Here we used geometric morphometrics to assess variation in plastron shell shape in 1314 neonatal slider turtles (Trachemys scripta) from 162 clutches of laboratory-incubated eggs from two nesting areas. Multivariate analysis of variance indicated that nesting area has a limited role in describing plastron shape variation among clutches, whereas differences between individual clutches were highly significant, suggesting a prominent clutch effect. The covariation between plastron shape and several possible maternal effect variables (yolk hormone levels and egg dimensions) was assessed for a subset of clutches and found to be negligible. We subsequently employed several recently proposed methods for estimating heritability from shape variables, and generalized a univariate approach to accommodate unequal sample sizes. Univariate estimates of shape heritability based on Procrustes distances yielded large values for both nesting populations (h2 approximately 0.86), and multivariate estimates of maximal additive heritability were also large for both nesting populations (h2max approximately 0.57). We also estimated the dominant trend in heritable shape change for each nesting population and found that the direction of shape evolution was not the same for the two sites. Therefore, although the magnitude of shape evolution was similar between nesting populations, the manner in which plastron shape is evolving is not. We conclude that the univariate approach for assessing quantitative genetic parameters from geometric morphometric data has limited utility, because it is unable to accurately describe how shape is evolving.

Animals↗

DRUIDS--detection of regions with unexpected internal deviation from stationarity.

Most methods for inferring phylogenies from sequence data assume that patterns of substitution have been stationary over time. Changes in evolutionary constraint can result in nonstationary substitution patterns that are phylogenetically misleading unless modeled appropriately. Here we present a multiple-alignment-based method to identify regions that are likely to contain misleading phylogenetic signals due to changes in evolutionary constraints. The method uses a moving window approach to identify regions with a statistically significant deviation from stationarity in the physicochemical properties of amino acids among taxa. The protocol has been implemented in the software package DRUIDS (Detecting Regions of Unexpected Internal Deviation from Stationarity), available from the first author upon request.

Amino Acid Sequence↗