Nutritional imbalance is one of the main sources of stress in both extant and extinct human populations. Restricted availability of nutrients is thought to disrupt the buffering mechanisms that contribute to developmental stability and canalization, resulting in increased levels of fluctuating asymmetry (FA) and phenotypic variance among individuals. However, the literature is contradictory in this regard. This study assesses the effect of prenatal nutritional stress on FA and among-individual variance in cranial shape and size using a mouse model of maternal protein restriction. Two sets of landmark coordinates were digitized in three dimensions from skulls of control and protein restricted specimens at E17.5 and E18.5. We found that, by the end of gestation, maternal protein restriction resulted in a significant reduction of skull size. Fluctuating asymmetry in size and shape exceeded the amount of measurement error in all groups, but no significant differences in the magnitude of FA were found between treatments. Convsersely, the pattern of shape asymmetry was affected by the environmental perturbation since the angles between the first eigenvectors extracted from the covariance matrix of shape asymmetric component of protein restricted and control groups were not significantly different from the expected for random vectors. In addition, among-individual variance in cranial shape was significanlty higher in the protein restricted than the control group at E18.5. Overall, the results obtained from a controlled experiment do not support the view of fluctuating asymmetry of cranial structures as a reliable index for inferring nutritional stress in human populations.
The aim of this study is to use a Multilayer Perceptron (MLP) Artificial Neural Network (ANN) for phaseless imaging the human heel (modeled as a bilayer dielectric media: bone and surrounding tissue) and the calcaneus cross-section size and location using a two dimensional (2D) microwave tomographic array. Computer simulations were performed over 2D dielectric maps inspired by Computed Tomography (CT) images of human heels for training and testing the MLP. A morphometric analysis was performed to account for the scatterer shape influence on the results. A robustness analysis was also conducted in order to study the MLP performance in noisy conditions. The standard deviations of the relative percentage errors on estimating the dielectric properties of the calcaneus bone were relatively high. Regarding the calcaneus surrounding tissue, the dielectric parameters estimations are better, with relative percentage error standard deviations up to ≈ 15%. The location and size of the calcaneus are always properly estimated with absolute error standard deviations up to ≈ 3 mm.
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