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      Functional Evolution of the Feeding System in Rodents


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          The masticatory musculature of rodents has evolved to enable both gnawing at the incisors and chewing at the molars. In particular, the masseter muscle is highly specialised, having extended anteriorly to originate from the rostrum. All living rodents have achieved this masseteric expansion in one of three ways, known as the sciuromorph, hystricomorph and myomorph conditions. Here, we used finite element analysis (FEA) to investigate the biomechanical implications of these three morphologies, in a squirrel, guinea pig and rat. In particular, we wished to determine whether each of the three morphologies is better adapted for either gnawing or chewing. Results show that squirrels are more efficient at muscle-bite force transmission during incisor gnawing than guinea pigs, and that guinea pigs are more efficient at molar chewing than squirrels. This matches the known diet of nuts and seeds that squirrels gnaw, and of grasses that guinea pigs grind down with their molars. Surprisingly, results also indicate that rats are more efficient as well as more versatile feeders than both the squirrel and guinea pig. There seems to be no compromise in biting efficiency to accommodate the wider range of foodstuffs and the more general feeding behaviour adopted by rats. Our results show that the morphology of the skull and masticatory muscles have allowed squirrels to specialise as gnawers and guinea pigs as chewers, but that rats are high-performance generalists, which helps explain their overwhelming success as a group.

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          Generalized n-dimensional biomechanical field analysis using statistical parametric mapping.

          A variety of biomechanical data are sampled from smooth n-dimensional spatiotemporal fields. These data are usually analyzed discretely, by extracting summary metrics from particular points or regions in the continuum. It has been shown that, in certain situations, such schemes can compromise the spatiotemporal integrity of the original fields. An alternative methodology called statistical parametric mapping (SPM), designed specifically for continuous field analysis, constructs statistical images that lie in the original, biomechanically meaningful sampling space. The current paper demonstrates how SPM can be used to analyze both experimental and simulated biomechanical field data of arbitrary spatiotemporal dimensionality. Firstly, 0-, 1-, 2-, and 3-dimensional spatiotemporal datasets derived from a pedobarographic experiment were analyzed using a common linear model to emphasize that SPM procedures are (practically) identical irrespective of the data's physical dimensionality. Secondly two probabilistic finite element simulation studies were conducted, examining heel pad stress and femoral strain fields, respectively, to demonstrate how SPM can be used to probe the significance of field-wide simulation results in the presence of uncontrollable or induced modeling uncertainty. Results were biomechanically intuitive and suggest that SPM may be suitable for a wide variety of mechanical field applications. SPM's main theoretical advantage is that it avoids problems associated with a priori assumptions regarding the spatiotemporal foci of field signals. SPM's main practical advantage is that a unified framework, encapsulated by a single linear equation, affords comprehensive statistical analyses of smooth scalar fields in arbitrarily bounded n-dimensional spaces. 2010 Elsevier Ltd. All rights reserved.
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            Requirements for comparing the performance of finite element models of biological structures.

            The widespread availability of three-dimensional imaging and computational power has fostered a rapid increase in the number of biologists using finite element analysis (FEA) to investigate the mechanical function of living and extinct organisms. The inevitable rise of studies that compare finite element models brings to the fore two critical questions about how such comparative analyses can and should be conducted: (1) what metrics are appropriate for assessing the performance of biological structures using finite element modeling? and, (2) how can performance be compared such that the effects of size and shape are disentangled? With respect to performance, we argue that energy efficiency is a reasonable optimality criterion for biological structures and we show that the total strain energy (a measure of work expended deforming a structure) is a robust metric for comparing the mechanical efficiency of structures modeled with finite elements. Results of finite element analyses can be interpreted with confidence when model input parameters (muscle forces, detailed material properties) and/or output parameters (reaction forces, strains) are well-documented by studies of living animals. However, many researchers wish to compare species for which these input and validation data are difficult or impossible to acquire. In these cases, researchers can still compare the performance of structures that differ in shape if variation in size is controlled. We offer a theoretical framework and empirical data demonstrating that scaling finite element models to equal force: surface area ratios removes the effects of model size and provides a comparison of stress-strength performance based solely on shape. Further, models scaled to have equal applied force:volume ratios provide the basis for strain energy comparison. Thus, although finite element analyses of biological structures should be validated experimentally whenever possible, this study demonstrates that the relative performance of un-validated models can be compared so long as they are scaled properly.
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              Rodent phylogeny revised: analysis of six nuclear genes from all major rodent clades

              Background Rodentia is the most diverse order of placental mammals, with extant rodent species representing about half of all placental diversity. In spite of many morphological and molecular studies, the family-level relationships among rodents and the location of the rodent root are still debated. Although various datasets have already been analyzed to solve rodent phylogeny at the family level, these are difficult to combine because they involve different taxa and genes. Results We present here the largest protein-coding dataset used to study rodent relationships. It comprises six nuclear genes, 41 rodent species, and eight outgroups. Our phylogenetic reconstructions strongly support the division of Rodentia into three clades: (1) a "squirrel-related clade", (2) a "mouse-related clade", and (3) Ctenohystrica. Almost all evolutionary relationships within these clades are also highly supported. The primary remaining uncertainty is the position of the root. The application of various models and techniques aimed to remove non-phylogenetic signal was unable to solve the basal rodent trifurcation. Conclusion Sequencing and analyzing a large sequence dataset enabled us to resolve most of the evolutionary relationships among Rodentia. Our findings suggest that the uncertainty regarding the position of the rodent root reflects the rapid rodent radiation that occurred in the Paleocene rather than the presence of conflicting phylogenetic and non-phylogenetic signals in the dataset.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                27 April 2012
                : 7
                : 4
                : e36299
                [1 ]Hull York Medical School, University of Hull, Hull, United Kingdom
                [2 ]Department of Earth Sciences, University of Bristol, Bristol, United Kingdom
                [3 ]Department of Engineering, University of Hull, Hull, United Kingdom
                [4 ]Département d'Ecologie et de Gestion de la Biodiversité, Muséum National d'Histoire Naturelle, Paris, France
                [5 ]Department of Bioengineering, Shinshu University, Ueda, Japan
                [6 ]Department of Musculoskeletal Biology, University of Liverpool, Liverpool, United Kingdom
                University College London, United Kingdom
                Author notes

                Conceived and designed the experiments: PGC EJR MJF NJ. Performed the experiments: PGC MJF AH. Analyzed the data: PGC EJR MJF AH TCP NJ. Contributed reagents/materials/analysis tools: EJR MJF AH TCP NJ. Wrote the paper: PGC EJR MJF AH TCP NJ.

                Cox et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                : 1 February 2012
                : 4 April 2012
                Page count
                Pages: 11
                Research Article
                Anatomy and Physiology
                Musculoskeletal System
                Muscle Functions
                Musculoskeletal Anatomy
                Developmental Biology
                Evolutionary Developmental Biology
                Evolutionary Biology
                Evolutionary Processes
                Comparative Anatomy
                Veterinary Science
                Animal Types
                Small Animals



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