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Objective: Structural measurements after separation of cortical from trabecular bone are of interest to a wide variety of communities but are difficult to obtain because of the lack of accurate automated techniques. Methods: We d present a structure-based algorithm for separating cortical from trabecular bone in binarized images. Using the thickness of the cortex as a seed value, bone connected to the cortex within a spatially local threshold value is identified and separated from the remaining bone. The algorithm was tested on seven biological data sets from four species imaged using micro-computed tomography (μ-CT) and high-resolution peripheral quantitative computed tomography (HR-pQCT). Area and local thickness measurements were compared to images segmented manually. Results: The algorithm was approximately 11 times faster than manual measurements and the median error in cortical area was -4.47 ± 4.15%. The median error in cortical thickness was approximately 0.5 voxels for μ-CT data and less than 0.05 voxels for HR-pQCT images resulting in an overall difference of -28.1 ± 71.1 μm. Conclusion: A simple and readily implementable methodology has been developed that is repeatable, efficient, and requires few user inputs, providing an unbiased means of separating cortical from trabecular bone. Significance: Automating the segmentation of variably thick cortices will allow for the evaluation of large data sets in a time-efficient manner and allow for full-field analyses that have been previously limited to small regions of interest. The MATLAB code can be downloaded from https://github.com/TBL-UIUC/downloads.git. 

Abstract ObjectivesAs a complex, polygenic trait, brain size has likely been influenced by a range of direct and indirect selection pressures for both cognitive and non‐cognitive functions and capabilities. It has been hypothesized that hominin brain expansion was, in part, a correlated response to selection acting on aerobic capacity (Raichlen & Polk, 2013). According to this hypothesis, selection for aerobic capacity increased the activity of various signaling molecules, including those involved in brain growth. One key molecule is brain‐derived neurotrophic factor (BDNF), a protein that regulates neuronal development, survival, and plasticity in mammals. This review updates, partially tests, and expands Raichlen and Polk's (2013) hypothesis by evaluating evidence for BDNF as a mediator of brain size. DiscussionWe contend that selection for endurance capabilities in a hot climate favored changes to muscle composition, mitochondrial dynamics and increased energy budget through pathways involving regulation of PGC‐1α and MEF2 genes, both of which promote BDNF activity. In addition, the evolution of hairlessness and the skin's thermoregulatory response provide other molecular pathways that promote both BDNF activity and neurotransmitter synthesis. We discuss how these pathways contributed to the evolution of brain size and function in human evolution and propose avenues for future research. Our results support Raichlen and Polk's contention that selection for non‐cognitive functions has direct mechanistic linkages to the evolution of brain size in hominins.