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changes in the diffusion, growth, and death parameters was performed, in order to find a set of parameter values that accurately model observed tumor growth for a given patient. Additional changes were made to the diffusion parameters to account for the arrangement of nerve tracts in the brain, resulting in varying rates of diffusion. In general, small changes in the growth rates had a large impact on the outcome of the simulations, and for each patient there exists a set of parameters that allow the model to simulate a tumor that matches observed tumor growth in the patient over a period of two or three months. Furthermore, these results are more accurate with anisotropic diffusion, rather than isotropic diffusion. However, these parameters lead to inaccurate results for patients with tumors that undergo no observable growth over the given time interval. While it is possible to simulate long-term tumor growth, the simulation requires multiple comparisons to available MRI scans in order to find a set of parameters that provide an accurate prognosis.
In this work, a Bio-Inspired Design approach was taken to answer this question, primarily since the hexagonal lattice is so commonly found in wasp and bee nests, including the well-known bee’s honeycomb that inspired these panel designs to begin with. Whereas prior honeycomb panel design has primarily focused on the hexagonal shape of the unit cell, in this work we examine the relationship between the various parameters constituting the hexagonal cell itself, specifically the wall thickness and the corner radius, and also examine out-of-plane features that have not been previously translated into panel design. This work reports findings from a study of insect nests across 70 species using 2D and 3D measurements with optical microscopy and X-ray tomography, respectively. Data from these biological nests were used to identify design parameters of interest, which were then translated into design principles. These design principles were implemented in the design of honeycomb panels manufactured with the Selective Laser Sintering process and subjected to experimental testing to study their effects on the mechanical behavior of these panels.
This work investigates mechanisms that can extend the spatial reach of fertility signaling and reproductive regulation in three polydomous ant species. In Novomessor cockerelli, the presence of larvae but not eggs is shown to inhibit worker reproduction. Then, in Camponotus floridanus, 3-methylheptacosane found on the queen cuticle and queen-laid eggs is verified as a releaser pheromone sufficient to disrupt normally occurring aggressive behavior toward foreign workers. Finally, the volatile and cuticular hydrocarbon pheromones present on the cuticle of Oecophylla smaragdina queens are shown to release strong attraction response by workers; when coupled with previous work, this result suggests that these chemicals may underly both the formation of a worker retinue around the queen as well as egg-located mechanisms of reproductive regulation in distant satellite nests. Whereas most previous studies have focused on the short-range role of hydrocarbons on the cuticle of the queen, these studies demonstrate that eusocial insects may employ longer range regulatory mechanisms. Both queen volatiles and distributed brood can extend the range of queen fertility signaling, and the use of larvae for fertility signaling suggest that feeding itself may be a non-chemical mechanism for reproductive regulation. Although trail laying in mass-recruiting ants is often used as an example of complex communication, reproductive regulation in ants may be a similarly complex example of insect communication, especially in the case of large, polydomous ant colonies.
Cooperative cellular phenotypes are universal across multicellular life. Division of labor, regulated proliferation, and controlled cell death are essential in the maintenance of a multicellular body. Breakdowns in these cooperative phenotypes are foundational in understanding the initiation and progression of neoplastic diseases, such as cancer. Cooperative cellular phenotypes are straightforward to characterize in extant species but the selective pressures that drove their emergence at the transition(s) to multicellularity have yet to be fully characterized. Here we seek to understand how a dynamic environment shaped the emergence of two mechanisms of regulated cell survival: apoptosis and senescence. We developed an agent-based model to test the time to extinction or stability in each of these phenotypes across three levels of stochastic environments.