Much is still unknown about dominance hierarchies. Many different species form dominance hierarchies and each species have very different ways of forming these hierarchies. Some engage in various different dominance interactions to establish a dominant position. This experiment aims to use the ant species, Harpegnathos saltator, as a model to explore what sets dominant individuals, or gamergates in this case, apart from non-dominant individuals, or non-gamergates. H. saltator ants perform various different behaviors such as dueling, which is a mutually beneficial behavior, dominance biting, which is an aggressive behavior, and policing which is used to bring down those who are dominant. These behaviors can be used to study the importance of initiation and aggression in hierarchy formation. This experiment will explore how aggression through dominance biting, duel initiation, group size, and time period affect the formation of gamergates. To do so, socially unstable colonies of 15, 30, and 60 ants were video recorded for days until gamergates were established. Then, from the recordings, a period of high activity was selected and observed for dueling, duel initiation, dominance biting, dominance bite downs, and policing. The results showed that gamergates tended to perform dominance biting and dominance bite downs far more than non-gamergates during the period of high activity, but not as clearly with duelling and duel initiations. It was inconclusive whether or not the combination of both dueling and dominance biting was what set gamergates apart from non gamergates as different groups showed different results. Gamergates performed visibly more dominance bite downs than non-gamergates, so aggression may be important in setting gamergates apart from non-gamergates. In terms of group size, the smallest group had the least number of gamergates and the least activity, and the medium and large group had a similar number of gamergates and activity.

Five immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at five separate time points to characterize growth and development of the tumor. After 25 days, the final tumor volumes of the mice varied from 12 mm³ to 62 mm³, even though mice were inoculated from the same tumor cell line under carefully controlled conditions. We generated hypotheses to explore large variances in final tumor size and tested them with our simple reaction-diffusion model in both a 3-dimensional (3D) finite difference method and a 2-dimensional (2D) level set method. The parameters obtained from a best-fit procedure, designed to yield simulated tumors as close as possible to the observed ones, vary by an order of magnitude between the three mice analyzed in detail. These differences may reflect morphological and biological variability in tumor growth, as well as errors in the mathematical model, perhaps from an oversimplification of the tumor dynamics or nonidentifiability of parameters. Our results generate parameters that match other experimental in vitro and in vivo measurements. Additionally, we calculate wave speed, which matches with other rat and human measurements.

Over time, tumor treatment resistance inadvertently develops when androgen de-privation therapy (ADT) is applied to metastasized prostate cancer (PCa). To combat tumor resistance, while reducing the harsh side effects of hormone therapy, the clinician may opt to cyclically alternates the patient’s treatment on and off. This method,known as intermittent ADT, is an alternative to continuous ADT that improves the patient’s quality of life while testosterone levels recover between cycles. In this paper,we explore the response of intermittent ADT to metastasized prostate cancer by employing a previously clinical data validated mathematical model to new clinical data from patients undergoing Abiraterone therapy. This cell quota model, a system of ordinary differential equations constructed using Droop’s nutrient limiting theory, assumes the tumor comprises of castration-sensitive (CS) and castration-resistant (CR)cancer sub-populations. The two sub-populations rely on varying levels of intracellular androgen for growth, death and transformation. Due to the complexity of the model,we carry out sensitivity analyses to study the effect of certain parameters on their outputs, and to increase the identifiability of each patient’s unique parameter set. The model’s forecasting results show consistent accuracy for patients with sufficient data,which means the model could give useful information in practice, especially to decide whether an additional round of treatment would be effective.