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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.
First, prostate cancer is modeled, where androgen is considered the limiting nutrient since most tumors depend on androgen for proliferation and survival. The model's accuracy for predicting the biomarker for patients on intermittent androgen deprivation therapy is tested by comparing the simulation results to clinical data as well as to an existing simpler model. The results suggest that a simpler model may be more beneficial for a predictive use, although further research is needed in this field prior to implementing mathematical models as a predictive method in a clinical setting.
Next, two chronic myeloid leukemia models are compared that consider Imatinib treatment, a drug that inhibits the constitutively active tyrosine kinase BCR-ABL. Both models describe the competition of leukemic and normal cells, however the first model also describes intracellular dynamics by considering BCR-ABL as the limiting nutrient. Using clinical data, the differences in estimated parameters between the models and the capacity for each model to predict drug resistance are analyzed.
Last, a simple model is presented that considers ovarian tumor growth and tumor induced angiogenesis, subject to on and off anti-angiogenesis treatment. In this environment, the cell quota represents the intracellular concentration of necessary nutrients provided through blood supply. Mathematical analysis of the model is presented and model simulation results are compared to pre-clinical data. This simple model is able to fit both on- and off-treatment data using the same biologically relevant parameters.