p53 Regulates the Formation of Lamellipodia and Circular Dorsal Ruffles Through Caldesmon and PTEN

Vascular smooth muscle cell migration is a significant contributor to many aspects of heart disease, and specifically atherosclerosis. Tissue damage in the arteries can result in the formation of a fatty streak. Smooth muscle cells (SMC) can then migrate to this site to form a fibrous cap, stabilizing the fatty plaque. Since cardiovascular disease is the leading cause of death in developed countries, this function of SMC is an essential area of study. The formation of lamellipodia and circular dorsal ruffles were studied in this project as indicators that cell migration is occurring. The roles of the proteins p53, Rac, caldesmon and PTEN were investigated with regards to these actin-based structures. The tumour suppressor p53 is often reported to cause apoptosis, senescence or cell cycle arrest when stress is placed on a cell, but has recently been shown to regulate cell migration as well. It was determined in this project that p53 could inhibit the formation of both lamellipodia and circular dorsal ruffles. It was also shown that this could occur directly through an inhibition of the GTPase Rac. Previous studies have shown that p53 can upregulate caldesmon, a protein which is known to bind to and stabilize actin filaments while inhibiting Arp2/3-mediated branching. It was confirmed that p53 could upregulate caldesmon, and that caldesmon could inhibit the formation of lamellipodia and circular dorsal ruffles. The phosphorylation of caldesmon by p21-associated kinase (PAK) or extracellular signal-related kinase (Erk) was shown to effectively reverse the ability of caldesmon to inhibit these structures. The role of phosphatase and tensin homologue deleted on chromosome 10 (PTEN) was also studied with regards to this signalling pathway. PTEN was shown to inhibit lamellipodia and circular dorsal ruffles through its lipid phosphatase activity. It was concluded that p53 can inhibit the formation of lamellipodia and circular dorsal ruffles in vascular SMC, and that this occurs through Rac, caldesmon and PTEN.

Computational models for improved diagnosis and prognosis of stroke using robot-based biomarkers

Stroke is a leading cause of death and permanent disability worldwide, affecting millions of individuals. Traditional clinical scores for assessment of stroke-related impairments are inherently subjective and limited by inter-rater and intra-rater reliability, as well as floor and ceiling effects. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of neurological impairments following stroke. KINARM is an exoskeleton robotic device that provides objective, reliable tools for assessment of sensorimotor, proprioceptive and cognitive brain function by means of a battery of behavioral tasks. As such, KINARM is particularly useful for assessment of neurological impairments following stroke. This thesis introduces a computational framework for assessment of neurological impairments using the data provided by KINARM. This is done by achieving two main objectives. First, to investigate how robotic measurements can be used to estimate current and future abilities to perform daily activities for subjects with stroke. We are able to predict clinical scores related to activities of daily living at present and future time points using a set of robotic biomarkers. The findings of this analysis provide a proof of principle that robotic evaluation can be an effective tool for clinical decision support and target-based rehabilitation therapy. The second main objective of this thesis is to address the emerging problem of long assessment time, which can potentially lead to fatigue when assessing subjects with stroke. To address this issue, we examine two time reduction strategies. The first strategy focuses on task selection, whereby KINARM tasks are arranged in a hierarchical structure so that an earlier task in the assessment procedure can be used to decide whether or not subsequent tasks should be performed. The second strategy focuses on time reduction on the longest two individual KINARM tasks. Both reduction strategies are shown to provide significant time savings, ranging from 30% to 90% using task selection and 50% using individual task reductions, thereby establishing a framework for reduction of assessment time on a broader set of KINARM tasks. All in all, findings of this thesis establish an improved platform for diagnosis and prognosis of stroke using robot-based biomarkers.