Thesis (Ph. D.)--University of Toronto, 2008. / Includes bibliographical references.

Thesis (Ph.D.)--Syracuse University, 2008. / "Publication number: AAT 3323042."

Thesis (Ph.D.)--Syracuse University, 2008. / "Publication number: AAT 3347261."

Thesis (Ph.D)--Algorithms, Combinatorics, and Optimization, Georgia Institute of Technology, 2010. / Committee Chair: Tovey, Craig; Committee Member: Butera, Rob; Committee Member: Nemirovski, Arkadi; Committee Member: Prinz, Astrid; Committee Member: Sokol, Joel. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (PH.D.)--Syracuse University, 2003. / "Publication number AAT 3081645."

Thesis (Ph. D.)--Washington State University, December 2006. / Includes bibliographical references (p. 71-73).

Thesis (Ph.D.)--Montana State University--Bozeman, 2007. / Typescript. Chairperson, Graduate Committee: John P. Miller. Includes bibliographical references (leaves 152-171).

Pas de résumé en français / Posttraumatic stress disorder (PTSD) is a highly heterogeneous condition, ranging from individual traumatic incidents such as car accidents to national tragedies such as natural disasters. Every individual has a different depending on their personality and past experiences, especially regarding their tendency to depression. Hence the condition is better termed psychotrauma spectrum disorder (PSD). Its heterogeneity hinders reliable diagnosis, as detection is entirely dependent upon a clinician’s subjective impression and sensitivity to comorbidities and there is always the possibility of concealment. Yet early diagnosis is essential, as the earlier PSD is detected the more likely treatment will be successful. Furthermore, reliable biomarkers of PSD would allow for much more accurate detection and monitoring of progression. Here we propose a new computational approach building on our prior work on the early detection of Parkinson’s, Alzheimer’s and depression. We will use a new analysis tool, called the Brain Code (BC). This concept was developed to integrate many different kinds of data, for e.g. the often fragmented and incomplete outputs from body sensors that record balance, dexterity, postural, facial and vocal movements combined together with cognitive or clinical outputs such as the intentional or emotive content of speech. The Brain Code allows us to fit all these different data streams together in such a way as to compensate for the deficiencies of each individually. It can put disparate physiological and cognitive data into the same ‘coordinate system’, so that we will be able to develop a reliable quantitative ‘signature’ of PSD. These quantitative biomarkers will be designed so that they are useful for both physicians in a clinical setting and for communities affected by a large-scale traumatic event.

<p>Biological processes such as cell division and synaptic plasticity are regulated by concentration gradients of signaling molecules. A number of biochemical mechanisms can result in intracellular signaling gradients. For example, restriction of diffusional flux of a chemical from one compartment to another will result in a transient gradient. A sustained gradient can be generated by opposite reactions such as phosphorylation and dephosphorylation of a signaling substrate taking place at different locations in the cell. More sophisticated mechanisms for non-uniform spatial signaling profiles include Turing type patterning and wave-pinning. It is becoming apparent that cell shape can regulate concentration gradients and modulate the downstream processes. In Chapter 1 we review how cell geometry can regulate intracellular signaling gradients in the context of the aforementioned gradient-generating mechanisms. The works reviewed make heavy use of mathematical modeling in order to investigate how reaction and diffusion taking place in complex cell geometries can modulate concentration gradients. That is a motivation for Chapter 2 where we implement a computational method to simulate reaction and diffusion on curved surfaces representing the cell membrane coupled with reaction and diffusion in the enclosed volume (representing the cell cytosol). To solve the reaction-diffusion equations on the surface we use the closest point method, a finite-difference technique that embeds the equations in the surrounding space. Such method is coupled with an embedded boundary technique to solve the equations in the enclosed volume with boundary conditions accounting for material exchange between surface and volume. The method is second-order convergent in the grid spacing despite a simple accuracy analysis predicts first-order errors. In Chapter 3 we use mathematical modeling in order to propose mechanisms accounting for the spatiotemporal dynamics of Rho-GTPase signaling at dendritic spines during synaptic plasticity. Dendritic spines are the postsynaptic terminals of most excitatory synapses in the mammalian brain. Learning and memory are associated with long-lasting structural remodeling of dendritic spines (structural plasticity) through an actin-mediated process regulated by the Rho-family GTPases RhoA, Rac, and Cdc42. These GTPases undergo sustained activation following synaptic stimulation, but whereas Rho activity can spread from the stimulated spine, Cdc42 activity remains localized to the stimulated spine. Since Cdc42 itself diffuses rapidly in and out of the spine, the basis for the retention of Cdc42 activity in the stimulated spine long after synaptic stimulation has ceased remains unclear. We model the spread of Cdc42 activation at dendritic spines by means of reaction-diffusion equations solved on spine-like geometries. Excitable behavior arising from positive feedback in Cdc42 activation leads to spreading waves of Cdc42 activity. However, because of the very narrow neck of the dendritic spine, wave propagation is halted through a phenomenon we term geometrical wave-pinning. We show that this can account for the localization of Cdc42 activity in the stimulated spine and interestingly, retention is enhanced by high diffusivity of Cdc42. These findings are broadly applicable to other instances of signaling in extreme geometries, including filopodia and primary cilia.</p> / Dissertation

The hexanucleotide repeat expansion (HRE) mutation within C9orf72 gene is the most common cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Several hypotheses have been proposed for how the mutation contributes to pathogenicity, including the loss of C9orf72 gene function, RNA-mediate toxicity and the formation of toxic dipeptides by repeat-associated non-ATG (RAN) translation. Patient-specific iPSCs provide a promising tool for the study of the cellular and molecular mechanisms of human diseases in relevant cell types and discovering potential therapies. The CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9-mediated homology directed repair (HDR) system represents an attractive approach for disease modelling and development of therapeutic strategies. In this thesis, iPSCs derived from ALS/FTD patient carrying the HRE mutation were generated and subsequently gene edited to remove a massive repeat expansion from the patient cells and replace it with the wild-type size of the repeats using HDR and a plasmid donor template. The successful genotypic correction of the mutation resulted in the normalization of the C9orf72 gene promoter methylation level and the gene variants RNA expression level. Removal of the mutation also resulted in abolition of sense and antisense RNA foci formation and reduction of DPRs accumulation. Furthermore, the repeat size correction also rescued the susceptibility of cells to Glutamate excitotoxicity, decreased the apoptotic cell death and stress granules formation under the baseline and stress conditions. This work provides a proof-of-principle that removal of the HRE can rescue ALS disease phenotypes and provides an evidence that HRE mutation is an attractive target for therapeutic strategies and drug screening, to block the underlying disease mechanisms.