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archives@tulane.edu / Structural changes in the cytoskeleton during metastatic transformation make cancer cells more deformable, and recent experimental studies confirm a direct correlation between cell invasiveness and cell deformability. Several microfluidic approaches have recently developed to exploit this cellular property for high-throughput assessment of metastatic risk from small samples of patient’s blood. While demonstrating feasibility in the lab, these technologies often lack a solid theoretical foundation or do not show adequate sensitivity to cellular mechanical properties (“mechanotype”). The long-term goal of this project is to optimize microfluidic tests for metastatic risk assessment, including circulating tumor cell (CTC) isolation and mechanotype analysis, through predictive computational modeling. Specific aims of the presented study are 1) to expand the capability of our custom computational algorithm for viscoelastic cell deformation and migration to simulate cell sorting and CTC isolation in channels with complex geometry, including channels with pillars and bifurcations, and 2) to demonstrate the capability of our algorithm to optimize microfluidic methods for cancer cell mechanotype measurement. / 1 / Scott J. Hymel

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No description available.

archives@tulane.edu / The thalamocortical network generates rhythmic oscillations of various frequencies that underlie different brain states. Importantly, the transition from a faster frequency of firing, spindle, to slower oscillations, spike and wave discharges, is indicative of the pathological epileptic seizure development. Previous investigations have shown that the complex interactions between neurons in the thalamocortical network based on intrinsic and synaptic properties give rise to the observed frequency changes. However, the exact mechanism of how perturbations in this circuit disrupt the oscillations is not known. In this project, we used a well-established thalamocortical network computational model to perform receptor conductance changes to see how the oscillatory activity in the thalamocortical network changes. Computational methods can be used to provide some mathematical explanations regarding the mechanism of oscillations. Therefore, we generated several phase resetting curves by perturbing neurons during its oscillating period. Our results showed that the frequency reduction under the pathological state in the thalamocortical network might be caused by hyper-synchronization of neuronal activities in this circuit mediated by glutamatergic AMPA receptors. Notably, thalamic reticular neurons are capable of firing at a faster or slower frequency depending on the timing of the input that they receive from other neurons. Overall, our results provided evidence to support the hypothesis that thalamic reticular neurons might be the ultimate pacemakers in the thalamocortical network. / 1 / Hanyun Wang

A major obstacle for developing new antidepressants has been limited knowledge of the structure and function of a central target, the serotonin transporter (SERT). Established SERT inhibitors (SSRIs) were docked to an in silico SERT model to identify likely binding pocket amino acid residues. When mutated singly, no one of five implicated residues was critical for high affinity in vitro binding of SSRIs or cocaine. The in silico SERT model was used in ligand virtual screening (VS) of a small molecule structural library. Selected VS "hit" compounds were procured and tested in vitro; encouragingly, two compounds with novel structural scaffolds bound SERT with modest affinity. The combination of computational modeling, site-directed mutagenesis and pharmacologic characterization can accelerate binding site elucidation and the search for novel lead compounds. Such compounds may be tailored for improved serotonin receptor selectivity and reduced affinity for extraneous targets, providing superior antidepressants with fewer adverse effects. / Mylan School of Pharmacy and the Graduate School of Pharmaceutical Sciences; / Pharmacology / MS; / Thesis;

The role of the cardiovascular system is is to deliver oxygen and nutrients via arteries to the tissues of the body and to remove their waste products through the venous system. Due to certain pathological processes, arteries can be damaged resulting in a reduction of well oxygenated nutrient rich blood delivered to the tissues. Chronic hypoperfusion to the brain has been related to Alzeimer„s disease (AD). AD primarily affects people over 55 years of age, with an average duration of 7-10 years, resulting in death. Currently there are 600 million people in the world aged 60 years and over. This figure is expected to double by 2025 and to reach 2 billions by 2050. Finding a cure for a neurodegenerative disease such as AD would herald a major breakthrough in medical care. Currently AD is being widely investigated, but in order to find a cure, the complete pathophysiology of AD needs to be understood. Physilogical modelling could play a significant role to further develop that understanding. The underlying cause for AD is debated although several genetic loci have been identified for AD. Scientists have also demonstrated a strong connection with cerebral hypoperfusion. This results in tissue oxygen and nutrition deprivation which is a possible causative factor in the development of AD. In this thesis a Simulation model (SM) has been built to produce an arterial tree which resembles a natureal arterial tree. The SM model is based on Schreiner et al´s Constrained Constructive Optimization (CCO) method. The SM model produces a binary tree by choosing a random point in a defined area, and connects it to an exising tree structure, each time forming a new bifurcation. This bifurcation is optimized using the target function total minimum volume of the tree. The main difference between the CCO and SM method is the handling of the constrained areas in which the binary trees are grown within. The CCO method inceases the constrained area each time a segment is added to the tree structure, resulting in rescaling of the total tree each time. The SM tree utilizes a unit circle for the tree to grow in and uses a scaling factor to retrieve the real values of the tree segments as needed. Two trees were produced using the SM method, containing 250 (T250) and 2000 (T2000) terminals respectively. The segment Radii and length of the T2000 terminal tree was extracted and reorganized to fit the data structure of a zero-dimensional model developed by Alzaidi. This model was used to produce pressure and flow rate results for the T2000 tree. The relative perfusion of the infiltrated area in the T2000 tree was also calculated. This thesis shows a close resemblance between the SM tree and a true arterial tree, both visually and geometrically. The morphometric distribution of radii and length showed a good correlation between the SM tree and previous experimental research. The real values of radii and length found in the T2000 SM tree were found to be of larger radii and shorter length compared to previously reported values in the literature. However the results from the T250 SM tree showed excellent correlation with previous experimental results. The physiological parameters of pressure changes in the SM T2000 tree strongly mimic known in vivo physiological parameters from the human circulation. The flow rate in the tree was larger than expected, but can easily be rectified by changing the initial parameters of the SM program. The perfusion distribution diagram demonstrates a well known in vivo occurrence known as watershed zones which has recently been shown to be strongly associated with pathophysiological changes found on autopsies of brains from Alzheimer‟s patients.

The objective of this thesis is to develop and validate a computational framework based on mathematical models for the motion prediction and dynamic stability quantification of human walking, which can differentiate the dynamic stability of human walking with different mechanical properties of the leg. Firstly, a large measurement database of human walking motion was created. It contains walking measurement data of 8 subjects on 3 self-selected walking speeds, which 10 trials were recorded at each walking speed. The motion of whole-body centre of mass and the leg were calculated from the kinetic-kinematic measurement data. The fundamentals of leg property have been presented, and the parameters of leg property were extracted from the measurement data of human walking where the effects of walking speed and condition of foot-ground contact were investigated. Three different leg property definitions comprising linear axial elastic leg property, nonlinear axial elastic leg property and linear axial-tangential elastic leg property were used to extracted leg property parameters. The concept of posture-dependent leg property has been proposed, and the leg property parameters were extracted from the measurement data of human walking motion where the effects of walking speed and condition of foot-ground contact were also investigated. The compliant leg model with axial elastic property (CAE) was used for the dynamic stability analysis of human walking with linear and nonlinear axial elastic leg property. The compliant leg model with axial and tangential elastic property (CATE) was used for that with linear axial-tangential elastic leg property. The posture - dependent elastic leg model (PDE) was used for that with posture-dependent leg property. It was found that, with linear axial elastic leg property, the global stability of human walking improves with the bigger touchdown contact angle. The average leg property obtained from the measurement data of all participants allows the maximum global stability of human walking. With nonlinear axial elastic leg property, the global stability decreases with the stronger nonlinearity of leg stiffness. The incorporation of the tangential elasticity improves the global stability and shifts the stable walking velocity close to that of human walking at self-selected low speed (1.1-1.25 m/s).By the PDE model, the human walking motions were better predicted than by the CATE model. The effective range of walking prediction was enlarged to 1.12 – 1.8 m/s. However, represented by PDE model, only 1-2 walking steps can be achieved. In addition, the profiles of mechanical energies represented by the PDE model are different from that of the orbital stable walking represented by CATE model. Finally, the minimal requirements of the human walking measurements and the flexibility of simple walking models with deliberate leg property definitions allow the computational framework to be applicable in the dynamic stability analysis of the walking motion with a wide variety of mechanical property of the leg.

Parallel Distributed Processing (PDP) modelling has simulated developmental learning across a range of domains such as reading (e.g. Seidenberg & McClelland,1989) or Semantics (e.g. Rogers et al. 2004). However aside from two notable exceptions (Plaut, 1996; Welbourne & Lambon Ralph, 2005b) modelling research has not addressed the simulation of relearning during spontaneous recovery or rehabilitation after brain damage, and no research has considered the effect of the learning environment. This thesis used an established PDP model of semantic memory (Rogers et al., 2004) to simulate the influence of the learning environment. A novel quantitative measure (called representational economy) was developed to monitor efficiency during learning. Developmental learning is considered to be multimodal (e.g. Gogate et al., 2000) whereas rehabilitation is normally carried out through therapy sessions employing unimodal learning tasks (Best & Nickels, 2000). This thesis hoped to discover whether multimodal rehabilitation may be more efficient (as suggested by Howard et al., 1985). Three sets of simulations were conducted: The first set contrasted multimodal and unimodal learning in development and recovery, and tested internal representations for robustness to damage finding multimodal learning to be more efficient in all cases. The second set looked at whether this multimodal advantage could be approximated by reordering unimodal tasks at the item level. Findings indicated that the multimodal advantage is dependent upon simultaneous item presentation across multiple modalities. The third set of simulations contrasted multimodal and unimodal environments during rehabilitation while manipulating background spontaneous recovery, therapy set size and damage severity finding a multimodal advantage for all conditions of rehabilitation. The thesis findings suggest PDP models may be well-suited to predicting the effects of rehabilitation, and that clinical exploration of multimodal learning environments may yield substantial benefits in patient-related work.