Source: Dissertation Abstracts International, Volume: 37-10, Section: B, page: 4834. / Thesis (Ph.D.)--The Florida State University, 1976.

Source: Dissertation Abstracts International, Volume: 35-10, Section: B, page: 4774. / Thesis (Ph.D.)--The Florida State University, 1974.

Source: Dissertation Abstracts International, Volume: 36-12, Section: B, page: 5935. / Thesis (Ph.D.)--The Florida State University, 1975.

Source: Dissertation Abstracts International, Volume: 36-12, Section: B, page: 5931. / Thesis (Ph.D.)--The Florida State University, 1975.

Source: Dissertation Abstracts International, Volume: 39-06, Section: B, page: 2630. / Thesis (Ph.D.)--The Florida State University, 1978.

Construímos um modelo de caráter probabilístico para a embriogênese e a diferenciação celular, baseado nas redes genéticas, aleatoriamente conectadas, e no processo de criticalidade auto-organizada. Estudamos redes com 3, 4, 5, 10, 20, 30, 64 e 128 genes para as quais fizemos um levantamento do perfil da distribuição populacional da diversidade de atratores, e avaliamos a frequência com que foram gerados. Obtivemos resultados exatos para redes com 3 e 4 genes. Para redes maiores, foram obtidos resultados quantitativos através de varreduras aleatórias. Construímos autômatos de pilha de areia não direcionais, numa rede quadrada (L POT.2), e determinamos os máximos populacionais a eles associados para L=3, 4, 5, 6, 7, 8 e 9. Mostramos que os parâmetros do Caenorhabidits elegans, cuja historia desenvolvimental e bem conhecida, são compatíveis com o modelo proposto. / A probalistic model for Embriogenesis and Cellular Diferentiation, has been constructed, based on the random genetic networks and the self organized criticality process. Networks with 3, 4, 5, 10, 20, 30, 64, 128 genes were studied. A survey of the population distribution profile was made and their frequency of generation were evaluated. We obtained exact results for nets with 3 and 4 genes. Quantitative results were obtained for the larger ones by means of random scanning. We constructed a undirected sand pile model in a square net (L POT.2) and determined the population maxima for L = 3, 4, 5, 6, 7, 8 and 9. We showed that parameters for Caenorhabidits elegans, that has a well known developmental story, are in agreement with the proposed model.

A comprehensive mathematical model of the respiratory system is developed using available physiological data and structural information. The model evolves through systemic analysis and development of causal relationships describing the three main subsystems; neural control, lung mechanics and gas exchange. The subsystem models are based upon physiological evidence where possible but limited experimental data necessitates some structural hypothesisation particularly in the neural control model where knowledge concerning the central respiratory centre is scant and vague. Investigation of the neural system employs the concept of maintained respiratory rhythmicity through two coupled oscillators. Software and hardware models are generated and implemented and comparative testing gives a better understanding of the system behaviour. An improved model of the lung mechanics system is developed incorporating the concept of the equipressure point and a new theoretical approach to aid analysis. Performance of new experiments on humans allows further validation of a suitably adapted, existing gas exchange model. Detailed analysis and validation of the individual subsystem models using appropriate performance criteria, and their subsequent combination through the design of physiologically acceptable interfaces leads to the overall model of the respiratory system. Model uniqueness may be revealed through validation processes and the applicability of two approaches to structural identification and parameter estimation to the models of the respiratory system is demonstrated. A combination of the two techniques (functional minimisation and feature space pattern recognition) in conjunction with sensitivity analysis and model reduction is proposed as a superior means of identification of physiological systems. The comprehensive model of the respiratory system and the subsystem models highlight areas of uncertainty, providing , stimulation for future research in physiological and modelling fields,' Suggestions for further experimentation and theoretical studies in relevant areas are presented.

Many fundamental cellular processes hinge on the ability of cells to exert contractile force. Contractility is used by cells to divide, to migrate, to heal wounds, and to pump the heart and move limbs. Contractility is mediated by the actin and myosin cytoskeleton, a dynamic and responsive meshwork that assembles into various well-defined structures used by the cell to accomplish specific tasks. While muscle contraction is well-characterized, the contraction mechanisms of actomyosin structures in nonmuscle cells are relatively obscure. Here we elucidate the contraction mechanisms of two prominent and related actomyosin structures: the contractile ring, which constricts to divide the cell during cytokinesis, and the stress fiber, which is anchored to the extracellular matrix and allows the cell to exert contractile forces on its surroundings. In the first part of the thesis, we develop a mathematical model to characterize the constriction mechanism of contractile rings in the Schizosaccharomyces pombe model organism. Our collaborators observed that after digesting the cell wall to create protoplasts, contractile rings constricted by sliding along the plasma membrane without cleaving the cell. This novel approach allowed direct comparison of our model predictions for the ring constriction rate and ring shape to the experimental data, and demonstrated that the contractile ring's rate of constriction is determined by a balance between ring tension and external resistance forces. Our results describe a casual relationship between ring organization, actin turnover kinetics, tension, and constriction. Ring tension depends on ring organization through the actin and myosin concentrations and their statistical correlations. These correlations are established and renewed by actin turnover on a timescale much less than the constriction time so that rapid actin turnover sets the tension and provides the mechanism for continuous remodeling during constriction. Thus, we show that the contractile ring is a tension-producing machine regulated by actin turnover whose constriction rate depends on the response of a coupled system to the ring tension. In the second part of the thesis we examine the contraction mechanisms of stress fibers, which have a sarcomeric structure reminiscent of muscle. We developed mathematical models of stress fibers to describe their rapid shortening after severing and to describe how the kinetics of sarcomere contraction and expansion depend on actin turnover. To test these models, we performed quantitative image analysis of stress fibers that spontaneously severed and recoiled. We observed that after spontaneous severing, stress fibers shorten by ~80% over ~15-30 s, during which ~50% of the actin initially present was disassembled. Actin disassembly was delayed by ~50 s relative to fiber recoil, causing a characteristic increase, peak, and decay in the actin density after severing. Model predictions were in excellent agreement with the observations. The model predicts that following breakage, fiber shortening due to myosin contractile force increases actin filament overlap in the center of the sarcomeres, which in turn causes compressive actin-actin elastic stresses. These stresses promote actin disassembly, thereby shortening the actin filaments and allowing further contraction. Thus, the model identifies a mechanism whereby coupling between actin turnover and mechanical stresses allows stress fibers to dynamically adjust actin filament lengths to accommodate contraction.

The IKs potassium channel, critical to control of heart electrical activity, requires assembly of pore-forming alpha subunits (KCNQ1) and accessory beta (KCNE1) subunits. IKs is the slowly activating component of delayed rectifier K+ current in the heart and is a major contributor to the timing of repolarization of the cardiomyocyte membrane potential. Inherited mutations in either IKs channel subunit are associated with cardiac arrhythmia syndromes, including long QT syndrome (LQTS), short QT syndrome (SQTS) and familial atrial fibrillation (FAF). The biophysical properties of IKs channel current are dramatically altered when KCNE1 associates with the KCNQ1 channel. Functional tetrameric channels can be formed by KCNQ1 alone, but co-assembly with KCNE1 is required for the unique kinetics necessary to regulate human cardiac electrical activity as well as for the channel's functional response to the sympathetic nervous system. Specifically, KCNE1 co-assembly results in a depolarizing shift in the voltage dependence of activation, an increase in the single channel conductance, and an increase in current density. IKs channel current is also characterized by slow activation and deactivation kinetics, with little or no inactivation, in contrast to the KCNQ1 homomeric channel, which is characterized by fast activation and deactivation kinetics and clear inactivation. We wanted to understand how KCNE1 modulates the KCNQ1 channel functionally and investigate the structural determinants of this modulation. In Chapter II, we explore the role(s) of KCNE1 in the context of two KCNQ1 atrial fibrillation associated mutations, S140G and V141M. In contrast to published results, we find distinct dependence on the KCNE1 subunit for V141M, but not for S140G. Having determined the importance of KCNE1 for V141M functionally, we continued to explore the role of KCNE1 structurally for this mutation. Using cysteine substitution in both KCNQ1 and KCNE1 subunits, we monitored spontaneous disulfide bond formation and find that V141C crosslinks to KCNE1, while S140C does not. Having established the functional and structural importance of KCNE1 for V141M, we proposed that there could be mutations in KCNE1 that could reverse the consequences of slow deactivation in the V141M mutation. In Chapter III, we engineer amino terminal KCNE1 mutations and demonstrate that this domain is important for controlling deactivation, but not activation, kinetics of the KCNQ1 channel. We find two KCNE1 mutations, L45F and Y46W, which when co-expressed with either V141M or S140G mutations in KCNQ1, help restore the mutant channel back towards a wild-type IKs channel. From these results, we propose that the amino-terminal domain could play an important role in mediating the rate of deactivation in KCNQ1/KCNE1 channels. After testing mutations on KCNE1 that could affect normal channel function, we continued with a project to study mutations on KCNQ1 that would have similar dramatic effects on the channel. In Chapter IV, we mutated KCNQ1 residue S140 to Threonine and found that S140T co-assembled with KCNE1 produced a channel having functional characteristics opposite to that of S140G/KCNE1 channels. In contrast to S140G/KCNE1 channels, where channels tend to stay open due to very slow deactivation kinetics, S140T/KCNE1 channels tend to be stabilized in the closed state and require more depolarized pulses to open channels. In addition, we find that a mutation at position Y46 in KCNE1, when co-expressed with the S140T mutation in KCNQ1, helps restore the mutant channel back towards a wild-type channel. Again, here we provide evidence that the amino terminal end of KCNE1 could play a role in controlling deactivation. In Chapter V, we investigated the importance of where KCNE1 is located in the channel and also how KCNQ1/KCNE1 subunits assemble using a tandem construct, with 1 KCNE1 subunit tethered to 2 KCNQ1 subunits (EQQ). To investigate the significance of KCNE1 location, we explored the functional consequences of having the S140G or V141M mutations in the proximal (closest to KCNE1) or distal (farthest from KCNE1) KCNQ1 subunit. We find that having a mutation in the proximal subunit is subject to modulation by KCNE1, but not the distal subunit. Using crosslinking, we want to confirm proper assembly of the heterotetrameric channel to verify that KCNE1 assembles between S1 from one KCNQ1 subunit and the S6 domain of an opposing KCNQ1 subunit. Taken together, we demonstrate that the proximity between the N-terminus of KCNE1 and the S1 domain of KCNQ1 could play a role in modulating deactivation kinetics of KCNQ1. These findings will be of great importance in understanding normal IKs channel function, which will be essential for maintaining proper heart function.

Spike-timing dependent plasticity (STDP), a widespread synaptic modification mechanism, is sensitive to correlations between presynaptic spike trains, and organizes neural circuits in functionally useful ways. In this dissertation, I study the structures arising from STDP in a population of synapses with an emphasis on the interplay between synaptic stability and Hebbian competition, explained in Chapter 1. Starting from the simplest description of STDP which relates synaptic modification to the intervals between pairs of pre- and postsynaptic spikes, I show in Chapter 2 that stability and Hebbian competition are incompatible in this class of ``pair-based'' STDP models, either when hard bounds or soft bounds are imposed to the synapses. In chapter 3, I propose an alternative biophysically inspired method for imposing bounds to synapses, i.e. introducing a small temporal shift in the STDP window. Shifted STDP overcomes the incompatibility of synaptic stability and competition and can implement both Hebbian and anti-Hebbian forms of competitive plasticity. In light of experiments the explored a variety of spike patterns, STDP models have been augmented to account for interactions between multiple pre- and postsynaptic action potentials. In chapter 4, I study the stability/competition interplay in three different proposed multi-spike models of STDP. I show that the ``triplet model'' leads to a partially steady-state distribution of synaptic weights and induces Hebbian competition. The ``suppression model'' develops a stable distribution of weights when the average weight is high and shows predominantly anti-Hebbian competition. The "NMDAR-based" model can lead to either stable or partially stable synaptic weight distribution and exhibits both Hebbian and anti-Hebbian competition, depending on the parameters. I conclude that multi-spike STDP models can produce radically different effects at the population level depending on how they implement multi-spike interactions. Finally in chapter 5, I focus on the types of global structures that arise from STDP in a recurrent network. By analyzing pairwise interactions of neurons through STDP and also numerical simulations of a large network, I show that conventional pair-based STDP functions as a loop-eliminating mechanism in a network of spiking neurons and organizes neurons into in- and out-hubs. Loop-elimination increases when depression dominates and decreases when potentiation dominates. STDP with dominant depression implements a buffering mechanism for network firing rates, and shifted STDP can generate recurrent connections in a network, and also functions as a homeostatic mechanism that maintains a roughly constant average value of the synaptic strengths. In conclusion, studying pairwise interactions of neurons through STDP provides a number of important insights about the structures that arise from this plasticity rule in large networks. This approach can be extended to networks with more complex STDP models and more structured external input.