Matching Items (105)
Description
Diseases have been part of human life for generations and evolve within the population, sometimes dying out while other times becoming endemic or the cause of recurrent outbreaks. The long term influence of a disease stems from different dynamics within or between pathogen-host, that have been analyzed and studied by many researchers using mathematical models. Co-infection with different pathogens is common, yet little is known about how infection with one pathogen affects the host's immunological response to another. Moreover, no work has been found in the literature that considers the variability of the host immune health or that examines a disease at the population level and its corresponding interconnectedness with the host immune system. Knowing that the spread of the disease in the population starts at the individual level, this thesis explores how variability in immune system response within an endemic environment affects an individual's vulnerability, and how prone it is to co-infections. Immunology-based models of Malaria and Tuberculosis (TB) are constructed by extending and modifying existing mathematical models in the literature. The two are then combined to give a single nine-variable model of co-infection with Malaria and TB. Because these models are difficult to gain any insight analytically due to the large number of parameters, a phenomenological model of co-infection is proposed with subsystems corresponding to the individual immunology-based model of a single infection. Within this phenomenological model, the variability of the host immune health is also incorporated through three different pathogen response curves using nonlinear bounded Michaelis-Menten functions that describe the level or state of immune system (healthy, moderate and severely compromised). The immunology-based models of Malaria and TB give numerical results that agree with the biological observations. The Malaria--TB co-infection model gives reasonable results and these suggest that the order in which the two diseases are introduced have an impact on the behavior of both. The subsystems of the phenomenological models that correspond to a single infection (either of Malaria or TB) mimic much of the observed behavior of the immunology-based counterpart and can demonstrate different behavior depending on the chosen pathogen response curve. In addition, varying some of the parameters and initial conditions in the phenomenological model yields a range of topologically different mathematical behaviors, which suggests that this behavior may be able to be observed in the immunology-based models as well. The phenomenological models clearly replicate the qualitative behavior of primary and secondary infection as well as co-infection. The mathematical solutions of the models correspond to the fundamental states described by immunologists: virgin state, immune state and tolerance state. The phenomenological model of co-infection also demonstrates a range of parameter values and initial conditions in which the introduction of a second disease causes both diseases to grow without bound even though those same parameters and initial conditions did not yield unbounded growth in the corresponding subsystems. This results applies to all three states of the host immune system. In terms of the immunology-based system, this would suggest the following: there may be parameter values and initial conditions in which a person can clear Malaria or TB (separately) from their system but in which the presence of both can result in the person dying of one of the diseases. Finally, this thesis studies links between epidemiology (population level) and immunology in an effort to assess the impact of pathogen's spread within the population on the immune response of individuals. Models of Malaria and TB are proposed that incorporate the immune system of the host into a mathematical model of an epidemic at the population level.
ContributorsSoho, Edmé L (Author) / Wirkus, Stephen (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2011
Description
Like individual organisms, complex social groups are able to maintain predictable trajectories of growth, from initial colony foundation to mature reproductively capable units. They do so while simultaneously responding flexibly to variation in nutrient availability and intake. Leafcutter ant colonies function as tri-trophic systems, in which the ants harvest vegetation to grow a fungus that, in turn, serves as food for the colony. Fungal growth rates and colony worker production are interdependent, regulated by nutritional and behavioral feedbacks. Fungal growth and quality are directly affected by worker foraging decisions, while worker production is, in turn, dependent on the amount and condition of the fungus. In this dissertation, I first characterized the growth relationship between the workers and the fungus of the desert leafcutter ant Acromyrmex versicolor during early stages of colony development, from colony foundation by groups of queens through the beginnings of exponential growth. I found that this relationship undergoes a period of slow growth and instability when workers first emerge, and then becomes allometrically positive. I then evaluated how mass and element ratios of resources collected by the ants are translated into fungus and worker population growth, and refuse, finding that colony digestive efficiency is comparable to digestive efficiencies of other herbivorous insects and ruminants. To test how colonies behaviorally respond to perturbations of the fungus garden, I quantified activity levels and task performance of workers in colonies with either supplemented or diminished fungus gardens, and found that colonies adjusted activity and task allocation in response to the fungus garden size. Finally, to identify possible forms of nutrient limitation, I measured how colony performance was affected by changes in the relative amounts of carbohydrates, protein, and phosphorus available in the resources used to grow the fungus garden. From this experiment, I concluded that colony growth is primarily carbohydrate-limited.
ContributorsClark, Rebecca, 1981- (Author) / Fewell, Jennifer H (Thesis advisor) / Mueller, Ulrich (Committee member) / Liebig, Juergen (Committee member) / Elser, James (Committee member) / Harrison, Jon (Committee member) / Arizona State University (Publisher)
Created2011
Description
The repression of reproductive competition and the enforcement of altruism are key components to the success of animal societies. Eusocial insects are defined by having a reproductive division of labor, in which reproduction is relegated to one or few individuals while the rest of the group members maintain the colony and help raise offspring. However, workers have retained the ability to reproduce in most insect societies. In the social Hymenoptera, due to haplodiploidy, workers can lay unfertilized male destined eggs without mating. Potential conflict between workers and queens can arise over male production, and policing behaviors performed by nestmate workers and queens are a means of repressing worker reproduction. This work describes the means and results of the regulation of worker reproduction in the ant species Aphaenogaster cockerelli. Through manipulative laboratory studies on mature colonies, the lack of egg policing and the presence of physical policing by both workers and queens of this species are described. Through chemical analysis and artificial chemical treatments, the role of cuticular hydrocarbons as indicators of fertility status and the informational basis of policing in this species is demonstrated. An additional queen-specific chemical signal in the Dufour's gland is discovered to be used to direct nestmate aggression towards reproductive competitors. Finally, the level of actual worker-derived males in field colonies is measured. Together, these studies demonstrate the effectiveness of policing behaviors on the suppression of worker reproduction in a social insect species, and provide an example of how punishment and the threat of punishment is a powerful force in maintaining cooperative societies.
ContributorsSmith, Adrian A. (Author) / Liebig, Juergen (Thesis advisor) / Hoelldobler, Bert (Thesis advisor) / Gadau, Juergen (Committee member) / Johnson, Robert A. (Committee member) / Pratt, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
Description
Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.
ContributorsIslam, Gazi (Author) / Li, Baoxin (Thesis advisor) / Liang, Jianming (Thesis advisor) / Dinu, Valentin (Committee member) / Greenes, Robert (Committee member) / Smith, Marshall (Committee member) / Kahol, Kanav (Committee member) / Patel, Vimla L. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Solution methods for certain linear and nonlinear evolution equations are presented in this dissertation. Emphasis is placed mainly on the analytical treatment of nonautonomous differential equations, which are challenging to solve despite the existent numerical and symbolic computational software programs available. Ideas from the transformation theory are adopted allowing one to solve the problems under consideration from a non-traditional perspective. First, the Cauchy initial value problem is considered for a class of nonautonomous and inhomogeneous linear diffusion-type equation on the entire real line. Explicit transformations are used to reduce the equations under study to their corresponding standard forms emphasizing on natural relations with certain Riccati(and/or Ermakov)-type systems. These relations give solvability results for the Cauchy problem of the parabolic equation considered. The superposition principle allows to solve formally this problem from an unconventional point of view. An eigenfunction expansion approach is also considered for this general evolution equation. Examples considered to corroborate the efficacy of the proposed solution methods include the Fokker-Planck equation, the Black-Scholes model and the one-factor Gaussian Hull-White model. The results obtained in the first part are used to solve the Cauchy initial value problem for certain inhomogeneous Burgers-type equation. The connection between linear (the Diffusion-type) and nonlinear (Burgers-type) parabolic equations is stress in order to establish a strong commutative relation. Traveling wave solutions of a nonautonomous Burgers equation are also investigated. Finally, it is constructed explicitly the minimum-uncertainty squeezed states for quantum harmonic oscillators. They are derived by the action of corresponding maximal kinematical invariance group on the standard ground state solution. It is shown that the product of the variances attains the required minimum value only at the instances that one variance is a minimum and the other is a maximum, when the squeezing of one of the variances occurs. Such explicit construction is possible due to the relation between the diffusion-type equation studied in the first part and the time-dependent Schrodinger equation. A modication of the radiation field operators for squeezed photons in a perfect cavity is also suggested with the help of a nonstandard solution of Heisenberg's equation of motion.
ContributorsVega-Guzmán, José Manuel, 1982- (Author) / Sulov, Sergei K (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Platte, Rodrigo (Committee member) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2013
Description
Of all the signals and cues that orchestrate the activities of a social insect colony, the reproductives' fertility pheromones are perhaps the most fundamental. These pheromones regulate reproductive division of labor, a defining characteristic of eusociality. Despite their critical role, reproductive fertility pheromones are not evenly expressed across the development of a social insect colony and may even be absent in the earliest colony stages. In the ant Camponotus floridanus, queens of incipient colonies do not produce the cuticular hydrocarbons that serve as fertility and egg-marking signals in this species. My dissertation investigates the consequences of the dramatic change in the quantity of these pheromones that occurs as the colony grows. C. floridanus workers from large, established colonies use egg surface hydrocarbons to discriminate among eggs. Eggs with surface hydrocarbons typical of eggs laid by established queens are nurtured, whereas eggs lacking these signals (i.e., eggs laid by workers and incipient queens) are destroyed. I characterized how workers from incipient colonies responded to eggs lacking queen fertility hydrocarbons. I found that established-queen-laid eggs, incipient-queen-laid eggs, and worker-laid eggs were not destroyed by workers at this colony stage. Destruction of worker-laid eggs is a form of policing, and theoretical models predict that policing should be strongest in incipient colonies. Since there was no evidence of policing by egg-eating in incipient C. floridanus colonies, I searched for evidence of another policing mechanism at this colony stage. Finding none, I discuss reasons why policing behavior may not be expressed in incipient colonies. I then considered the mechanism that accounts for the change in workers' response to eggs. By manipulating ants' egg experience and testing their egg-policing decisions, I found that ants use a combination of learned and innate criteria to discriminate between targets of care and destruction. Finally, I investigated how the increasing strength of queen-fertility hydrocarbons affects nestmate recognition, which also relies on cuticular hydrocarbons. I found that queens with strong fertility hydrocarbons can be transferred between established colonies without aggression, but they cannot be introduced into incipient colonies. Queens from incipient colonies cannot be transferred into incipient or established colonies.
ContributorsMoore, Dani (Author) / Liebig, Juergen (Thesis advisor) / Gadau, Juergen (Committee member) / Pratt, Stephen (Committee member) / Smith, Brian (Committee member) / Rutowski, Ronald (Committee member) / Arizona State University (Publisher)
Created2012
Description
This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
Description
The living world we inhabit and observe is extraordinarily complex. From the perspective of a person analyzing data about the living world, complexity is most commonly encountered in two forms: 1) in the sheer size of the datasets that must be analyzed and the physical number of mathematical computations necessary to obtain an answer and 2) in the underlying structure of the data, which does not conform to classical normal theory statistical assumptions and includes clustering and unobserved latent constructs. Until recently, the methods and tools necessary to effectively address the complexity of biomedical data were not ordinarily available. The utility of four methods--High Performance Computing, Monte Carlo Simulations, Multi-Level Modeling and Structural Equation Modeling--designed to help make sense of complex biomedical data are presented here.
ContributorsBrown, Justin Reed (Author) / Dinu, Valentin (Thesis advisor) / Johnson, William (Committee member) / Petitti, Diana (Committee member) / Arizona State University (Publisher)
Created2012
Description
A notable feature of advanced eusocial insect groups is a division of labor within the sterile worker caste. However, the physiological aspects underlying the differentiation of behavioral phenotypes are poorly understood in one of the most successful social taxa, the ants. By starting to understand the foundations on which social behaviors are built, it also becomes possible to better evaluate hypothetical explanations regarding the mechanisms behind the evolution of insect eusociality, such as the argument that the reproductive regulatory infrastructure of solitary ancestors was co-opted and modified to produce distinct castes. This dissertation provides new information regarding the internal factors that could underlie the division of labor observed in both founding queens and workers of Pogonomyrmex californicus ants, and shows that changes in task performance are correlated with differences in reproductive physiology in both castes. In queens and workers, foraging behavior is linked to elevated levels of the reproductively-associated juvenile hormone (JH), and, in workers, this behavioral change is accompanied by depressed levels of ecdysteroid hormones. In both castes, the transition to foraging is also associated with reduced ovarian activity. Further investigation shows that queens remain behaviorally plastic, even after worker emergence, but the association between JH and behavioral bias remains the same, suggesting that this hormone is an important component of behavioral development in these ants. In addition to these reproductive factors, treatment with an inhibitor of the nutrient-sensing pathway Target of Rapamycin (TOR) also causes queens to become biased towards foraging, suggesting an additional sensory component that could play an important role in division of labor. Overall, this work provides novel identification of the possible regulators behind ant division of labor, and suggests how reproductive physiology could play an important role in the evolution and regulation of non-reproductive social behaviors.
ContributorsDolezal, Adam G (Author) / Amdam, Gro V (Thesis advisor) / Brent, Colin S. (Committee member) / Gadau, Juergen (Committee member) / Hoelldobler, Bert (Committee member) / Liebig, Juergen (Committee member) / Arizona State University (Publisher)
Created2012
Description
Critical care environments are complex in nature. Fluctuating team dynamics and the plethora of technology and equipment create unforeseen demands on clinicians. Such environments become chaotic very quickly due to the chronic exposure to unpredictable clusters of events. In order to cope with this complexity, clinicians tend to develop ad-hoc adaptations to function in an effective manner. It is these adaptations or "deviations" from expected behaviors that provide insight into the processes that shape the overall behavior of the complex system. The research described in this manuscript examines the cognitive basis of clinicians' adaptive mechanisms and presents a methodology for studying the same. Examining interactions in complex systems is difficult due to the disassociation between the nature of the environment and the tools available to analyze underlying processes. In this work, the use of a mixed methodology framework to study trauma critical care, a complex environment, is presented. The hybrid framework supplements existing methods of data collection (qualitative observations) with quantitative methods (use of electronic tags) to capture activities in the complex system. Quantitative models of activities (using Hidden Markov Modeling) and theoretical models of deviations were developed to support this mixed methodology framework. The quantitative activity models developed were tested with a set of fifteen simulated activities that represent workflow in trauma care. A mean recognition rate of 87.5% was obtained in automatically recognizing activities. Theoretical models, on the other hand, were developed using field observations of 30 trauma cases. The analysis of the classification schema (with substantial inter-rater reliability) and 161 deviations identified shows that expertise and role played by the clinician in the trauma team influences the nature of deviations made (p<0.01). The results shows that while expert clinicians deviate to innovate, deviations of novices often result in errors. Experts' flexibility and adaptiveness allow their deviations to generate innovative ideas, in particular when dynamic adjustments are required in complex situations. The findings suggest that while adherence to protocols and standards is important for novice practitioners to reduce medical errors and ensure patient safety, there is strong need for training novices in coping with complex situations as well.
ContributorsVankipuram, Mithra (Author) / Greenes, Robert A (Thesis advisor) / Patel, Vimla L. (Thesis advisor) / Petitti, Diana B. (Committee member) / Dinu, Valentin (Committee member) / Smith, Marshall L. (Committee member) / Arizona State University (Publisher)
Created2012