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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
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
Land management practices such as domestic animal grazing can alter plant communities via changes in soil structure and chemistry, species composition, and plant nutrient content. These changes can affect the abundance and quality of plants consumed by insect herbivores with consequent changes in population dynamics. These population changes can translate to massive crop damage and pest control costs. My dissertation focused on Oedaleus asiaticus, a dominant Asian locust, and had three main objectives. First, I identified morphological, physiological, and behavioral characteristics of the migratory ("brown") and non-migratory ("green") phenotypes. I found that brown morphs had longer wings, larger thoraxes and higher metabolic rates compared to green morphs, suggesting that developmental plasticity allows greater migratory capacity in the brown morph of this locust. Second, I tested the hypothesis of a causal link between livestock overgrazing and an increase in migratory swarms of O. asiaticus. Current paradigms generally assume that increased plant nitrogen (N) should enhance herbivore performance by relieving protein-limitation, increasing herbivorous insect populations. I showed, in contrast to this scenario, that host plant N-enrichment and high protein artificial diets decreased the size and viability of O. asiaticus. Plant N content was lowest and locust abundance highest in heavily livestock-grazed fields where soils were N-depleted, likely due to enhanced erosion and leaching. These results suggest that heavy livestock grazing promotes outbreaks of this locust by reducing plant protein content. Third, I tested for the influence of dietary imbalance, in conjunction with high population density, on migratory plasticity. While high population density has clearly been shown to induce the migratory morph in several locusts, the effect of diet has been unclear. I found that locusts reared at high population density and fed unfertilized plants (i.e. high quality plants for O. asiaticus) had the greatest migratory capacity, and maintained a high percent of brown locusts. These results did not support the hypothesis that poor-quality resources increased expression of migratory phenotypes. This highlights a need to develop new theoretical frameworks for predicting how environmental factors will regulate migratory plasticity in locusts and perhaps other insects.
ContributorsCease, Arianne (Author) / Harrison, Jon (Thesis advisor) / Elser, James (Thesis advisor) / DeNardo, Dale (Committee member) / Quinlan, Michael (Committee member) / Sabo, John (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
Description
Conditions during development can shape the expression of traits at adulthood, a phenomenon called developmental plasticity. In this context, factors such as nutrition or health state during development can affect current and subsequent physiology, body size, brain structure, ornamentation, and behavior. However, many of the links between developmental and adult phenotype are poorly understood. I performed a series of experiments using a common molecular currency - carotenoid pigments - to track somatic and reproductive investments through development and into adulthood. Carotenoids are red, orange, or yellow pigments that: (a) animals must acquire from their diets, (b) can be physiologically beneficial, acting as antioxidants or immunostimulants, and (c) color the sexually attractive features (e.g., feathers, scales) of many animals. I studied how carotenoid nutrition and immune challenges during ontogeny impacted ornamental coloration and immune function of adult male mallard ducks (Anas platyrhynchos). Male mallards use carotenoids to pigment their yellow beak, and males with more beaks that are more yellow are preferred as mates, have increased immune function, and have higher quality sperm. In my dissertation work, I established a natural context for the role that carotenoids and body condition play in the formation of the adult phenotype and examined how early-life experiences, including immune challenges and dietary access to carotenoids, affect adult immune function and ornamental coloration. Evidence from mallard ducklings in the field showed that variation in circulating carotenoid levels at hatch are likely driven by maternal allocation of carotenoids, but that carotenoid physiology shifts during the subsequent few weeks to reflect individual foraging habits. In the lab, adult beak color expression and immune function were more tightly correlated with body condition during growth than body condition during subsequent stages of development or adulthood. Immune challenges during development affected adult immune function and interacted with carotenoid physiology during adulthood, but did not affect adult beak coloration. Dietary access to carotenoids during development, but not adulthood, also affected adult immune function. Taken together, these results highlight the importance of the developmental stage in shaping certain survival-related traits (i.e., immune function), and lead to further questions regarding the development of ornamental traits.
ContributorsButler, Michael (Author) / McGraw, Kevin J. (Thesis advisor) / Chang, Yung (Committee member) / Deviche, Pierre (Committee member) / DeNardo, Dale (Committee member) / Rutowski, Ronald (Committee member) / Arizona State University (Publisher)
Created2012
Description
This work involved the analysis of a public health system, and the design, development and deployment of enterprise informatics architecture, and sustainable community methods to address problems with the current public health system. Specifically, assessment of the Nationally Notifiable Disease Surveillance System (NNDSS) was instrumental in forming the design of the current implementation at the Southern Nevada Health District (SNHD). The result of the system deployment at SNHD was considered as a basis for projecting the practical application and benefits of an enterprise architecture. This approach has resulted in a sustainable platform to enhance the practice of public health by improving the quality and timeliness of data, effectiveness of an investigation, and reporting across the continuum.
ContributorsKriseman, Jeffrey Michael (Author) / Dinu, Valentin (Thesis advisor) / Greenes, Robert (Committee member) / Johnson, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
Immunosignaturing is a technology that allows the humoral immune response to be observed through the binding of antibodies to random sequence peptides. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides in a multiplexed fashion. There are computational and statistical challenges to the analysis of immunosignaturing data. The overall aim of my dissertation is to develop novel computational and statistical methods for immunosignaturing data to access its potential for diagnostics and drug discovery. Firstly, I discovered that a classification algorithm Naive Bayes which leverages the biological independence of the probes on our array in such a way as to gather more information outperforms other classification algorithms due to speed and accuracy. Secondly, using this classifier, I then tested the specificity and sensitivity of immunosignaturing platform for its ability to resolve four different diseases (pancreatic cancer, pancreatitis, type 2 diabetes and panIN) that target the same organ (pancreas). These diseases were separated with >90% specificity from controls and from each other. Thirdly, I observed that the immunosignature of type 2 diabetes and cardiovascular complications are unique, consistent, and reproducible and can be separated by 100% accuracy from controls. But when these two complications arise in the same person, the resultant immunosignature is quite different in that of individuals with only one disease. I developed a method to trace back from informative random peptides in disease signatures to the potential antigen(s). Hence, I built a decipher system to trace random peptides in type 1 diabetes immunosignature to known antigens. Immunosignaturing, unlike the ELISA, has the ability to not only detect the presence of response but also absence of response during a disease. I observed, not only higher but also lower peptides intensities can be mapped to antigens in type 1 diabetes. To study immunosignaturing potential for population diagnostics, I studied effect of age, gender and geographical location on immunosignaturing data. For its potential to be a health monitoring technology, I proposed a single metric Coefficient of Variation that has shown potential to change significantly when a person enters a disease state.
ContributorsKukreja, Muskan (Author) / Johnston, Stephen Albert (Thesis advisor) / Stafford, Phillip (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Parental care provides many benefits to offspring. One widely realized benefit is enhanced regulation of offspring's thermal environment. The developmental thermal environment during development can be optimized behaviorally through nest site selection and brooding, and it can be further enhanced by physiological heat production. In fact, enhancement of the developmental thermal environment has been proposed as the initial driving force for the evolution of endothermy in bird and mammals. I used pythons (Squamata: Pythonidae) to expand existing knowledge of behavioral and physiological parental tactics used to regulate offspring thermal environment. I first demonstrated that brooding behavior in the Children's python (Antaresia childreni) is largely driven by internal mechanisms, similar to solitary birds, suggesting that the early evolution of the parent-offspring association was probably hormonally driven. Two species of python are known to be facultatively thermogenic (i.e., are endothermic during reproduction). I expand current knowledge of thermogenesis in Burmese pythons (Python molurus) by demonstrating that females use their own body temperature to modulate thermogenesis. Although pythons are commonly cited as thermogenic, the actual extent of thermogenesis within the family Pythonidae is unknown. Thus, I assessed the thermogenic capability of five previously unstudied species of python to aid in understanding phylogenetic, morphological, and distributional influences on thermogenesis in pythons. Results suggest that facultative thermogenesis is likely rare among pythons. To understand why it is rare, I used an artificial model to demonstrate that energetic costs to the female likely outweigh thermal benefits to the clutch in species that do not inhabit cooler latitudes or lack large energy reserves. In combination with other studies, these results show that facultative thermogenesis during brooding in pythons likely requires particular ecological and physiological factors for its evolution.
ContributorsBrashears, Jake (Author) / DeNardo, Dale (Thesis advisor) / Harrison, Jon (Committee member) / Deviche, Pierre (Committee member) / McGraw, Kevin (Committee member) / Smith, Andrew (Committee member) / Arizona State University (Publisher)
Created2012
Description
Students across the United States lack the necessary skills to be successful college students in Science, Technology and Math (STEM) majors and as a result post-secondary institutions are developing summer bridge programs to aid in their transition. As they develop these programs, effective theory and approach are critical to developing successful programs. Though there are a multitude of theories on successful student development, a focus on self-efficacy is critical. Summer Bridge programs across the country as well as the Bio Bridge summer program at Arizona State University were studied alone and through the lens of Cognitive Self-Efficacy Theory as mentioned in Albert Bandura's "Perceived Self-Efficacy in Cognitive Development and Functioning." Cognitive Self-Efficacy Theory provides a framework for self-efficacy development in academic settings. An analysis of fifteen bridge programs found that a large majority focused on developing academic capabilities and often overlooked development of community and social efficacy. An even larger number failed to focus on personal psychology in managing self-debilitating thought patterns based on published goals. Further, Arizona State University's Bio Bridge program could not be considered successful at developing cognitive self-efficacy or increasing retention as data was inconclusive. However, Bio Bridge was tremendously successful at developing social efficacy and community among participants and faculty. Further research and better evaluative techniques need to be developed to understand the program's effectiveness in cognitive self-efficacy development and retention.
ContributorsTummala, Sailesh Vardhan (Author) / Orchinik, Miles (Thesis director) / Brownell, Sara (Committee member) / Shortlidge, Erin (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2015-05