Matching Items (88)
Description
In the face of widespread pollinator decline, research has increasingly focused on ways that pesticides could be harming bees. Fungicides are pesticides that are used in greater volumes than insecticides, yet significantly fewer studies have investigated the effects of these agrochemicals. The fungicide Pristine® is commonly used on bee-pollinated crops and has been shown to be detrimental to physiological processes that are key to honey bee foraging, such as digestion and learning. This study seeks to investigate how Pristine® exposure affects the amount of water, nectar, and pollen that honey bees collect. Colonies were fed either plain pollen patties or pollen patties containing 23 ppm Pristine®. Exposure to fungicide had no significant effect on corbicular pollen mass, the crop volumes of nectar or water foragers, or the proportions of foragers collecting different substances. There was a significantly higher sugar concentration in the crop of Pristine®-exposed nectar foragers (43.6%, 95% CI [38.8, 48.4]) compared to control nectar foragers (36.3%, 95% CI [31.9, 40.6]). The higher sugar concentration in the nectar of Pristine®-treated bees could indicate that the agrochemical decreases sucrose responsiveness or nutritional status in bees. Alternatively, fungicide exposure may increase the amount of sugar that bees need to make it back to the hive. Based on these results, it would appear that fungicides like Pristine® do not strongly affect the amounts of substances that honey bees collect, but it is still highly plausible that treated bees forage more slowly or with lower return rates.
ContributorsChester, Elise (Author) / Harrison, Jon (Thesis director) / DesJardins, Nicole (Committee member) / Smith, Brian (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2023-05
Description
Active sensing is a sensory phenomenon in which organisms use self-generated energy to examine their surroundings. This experiment strives to better understand active sensing in honeybees, predicting that active sensing may display itself primarily through antennae movement and that preventing antennae movement may result in differences in electroantennogram dose-response curves and associative learning plasticity. This will be done by examining changes in amplitude in electroantennogram response in both fixed-antenna and free-antenna bees over the course of a differential training protocol that establishes learned behavior discrimination.
ContributorsLei, Harry (Author) / Smith, Brian (Thesis director) / Albin-Brooks, Christopher (Committee member) / Barrett, The Honors College (Contributor)
Created2023-05
Description
By increasing the mean and variance of environmental temperatures, climate change has caused local extinctions and range shifts of numerous species. However, biologists disagree on which populations and species are most vulnerable to future warming. This debate arises because biologists do not know which physiological processes are most vulnerable to temperature or how to model these processes in complex environments. Using the South American locust (Schistocerca cancellata) as a model system, my dissertation addressed this debate and explained how climate limits the persistence of locust populations. Locusts of S. cancellata are serious agricultural pests with occasional outbreaks covering up to 4 million km2 over six countries. Because outbreaks are largely driven by climate, understanding how climate limits the persistence of locusts may help predict crop losses in future climates. To achieve this aim, I integrated observational, experimental, and computational approaches. First, I tested a physiological model of heat stress. By measuring the heat tolerance of locusts under different oxygen concentrations, I demonstrated that heat tolerance depends on oxygen supply during the hatchling stage only. Second, I modeled the geographic distribution of locusts using physiological traits. I started by measuring thermal effects on consumption and defecation of field-captured locusts, and I then used these data to model energy gain in current and future climates. My results indicated that incorporating physiological mechanisms can improve the accuracy of models and alter predicted impacts of climate change. Finally, I explored the causes and consequences of intraspecific variation in heat tolerance. After measuring heat tolerance of locusts in different hydration states and developmental stages, I modeled survival in historical microclimates. My models indicated that recent climate change has amplified the risk of overheating for locusts, and this risk depended strongly on shade availability, hydration state, and developmental stage. Therefore, the survival of locusts in future climates will likely depend on their access to shade and water. Overall, my dissertation argues that modeling physiological mechanisms can improve the ability of biologists to predict the impacts of climate change.
ContributorsYoungblood, Jacob (Author) / Angilletta, Michael (Thesis advisor) / Buckley, Lauren (Committee member) / Cease, Arianne (Committee member) / Smith, Brian (Committee member) / Vanden Brooks, John (Committee member) / Arizona State University (Publisher)
Created2022
Description
The representation of a patient’s characteristics as the parameters of a model is a key component in many studies of personalized medicine, where the underlying mathematical models are used to describe, explain, and forecast the course of treatment. In this context, clinical observations form the bridge between the mathematical frameworks and applications. However, the formulation and theoretical studies of the models and the clinical studies are often not completely compatible, which is one of the main obstacles in the application of mathematical models in practice. The goal of my study is to extend a mathematical framework to model prostate cancer based mainly on the concept of cell-quota within an evolutionary framework and to study the relevant aspects for the model to gain useful insights in practice. Specifically, the first aim is to construct a mathematical model that can explain and predict the observed clinical data under various treatment combinations. The second aim is to find a fundamental model structure that can capture the dynamics of cancer progression within a realistic set of data. Finally, relevant clinical aspects such as how the patient's parameters change over the course of treatment and how to incorporate treatment optimization within a framework of uncertainty quantification, will be examined to construct a useful framework in practice.
ContributorsPhan, Tin (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J (Committee member) / Crook, Sharon (Committee member) / Maley, Carlo (Committee member) / Bryce, Alan (Committee member) / Arizona State University (Publisher)
Created2021
Description
Synthetic biology (SB) has become an important field of science focusing on designing and engineering new biological parts and systems, or re-designing existing biological systems for useful purposes. The dramatic growth of SB throughout the past two decades has not only provided us numerous achievements, but also brought us more timely and underexplored problems. In SB's entire history, mathematical modeling has always been an indispensable approach to predict the experimental outcomes, improve experimental design and obtain mechanism-understanding of the biological systems. \textit{Escherichia coli} (\textit{E. coli}) is one of the most important experimental platforms, its growth dynamics is the major research objective in this dissertation. Chapter 2 employs a reaction-diffusion model to predict the \textit{E. coli} colony growth on a semi-solid agar plate under multiple controls. In that chapter, a density-dependent diffusion model with non-monotonic growth to capture the colony's non-linear growth profile is introduced. Findings of the new model to experimental data are compared and contrasted with those from other proposed models. In addition, the cross-sectional profile of the colony are computed and compared with experimental data. \textit{E. coli} colony is also used to perform spatial patterns driven by designed gene circuits. In Chapter 3, a gene circuit (MINPAC) and its corresponding pattern formation results are presented. Specifically, a series of partial differential equation (PDE) models are developed to describe the pattern formation driven by the MINPAC circuit. Model simulations of the patterns based on different experimental conditions and numerical analysis of the models to obtain a deeper understanding of the mechanisms are performed and discussed. Mathematical analysis of the simplified models, including traveling wave analysis and local stability analysis, is also presented and used to explore the control strategies of the pattern formation. The interaction between the gene circuit and the host \textit{E. coli} may be crucial and even greatly affect the experimental outcomes. Chapter 4 focuses on the growth feedback between the circuit and the host cell under different nutrient conditions. Two ordinary differential equation (ODE) models are developed to describe such feedback with nutrient variation. Preliminary results on data fitting using both two models and the model dynamical analysis are included.
ContributorsHe, Changhan (Author) / Kuang, Yang (Thesis advisor) / Wang, Xiao (Committee member) / Kostelich, Eric (Committee member) / Tian, Xiaojun (Committee member) / Gumel, Abba (Committee member) / Arizona State University (Publisher)
Created2021
Description
Transorbital surgery has gained recent notoriety due to its incorporation into endoscopic skull base surgery. The body of published literature on the field is cadaveric and observation. The pre-clinical studies are focused on the use of the endoscope only. Furthermore the methodology utilised in the published literature is inconsistent and does not embody the optimal principles of scientific experimentation. This body of work evaluates a minimally invasive novel surgical corridor - the transorbital approach - its validity in neurosurgical practice, as well as both qualitatively and quantitatively assessing available technological advances in a robust experimental fashion. While the endoscope is an established means of visualisation used in clinical transorbital surgery, the microscope has never been assessed with respect to the transorbital approach. This question is investigated here and the anatomical and surgical benefits and limitations of microscopic visualisation demonstrated. The comparative studies provide increased knowledge on specifics pertinent to neurosurgeons and other skull base specialists when planning pre-operatively, such as pathology location, involved anatomical structures, instrument maneuvrability and the advantages and disadvantages of the distinct visualisation technologies. This is all with the intention of selecting the most suitable surgical approach and technology, specific to the patient, pathology and anatomy, so as to perform the best surgical procedure. The research findings illustrated in this body of work are diverse, reproducible and applicable. The transorbital surgical corridor has substantive potential for access to the anterior cranial fossa and specific surgical target structures. The neuroquantitative metrics investigated confirm the utility and benefits specific to the respective visualisation technologies i.e. the endoscope and microscope. The most appropriate setting wherein the approach should be used is also discussed. The transorbital corridor has impressive potential, can utilise all available technological advances, promotes multi-disciplinary co-operation and learning amongst clinicians and ultimately, is a means of improving operative patient care.
ContributorsHoulihan, Lena Mary (Author) / Preul, Mark C. (Thesis advisor) / Vernon, Brent (Thesis advisor) / O' Sullivan, Michael G.J. (Committee member) / Lawton, Michael T. (Committee member) / Santarelli, Griffin (Committee member) / Smith, Brian (Committee member) / Arizona State University (Publisher)
Created2021
Description
Olfactory perception is a complex and multifaceted process that involves the detection of volatile organic compounds by olfactory receptor neurons in the nasal neuroepithelium. Different odorants can elicit different perceived intensities at the same concentration, while direct intensity ratings are vulnerable to framing effects and inconsistent scale usage. Odor perception is genetically determined, with each individual having a unique olfaction "footprint" and sensitivity levels. Genetic factors, age, gender, race, and environmental factors influence olfactory acuity. The olfactory system's complexity makes it challenging to create a standardized comparison system for olfactory perception tests. The COVID-19 pandemic has underscored the importance of olfactory dysfunction, particularly the loss of smell and taste as common symptoms. Research has demonstrated the widespread occurrence of olfactory impairment in various populations, often stemming from post-viral origins, which is the leading cause of permanent smell loss. Utilizing quantitative ranking on a qualitative scale enhances the precision and accuracy when evaluating and drawing conclusions about odor perception and how to mitigate problems caused by external factors. Pairwise comparisons enhance the accuracy and consistency of results and provide a more intuitive way of comparing items. Such ranking techniques can lead to early detection of olfactory disorders and improved diagnostic tools. The COVID-19 pandemic has shed light on the significance of olfactory dysfunction, emphasizing the need for further research and standardized testing methods in olfactory perception.
ContributorsDarden, Jaelyn (Author) / Smith, Brian (Thesis advisor) / Gerkin, Richard (Thesis advisor) / Spackman, Christy (Committee member) / Arizona State University (Publisher)
Created2023
Description
Since the 20th century, Arizona has undergone shifts in agricultural practices, driven by urban expansion and crop irrigation regulations. These changes present environmental challenges, altering atmospheric processes and influencing climate dynamics. Given the potential threats of climate change and drought on water availability for agriculture, further modifications in the agricultural landscape are expected. To understand these land use changes and their impact on carbon dynamics, our study quantified aboveground carbon storage in both cultivated and
abandoned agricultural fields. To accomplish this, we employed Python and various geospatial libraries in Jupyter Notebook files, for thorough dataset assembly and visual, quantitative analysis. We focused on nine counties known for high cultivation levels, primarily located in the lower latitudes of Arizona. Our analysis investigated carbon dynamics across not only abandoned and actively cultivated croplands but also neighboring uncultivated land, for which we estimated the extent. Additionally, we compared these trends with those observed in developed land areas.
The findings revealed a hierarchy in aboveground carbon storage, with currently cultivated lands having the lowest levels, followed by abandoned croplands and uncultivated wilderness. However, wilderness areas exhibited significant variation in carbon storage by county compared to cultivated and abandoned lands. Developed lands ranked highest in aboveground carbon storage, with the median value being the highest. Despite county-wide variations, abandoned croplands generally contained more carbon than currently cultivated areas, with adjacent wilderness lands containing even more than both. This trend suggests that cultivating croplands in the region reduces aboveground carbon stores, while abandonment allows for some replenishment, though only to a limited extent. Enhancing carbon stores in Arizona can be achieved through active restoration efforts on abandoned cropland. By promoting native plant regeneration and boosting aboveground carbon levels, these measures are crucial for improving carbon sequestration. We strongly advocate for implementing this step to facilitate the regrowth of native plants and enhance overall carbon storage in the region.
ContributorsGoodwin, Emily (Author) / Eikenberry, Steffen (Thesis director) / Kuang, Yang (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2024-05
Description
Glioblastoma Multiforme is a prevalent and aggressive brain tumor. It has an average 5-year survival rate of 6% and average survival time of 14 months. Using patient-specific MRI data from the Barrow Neurological Institute, this thesis investigates the impact of parameter manipulation on reaction-diffusion models for predicting and simulating glioblastoma growth. The study aims to explore key factors influencing tumor morphology and to contribute to enhancing prediction techniques for treatment.
ContributorsShayegan, Tara (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2024-05
Description
Development of the central nervous system is an incredible process that relies on multiple extracellular signaling cues and complex intracellular interactions. Approximately 1500 genes are associated with neurodevelopmental disorders, many of which are linked to a specific biochemical signaling cascade known as Extracellular-Signal Regulated Kinase (ERK1/2). Clearly defined mutations in regulators of the ERK1/2 pathway cause syndromes known as the RASopathies. Symptoms include intellectual disability, developmental delay, cranio-facial and cardiac deficits. Treatments for RASopathies are limited due to an in complete understanding of ERK1/2’s role in brain development. Individuals with Neurofibromatosis Type and Noonan Syndrome, the two most common RASopathies, exhibit aberrant functional and white matter organization in non-invasive imaging studies, however, the contributions of neuronal versus oligodendrocyte deficits to this phenotype are not fully understood. To define the cellular functions of ERK1/2 in motor circuit formation, this body of work focuses on two long-range projection neuron subtypes defined by their neurotransmitter. With genetic mouse models, pathological ERK1/2 in glutamatergic neurons reduces axonal outgrowth, resulting in deficits in activity dependent gene expression and the ability to learn a motor skill task. Restricting pathological ERK1/2 within cortical layer V recapitulates these wiring deficits but not the behavioral learning phenotype. Moreover, it is uncovered that pathological ERK1/2 results in compartmentalized expression pattern of phosphorylated ERK1/2. It is not clear whether ERK1/2 functions are similar in cholinergic neuron populations that mediate attention, memory, and motor control. Basal forebrain cholinergic neuron development relies heavily on NGF-TrKA neurotrophic signaling known to activate ERK1/2. Yet the function of ERK1/2 during cholinergic neuronal specification and differentiation is poorly understood. By selectively deleting ERK1/2 in cholinergic neurons, ERK1/2 is required for activity-dependent maturation of neuromuscular junctions in juvenile mice, but not the establishment of lower motor neuron number. Moreover, ERK1/2 is not required for specification of choline acetyltransferase expressing basal forebrain cholinergic neurons by 14 days of age. However, ERK1/2 may be necessary for BFCN maturation by adulthood. Collectively, these data indicate that glutamatergic neuron-autonomous decreases in long-range axonal outgrowth and modest effects on later stages of cholinergic neuron maintenance may be important aspects of neuropathogenesis in RASopathies.
ContributorsRees, Katherina Pavy (Author) / Newbern, Jason (Thesis advisor) / Olive, Foster (Committee member) / Qiu, Shenfeng (Committee member) / Sattler, Rita (Committee member) / Smith, Brian (Committee member) / Arizona State University (Publisher)
Created2024