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THE RXR AGONIST MSU-42011 IS EFFECTIVE FOR THE TREATMENT OF PRECLINICAL NF1-DEFICIENT MODELS
No full textThesis (Ph.D.)--Michigan State University. Molecular, Cellular, and Integrative Physiology \u2013 Doctor of Philosophy, 2025Retinoid X receptors (RXRs) are nuclear receptors that act as ligand-dependent transcription factors by heterodimerizing with other nuclear receptors to regulate key signaling pathways influencing cancer progression. Activation of RXRs modulates cell proliferation, inflammation, and immune responses within the tumor microenvironment (TME), impacting tumor growth and immune surveillance. While RXR agonists like bexarotene have demonstrated clinical utility in cutaneous T cell lymphoma, their broader application in cancer immunomodulation is under active investigation. Our lab has synthesized novel RXR agonists, with my particular focus on MSU-42011, which has shown promising preclinical activity in modulating tumor-promoting immune cells and signaling pathways involved in cancer progression.Neurofibromatosis type 1 (NF1) is a genetic disorder characterized by the development of plexiform neurofibromas (PNFs), which may progress to malignant peripheral nerve sheath tumors (MPNSTs), aggressive sarcomas with limited treatment options. The MEK inhibitor selumetinib is FDA-approved for NF1-associated PNFs, but its efficacy against MPNSTs is modest and limited by toxicity. Given the prominent infiltration of tumor-promoting macrophages in NF1 lesions and their correlation with disease progression, targeting immune components of the TME presents a promising therapeutic avenue. This study evaluates the RXR agonist MSU-42011, alone and in combination with selumetinib, using NF1-deficient cell lines (bearing NF1, CDKN2A and TP53 deletions) and a syngeneic MPNST mouse model. In vivo, treatment with MSU-42011 significantly inhibited tumor growth, reduced pERK levels, indicating effective suppression of MAPK signaling. Selumetinib alone achieved similar reductions; however, the combination therapy resulted in greater effects. Immunophenotyping showed that MSU-42011 reduced tumor-promoting macrophages (CD206+ and CD163+) and FOXP3+ Tregs, while increasing activated CD8+ T cells, indicating a shift toward enhanced anti-tumor immunity. These effects were further strengthened by combination therapy. In vitro, conditioned media from NF1-deficient cells induced significant upregulation of pro-inflammatory cytokines and chemokines including IL-6, CCL2, and TNF\u3b1 in human THP1 cells and murine bone marrow-derived macrophages (BMDMs). Treatment with MSU-42011 or/and selumetinib partially reversed this induction. These findings highlight the potential of RXR agonists to reshape the TME by reducing tumor-promoting immune cells and increasing activated T cells. The combination of MSU-42011 with MEK inhibition further enhances anti-tumor efficacy, offering a promising therapeutic strategy for NF1-associated tumors. However, this study is limited by the genetic heterogeneity of NF1 and the rapid tumor progression observed in syngeneic models, which may not fully capture the complexity of human disease or immune editing dynamics. To overcome these limitations, ongoing studies are utilizing transgenic Nf1 mouse models and RNA sequencing-based immune profiling to further define the mechanisms of RXR agonist activity and to explore their effects on additional immune populations. In conclusion, this work supports the development of RXR-targeted therapies, either alone or in combination with MEK inhibitors, as a novel treatment strategy for NF1-associated tumors. These preclinical findings provide a strong foundation for future clinical translation aimed at improving therapeutic outcomes for patients with NF1.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
CONTROLS ON THE FORMATION AND PROPERTIES OF TEXTURAL PEDOFEATURES IN NORTHERN TEMPERATE FOREST SOILS : A CASE STUDY IN MICHIGAN (USA)
No full textThesis (Ph.D.)--Michigan State University. Geography - Doctor of Philosophy, 2025Data recently obtained from a Glossudalf in northern Lower Michigan indicated that loss of clay from the upper argillic (Bt) horizon, which is necessary to form a glossic (B/E or E/B) horizon, is initiated by free iron (Fe) oxide eluviation (Baish and Schaetzl, 2021). This finding runs counter to the long-held notion that decarbonation and acidification of the clay exchange complex drives clay (re)mobilization (and hence, argillic horizon degradation) in Alfisols and similar soils in the Great Lakes region. In this dissertation, I expand upon this earlier work by examining the mechanisms and processes underlying particle aggregation/disaggregation, as it is modulated by Fe oxide behavior, using data from six additional soils in Lower Michigan. I also use this information as a basis to assess the correspondence between regional soil development patterns and spatial variation in pedo-environmental conditions. The outcomes of this research better elucidate the controls on argilluviation (lessivage), textural (eluvial-illuvial) feature formation, and soil development, and as such, makes important contributions to pedogenic theory. The principal contributions of this work include the (1) description of the physiochemical interactions meditating particle aggregation, which lead to the formation (and degradation) of clay-illuvial features and horizons, (2) identification of the mechanisms responsible for the degradation of clay-illuvial features into glossic (eluvial) structures, and (3) determination of the relationships between the location and expression of these forms and the spatial distribution of pedo-environmental conditions. These contributions were realized through soil characterization, field observations, laboratory experiments, and geospatial modeling. Two representative pedons, each typifying argillic/glossic horizon expression in northern vs. southern Lower Michigan, were the primary focus of study and data generation. Together these data supported the refinement of the genetic model of Baish and Schaetzl (2021), enabling explanation of soil variability across Lower Michigan, as revealed through predictive mapping of soil properties. Aggregate dispersion experiments carried out on intact (non-degraded) illuvial materials led to the liberation of fine particles from soil aggregates following Fe oxide dissolution, confirming that Fe oxides play a central role in facilitating particle aggregation and structural stability in the clay-illuvial zone. Particle size and selective Fe extraction data further suggest that the strength of particle cohesion is modulated both by the content and mineralogy of Fe oxides, as well as the quantity of clay available to contribute surface area and charge for bonding interactions with Fe oxides. Coarser-textured soils exhibited weaker particle cohesion than did finer-texture textured soils, especially when the illuvial materials contained less total free Fe and less reactive crystalline Fe phases. Field observations and soil solution data also revealed that episodic establishment of perched water (hydromorphism) at the upper boundary of the argillic horizon is a key driver of Fe oxide dissolution in the degrading (glossic) zone. Subsequent Fe oxide dissolution experiments allowing leachates collected from the litter of major forest types to interact with intact illuvial materials further suggest that the kinetics of dissolution are modulated both by the (1) content and mineralogy of Fe oxides, and (2) quality of dissolved organic matter (DOM) delivered to the subsoil in percolating water. Mixed (coniferous-deciduous) litter leachates dissolved more Fe oxides than did leachates from deciduous litter, especially when the illuvial materials contained less total free Fe and more poorly crystalline Fe phases. Molecular analysis of DOM in leachates produced over the leaf-off period also shows that mixed forest litter consistently contributes higher average molecular weight compounds to the soil solution than does deciduous litter. Predictive mapping of soil properties revealed that horizon differentiation and profile development in loamy Alfisols and similar soils tends to be more strongly expressed in northern Lower Michigan, where the argillic horizon is coarser textured, redder, and less acidic. Congruence of these patterns with spatial variations in external environmental variables (parent material, climate, vegetation) suggest that argilluviation is accentuated where: (1) parent materials are coarser in texture (but with at least 10% clay); (2) winters are colder and snowier; and (3) forests contain a significant component of coniferous species. Together, these factors help to facilitate an overall greater capacity for particle transport during both the initial phase of Bt horizon development and the subsequent phase of Bt horizon degradation. In summary, these new findings imply that, although a similar mechanism (hydromorphism) may be responsible for triggering Fe mobilization, and consequently, clay movement, the processes involved are enhanced in the north, where pedo-environmental conditions facilitate lower aggregate stability and higher net matter (water and organic acid) flux.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
DEAD WAIT LOSS : 3 ESSAYS ON THE ECONOMICS OF KIDNEY TRANSPLANT
No full textThesis (Ph.D.)--Michigan State University. Economics - Doctor of Philosophy, 2025This dissertation consists of three chapters that center around the health economics of kidney transplants. In Chapter 1, I study how providing information on kidney donor quality affects transplant decision making. Despite a shortage of kidneys available for transplantation, the median candidate who dies while on the waitlist for a transplant declines 16 organ offers. Physicians decline or accept offers on behalf of their patients on the basis of kidney quality, which is difficult to evaluate. Starting in 2012, the Organ Procurement and Transplantation Network provided a simplified single-score metric, the Kidney Donor Profile Index (KDPI), to estimate the quality of a donor kidney relative to the median kidney recovered. Using a rich dataset provided by the Scientific Registry of Transplant Recipients containing all 28 million kidney transplant offers and decisions over a 5-year period, I exploit the provision of KDPI to evaluate the salience of this metric in physician decision-making. I utilize the natural experiment resulting from the exact timing when the values were calculable but not provided prominently with each offer. The introduction of the metric increased the weight placed upon KDPI in terms of individual offer acceptance, demonstrating that KDPI became increasingly salient to physicians. However, there was no corresponding increase in discard rates for low-quality organs as opposed to high-quality organs following the introduction of KDPI. I also find evidence of substantial preference shifts among physicians with regards to the individual donor characteristics. In Chapter 2, I seek to identify a potential source of inequity that leads to lower transplant rates and worse survival outcomes for Black kidney transplant candidates suffering from chronic kidney disease. I note that adjustments for race made to the formula for estimating kidney function systematically increased reported kidney function for Black patients. Utilizing data from the Scientific Registry of Transplant Recipients, I explore a policy change that required race-neutral calculations be used to estimate kidney function for Black patients. I find that the Black/non-Black disparities in eGFR reporting and preemptive listing reversed, so that Black patients actually became more likely than non-Black patients to report an eGFR and to preemptively list post-policy. In addition, I find that the Black/non-Black difference in dialysis prevalence at the time of listing decreased post-policy, suggesting that Black patients began listing at healthier states. Finally, I find that the preemptive transplant gap between non-Black and Black patients decreased post-policy. In Chapter 3, I study the incentive for young adults with kidney disease to register for a transplant before turning 18. Kidney transplant candidates who waitlist as pediatric patients are not subject to as stringent of criteria as those who attempt to waitlist as adults. In addition, pediatric status persists once candidates graduate to adulthood, along with allocation benefits. I find that there is a disproportionate number of candidates who join the waitlist just before turning 18. I also find that the candidates listing before turning 18 list at healthier initial states, and receive offers of greater average kidney quality compared to those listing after 18. However, these pediatric candidates receive fewer total offers, do not have a significantly increased probability of transplant, and their transplanted kidneys are of similar quality to those listing as young adults.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Boater and Angler Behavior to Minimize Spread of Aquatic Invasive Species
No full textThesis (M.S.)--Michigan State University. Fisheries and Wildlife - Master of Science, 2025Aquatic invasive species (AIS) negatively impact our waterways, often spreading via boaters and anglers who fail to clean equipment between waterbodies. Understanding why Michigan recreationalists skip essential AIS cleaning steps is necessary to address barriers. I conducted over 1000 interviews and 210 follow-up surveys with boaters and anglers to assess their knowledge of Michigan's AIS status, cleaning behaviors, barriers and motivations for cleaning, perceptions of AIS spread, and measure the impact of the outreach aspect of the interaction. Anglers were more knowledgeable about AIS, but boaters cleaned their equipment more frequently. One-quarter of powered vessel users and one-fifth of wading anglers reported traveling between waterbodies sooner than recommended passive equipment drying times. While these transient recreationalists are encouraged to clean their equipment frequently, only half reported doing so always or often. The primary motivation for cleaning among both groups was a preference for clean equipment. Time and inconvenience were the most-cited impediments to cleaning, with over three-quarters indicating that on-site cleaning stations would help them clean more often. While infrequent cleaners often saw no need to clean, the majority understood the importance of slowing AIS spread. The top concern among all groups was AIS impacts on native species. Participants were more interested in receiving more information on AIS impacts than on cleaning methods. There was a significant increase in knowledge and cleaning frequency from the initial interview to the follow-up survey. Additionally, many participants discussed AIS with others after the interview and felt compelled to learn more, highlighting the positive impact of in-person interactions. I installed boot scrub stations at popular angling sites to measure their usage rates. Although angler use was low, a fifth of passersby stopped to read the signage on the stations, providing a valuable passive outreach opportunity. The most effective signage framed AIS as \u201chitchhikers\u201d that travel via gear between waterways in a neutral tone, outperforming scientific and humorous framing. Therefore, I recommend addressing the inconvenience barrier by installing more cleaning stations that feature hitchhiker message framing. Additionally, in-person outreach efforts would be beneficial in increasing equipment cleaning frequency, as indicated by the positive impacts of the interactions of my interviews.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
GROWTH, DEVELOPMENT, AND PHOTOSYNTHETIC RESPONSES OF INDOOR FOLIAGE PLANTS TO AIR AND ROOT-ZONE TEMPERATURES, AND LIGHT QUANTITY AND DURATION
No full textThesis (Ph.D.)--Michigan State University. Horticulture - Doctor of Philosophy, 2025From 2013 to 2024, the wholesale value of the U.S. indoor foliage plant market increased from approximately USD 910 million, positioning them as one of the fastest-growing segments in ornamental horticulture. To meet the demand, greenhouse growers in temperate climates need tools to reduce propagation and production time of these slow rooting and growing crops, while not increasing energy costs. Therefore, we investigated methods to hastened foliage plant rooting and production by manipulating environmental parameters. The first study quantified the effects of daily light integral (DLI) on the rooting and shoot development of cuttings. As DLI increased from 10 to 16 mol\ub7m\u20132\ub7d\u20131, shoot dry mass and quality indices were generally promoted, though root biomass accumulation did not increase when DLI was >10 mol\ub7m\u20132\ub7d\u20131. In the second study, the greatest root biomass was typically observed at a root-zone temperature of 22 to 24 \ub0C, but species-specific variation was evident. The third study examined the effect of photoperiods between 9- to 16-h on growth, development, and morphological traits. Some species, such as Pilea peperomioides (Chinese money plant), showed pronounced increases in height and shoot biomass under daylengths >13-h, whereas others were relatively insensitive, or exhibited growth inhibition. The fourth study investigated the interactive effects of photoperiod (16-, 20-, or 24-h), DLI (4 or 8 mol\ub7m\u20132\ub7d\u20131), and constant air temperature (20, 24, 28, or 32 \ub0C). It revealed that biomass accumulation was reduced, and, in some cases, plant mortality occurred under a 24-h photoperiod combined with air temperatures 6528 \ub0C and a low DLI of 4 mol\ub7m\u20132\ub7d\u20131. Regardless of DLI, under a 16-h photoperiod, the light compensation points of Chinese money plant grown at 32 \ub0C were lower compared to those grown at lower air temperatures. In addition, CO2 assimilation rates were relatively high for plants grown at 32 \ub0C. Finally, the fifth study investigated the interactive effect of DLI (4.5 or 9 mol\ub7m\u20132\ub7d\u20131) and photoperiods and air average daily temperatures (day temperature/night temperature) of 20 (22.5/15), 23 (25.5/18), 26 (28.5/21), or 29 (31.5/24) \ub0C under a 16-h photoperiod, 20 (21/15), 23 (24/18), 26 (27/21), or 29 (30/24) \ub0C under a 20-h photoperiod, and 20, 23, 26, or 29 \ub0C under a 24-h photoperiod, respectively. With a day and night temperature differential, most foliage crops investigated exhibited higher biomass accumulation under a DLI of 9 mol\ub7m\u20132\ub7d\u20131 and a 24-h photoperiod. Overall, the dark respiration rate and light compensation points of Chinese money plant increased under a higher DLI and air temperatures and at daylengths 6420-h. Collectively, these studies demonstrate that DLIs 20-h, and constant air temperatures >28 \ub0C negatively impact the foliage plants investigated, reduce quality, and increase production time.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
TOWARDS AN INSECT BRAIN-BASED BIOELECTRONIC NEURAL SENSOR FOR DISEASE DETECTION
No full textThesis (Ph.D.)--Michigan State University. Biomedical Engineering - Doctor of Philosophy, 2025Health screening is an effective and widely accepted practice in healthcare and tools that can prevent or detect diseases at an early stage can potentially increase survival rates, improve long term quality of life, and reduce treatment costs. Additionally, timely diagnosis can lead to clinical interventions that guide the treatment of therapies. For the timely diagnosis to occur, diagnostic tools are needed to detect changes in biological fluids at a high sensitivity and specificity for patients with the disease. Despite several clinical and laboratory-based tests, diagnosis and especially early diagnosis can still have limitations due to accuracies, methodological restrictions, invasive procedures, sampling protocols, personnel skillsets, and time to diagnosis. Here we discuss the detection of two diseases associated with some of these limitations: endometriosis and lung cancer. Endometriosis is a chronic gynecological disease characterized by the presence of ectopic endometrial-like tissue outside the uterus. This inflammatory disease affects approximately 10% of women of reproductive age and is clinically associated with a range of symptoms that are common to other gynecological and non-gynecological disorders. Women with endometriosis experience a substantial decrease in quality of life and the financial and emotional burden of endometriosis is amplified by the diagnostic delay which ranges from 4 to 11 years. Barriers to the early diagnosis and treatment of endometriosis are a result of the current standard of surgical diagnosis via a diagnostic laparoscopy with histological verification to confirm the presence of endometriotic glands and stroma. Thus, a shift from surgical diagnosis to a clinical one is imperative and should be explored. Lung cancer is the second highest commonly diagnosed cancer in the world and is the predominate cause of cancer-related death for both women and men. Currently, the most promising approach for lung cancer screening is with low dose computed tomography in high-risk populations which have shown to provide statistically significant mortality reduction in patients. This approach, however, relies on risk modeling methodology to select high-risk populations and to minimize the potential damages to radiation exposure to a broader population. Further, lung cancer can be divided into two main types, (1) small cell lung cancer (SCLC) and (2) non-small cell lung cancer (NSCLC). The most common subtype of lung cancer is NSCLC and is often detected after it has already spread to other organs. Screening and early detection of NSCLC play an important role in receiving a more favorable long-term prognosis. One proposed avenue for the screening and detection of diseases is through the use of volatile organic compounds (VOCs). VOCs are carbon-based chemicals that vaporize readily due to their chemical characteristics. VOCs are also emitted from the human body via exhaled breath and other biological fluids. It is thought that the composition and concentrations of VOCs are altered due to metabolic processing which could be influenced when the body is in a diseased state. It has been shown previously that the presence of several disease including cancer changes the VOC headspace above in vitro cultured cells. Differences in VOC concentrations have also been found in the breath of cancer patients in comparison to control groups. For systemic and complex diseases, a chemical gas sensor that can generalize and differentiate subtle differences in mixtures of VOCs is essential. Biological systems have solved the problem of chemical sensing via evolution and have converged to a solution that is architecturally and operationally similar across species. This signifies that there might be a superior solution for gas sensing that is still inaccessible from an engineering standpoint. Living organisms use biological olfaction to detect VOC mixtures via their robust odor recognition capabilities and generalization for chemicals which can be employed for disease detection. This work addresses the potential of using VOCs for disease detection by harnessing the chemosensory array and coding mechanisms of biological olfaction and combing it with both electronic and computation techniques for neural recording and odor classification. This sensor was applied for the detection and differentiation of endometriotic and lung cancer cell culture models including multiple types of cells (i.e., epithelial vs stromal) and disease subtypes (SCLC vs NSCLC). By analyzing the cell culture headspace-evoked neural responses, we show that our sensor can distinguish multiple cell lines by their \u2018scent\u2019 (i.e., emitted VOC mixture). Further, by combining neural responses across experiments, we obtained high-dimensional population neural response templates that were used to classify unknown samples with a high accuracy. We obtained an accuracy of 89% in differentiating 4 endometriotic cell lines at two growth timepoints (24 hr. and 72 hr.) and obtained an accuracy of 88% in classifying epithelial co-cultures of endometriotic and endometrial cell lines cultured at 0%, 25%, 50%, 75%, and 100% in ascending/descending ratios. Moreover, when used to detect and differentiate lung cancer and its subtypes we achieved a classification accuracy of 85 %. By integrating a biological sensory system with electronic and computation techniques, this work introduces a novel approach for endometriosis and lung cancer detection and moves toward a VOC-based disease screening method that can offer an accessible and precise disease diagnosis.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
NONLINEAR ACOUSTIC WAVE PROPAGATION IN LAYERED MEDIA AND ITS APPLICATION TO CHARACTERIZING MATERIAL NONLINEARITY
No full textThesis (Ph.D.)--Michigan State University. Electrical and Computer Engineering - Doctor of Philosophy, 2025This dissertation investigates nonlinear acoustic wave propagation in inhomogeneous media formeasuring the acoustic nonlinearity parameter (\u3b2), which reflects how material stiffness responds to large deformations and serves as a sensitive indicator of internal microstructural features such as dislocations, precipitates, and early-stage damage in solids and fluids. Conventional techniques, such as contact-based detection and interferometry, face limitations due to calibration sensitivity, variability, and geometric constraints. Immersion-based methods improve repeatability but introduce modeling challenges related to diffraction, attenuation, and multilayer interactions. To overcome these, a theoretical model based on the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation was developed for n-layer media, featuring a novel diffraction correction that ensures Fresnel zone continuity that doesn\u2019t violate the physics of diffraction. This model supports an inversion algorithm that estimates \u3b2 by minimizing slope differences between measured and predicted second harmonic pressures. The model was validated using fused silica and the inversion algorithm was used to predict \u3b2 of rolled aluminum, showing strong agreement with literature values of \u3b2. To further understand nonlinear wave propagation in n-layer media, a unified model for nonlinear diffraction and attenuation in layered media is proposed. Unlike conventional layer-wise models that treat each layer as a new source, the unified model incorporates three key hypotheses: (1) the existence of a single Fresnel zone across all layers, (2) accumulated second harmonic waves propagate linearly and diffract with the source frequency, and (3) their attenuation is frequency- dependent. These hypotheses were tested by defining four cases and validated using numerical simulations. The results suggest that the unified model shows better agreement with numerical results than existing layer-wise approaches, especially for the high impedance mismatch cases. To simplify the present experimental procedure for measuring the calibration function of a transducer, a novel narrowband calibration method was developed. Measurement of narrowband calibration functions at specific frequencies of interest was demonstrated using immersion transducers The sensitivity of the technique was assessed by evaluating the calibration function and the corresponding \u3b2 of water for different values of source power, propagation length, and reflection coefficient. To further simplify the process of measuring the acoustic nonlinearity parameter \u3b2, a reference-based inversion framework was developed. This eliminates the need to calibrate the transducer by normalizing the second harmonic response using the response from a reference solid with known nonlinearity. This framework combines the previously developed theoretical model for nonlinear wave propagation with experimental measurements from immersion tests. Specifically, the ratio of second harmonic amplitudes measured for the test and reference solids is matched to the corresponding ratio of diffraction and attenuation losses predicted by the model. This method was used to measure \u3b2 for cast aluminum, Ti-64, and SS 420, and the measured values were consistent with those reported in the literature. Measuring acoustic nonlinearity (BA) and attenuation in liquids is crucial to understand their molecular structure and has been used to study contrast agents in ultrasound imaging and the compressibility and pressure-density relationship of fluids. To enable such characterization without calibration requirements or large sample volumes, the reference-based approach of solids was extended to liquids. The test involves placing a small amount of liquid in a thin-walled container that is immersed in water, forming a three-layer configuration similar to the method used for solids. This technique was used to successfully measure both BA and \u3b1 of salt water, olive oil, and fresh and degraded engine oils. Together, these contributions establish a robust, calibration-independent framework for nonlinear acoustic characterization in solids and liquids. By integrating modeling, inversion, calibration, and application across diverse materials, this work advances ultrasonic nondestructive evaluation and enables new approaches in nonlinear acoustics.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
EVALUATING NON-INVASIVE SURVEY TECHNIQUES TO INFORM CHRONIC WASTING DISEASE MODELING AND MANAGEMENT FOR WHITE-TAILED DEER (ODOCOILEUS VIRGINIANUS)
No full textThesis (M.S.)--Michigan State University. Fisheries and Wildlife - Master of Science, 2025Chronic wasting disease (CWD) has been confirmed in wild cervids across 36 U.S. states and three continents. Resilient prions shed in feces can persist for years, making environmental transmission a major management challenge. Quantifying how anthropogenic practices influence fecal accumulation can help reduce indirect transmission risk.From January\u2013April of 2021\u20132023, I quantified feces accumulation at 28 bait sites (139 measurements), 23 food plots (126), and 18 landscape forage areas (LFAs; 74) across 4,262 km2 in southcentral Michigan. Using bait sites as the reference, I found no significant difference in the amount of feces at food plots (\u3b2 = -0.84 [95% CI: -1.98\u20130.29]) or LFAs (\u3b2 = -0.60 [95% CI: -1.73\u20130.54]). However, the probability of encountering feces was lower at food plots (\u3b2 = -2.89 [95% CI: -4.66\u2013-1.49]) and LFAs (\u3b2 = -1.87 [95% CI: -3.57\u2013-0.41]). Julian day negatively influenced both feces quantity and detection probability. These results suggest increased environmental exposure risk at bait sites. To support deer management and surveillance, I assessed the use of small unoccupied aerial systems (sUAS) equipped with RGB and thermal sensors to detect deer in deciduous forest fragments. From January\u2013March 2023, I conducted 5\u20137 drone surveys across five fragments, reviewing 1,126 RGB and 1,147 thermal images. Detection probability was higher in thermal (0.89 [95% CI: 0.86\u20130.92]) than RGB (0.44 [95% CI: 0.37\u20130.52]). Group size had a strong positive effect in both (thermal \u3b2 = 1.58, RGB \u3b2 = 1.18). Observer ID had no effect in thermal (\u3b2 = 0.15) and was negative in RGB (\u3b2 = -0.57). Vegetation height increased mismatches between observers. Overcast conditions reduced mismatches in thermal imagery (\u3b2 = -1.20) but not RGB. These findings indicate thermal-equipped drones are an effective tool for deer detection and monitoring.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
MODELING POPULATION AND DISEASE DYNAMICS OF GREAT LAKES FISH EXPOSED TO PFAS
No full textThesis (M.S.)--Michigan State University. Fisheries and Wildlife - Master of Science, 2025ABSTRACTPer- and polyfluoroalkyl substances, otherwise known as PFAS, chemicals have been produced since the 1940s and are suspected to be harmful to humans, wildlife, and the environment. Previous research has found these compounds to have toxic effects on lipid metabolism, hepatotoxicity, immunotoxicity, development, reproduction, and growth in humans and various aquatic species. These compounds have been found in all five of the Laurentian Great lakes as well as within many of the valuable fish species that reside in the lakes. I created simulation models to explore population-levels effects on species such lake whitefish (Coregonus clupeaformis), lake trout (Salvelinus namaycush) and steelhead (Oncorhynchus mykiss) populations stemming from PFAS contamination effects on factors such as fish growth, fecundity, disease mortality, and egg survival. For interactions with disease, I used an infectious disease model that simulated lake whitefish exposures to viral hemorrhagic septicemia virus (VHSV), lake trout exposures to epizootic epitheliotropic disease virus (EEDV), and steelhead exposures to Flavobacterium psychrophilum. The population model results showed that decreases in growth in terms of weight and relative fecundity (i.e., eggs per kg) had the largest effect on population abundances across all three species. When factors were modeled in combination, all three species were predicted to experience 80% declines in abundance over a 65-year period. The results of the disease transmission model found that PFAS exposure caused the largest percentage increase in the maximum proportion of infected steelhead.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
FEATURE ENGINEERING OF ULTRASONIC CODA WAVES FOR NONDESTRUCTIVE EVALUATION AIDED BY MACHINE LEARNING
No full textThesis (Ph.D.)--Michigan State University. Electrical and Computer Engineering - Doctor of Philosophy, 2025Coda waves are diffuse field ultrasonic signals generated by multiple scattering and reflections from boundaries and heterogeneities within materials. Their long propagation times and decaying amplitudes, resulting from interactions with micro- and macro-scale features, create complex waveforms that appear noisy due to phase in-coherency and superposition of multiple scattered modes. Extracting meaningful features from these intricate signals is challenging. This thesis focuses on three problems where the changes/degradation at microstructural level: (i) microstructural variation in Grade 91 steel tubes, (ii) barely visible impact damage (BVID) in carbon fiber reinforced polymer (CFRP) composites, and (iii) the characterization of microcrack arrays in rails.Grade 91 steel, used extensively in power plants, local microstructural changes such as grain size variation reducing component serviceability. Initial feature extraction using loss of correlation (LOCOR) differentiated microstructure states into good (G), mid-level (M), and bad (B) groups with 6580% accuracy but could not fully resolve all eight targeted conditions. Statistical T-tests and clustering verified group distinguishability but indicated limitations in resolving subtle microstructural variation, motivating exploration of more sensitive approaches.To address these limitations, topological data analysis (TDA) methods were introduced for feature extraction from coda waves. TDA-derived features, including Carlsson\u2019s Coordinates, the Tent Function, and Interpolating Polynomials, provided quantitative descriptors from persistence diagrams of time-domain coda wave data. Machine learning classifiers trained on TDA features achieved 6590% accuracy (averaged across multiple cases), outperforming LOCOR, which did not exceed 57%. This demonstrated the capacity of TDA to resolve subtle microstructural features from coda waves.To distinguish eight microstructure conditions, a data fusion approach was used, integrating features from seven different ultrasonic experiments. Non-fused data models showed limited accuracy for eight-class classification, while both feature-level and decision-level fusion substantially improved performance. This confirmed that combining diverse features from multiple sources was essential for robust multi-class microstructure discrimination.Feature extraction from coda waves also proved critical for detecting BVID in composites. Carbon fiber reinforced polymer (CFRP) laminates of two different ply sequences (0\ub0 & 90\ub0) were subjected to low-energy impacts ranging from 2J-4.5J. Coda wave features distinguished between damages in different laminate types, while coda wave interferometry (CWI) provided the highest sensitivity to damage severity. Using machine learning, damage in different laminate sequences was classified with high accuracy, with most models achieving perfect classification. Within each laminate, impact energy levels above 2J (for 0\ub0 laminates) and above 3.5J (for 90\ub0 laminates) were identified with at least 80% classification accuracy.Finally feature engineering was applied to rolling contact fatigue (RCF) damage, which is typically found in rails and originated at the surface at micrometer scale. Previous work showed that using transmission coefficient to characterize the number and depth of cracks was impossible. Instead, this work proposed extracting features from the scatter field of Rayleigh waves. Specifically, it used LOCOR features along with ML regression models to predict multiple outputs for characterizing the (i) depth and (ii) number of cracks associated with RCF damage. LOCOR features with ML regression enabled simultaneous prediction of RCF crack depth and number of cracks with 6590% accuracy, while the transmission coefficient feature could achieve only ~50% accuracy.In summary, this thesis demonstrated that advanced feature engineering, encompassing statistical, topological, and data fusion strategies, substantially improved coda wave-based diagnostics, enabling accurate, actionable assessments across critical engineering materials.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references