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Characterizing resilience in weaned pigs : Associations between physiological stress phenotype at weaning and behavior, production, and molecular modifications
No full textThesis (Ph.D.)--Michigan State University. Genetics and Genome Sciences \u2013 Doctor of Philosophy, 2025Intensive genetic selection has led to incredible improvements in pig production traits but has resulted in increasing environmental sensitivity. This drives the need to breed a robust pig\u2014an animal exhibiting high genomic potential in combination with resilience to external stressors allowing it to achieve its maximum potential. Resilience is an animal\u2019s ability to be either minimally affected by a stressor or quickly return to its pre-stress state. Weaning is a multifaceted stressor and provides an excellent opportunity to investigate resilience. We conducted two studies characterizing physiological resilience (SR) or vulnerability (SV) to weaning stress using serum cortisol pattern surrounding weaning and investigated lasting impact on production, behavior, and molecular modifications. The first study was conducted on gilts from 26 crossbred litters (PIC 359 x Yorkshire sows) and the second study on gilts from 13 purebred Yorkshire litters. We detected no associations between resilience and post-weaning growth in either study. In crossbred gilts, there were no differences in pork quality measures at slaughter, but resilient gilts had lower live weight and hot carcass weight as well as a smaller loin muscle area. Crossbred SR gilts engaged in more agonistic interactions at 1 d post-mixing, as estimated by skin lesion counts, but this was not observed in purebred SR gilts. We observed differences in behavioral responses during a novel object test at 12 wk-of-age, but results varied between studies. Crossbred SR gilts exhibited greater object touches and fewer vocalizations, whereas purebred SR gilts exhibited less overall activity and fewer escape attempts. In our second study, we additionally performed RNAseq and whole genome bisulfite sequencing on hypothalamus and hippocampus samples from 10 gilts (5 SR, 5 SV) at 13 wk-of-age. We detected 97 differentially expressed genes (DEGs) in hippocampus and 5 DEGs in hypothalamus. Hypothalamic DEGs included down-regulation of FOS, ADCYAP1, and HDC in SR gilts; genes which have been established to be involved in stress regulation. Hippocampal DEGs included FOS, CARTPT, NPY2R, CHRNA4 and HTR2A, and were enriched for GO terms including behavior, neurological system process, and catecholamine secretion. Transcript abundance of DEGs were correlated with pre-weaning cortisol concentration and behavioral measures. We also identified 2,053 differentially methylated regions (DMRs) in hippocampus and 3,314 DMRs in hypothalamus. Hippocampal genes containing DMRs were enriched for processes of neuron differentiation and myelination, while hypothalamic genes containing DMRs were enriched for neuron migration and GTPase activity. Our results indicate that resilience to weaning stress is associated with modified transcriptomic and epigenetic profiles of brain tissues, as well as behavioral differences later in life. Further research is needed to determine if genes indicated in this study are predictive or adaptive in nature, and the biological relevance of the observed molecular modifications.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
LEVERAGING LARGE DATASETS TO INVESTIGATE THE DISTRIBUTION OF FITNESS EFFECTS IN PLANTS
No full textThesis (Ph.D.)--Michigan State University. Genetics and Genome Sciences \u2013 Doctor of Philosophy, 2025Mutations\u2014spontaneous changes in DNA sequences\u2014are fundamental to evolution, and contribute to everything from disease susceptibility in people to agriculture. Population geneticists are tasked with understanding mutations - historically categorizing them as either beneficial, harmful, or neutral based on how they affect fitness. However, our understanding of these categories is often limited by incomplete data and an inability to travel back in time to track mutations. Over four chapters, I will explore how large datasets can enhance our understanding of these three fundamental mutation categories. First, I will use 27 terabases of gene expression data from 300 studies to investigate whether rarely expressed genes accumulate harmful mutations at higher rates than constitutively expressed genes. Next, I will leverage about 205 terabases of DNA-sequencing data and use k-mers (DNA subsequences) to measure neutral variation in 112 natural plant species. The results suggest that current methods for estimating diversity reliant on reference genomes underestimate genetic variation. The following chapter expands upon the idea of using k-mers to measure genetic diversity, numerically and analytically exploring the relationship between k-mer diversity and nucleotide diversity. Overall, k-mer diversity scales linearly with nucleotide diversity and we showcase the use of bloom filters to decrease the memory burden of the k-mer diversity calculations. Finally, I will use 250,000 evolutionary simulations to train machine learning models to infer the time it took for a fixed beneficial mutation to spread. Overall, large datasets like these hold many opportunities to revisit old biological questions and further our understanding of mutation trajectories.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Integrating Phenomics and Genomics Towards Accelerating Genetic Gain in Soft Winter Wheat
Full text linkThesis (Ph.D.)--Michigan State University. Plant Breeding, Genetics and Biotechnology - Crop and Soil Sciences - Doctor of Philosophy, 2025Accelerating genetic gain in plant breeding demands increased selection intensity, enhanced selection accuracy, broader genetic diversity, and shortened breeding cycle. As phenomic platforms and genomic resources continue to evolve, integrating these complementary datasets offers opportunity to improve breeding pipelines. This dissertation explores multiple approaches to potentially incorporating phenomic information with genomic data, aiming to increase prediction accuracy and selection intensity, and identify genomic regions for economically important traits in soft winter wheat. Infrared thermal imaging enabled high-resolution differentiation of Fusarium head blight (FHB)-resistant and -susceptible genotypes at the single-spike level. However, field-scale implementation requires careful consideration due to uncontrolled factors under field conditions, where no direct relationship between plot-level infrared thermal readings and FHB-related traits was established. Hyperspectral imaging demonstrated superior predictive ability and prediction accuracy over genomic prediction alone for deoxynivalenol (DON) content. Integrating phenomic and genomic predictions by model blending enhanced prediction accuracy and allowed clustering-based selection on predicted DON content in F4:5 breeding lines. Additionally, multiple strategies for integrating UAV-derived vegetation indices (VIs) to improve genomic prediction accuracy were evaluated, with varying degrees of success depending on how UAV-derived information were used as fixed effect, as well as training set composition. Beyond enhancing prediction, phenomic data facilitated the identification of key genomic regions associated with DON content and grain yield, underscoring the potential of phenomic information as a phenotypic input in genome-wide association studies. Collectively, these findings support the potential application phenomics-genomics integration in potentially improving wheat breeding. By enhancing selection accuracy, identifying informative genomic regions, and potentially reducing selection intervals, this work lays the foundation for a more efficient breeding pipeline. However, careful consideration is essential when implementing combined phenomic-genomic approaches to ensure robust, field-applicable results.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
DIGITAL (IN)JUSTICE : AN INTERSECTIONAL STUDY ON BLACK RETURNING CITIZENS\u2019 SOCIO-DIGITAL INEQUALITIES
No full textThesis (Ph.D.)--Michigan State University. Criminal Justice - Doctor of Philosophy, 2025In the U.S., there are around 800,000 people on parole, and Black men and women areoverrepresented in correctional populations nationally and in the state of Michigan (Council of Criminal Justice, 2025; Kajstura & Sawyer, 2024; Sawyer & Wagner, 2024). Existing research shows that a common concern for returning citizens is completing parole supervision and dealing with the collateral consequences of incarceration (Jones, 2018; Vallas & Dietrich, 2014; Wang, 2023). To make matters worse, returning citizens also experience a more clandestine barrier of digital inequality (Blomberg et al., 2021; Digital Equity Act of 2021, 2021; Ogbonnaya-Ogburu et al., 2019; Reisdorf et al., 2022; Seo et al., 2020). The intersection of collateral consequences and digital inequality hinders returning citizens from completing supervision conditions and heightens their recidivism risk (Arguelles & Ortiz-Luis, 2021; McDougall et al., 2017; McDougall & Pearson, 2020), and reintegration challenges become even more salient across racial groups, as Black returning citizens experience collateral consequences, personal barriers, and digital inequality more often (Digital Equity Act of 2021, 2021; Gurusami, 2019; Kajstura & Sawyer, 2024; The Sentencing Project, 2018). Yet, the existing research on returning citizens\u2019 digital inequality is limited and fails to examine Black returning citizens\u2019 digital inequality despite their multiple marginalizing statuses. The current study builds on the Digital Rehabilitation Model framework (Reisdorf & Rikard, 2018) and the work of other digital inequality scholars (Gilbert, 2010; Helsper, 2012, 2021) by using the Intersectional Digital Rehabilitation Model as a framework to qualitatively explore 73 Black returning citizens\u2019 experiences with digital inequality. The study also uses an intersectional approach and methodology to explore potential nuances in the digital inequality of 14 Black men and 14 Black women in the sample. The study\u2019s results revealed that Black returning citizens experience socio-digital inequalities, meaning that their experiences with racism, sexism, and felony discrimination compound with their experience of digital inequalities, and this not only makes it harder for them to access and use technology but also to meet supervision requirements and get their other personal needs met. However, the findings also indicate that participants\u2019 digital inequality should be viewed along a spectrum because they had positive experiences as well and recognized that technology could serve a convenient and helpful purpose in their reentry process so long as they can access it and have the skills to use it. Furthermore, there were not very many nuances that emerged in the narratives of the Black men and women, except that the men more often described negative online job search experiences and perceptions of the cost of rideshare services, whereas the women more often described negative experiences using technology for health and transportation-related needs but more positive experiences with rideshare services. Taken together, the results indicate that correctional facilities and organizations working with returning citizens can and need to do more to increase their access to quality, affordable technology, and digital skills, as technology is becoming increasingly entrenched in the reentry process.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
USE OF IMMERSIVE AND NON-IMMERSIVE TECHNOLOGIES AND SENSORS TO IMPROVE BUILDING ENERGY AUDITS AND ENERGY WORKFORCE DEVELOPMENT
Full text linkThesis (Ph.D.)--Michigan State University. Civil Engineering - Doctor of Philosophy, 2025The demand for energy efficiency has increased significantly in response to global efforts to reduce carbon emissions and enhance sustainability. The building sector alone accounts for nearly 30% of global energy consumption, highlighting the need for building technologies such as sensors that support energy-efficiency, and a skilled workforce capable of designing, implementing, and managing energy-efficient building systems. Meeting these workforce demands requires a shift from traditional educational approaches to more dynamic, technology-driven training solutions. Immersive technologies, such as Virtual Reality (VR) and interactive virtual models, have emerged as powerful tools for transforming energy workforce training. In addition, the integration of advanced sensor systems such as occupancy sensors plays a critical role in optimizing building energy efficiency. By incorporating sensor systems into immersive training platforms, trainees can experiment with various control strategies and observe the immediate effects on energy consumption, thereby gaining practical insights into the benefits and limitations of these systems. Therefore, this dissertation is structured around two main focus areas: (1) the investigation of sensor systems, particularly occupancy counting sensors, to evaluate their performance and accuracy in optimizing building energy efficiency, and (2) the use of VR and interactive virtual models to enhance training in energy audits and complex building energy systems for workforce development.The integration of sensors in this research develops a standardized methodology for testing the reliability of occupancy counting sensors, including typical and failure testing phases. Typical testing assesses sensor performance under normal conditions, while failure testing identifies performance limits under extreme scenarios. A case study involving two novel sensor systems in office and academic building settings demonstrates the methodology with a modified confusion matrix to effectively identify failures. Findings suggest that the testing methodology enables a more reliable evaluation of occupancy counting sensors, supporting their integration into energy management systems for improved building efficiency. The second focus area explores the use of VR and interactive virtual models to enhance energy audit training and workforce development, comparing their effectiveness in improving participants' ability to identify energy-saving opportunities and understand complex building systems. Results indicate that virtual training methods outperform traditional approaches, by improving knowledge gain in HVAC system training and enhancing participants' ability to identify energy-saving opportunities. The study further highlights the potential of VR technology and interactive virtual models to bridge the gap between theoretical knowledge and practical application, offering scalable training solutions for energy professionals. Overall, this dissertation contributes to advancing energy efficiency and workforce development by addressing critical gaps in both sensor technology and training methodologies. Together, these contributions support the transition to a more sustainable and energy-efficient built environment, equipping the workforce with the skills needed to meet the challenges of a rapidly evolving energy area.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
INVESTIGATING BIOLOGICAL DISTANCE AND SKELETAL STRESS IN A LATE ANTIQUE AND EARLY MEDIEVAL TUSCAN TOWN
Full text linkThesis (Ph.D.)--Michigan State University. Anthropology - Doctor of Philosophy, 2025The Late Antique and Early Medieval eras in the Mediterranean (5th-10th centuries AD) were an extremely turbulent time. In the centuries following the fall of the Western Roman Empire (c. 476 AD), Italy experienced the Gothic War, the plague of Justinian, the Lombard invasion, the rise of the Carolingian dynasty, and the spread of Christianity. The nature of this transitional period has garnered considerable debate in archaeological and historical literature, resulting in some scholars advocating for a \u201cDark Age\u201d of isolation, disease, and cultural stagnation, while others have suggested these eras were marked by adaptation, interconnectivity, and resilience. Notably, there has been relatively little focus on the ways in which bioarchaeology can contribute to this conversation. At present, no studies have used a diachronic, intracemetery analysis with paleopathological and biological distance (biodistance) approaches to understand the effects of this time period on the residents of Tuscany, Italy.In order to address these scholarly gaps, this dissertation focuses on the site of Rusellae (Tuscany, Italy) and its cemetery, which was in use between the 6th and 12th centuries AD. The present study focuses on a sample of 160 adults excavated in a collaboration between the Art and Archaeology Museum of the Maremma and the Archaeological Superintendence of Tuscany between 1987 and 1991. The burials comprise individuals from two archaeologically-defined phases: Phase I (6th-7th centuries AD) and Phase II (8th-12th centuries AD). The primary foci of this study are: an examination of biological distance within Rusellae and among Rusellae and contemporary sites using craniometrics; a craniometric population affinity analysis within Rusellae; an exploration of craniometric variation over time; and the frequency of skeletal stress indicators (cribra orbitalia, porotic hyperostosis, periosteal reaction, and linear enamel hypoplasias) between cemetery phases and population affinities.The results showed that, despite exhibiting an overall greater affinity with contemporary European samples than African references, Rusellae was a biologically heterogeneous site comprising several craniofacially distinct groups. Further, the presence of several individuals consistent with African affinity was preliminarily attested at the site. Notably, when compared with individuals showing greater European affinity, the individuals with a greater affinity to African reference samples showed no significant difference in frequencies of the skeletal stress markers analyzed, with the exception of linear enamel hypoplasia of the maxillary central incisor. In addition, there were no statistically significant differences in either skeletal stress indicators or cranial measurements between the earlier and later phases of the cemetery.Broadly, these results suggest genetic continuity between Rusellae and other European populations, but not to the exclusion of some contribution from the African continent. These findings are consistent with continued circum-Mediterranean trade and migration, including exchange between Tuscany and North Africa, during this period. Additionally, the lack of diachronic change in skeletal stress indicators and craniometrics suggests a degree of biological, ecological, environmental, and psychosocial stability throughout Late Antiquity and the Early Middle Ages at Rusellae. Further, the findings indicate a generally similar experience between affinities, at least with respect to the stress indicators analyzed, possibly due to a social structure that prioritized religious cohesion over ancestral divisions. Thus, the totality of the evidence supports a view of the transitional period between the 6th and 12th centuries, not as a \u201cDark Age\u201d characterized by collapse, but as an era of continuity, connectivity, and resilience for Rusellae.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Topological Distances between Directional Transform Representations of Graphs
Full text linkThesis (Ph.D.)--Michigan State University. Computational Mathematics, Science and Engineering - Doctor of Philosophy, 2025Shape analysis is important in fields like computational geometry, biology, and machine learning, where understanding differences in structure and tracking changes over time is useful. Topological Data Analysis (TDA) provides tools to study shape in a way that is resistant to noise and captures both fine and large-scale features. This dissertation focuses on directional transforms, a method that encodes shape by looking at its structure from different directions.First, we introduce the Labeled Merge Tree Transform (LMTT), a new way to compare embedded graphs using merge trees and directional transforms. We test this method on real-world datasets and show that it works better than existing distance measures in some cases. Next, we develop a kinetic data structure (KDS) for bottleneck distance, which allows us to update shape comparisons efficiently when the data changes over time. We apply this method to the Persistent Homology Transform (PHT) and show that it reduces computation time while keeping accurate results. Finally, we explore a future direction that extends the kinetic data structure to the Wasserstein distance. These contributions improve the use of topology in studying dynamic shapes and open new research possibilities in both theory and practical applications.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Exploring behavior change intervention pathways to reduce the spread of amphibian diseases through the exotic pet trade
No full textThesis (M.S.)--Michigan State University. Fisheries and Wildlife - Master of Science, 2025Human behavior is a driving factor of global conservation challenges, including biodiversity loss, pollution, resource consumption, and climate change. Conservation social scientists are increasingly using behavior change interventions, \u201ccoordinated sets of activities designed to change specified behavior patterns\u201d, to address these conservation challenges. The amphibian pet trade community has partially facilitated the spread of highly virulent amphibian diseases and subsequent species declines and extinctions. Amphibian businesses and owners can lack biosecurity behaviors, leading to disease spillover events into wild ecosystems. We begin researching these biosecurity behaviors, including wearing gloves and disinfecting equipment, and behavior influences, including knowledge and social norms, of these community members to inform behavior change intervention development. Our goal is to provide a knowledge base of community behaviors and contexts to create a behavior intervention that is relevant, applicable, and effective at increasing biosecurity practices and reducing the risk of disease spread. We first used an intercept survey method at exotic pet trade shows in four Midwest states (Michigan, Ohio, Indiana, and Illinois) to investigate knowledge transfer, social interaction, and community characteristics of exotic pet trade show attendees. We found that attendees learn new information and create and maintain social connections at these shows, both of which are potential behavioral influences. Additionally, we identified sub-populations of attendees to possibly tailor efforts towards. We also conducted a national online survey with amphibian pet trade businesses to investigate characteristics of a business itself, how said businesses interact with others, and how these relate to the number of biosecurity practices performed. We found that importers perform fewer biosecurity actions, the source of amphibians can impact biosecurity practices, and that social image and pressures can increase biosecurity practices. The findings from these two analyses provide fundamental context to build a community-relevant, and potentially community-engaged, behavioral intervention. We found support for and recommend that researchers collaborate with specific community members for a social norms intervention to increase biosecurity behaviors and reduce amphibian disease spread.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
An Extension of the Ego-defensive Model to Include Collective Self-esteem
Full text linkThesis (M.A.)--Michigan State University. Communication - Master of Arts, 2025People desire to maintain positive self-esteem; however, some messages contain information that can directly conflict with the positive image we hold of ourselves or our social groups. Ego-defensive attitudes, attitudes that protect individuals from threats to identity, are hard to measure, due to their subconscious nature. To measure ego-defensive attitudes, Lapinski and Boster (2001) conceptualized the ego-defensive model, which maps the process by which individuals respond to counterattitudinal messages on topics in which they are heavily ego-involved. Although originally the model was tested with a threat to personal self-esteem, the current study will provide an additional test of the ego-defensive model and extend existing research by testing the model with an issue that challenges collective self-esteem: esteem derived from social identity, and more specific to this study, attachments to gender identity. Findings were not consistent with the entirety of the ego-defensive model: contrary to predictions, negative thoughts were negatively associated with instances of message discounting, and source derogation was not associated with overall attitudes towards the message. However, results indicated a strong positive relationship between message discounting and source derogation, as predicted. Those with high collective self-esteem in the threat condition responded with more positive thoughts and less negative thoughts relative to those with low self-esteem. Collective self-esteem was found to have a buffering effect, such that those high in collective self-esteem participated less in message discounting and source derogation, and have more overall positive attitudes towards the message.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Algebraic Combinatorics on Partially Ordered Sets and Graphs
Full text linkThesis (Ph.D.)--Michigan State University. Mathematics - Doctor of Philosophy, 2025This thesis considers three algebraically motivated combinatorics questions on partially ordered sets (posets) and graphs. In the process, we consider rooted tree posets, inflated rooted tree posets, shoelace posets, -free posets, as well as incomparability graphs of a given poset. Rooted trees are posets whose Hasse diagram is a graph-theoretic tree having a unique minimal element. We study rowmotion on antichains and lower order ideals of rooted trees. Recently Elizalde, Roby, Plante, and Sagan considered rowmotion on fences which are posets whose Hasse diagram is a path (but permitting any number of minimal elements). They showed that in this case, the orbits could be described in terms of tilings of a cylinder. They also defined a new notion called homometry where a statistic takes a constant value on all orbits of the same size. This is a weaker condition than the well-studied concept of homomesy which requires a constant value for the average of the statistic over all orbits. Rowmotion on fences is often homometric for certain statistics, but not homomesic. We introduce a tiling model for rowmotion on rooted trees. We use it to study various specific types of trees and show that they exhibit homometry, although not homomesy, for certain statistics.We also study Defant and Kravitz's generalization of Sch\"utzenberger's promotion operator to arbitrary labelings of finite posets. Defant and Kravitz showed that applying the promotion operator times to a labeling of a poset on elements always gives a natural labeling of the poset and called a labeling tangled if it requires the full promotions to reach a natural labeling. They also conjectured that there are at most tangled labelings for any poset on elements. We propose a strengthening of their conjecture by partitioning tangled labelings according to the element labeled and prove that this stronger conjecture holds for inflated rooted forest posets and a new class of posets called shoelace posets. We also introduce sorting generating functions and cumulative generating functions for the number of labelings that require applications of the promotion operator to give a natural labeling. We prove that the coefficients of the cumulative generating function of the ordinal sum of antichains are log-concave and obtain a refinement of the weak order on the symmetric group.We also consider -free posets, motivated by a reduction of the Stanley-Stembridge conjecture posited by Foley, Ho\`ang, and Merkel (2019), stating that the twinning operation on graphs preserves -positivity of the chromatic symmetric function. A counterexample to this general conjecture was given by Li, Li, Wang, and Yang (2021). We prove that -positivity is preserved by the twinning operation on cycles, by giving an -positive generating function for the chromatic symmetric function, as well as an -positive recurrence. We derive similar -positive generating functions and recurrences for twins of paths. Our methods make use of the important triple deletion formulas of Orellana and Scott (2014), as well as new symmetric function identities.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references