How Spirituality and Fatigue Interact to Affect Quality of Life in Patients with Metastatic Breast Cancer

Title from PDF of title page, viewed January 8, 2024Dissertation advisor: Kymberley K. BennettVitaIncludes bibliographical references (pages 93-108)Dissertation (Ph.D.)--Department of Psychology. University of Missouri--Kansas City, 2023The cognitive theory of stress and coping by Lazarus and Folkman can explain how individuals cope with a stressful chronic illness, specifically metastatic breast cancer (MBC). If an individual appraises their MBC as stressful and concludes that they have the coping resources and ability to use them, they may effectively cope with and adapt to the stressor. Spirituality may be an important coping mechanism for patients with MBC, while symptoms of fatigue may lead to increased risk of developing psychiatric comorbidities such as depression, anxiety and panic disorders, eating disorders, substance abuse disorders, and somatization disorder. The limited number of studies conducted on the topics have examined relationships between spirituality, fatigue, QoL, and/or distress (i.e., symptoms of stress, anxiety, and depression) among patients and survivors of cancer, as research on patients with MBC is limited. This present study aimed to fill the gap in the literature by examining whether an interaction exists between spirituality and fatigue that affects QoL in the long term. Specifically, this project aimed to examine whether levels of spirituality would interact with fatigue to predict QoL over two periods of data collection. It was hypothesized that the combination of low fatigue and high spirituality would predict the highest levels of QoL. The sample consisted of 25 patients with MBC who were recruited from an MBC clinic in the Midwest. Measures consisted of data collected from participants’ electronic health records (EHRs) and from self-report validated questionnaires. Due to low statistical power attributed to a small sample size, hypotheses were modified so that analyses could focus on bivariate correlations instead of the originally planned upon linear regressions, although power was still limited. Therefore, it was hypothesized that spirituality would be positively related to QoL and negatively related to fatigue, while fatigue would be negatively related to QoL. Findings indicated that Spiritual Peace, Spiritual Faith, and total spirituality were positively associated with Emotional QoL. Spiritual Peace was positively associated with Functional QoL, and Functional QoL was significantly negatively associated with fatigue. All other associations did not reach statistical significance based on p-values. Implications, limitations, and further directions are discussed.Introduction -- Review of the literature -- Methodology -- Results -- Discussion -- Appendi

Essays on the econometrics of ordinal data

[EMBARGOED UNTIL 8/1/2024] In economics, ordinal variables like general health, mental health, and happiness level play a crucial role. Ordinal data is commonly used in surveys and questionnaires due to its ordered structure. However, incorporating an ordinal outcome variable in economic studies presents challenges. The categorical and fixed order nature of ordinal data sets it apart from continuous data. Additionally, most ordinal data exhibits unknown and inconsistent variations across categories. Consequently, specific methodologies are needed for econometric analysis when dealing with an ordinal variable. In Chapter 1, I develop a methodology for testing stochastic monotonicity when the outcome variable of interest is ordinal. I use a multiple testing procedure (MTP) technique to evaluate whether and where ordinal stochastic monotonicity exists, rather than using a single null hypothesis test. Additionally, I estimate the true set where ordinal stochastic monotonicity holds and construct "inner" and "outer" confidence sets by inverting the recommended MTP that controls the familywise error rate. With high asymptotic probability, an "inner" confidence set is contained inside the true set, whereas the "outer" confidence set contains the true set. Simulations illustrate that the MTP controls the familywise error rate well. Three empirical examples, including general health with educational level, depression with educational level, and inner peace with income class, illustrate the methodology. The famous Blinder-Oaxaca decomposition (BOD) takes an unconditional mean difference and decomposes it into a portion that is assigned to the levels of explanatory variables and a portion that is related to the magnitude of regression coefficients. However, the conventional BOD assumes Y has a cardinal meaning, not ordinal. To address this limitation and facilitate decomposition analysis of ordinal outcomes, in Chapter 2, I compare several alternative approaches. To illustrate these approaches, I use an empirical example to study how much of the disparity in general depression levels between rural and urban residents can be attributed to differences in educational attainment, income, age, and other observables. Each approach relies on different assumptions and offers different interpretations, allowing researchers to extract meaningful information from ordinal data. To better understand and distinguish these approaches, I conduct simulation studies that provide valuable insights into their practical implications and performance. These approaches are practically helpful for researchers employing decomposition with an ordinal outcome.Includes bibliographical references

Collaborative human-robot order picking system : algorithms for task allocation and routing in complex environments

[EMBARGOED UNTIL 8/1/2024] Order picking, which involves retrieving items from storage locations for an internal or external customer, is a core function in warehouses and accounts for up to 65 percent of the total operating cost. It is considered as a crucial driver for supply chain performance as improper planning of picking operations leads to inefficient asset utilization and delayed deliveries, which, in turn, adversely affects customer satisfaction, operating cost, and competitiveness. A majority of warehouses adopt a picker-to-parts system (workers travel through a warehouse to retrieve and transport items from storage to packing station), and the fulfillment speed of such order picking system (OPS) depends on the following key decisions - (i) set of orders to be picked in a tour (order batching decision), (ii) assignment of a batch to a picker and order in which their a processed (batch assignment and sequencing decisions), and (iii) route followed x by the picker to collect the orders in each batch (picker routing decision). However, with the growing customer demand and global labor shortage, warehouses are seeking efficient and less labor-intensive order picking systems. Autonomous mobile robots (AMRs) or collaborative robots (cobots) have the potential to alleviate the strain on human workers and expedite order picking operations. However, there are several key operational challenges to address for ensuring an effective collaborative human-robot order-picking system (CHR-OPS), where humans perform item retrieval tasks, and AMRs handle item transportation to the depot. This research aims to improve the fulfillment efficiency of a picker-to-parts CHROPS by optimizing key decisions associated with two warehouse picking strategies, namely, static picking and dynamic picking. In the case of static picking, the items to be retrieved from storage for a given day are known as apriority. On the other hand, the dynamic picking strategy allows for orders to arrive over time (e.g., e-commerce warehouses), and the pick cycle (or picking plan) can be updated in real time. First, we address the problem of optimizing the following key subproblems of a CHR-OPS with a static picking strategy: (i) order batching (how many items should be collected in each AMR tour?), (ii) batch assignment and sequencing (how to assign batches to AMRs, and in what order should they be processed?), and (iii) picker-robot routing (how should the AMR and picker be routed to coordinate the picking process?). Existing literature has not dealt with the three subproblems, and this work is the first to address them for a picker-to-parts CHR-OPS system employing multiple pickers and AMRs. A mixed integer linear programming model is developed to jointly optimize the three subproblems with the objective of minimizing the total tardiness of all orders. The MILP model is validated and solved to optimality for small instances. However, since the problem under consideration is NP-hard, it is computationally intractable for larger instances. To efficiently handle large instances, we proposed deterministic and stochastic local search algorithms, namely variable neighborhood descent and a new variant of simulated annealing. The numerical experiments demonstrate the superior performance of the proposed solution approach compared to existing methods. Besides, our results also show that the picking efficiency is impacted by human{robot team composition, AMR speed, AMR capacity and warehouse layout. Subsequently, we address the CHR-OPS with dynamic picking and developing interventionist picking algorithms for a multi-robot multi-human setting. Specifically, we propose two interventionist policies for dynamic collaborative order picking, namely, the collaborative human-robot interventionist picking algorithm (CHRIPA) and the collaborative human-robot rule-based interventionist picking algorithm (CHR-RIPA). The evaluation of the policies demonstrates that the proposed rules can improve the overall performance of the system compared to benchmark approaches (human-only dynamic picking and collaborative picking with no intervention). In addition, results indicate CHR-IPA outperforms CHR-RIPA in terms of average tar diness and order completion time, albeit with a slightly higher travel distance for human workers. The results have led to several managerial implications for a collaborative order picking system. Further, the proposed models and algorithms are modular and can be adapted to any warehouse setting by accounting for the relevant parameters such as warehouse layout, AMR capacity and human-robot composition. Finally, the directions for future research have been identified and summarized.Includes bibliographical references

Machine learning for mixed quantum-classical dynamics and transition metal chlorides oxidation potential via density functional theory

[EMBARGOED UNTIL 8/1/2024] Chemical phenomena in our daily life are understood to be the result of physical interactions between matter. These interactions are governed by physical laws that mostly has been understood and well-described through the principle of quantum mechanics (QM). In 1929, Dirac stated4: "The fundamental laws necessary for the mathematical treatment of a large part of physics and the whole of chemistry are thus completely known, and the difficulty lies only in the fact that application of these laws leads to equations that are too complex to be solved." QM in principle is capable of providing a description to any given system and thus predict a likely outcome or an accurate measurable observation for that system. Many would agree that while the physical laws itself is well understood and the equation governing the interaction is readily constructable, solving these equations for many chemical systems still require approximations due to computational power restriction. This in turn limit the accuracy of the predicted outcomes, which can affect our capability to understand the given system. An example of a system that represent an important chemical research area is the interaction between light and molecules. The interaction between these matters governs the study of excited state molecules. Many natural processes, such as photosynthesis,5 to important technologies, such as photovoltaic cells6,7 and spectral analysis8-10 arise from understanding these interactions. When photons interact with a molecular system, depending on the suitability of the wavelength of the given light, the molecular system can absorb the photon energy sending its electron to a different electronic state and transition the system to an excited state. After this photoexcitation, the system can undergo various decay which include radiative decay or nonradiative pathway to other electronic states. In a radiative decay (or photoluminescence), the system release photon with energy that corresponds to the difference in energy between the two electronic states. Whereas in a nonradiative decay, the system undergoes an internal conversion or an intersystem crossing. Internal conversion is a transition between electronic states of the same spin multiplicity. (e.g., singlet to singlet or triplet to triplet.) An intersystem crossing is a nonradiative transition between electronic states of different spin multiplicities. (e.g., singlet to triplet or triplet to singlet.) It is understood that intersystem crossing is facilitated by spin-orbit coupling which tends to be small for small systems. However, it is also has been shown that it can occur at short times and compete with internal conversion even in small molecules,11 particularly organometallics with heavy elements.12 Furthermore, triplets are understood to have longer lifetimes that allow organic molecules to undergo phosphorescence with good quantum efficiency.13,14 A hundred years since its development, QM have developed several methods to approximate the interaction between particles to a varying degree of accuracy. Some of those method includes Hartree-Fock (HF),15,16 Kohn-Sham density functional theory (DFT),17,18 configuration interaction (CI),19 and coupled-cluster (CC).20 As the accuracy of these approximation method increases, so is the computational cost to solve the QM equations. The exponential advancement of computing technology has led to increasingly powerful computer over the years. This progress has enabled us to study larger systems more effectively using an increasingly accurate method. However, for many large systems, studying their excited state accurately remained computationally challenging due to the manifold of degenerate states and their couplings. Recent advancements of new approximative method through machine learning (ML) and their increasingly accurate prediction at fraction of the computational costs,21,22 is a promising method to provide solutions for excited state dynamical study. In an effort to contribute to the development of this new chemical frontier, this dissertation aims to presents a methodical approach in developing a good initial dataset to train ML model that are capable of good accurate chemical prediction. In addition to the works in ML, this dissertation also includes collaborative efforts with Dr. Young's group. We performed DFT calculations that provide support to the mechanistic picture they established for the surface reactions responsible for the oxidative molecular layer deposition (OMLD), a mechanism that enables polymer growth on the surface of thin films for various electrochemical applications including energy storage,23-25 sensors,26,27 textiles,28-31 and desalination.32 Building upon this insight, we sought to benchmark oxidation potentials of various transition metal chlorides using DFT method. This investigation aims to enable other transition metal chloride oxidants to be selectively paired with various monomers thereby facilitating novel chemistry to be explored via OMLD mechanism. This work also hopes to motivate further computational studies to further explore and better characterizes various metal-halides compounds that can been used as oxidant for OMLD mechanism.Includes bibliographical references

Journalist or influencer? Exploring young public media journalists' perceptions of individual branding on Twitter

[EMBARGOED UNTIL 5/1/2024] As the news continues to be increasingly crafted and consumed online, media practitioners and media scholars are becoming more engaged in a complex discourse about journalistic branding, how it manifests itself on Twitter, and where it belongs among the other traditional practices of journalism. The following research study explores how young public media journalists perceive individual journalistic branding and what motivates their own methods for curating their Twitter profiles. To better understand how these digital natives and young entrants into the work force are negotiating between traditional journalistic values and Twitter logic, semi-structured, in-depth interviews were conducted with 16 participants. The research questions were guided by market theory, self-discrepancy theory and the individual level of analysis within the hierarchy of influences. Branding was found to be perceived as a justifiable addition to journalism, even though its necessity to journalism is in question. Young journalists also seem to be insecure about their branding methods and very self-conscious about how they will be perceived online. Here, the journalistic view of market theory that predicts gaining attention will become an end instead of a means to an end of informing does not seem to ring true for these journalists who are still prioritizing traditional journalistic values above having the most attractive Twitter profiles.Includes bibliographical references

EC-SGK1 and EnNaC mediate vascular stiffening

[EMBARGOED UNTIL 5/1/2024] Vascular stiffening is an independent predictor of cardiovascular diseases, the leading cause of death worldwide. High dietary salt intake has been shown to increase vascular stiffness in humans, especially in salt-sensitive populations. To date, the underlying mechanisms of salt-sensitivity related vascular stiffening remain poorly understood. In this study, we aim to examine the role of the endothelial sodium channel (EnNaC), and its upstream regulator, serum and glucocorticoid regulated kinase 1 (SGK1) in salt-sensitivity related EC and arterial stiffening. To probe signaling pathways, we combined both in vivo (e.g. pulse wave velocity) and in vitro (e.g. atomic force microscopy) approaches and used a variety of experimental models including mice with [alpha]EnNaC deletion, mice treated with a pharmacological mTOR (a upstream target of both [alpha]EnNaC and SGK1) inhibitor, mice with global SGK1 deletion, mice with EC selective SGK1 deletion, and to a more clinical perspective, primary human aortic ECs treated with a pharmacological SGK1 inhibitor. Importantly, our study has showed that deficiency/inhibition of EnNaC or EC-SGK1 prevented/attenuated salt-sensitivity related EC and arterial stiffening, suggesting a therapeutic potential of targeting EnNaC and EC-SGK1 expression in salt-sensitivity related cardiovascular dysfunction. Nevertheless, whether this is directly mediated through EC-SGK1 regulation of EnNaC requires further examination.Includes bibliographical references

Cardiomyocyte calcium and stress-induced ventricular arrhythmia

[EMBARGOED UNTIL 5/1/2024] Duchenne muscular dystrophy (DMD) is the most common muscular dystrophy and is caused by mutations in the dystrophin gene. Subclinical signs of cardiac disease present early and usually progress to dilated cardiomyopathy in late stage DMD patients. Dystrophin deficiency is associated with structural and functional changes of the muscle cell sarcolemma and/or stretch-induced ion channel activation. However, the mechanism of cardiac dysfunction remains poorly understood. In this investigation, we use mice with transgenic cardiomyocyte-specific expression of the GCaMP6f Ca2+ indicator to test the hypothesis that dystrophin deficiency leads to cardiomyocyte Ca2+ handling abnormalities and cardiomyocyte damage following acute ventricular preload challenge. Excessive activity of the potent octapeptide Angiotensin II (Ang II) associates with adverse cardiac remodeling and arrhythmogenesis. While the long-term detrimental effects of Ang II excess on the heart are well-established, the acute effects of Ang II on ventricular arrhythmogenesis remain controversial, particularly in aged populations with associated structural heart disease. The Transient Receptor Potential Vanilloid 4 (TRPV4) ion channel exhibits increased activity in cardiomyocytes with aging, and Ang II has been shown to increase TRPV4-mediated Ca2+ influx in several cell types. The goal of this investigation was to examine the acute effects of Ang II on cardiomyocyte Ca2+ transients and ventricular arrhythmia in the aged heart.Includes bibliographical references

Enhancing Missouri agritourism: a comprehensive evaluation of visitors' intrinsic motivation, environmental behavior, and satisfaction

[EMBARGOED UNTIL 12/1/2024] Unstable farm income and the desire to diversify revenue sources have increased the significance of agritourism as an alternative economic opportunity for farmers and ranchers. In Missouri, agriculture and tourism contribute an annual economic impact of $93.7B and$13.5B, respectively. Agritourism connects the top two economic drivers and has been identified as the most meaningful complementary business for farmers to generate additional income and mitigate the financial uncertainties associated with the traditional farming enterprise. Visitors' satisfaction is critical in operating a successful agritourism business because it influences the choice of destination, the consumption of products and services, and their decision to return. This study examined the relationship between Missouri agritourism visitors' intrinsic motivation, environmental behavior, satisfaction, and revisit and recommendation intentions. The study also analyzed the moderating effects of visitors' COVID-19 emotions and clustered them based on their enduring involvement. An online survey was conducted among Missouri agritourism visitors who had visited any agritourism destination since 2020. Six hundred fifteen responses were collected as a part of the survey and considered for the data analysis. The respondents were divided into two groups (High Vs. Low) based on their COVID-19 emotions related to agritourism. The results revealed a significant direct relationship among the study variables. Regarding the moderating effects, the two groups showed significant differences in the relationship between their intrinsic motivations and satisfaction with destination and risk attributes and between their environmental behavior and satisfaction with the destination, risk, and food attributes. Along with this, based on the enduring involvement, the visitors were divided into three clusters: Agritourism lovers, Greenies, and Neophytes. Assessing visitors' overall satisfaction will enable agritourism operators, industry experts, policy makers, and others to take corrective actions, critical business decisions, and formulate appropriate policies for the sustainable development of this important sector of the tourism industry. Future promotional, educational, and marketing tools could be developed and designed based on the findings of this study.Includes bibliographical references

A culturally appropriate mindfulness intervention to reduce health disparities among African Americans : feasibility, acceptability, and efficacy of mantram repetition

[EMBARGOED UNTIL 5/1/2024] Mindfulness interventions improve psychological and physiological health outcomes because they interrupt the link between stress and disease processes. Despite the promise of these interventions in promoting health among clinical and non-clinical populations, African Americans--who share a disproportionate burden of chronic stress-related diseases--have been underrepresented in mindfulness research. Mindfulness interventions have been successfully adapted for specific treatment outcomes and some underserved populations, but despite the recognized need for culturally adapted interventions, little progress has been made in this area. Mantram repetition is one type of mindfulness intervention that is more flexible, culturally adaptable, and cost-efficient compared to many other mindfulness interventions. In four studies, the feasibility, acceptability, and efficacy of mantram repetition were examined. Meta-analytic results from Study 1 indicated that mantram repetition has a small, significant effect on various health and well-being outcomes (g = .444). In Study 2, results from qualitative interviews suggested that an online, asynchronous, customized mantram repetition intervention was of interest to African American community members. In Study 3, a customized intervention was developed and refined. In Study 4, the feasibility, acceptability, and efficacy of the customized intervention were demonstrated. The current studies suggest mantram repetition can be successfully implemented to improve health outcomes among African Americans.Includes bibliographical references

On the role of the purinergic receptor P2Y2R in oral cancer and salivary gland dysfunction

[EMBARGOED UNTIL 5/1/2024] Due to the important roles the oral cavity plays in our daily lives ranging from eating and drinking to speech, diseases of the oral cavity significantly impact the quality of life. Oral cancers are a subtype of head and neck cancers that mainly originate in the epithelial lining of the oral cavity. Despite the best efforts by our immune system, tumors manage to grow and destroy the surrounding tissues. Additionally, the immune system is itself capable of mediating irreparable tissue damage. The autoimmune exocrinopathy Sjogren's Disease (SjD) is one example of a disease that manifests due to aberrant immune responses. One factor that consistently appears in the study of various tumors as well as influences the immunopathology of SjD in numerous models is the G-protein coupled nucleotide receptor, P2Y2R. This metabotropic purinergic receptor is endogenously activated by extracellular ATP and UTP, and its expression has been shown in many types of tissues and cells including epithelium and immune cells. In this work, we studied the role of P2Y2Rs in the development of oral cancer tumors in vivo and examined salivary gland infiltrating immune cells in murine models of SjD and the influence of P2Y2Rs on them. To accomplish our first objective, we utilized two strategies of P2Y2R antagonism, pharmacological antagonism with the P2Y2R selective antagonist AR-C118925 and genetic ablation utilizing CRISPR-Cas9 gene editing to knock out the P2Y2R. First, we evaluated human and syngeneic murine models of head and neck squamous cell carcinoma (HNSCC) utilizing bioinformatic, genetic, and functional analyses. Second, we generated a functional P2Y2R knockout clonal MOC2 cell line and evaluated the influence of host-derived and tumor-derived P2Y2Rs in tumorigenesis in vivo. Lastly, we examined how P2Y2R expression influenced the host anti-tumor immune response. Our studies demonstrate that P2Y2R plays a role in tumor development in our murine model of oral cancer and both host- and tumor-derived expressions of P2Y2R influence the host anti-tumor immune response in distinct manners. To accomplish our second objective, we utilized three models of SjD: the NOD.H2h4, NOD.H2h4 DKO, and IL-14aTG mice. First, we conducted immunoprofiling to examine the salivary gland-accumulating leukocyte compartment of NOD.H2h4, NOD.H2h4 DKO, and age-matched C57BL/6 mice. Secondly, we isolated T lymphocytes from the salivary glands and spleens of two inflamed models of SjD, the NOD.H2h4 DKO, and the IL-14aTG models, and measured P2Y2R activity. Collectively, these works illustrate a plausible therapeutic role for antagonism of P2Y2R in oral cancer and shed light on the influence of P2Y2Rs on salivary gland accumulating T lymphocytes in SjD mouse models.Includes bibliographical references