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FIELD CANCERIZATION AND MICROBIOME EFFECTS ON LUNG CANCER: A SOURCE OF EARLY DETECTION BIOMARKERS TO IMPROVE PATIENTS’ OUTCOME
No full textLung cancer results in more deaths than any other cancer in the United States and worldwide, with non-small cell lung cancer (NSCLC) accounting for most cases. Diagnosis typically involves chest imaging, molecular testing, and biopsy. However, most patients are diagnosed at advanced stages, with only a 6% chance of a 5-year survival rate. In contrast, early-stage diagnosis and treatment can result in a favorable prognosis, with a high 5-year survival rate of 70-90%.The concept of tumor field cancerization describes a phenomenon where exposure to carcinogens can cause histologic changes in large areas of tissue, creating a field of pre-malignant cells that can eventually develop into tumors. Additionally, microbiota dysbiosis might influence tumor development. Studies have identified several commensal bacteria present in the lower airway tracts, such as Streptococcus, Prevotella, and Veillonella. The high mortality rate of lung cancer is often attributed to i) its late-stage diagnosis, ii) aggressive nature given its ability to metastasize early in the disease process complicating treatment and reducing survival rates, and iii) significant therapeutic challenges despite current treatments such as surgery, chemotherapy, radiation therapy, targeted therapy and immunotherapy. Despite advancements, the survival rate for advanced lung cancer remains low. To address this challenge, our research focuses on identifying risk protein biomarkers that are associated with the earliest molecular changes indicative of an ongoing tumorigenic process, thus offering significant potential for early intervention. Our study investigates the phenotypic molecular changes in the bronchial tree of NSCLC patients in light of the field cancerization theory and correlates these findings with blood biomarkers to support the future development of a non-invasive risk assessment test. Using enhanced liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomic analysis and two independent cohorts of lung cancer patients (N=18, and N=263) with matched plasma and bronchial tree tissue specimens, we identified a set of 6 and 13 candidate risk plasma biomarkers with tissue origin. Additionally, we explored the microbiome proteome composition in NSCLC patient tissue and plasma to support future characterization of its potential role in cancer development.Risk biomarkers will enable the evaluation of individuals at high risk, guiding necessary lifestyle adjustments and facilitating the development of personalized prevention plans and therapies
Is Less More? The Quasi-Experimental Effects of Four-Day School Week Adoption on Teacher, Principal, and Paraprofessional Staff Turnover and District Financial Outcomes
Get PDFFour-day school week (4DSW) adoption is an increasingly popular policy, particularlyfor rural districts that are seeking to reduce educator turnover and district expenditures. Using a staggered treatment event study design, I am among the first to estimate the quasi-experimental effects of 4DSW adoption on teacher turnover, and I am the first to estimate the quasi-experimental effects of 4DSW adoption on principal turnover and paraprofessional staff turnover. Further, I provide a valuable conceptual replication of prior work by examining the implications of 4DSW adoption on district expenditures and revenue. Results suggest that 4DSW adoption may not impact teacher, principal, and paraprofessional staff turnover. However, I do detect possible short-term reductions in per-pupil federal revenue, support service expenditures, and salary expenditures. Expenditure savings are driven by reductions in food service and transportation salary expenditures. Future research should examine changes in the total hours worked by 4DSW staff and potential heterogeneous effects by the type of 4DSW schedule implemented. Overall, district leaders who seek to decrease turnover rates should pursue alternative strategies. Those who seek to decrease expenditures may see savings actualized, however, they should carefully consider potential negative effects on student achievement and redistribute dollars saved in ways that will positively improve student outcomes
Exploring the Effects of a Universally Designed Technology-Based Graphic Organizer with Embedded Self-Regulated Learning Strategies on Mathematical Writing, Problem-Solving, and Self-Efficacy for Adolescents with and without Disabilities
Get PDFMathematics literacy, which encompasses vital life skills such as learning to communicate and justify reasoning, is important for all people throughout their lives. Technology tools such as technology-based graphic organizers (TBGOs) provide universal accessibility supports for learners who experience difficulties with a variety of aspects of mathematics, from organizing their problem-solving process to expressing and defending their reasoning in writing. This study was designed to investigate the functional relation between a TBGO with embedded self-regulated learning (SRL) strategies on the quantity and quality of students’ argumentative mathematical writing (MW) and changes in mathematics performance. The study aimed to improve MW and mathematics problem-solving as well as the self-efficacy for SRL in mathematics problem solving and writing of seventh-grade students with and without disabilities struggling with mathematics learning. A multiple-baseline across-participants study was conducted with 18 seventh-grade students, both with and without disabilities. Data were collected on students’ MW performance (number of words and symbols [TWWS], transition words [TWs], and MW quality [MWQ]) as well as mathematics problem-solving (number of problems solved correctly) across four phases: (a) baseline (solving problems and writing on the computer without the TBGO), (b) Intervention with TBGO (solving problems and writing on the computer with the TBGO), (c) maintenance (solving problems and writing on the computer without the TBGO), and (d) generalization (solving different problems and writing on the computer with and without the TBGO). Visual and statistical analyses were used to evaluate changes in students’ MW and problem-solving. Statistical and thematic analysis of students’ self-efficacy for SRL ratings for MW and mathematics was also conducted. Results indicated moderate evidence of a functional relation between the MW intervention with TBGO and all MW measures. Additional analyses revealed significant differences in students’ pre- and post- mathematics problem-solving and ratings of self-efficacy beliefs. Student interview data were used to discuss the social validity of this novel technology-based intervention. Most students reported that the TBGO was helpful for supporting their MW and problem-solving. Limitations as well as implications for future research and practice are also addressed
Characterization of Myofascial Trigger Points Utilizing an Automated Shear Wave Elastography Approach
Get PDFMPS is a leading and challenging musculoskeletal chronic pain problem, typically localized, that is well recognized but lacks a clear definition across the board. The lack of a clear definition results from limited epidemiology, pathophysiology, and diagnosis information regarding MPS. A key characteristic of MPS is having myofascial trigger points (MTrPs), defined as a palpable nodule within a taut band of a skeletal muscle and linked to patient-specific pain symptoms. Advances in ultrasound and shear wave elastography technologies to characterize MTrPs have shown merit to localize, determine hypoechogenicity properties, anisotropy properties of tissue, variance in blood flow distribution, map tissue stiffness properties, understanding the impact on surrounding tissue, provide targeted and local treatment, and the role of fascia within MTrPs. Based on previous research advances, our group focused on using SWE to characterize the tissue anisotropy of MTrPs from different population groups to extract potential biomarkers for detecting and characterizing MTrPs. However, to address the current limitations of SWE and data acquisition, our group investigated the merit of using an automated SWE method for improving reproducibility and minimizing variance on extracted data. In this research, we conducted three pilot studies in the following areas: (1) the reproducibility and variance observed utilizing three SWE devices, each from different manufacturers using a manual SWE method, (2) understanding the reproducibility and variance utilizing an automated SWE method of different muscle groups, and (3) using an automated SWE method to characterize MTrPs on the upper trapezius muscle group from a small sample group. Muscle groups evaluated during these pilot studies included trapezius and vastus lateralis. The results of this study showed that the reproducibility within a single US-SWE device has a moderate to high amount of CV and moderate to low ICC on images analyzed. Moreover, the reproducibility across multiple SWE devices when evaluating the same muscle group shows a statistically significant SWS distribution across devices. This highlights the impact of US-SWE devices estimating SWS differently and providing different profiles within a given muscle group. The results of the MTrPs pilot study demonstrated that using the shear anisotropy ratio (SAR) as an extracted feature for distinguishing between different population groups has potential merit. However, SAR is affected by the variance observed from a given SWE device, the estimation of shear wave speed by a SWE device, and the data acquisition methodology. This research highlights the value of using an automated SWE method, the limitations and implications of existing SWE devices, and potential features, like SAR, having the merit of being biomarkers for characterizing and detecting MTrPs
In Context Verb Disambiguation: A Korean Case Study With Reference to Czech
Get PDFOver the past 20 years, strategies languages use to manage the distribution of information within and across words, sentences, and even broader domains have become an active area of linguistic research. Studies range from distribution on sounds and speech rate properties (Pellegrino et al., 2011) and morphological system organization Ackerman and Malouf (2013); Filipović Ðurđević and Milin (2018) to sentence properties (Futrell et al., 2015; Levy, 2008; Levy and Jaeger, 2007; Wasow et al., 2011) and even studies of broader speaker interaction
(Depperman, 2015). One particular recent focus has been the relation between word class properties and their relation to language learning and sentence processing, specifically from a perspective of uncertainty reduction. Dye et al. (2018) offer an analysis of noun classification in languages with (German) and without (English) gender and identify two major strategies for reducing uncertainty: a deterministic system and a probabilistic system. Existing studies in this area have primarily focused on noun classification. Verbs and their interaction with argument structures, which have been extensively discussed in the theoretical and applied literature, including in work incorporating suggestions from Levin (1993, 2015), have received less attention within quantitative literature focusing more directly on cognitive dimensions, and specifically on how verbs and argument structures interact with verb classification.
This thesis uses quantitative metrics based on distributional semantics to explore how argument structures and verb meanings interact and define argument-structure-based verb classes. The focus of this thesis lies primarily on Korean, a strict verb-final language, but results for Korean are compared to Czech. In terms of argument structure marking and argument expression, Czech and Korean share a range of features, but contrary to Korean, Czech has flexible verb placement. It is used as a counterpoint to further assess whether the results found for Korean are specific to a language with strictly clause-final verb placement or whether some of them may be more general. The results of this thesis strongly suggest that (at least in two typologically different languages such as Korean and Czech) verbs generally follow a probabilistic classification strategy (in the sense of Dye et al. (2018)). Verbs in both Korean and Czech appear to be classified by their argument structure in a taxonomic way and do not replicate partial idiosyncratic patterns found for nouns in high frequency contexts (Dye et al., 2017; Wang and Walther, 2023a). By highlighting the complex interactions between frequency, semantic similarity, and argument structure, this thesis provides insights into the role of argument structure alternations (including argument omission) in verb disambiguation and classification
Culturally Responsive Leadership Practices During the COVID-19 Pandemic: Addressing the Literacy Skills of Emergent Multilingual Learners in Secondary Schools
Get PDFThis research study aims to better understand educational administrators’ decision-making experiences supporting Emergent Multilingual Learners (EMLs) in their literacy skills during the COVID-19 pandemic. United States public schools at the K-12 level are becoming more racially and socio-economically diverse. Considering changing national demographics, one in four children are from an immigrant family and come from a home where another language besides English is spoken. Emergent Multilingual Learners tend to underachieve in comparison with fluent English-speaking classmates on tests of English literacy. Culturally responsive leadership is important to attend to the increasingly ethnically and linguistically diverse student populations. It builds on culturally responsive pedagogy by broadening the understanding and moving beyond the classroom to the larger school context and decision making in schools. There is literature around equity and cultural responsiveness, however, there is a dearth of research regarding culturally responsive leadership practices of educational administrators during the COVID-19 pandemic to address literacy needs of EMLs. The research question is: How have educational administrators used culturally responsive leadership practices during the COVID-19 pandemic to address the literacy skills of EMLs in secondary schools? The two sub questions are: (a) What strategies did educational administrators use to demonstrate culturally responsive leadership practices during COVID? (b) What opportunities or challenges did educational administrators encounter? And how did they address them? The theoretical framework that underpins this study is culturally responsive leadership, sensemaking theory, and multiliteracies and EMLs. This qualitative research study interviewed middle school and high school principals and assistant principals in three school districts in Virginia. To recruit the administrators, purposeful sampling was used. Varying criteria was used such as gender, number of years of teaching and leadership experience, and ethnic background. Through conducting semi-structured tiered interviews, I was able to follow-up, refine, and extend the research study. Semi-structured interviews via Zoom and in-person were conducted and each participant was asked the same set of open-ended questions created based on the research questions. All interviews were audio recorded and transcribed. Data was organized through coding and thematic analysis. Object inquiry was also used as a data collection source. Object inquiry was another type of data collection where participants brought a visual or tangible object that represents a profound experience that illustrated culturally responsive leadership during the pandemic. The findings described the strategies, opportunities, and challenges administrators encountered while leading their schools. Administrators practiced ongoing reflection by focusing on the needs of students. They also focused on creating and sustaining a culturally responsive and inclusive school environment for their students to grow and thrive. In instructional settings, using all language domains and academic discourse was strongly encouraged and scaffolded. Modeling and connecting with the school community also reflected the ways they supported their staff and students
How Cyberspace Has Changed Journeys to Crime: Examining Distances Sexual Groomers Travel to Commit Offline Offenses against Minors Using Federal Court Records
Get PDFThe Internet has transformed almost every aspect of human life, including how sex offenders engage victims. While traditionally groomers had to identify, groom, and offend against their victims offline, contact-driven offenders use the Internet to identify and groom minors to meet offline to engage in illicit sexual contact. The offline sexual contact remains constant, but how have journeys-to-crime changed as our society becomes increasingly reliant on the Internet, and are contact-driven offenders different from traditional offline groomers? Both the existing literature and opportunity theories suggest that: (H1) contact-driven offenders will travel longer distances to meet their victims when compared to traditional offline groomers; (H2) contact-driven offenders who communicate online for longer durations of time will travel longer distances compared to contact-driven offenders with shorter durations of engagement; and, (H3) contact-driven offenders are younger and more educated than traditional offline groomers. To test these hypotheses, the author extracted data on offenders, victims, crimes, and distances traveled from federal court dockets for cases in which the defendant was charged under the federal anti-grooming statute (18 U.S.C. 2422) from 2000 through 2019. Journey-to-crime distances were measured at both an ordinal- and interval-level. The author qualitatively reviewed 50 cases from the full sample (n = 331 journeys-to-crime committed by 308 offenders) to describe the types of cases in the full sample and contextualize the quantitative findings. Results from a series of regression analyses supported Hypothesis One in that contact-driven offenders on average traveled farther to their victims than traditional offline groomers. Results also supported Hypothesis Two in that contact-driven offenders’ duration of communication with victims was significantly associated with jurisdictional journey-to-crime distances and significantly predicted longer journey-to-crime distances that were measured at the interval level. Finally, the results of testing Hypothesis Three did not suggest that contact-driven offenders tended to be younger or more educated on average when compared to offline traditional groomers, as these results were not statistically significant. The author concludes with a discussion of findings, implications for policy and practice, limitations, and a path for future research
ANTECEDENTS TO HIGHLY AUTOMATED VEHICLE USAGE TO IMPROVE CHILDHOOD INDEPENDENT MOBILITY
Get PDFChildhood Independent Mobility (CIM) has numerous cognitive and physical benefits forchildren but has been on a steady decline for many years. With the rapid increase in vehicle automation technology, it is imperative to understand when and why parents may decide to let their children travel independently in Highly Automated Vehicles (HAVs). Study one created and validated a measure of Parental Intention to transport children in these vehicles. Further, this additional measure, Parental Intention to transport children in automated Vehicles (PI), was examined relative to pre-existing technology acceptance models. PI showed satisfactory reliability, as well as satisfactory global and local fit, making it a viable measure for future analyses. Study two focused on a new parallel mediating model between Parental Fear (PF), Fear of Strangers (FoS), Perceived Positive Potentiality of Outdoor Autonomy (PPAC), and PI with CIM. Study two provided the first link between CIM measures related to intention to use HAVs to transport children. Study three amended measures at the intersection of CIM and HAV research, to find unique predictors for PI. The newly amended measures were Perceived Travel Competence (PTC), Perceived Disapproval from Others (PDO), and Parental Automated Vehicle Fear (PAVF), and Trust in Automation (TiA). These three measures may provide unique predictions into why parents might let their child use HAVs unsupervised. Each study tackled behavioral intention from different theoretical perspectives: First, from automated vehicles, then from independent mobility, and last, from the intersection of these two research areas
TIME-AVAILABILITY AND RESOURCE-BARGAINING IN HOUSEWORK DIVISION: A STUDY OF SOUTH ASIAN COUPLES IN THE U.S. AND U.K.
Get PDFThis dissertation investigates the division of housework among South Asian immigrant couples residing in the United States and the United Kingdom. Utilizing secondary data from the American Time Use (ATUS) and the U.K. Household Study (UKHLS), the study focuses on married individuals aged 18 to 64 who identify as Pakistani, Indian, Bangladeshi, or Sri Lankan. The primary objective is to examine how time-availability and relative resources influence housework allocation among women and men within these communities and to assess whether these factors operate differently across the two national contexts. The research tests two main hypotheses: first, that time availability and relative resources are less predictive of housework time for South Asian men compared to women in both countries; and second, that the effects of these predictors differ between the U.S. and the U.K., with stronger impacts expected in the U.K. Ordinary least squares (OLS) regression models are employed to analyze the data and test these hypotheses. Findings reveal that South Asian women consistently perform a greater share of housework than men in both the U.S. and U.K., even when engaged in paid employment. For women, time availability significantly influences housework hours, supporting the time-availability theory: as paid work hours increase, housework hours decrease. However, men’s housework hours remain largely unaffected by their spouses’ paid work hours, suggesting that traditional gender norms continue to shape men’s limited participation in domestic tasks. The resource-bargaining theory, which posits that greater economic resources would reduce housework time, finds only partial support. While higher education among U.K. women appears to facilitate a reduction in their housework time. Additionally, higher income and educational attainment do not consistently decrease housework for either gender, highlighting how cultural norms may override economic factors in determining the division of housework
Machine Learning for Mobile Healthcare
Get PDFAs AI becomes increasingly ubiquitous across industries, there is a growing demand for ML models to be deployed on edge devices, driven by the democratization of AI. However,
the decision-making processes of AI systems often exhibit biases, prompting a renewed focus on fairness, particularly in industries prioritizing equitable outcomes such as security
surveillance, face recognition, and medical applications like dermatology. This research addresses the need for fairness in mobile healthcare, specifically in dermatology, by developing an Android application for skin disease detection and mobile dermatology assistance in remote areas. While existing AI systems boast high overall accuracies, they often neglect fairness considerations, resulting in subpar performance, especially on datasets representing diverse skin tones. Despite the importance of fairness, most neural network architectures prioritize other metrics, disregarding the need for models to run efficiently on edge devices. To bridge this gap, there is a call for smaller networks optimized for hardware constraints, without compromising fairness.
This study explores the paper ”The Larger The Fairer? Small Neural Networks Can Achieve”, presented at the Design Automation Conference – 2022. Which introduces an automatic neural architecture search (NAS) methodology called as Fairness and Hardwareaware Neural architecture search (FaHaNa) for network selection. FaHaNa employs a freezing
method to accelerate optimization while preserving fairness, effectively minimizing network size and latency for edge devices. The thesis discusses about the successful application of the FaHaNa framework on Android devices illustrates its potential to democratize healthcare diagnostics across diverse demographic and geographic landscapes, making advanced healthcare solutions more accessible and reducing disparities in medical care availability. This work not only showcases the feasibility of achieving fairness in mobile healthcare applications but also sets a solid foundation for future innovations in the domain of equitable, AI-enabled healthcare solutions