Environmental and Occupational Health Sciences Institute
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Bilingual and bicultural support for first year Chinese international students: a case study of the first year study-abroad program
No full textChinese international students (CISs) represent the largest population of international students in the U.S., yet research on their experiences often adopts deficit-based perspectives (Heng, 2018; Wang, 2021). The challenges they face were exacerbated during the COVID-19 pandemic by explicit xenophobia and worsen U.S.-China political relations. To address these challenges, Rise University implemented the First Year Study-at-Home (FYSH) program during the pandemic to support newly admitted CISs who could not study on the U.S. campus. The FYSH program combined in-person classes taught by local instructors in China with online coursework taught by Rise professors. It fostered a cross-cultural environment where students used both English and Mandarin. From Fall 2020 to Fall 2022, the program supported 538 students, achieving a 98% retention rate as students transitioned to on-campus studies in Spring 2023. While the FYSH program was discontinued after the pandemic, it is essential to evaluate it to guide effective programs for international students. This study aims to explore the FYSH program’s impact on students’ learning experiences during the pandemic and in the U.S. campus. Using a mixed-methods approach, the study analyzed qualitative data from twelve retrospective semi-structured interviews and quantitative data from surveys of 347 and 118 students across two academic years, alongside academic performance data. Key findings include: (1) FYSH program effectively addressed most challenges that CISs faced during the program and prepared them to transition to the U.S. campus. (2) Students expressed high satisfaction with the FYSH program, particularly regarding in-person classes. In addition, students leveraged their funds of knowledge, including their native language, culture, and prior learning experiences to navigate their cultural identity and adapt to challenges. (3) FYSH did not effectively address the challenges in preparing students to network with peers from other racial groups and deal with racism after transitioned to the U.S. campus. These findings proved the importance of incorporating Culturally Sustaining Pedagogy (CSP) into program design to sustain international students’ cultural and language competencies. Additionally, the study highlights the need to address racism in CSP program design, offering practical and theoretical insights for designing effective academic and cultural programs tailored to international students’ needs.Ed.D.Includes bibliographical reference
Evaluating pharmacokinetics and dosing strategies of antibiotics and biologics in lean and obese animal models
No full textObesity is a global health concern impacting over 890 million adults and poses significant challenges to healthcare systems worldwide. Despite its prevalence, our understanding of how obesity influences pharmacokinetics and drug biodisposition remains limited. Understanding how obesity affects drug disposition is crucial, as traditional dosing strategies are often based on studies conducted in non-obese individuals. This reliance can result in suboptimal therapeutic outcomes for obese patients, who may experience altered pharmacokinetics due to the physiological changes associated with increased body fat. This dissertation investigates the pharmacokinetic alterations associated with obesity, focusing on antibiotics such as cefoxitin, cefazolin, and piperacillin, along with biologics including nivolumab and recombinant human erythropoietin. By examining obesity-induced changes in the pharmacokinetics of these commonly used drugs, this research aims to determine whether current dosing regimens need to be adjusted for the obese population. In Chapter 1, the introduction provides an overview of the obesity epidemic, discusses the impact of obesity on drug pharmacokinetics, and highlights the importance of body composition in pharmacokinetics. Additionally, it covers the general pharmacokinetic profiles of cefoxitin, cefazolin, piperacillin, nivolumab, and recombinant human erythropoietin. Chapter 2 presents a fully validated LC-MS/MS method for the simultaneous quantitation of cefoxitin, cefazolin, and piperacillin in rat plasma and twelve tissues including abdominal adipose tissue, brain, heart, kidney, liver, lungs, muscle, subcutaneous adipose tissue, skin, small intestine, spinal cord, and spleen. This method demonstrates efficiency through its sensitivity and high throughput, requiring only a minimal sample volume of 5 μL for plasma and 50 – 100 μL for tissue homogenates. Building on the validated bioanalytical method presented in Chapter 2, Chapter 3 quantifies the plasma and tissue concentrations of cefoxitin, cefazolin, and piperacillin collected from lean and obese rats collected at 5, 15, 30, 45, 60, 90, and 120 minutes following intravenous administration of these antibiotics according to body weight. Comprehensive experimental data are collected, including body measurements (total body weight, body length, abdominal circumference), body composition (fat mass and lean mass), and tissue weights from both lean and obese rats. Noncompartmental analysis is performed to compare pharmacokinetics parameters between lean and obese animals. The results indicated that mg/kg dosing is required for obese animals to achieve drug exposure levels comparable to those in lean animals. A whole-body physiologically based pharmacokinetic model is then developed to describe these concentrations, integrating physiological parameters such as tissue weight and blood flow rates for both groups. This model provides a mechanistic framework that enhances our understanding of drug distribution across various tissues. The data generated from this study is anticipated to inform future translational research and support the optimization of antibiotic dosing strategies for the obese population in clinical settings. In Chapter 4, the dissertation further investigates the pharmacokinetics of biologics, specifically focusing on nivolumab and recombinant human erythropoietin using a diet-induced obese rat model. Male Long-Evans rats were fed a high-fat diet to induce obesity, with their progress monitored through various body metrics. The rats were then received nivolumab or recombinant human erythropoietin via intravenous or subcutaneous injection. The collected serum samples were analyzed using ELISA, and pharmacokinetic parameters were calculated using noncompartmental pharmacokinetics analysis. While our previous studies indicated significant differences in pharmacokinetics of human IgG in lean and obese rats, this study found no observable differences in nivolumab and recombinant human erythropoietin in pharmacokinetics between lean and obese rats. The results that mg/kg dosing of these 2 biologics is necessary for obese animals to achieve comparable drug exposure to lean animals. Further research with other biologics is needed in both preclinical and clinical settings to identify optimal dosing strategies for obese populations. Male Long-Evans rats were fed a high-fat diet to induce obesity, with their progress monitored through various body metrics. The rats then received either nivolumab or recombinant human erythropoietin via intravenous or subcutaneous injection. Serum samples were collected and analyzed using ELISA, and pharmacokinetic parameters were calculated using noncompartmental analysis. While our previous studies indicated significant pharmacokinetic differences for human IgG between lean and obese rats after intravenous and subcutaneous injection, this study found no significant differences in the pharmacokinetics of nivolumab and recombinant human erythropoietin between the two groups. These findings suggest that mg/kg dosing of nivolumab and recombinant human erythropoietin is necessary for obese animals to achieve drug exposure comparable to that of lean animals. The differing conclusions between our previous findings on human IgG and the current study also highlight that the pharmacokinetics of each biologic may vary in obese populations. Therefore, further research with other biologics currently in use is essential in both preclinical and clinical settings to establish optimal dosing strategies for obese individuals. Overall, this dissertation explores the impact of obesity on the pharmacokinetics of both small and large molecules, emphasizing the necessity for tailored dosing strategies to improve therapeutic efficacy using a diet-induced animal model. These findings aim to enhance our understanding of drug biodisposition in obese populations and provide a foundation for optimizing therapeutic approaches in this growing demographic.Ph.D.Includes bibliographical reference
A finite element and data-science assisted deep learning framework to interpret the constitutive behavior of brain white matter
No full textThe finite element methods (FEM) are widely utilized in numerical modeling of Brain White Matter (BWM) to depict traumatic brain injuries (TBI). These injuries could manifest in several forms such as tensile, compressive or shear loads on axons in both quasi-static and dynamic forms. Novel data-driven multi-scale numerical models are formulated to characterize BWM response when subjected to ensemble of traumatic loading scenarios. The purpose of this study is to propose computational solutions that connects AI (data-science), optimizations, medical imaging, multi-scale biomechanics and soft tissue modeling. These models would act as foundation studies for attaining highly repeatable and accurate data driven FEM and Machine-Learning (ML) models for multi-scale depiction of brain by incorporating axon/neuroglia composite anisotropy, axonal tracts tortuosity and brain aging/softening effects due to demyelination. Firstly, a bi-phasic 3D finite element model (FEM) has been proposed to study the mechanical response of axons embedded in ECM when subjected to tensile loads. The Ogden hyper-elastic (HE) material model describes the axons and the ECM materials. The developed model investigates several tethering scenarios between axons and oligodendrocytes using two FEM sub-models (single-OL and multi-OL) configurations. These tethering are deployed as linear spring-dashpot element. To gauge dynamic response and stress accumulation & relaxation effects, a hyper-viscoelastic (HVE) model is also proposed leveraging both analytical and optimization based frameworks. This generalizable approach enables a comprehensive analysis of the role of oligodendrocytes on stress redistribution and propagation, under static and repeated loading using a combination of static, steady-state (SSD), and explicit (ED) dynamic models. Next, a series of novel 3D micromechanical FEM proof-of-concept (POC) models are developed in house using Representative volume element (RVE) with axons embedded in extra-cellular glial matrix (ECM) for simulating the BWM response under shear. These models exhibit the Poynting effect (PE) in brain matter. PE is a nonlinear phenomenon associated with soft materials whereby they tend to elongate (positive) or contract (negative Poynting effect) in a direction perpendicular to the shearing or twisting plane. In-depth investigation is carried out using single, scaled-up and biconically modeled myelinated axons-ECM tri-phasic RVEs (Ogden hyperelastic) to characterize trends in degree of Poynting effect when subjected to ensemble of simple and pure shear loads. Leveraging the developed 3D FEMs built for simulating the Poynting effect, a deep 3D convolution neural network (CNN) algorithm combined with the 3D anisotropic REV FEM was employed to predict the WM's anisotropic stress & stiffness/material properties. 3D FEM geometrical information encoded in the voxelated locations & isotropic Ogden material properties are used as input data and consequently incorporated into a 3D CNN model that cross-references the RVEs' stress and stiffness (output). These output data are calculated in parallel using in-house developed tri-phasic 3D FEM, which depicts RVE samples as axon-myelin-glia composites. This novel hybrid CNN-FEM framework dramatically reduced the computation time compared to conventional FEMs to generate stress-stiffness tensor for sheared brain. In continuing the data-science based BWM modeling efforts, a synthetic 2D-FEM viscoelastic modeled BWM simulation dataset generated from previous research was used to build an end-to-end predictive ML forward model workflow to predict brain tissue properties (i.e., storage modulus) of a visco-elastic modeled brain. Developed framework incorporates uncertainty quantification in property estimations and also achieves model interpretability & explainability by analyzing sensitivity of constituent RVE components on predicted target BWM properties. The proposed transferable ML framework will aid soft tissue-characterization, tissue sensitivity & inverse model research for non-linear composites. Lastly, a novel high-order 3D FEM Ogden hyper-elastic brain aging model has been put forward to depict physiological aging and tissue degeneration in BWM. Magnetic Resonance Imaging (MRI) data from test subjects’ of different ages are analyzed using image processing libraries in python and MATLAB scripts used to calculate white matter volume fraction (VF) shrinkage and shear moduli depreciation functions with age. An ensemble of RVE models are developed with straight and tortuous myelinated axonal tracts embedded in glial matrix to characterize and interpret an aging brain response. Proposed novel proof-of-concept aging brain micro-mechanical FEMs would enable advanced pathology identification (brain tissue decay) and facilitate preventive health measures planning for TBI/aged brain.Ph.D.Includes bibliographical reference
A parametric study on the structures of the trap impactor
No full textThe onset of the SARS-CoV-2, or COVID 19, global pandemic greatly contributed tothe worldwide awareness of airborne pathogens. This fact forced the development of accurate
and quick testing procedures. The current tests generally involve obtaining a sample of
saliva or mucus via swabbing and attempting to detect antigens. However, a novel method
of detection utilizes inertial impactors to capture aerosolized saliva blown from an individual’s
breath onto a biosensor, aiming to facilitate a faster and easier testing technique.
Among factors that influence the capture of particles onto the biosensor, the geometry
through which flow travels can greatly affect the presence of flow structures. This work
aims to determine whether or not the parametrization of the trap impactors gap size has
an effect on the flow structures that develop within the device, in order to determine a
theoretical optimal geometric configuration.M.S.Includes bibliographical reference
Coupling structural, adsorption, and mechanical properties of nanoporous carbons using advanced molecular simulation methods
No full textNanoporous carbons are integral to numerous industries, including mixture separations, carbon capture, batteries, and electrodes. These carbons are composed of highly disordered graphene-like domains that form networks of convoluted pores with broad size distributions ranging from ultramicropores (2 nm). Traditional pore characterization techniques have been extensively applied to predict the properties of practical carbons; however, these methods predominantly rely on the adsorption of pure fluids in simplified, rigid pore models, which cannot fully capture the complex interplay between mixture adsorption, pore space morphology, and structure flexibility.This dissertation extends the traditional techniques through a progression of increasingly sophisticated modeling approaches. First, a novel thermodynamic deformation model, based on the binary Langmuir adsorption model, is developed to predict mixture-induced deformation from pure component measurements. The model's effectiveness is demonstrated using CH4/CO2 mixtures in hard coals, where it successfully predicts both adsorption capacity and volumetric strain under geological conditions. Next, the applicability of Density Functional Theory (DFT) calculations, coupled with Statistical Associating Fluid Theory (SAFT-DFT), is explored to predict mixture adsorption and subsequent deformation of slit-shaped carbon nanopores. The SAFT-DFT results show excellent agreement with atomistic Grand Canonical Monte Carlo (GCMC) simulations while requiring only a fraction of the computational cost, revealing important insights into the nonmonotonic strain behavior and molecular packing effects.
The focus then shifts to more realistic material representations through the development and characterization of three-dimensional carbon models. These models exhibit disordered networks of pores between corrugated and defected fragments of graphene sheets, better representing the complex morphology of practical carbons. A selected model is fully characterized using both geometric and adsorption methods, demonstrating remarkable agreement between its predicted adsorption capacities for various gases (N2, CO2, SO2, and hydrocarbons) and experimental measurements on the practical Norit R1 Extra activated carbon. Finally, a hybrid Monte Carlo/Molecular Dynamics simulation scheme is developed to directly simulate adsorption-induced deformation in these 3D models. This approach reveals complex relationships between carbon density, pore morphology, and deformation behavior, while providing novel insight into how mixture composition affects structural response.
This dissertation represents a significant advancement in the development of porous material characterization techniques, providing new computational tools and theoretical frameworks for understanding and predicting the coupled structural, adsorption, and mechanical properties of nanoporous carbons. The methods developed here have important implications for optimizing materials in applications ranging from gas separation and storage to carbon capture and sequestration.Ph.D.Includes bibliographical reference
R.E.P.U.T.A.T.I.O.N (RIPK3’s version) - RIPK3 promotes neuronal survival by suppressing excitatory neurotransmission during CNS viral infection
No full textWhile recent work has identified roles for immune mediators in the regulation of neural activity, the capacity for cell intrinsic innate immune signaling within neurons to influence neurotransmission remains poorly understood. However, the existing evidence linking immune signaling with neuronal function suggests that modulation of neurotransmission may serve previously undefined roles in host protection during infection of the central nervous system. Here, we identify a specialized function for RIPK3, a kinase traditionally associated with necroptotic cell death, in preserving neuronal survival during neurotropic flavivirus infection through the suppression of excitatory neurotransmission. We show that RIPK3 coordinates transcriptomic changes in neurons that suppress neuronal glutamate signaling, thereby desensitizing neurons to excitotoxic cell death. These effects occur independently of the traditional functions of RIPK3 in promoting necroptosis and inflammatory transcription. Instead, RIPK3 promotes phosphorylation of the key neuronal regulatory kinase CaMKII, which in turn activates the transcription factor CREB to drive a neuroprotective transcriptional program and suppress deleterious glutamatergic signaling. These findings identify an unexpected function for a canonical cell death protein in promoting neuronal survival during viral infection through the modulation of neuronal activity, highlighting new mechanisms of neuroimmune crosstalk.Ph.D.Includes bibliographical reference
Understanding the classroom experiences of black first-generation college students using the strengths perspective: a student and instructor view
No full textBlack first-generation college students (FGCS) often encounter challenges in the collegiate classroom due to implicit racism, academic unpreparedness, and cultural shifts. My study explores how strengths philosophy, a social work framework that leverages inherent strengths to encourage agency and change, can enhance the self-efficacy of Black FGCS. Self-efficacy, the belief in one's ability to achieve specific goals, is critical to academic success. This research examines whether strengths philosophy practices are present in the college classrooms of Black FGCS and whether instructors intentionally or unintentionally employ these practices. By analyzing the experiences of both students and instructors, my study aims to empower Black FGCS, ultimately contributing to their academic success. The findings can transform college classrooms into environments that nurture the strengths and abilities of Black FGCS, fostering their self-efficacy and increasing their chances of success. This research is a vital step in addressing educational disparities and breaking the cycle of poverty that has historically affected Black communities.Ed.D.Includes bibliographical reference
Tracing Romina’s Growth in Reasoning and Sense-Making in 4 th and 6 th Grades
No full textThis is Analytic 1 (of 3) of "Tracing Romina’s Growth In Reasoning And Sense-Making about Math Problems and Development of Beliefs about Math Teaching/Learning"This analytic traces the development of Romina’s problem-solving heuristics andexamines examples of her behaviors in collaborative settings from fourth and sixth grades.Specifically, we examine video data from February 6, 1992 when Romina was in 4 th grade andworking with a partner during her first exposure to the Towers Problem (generating allcombinations of “towers” 5-tall, selecting from 2 colors). Next, we see Romina as a 6 th graderworking with the same partner on an algebraic task of Guess My Rule. In both episodes wewatch Romina create models for her mathematical ideas as she questions herself and others. As explored in Steffero (2010), Romina’s questions in fourth grade consist primarily of asking for information or seeking verification of her mathematical ideas involving the possible towercombinations. In sixth grade, we again hear Romina’s questions along with her explanationsregarding slope and y-intercept for her partner.References Steffero, M. (2010). Tracing beliefs and behaviors of a participant in a longitudinal study for the development of mathematical ideas and reasoning: A case study. Rutgers The State University of New Jersey, School of Graduate Studies
The behavioral and physiological effects of video-mediated education
No full textVideo Delivered Training has been associated with increased exhaustion, less engagement, and less retention of the material presented to neurotypical people. In contrast, pre-recorded video training has been shown to be the most effective training method for people with autism. This study aimed to determine which method of training (Pre-Recorded Video, Zoom Synchronous and Live in class) was least stressful and most engaging for students and if differences existed based on a specific disability, focusing on students with ASD. The subjects were asked to wear a Shimmer GSR+ glove to measure heart rate and galvanic skin response and TobiiPro Eye Tracking Glasses to measure pupil size and blink rate and track the subject’s gaze and eye movements and to provide a saliva sample before and after each visit to measure cortisol levels. These measurements were taken at each visit, which took place on three separate days at the same time of day. While we found limited statistical significance in the analysis, we found appreciable effect sizes in all measurements, with the largest effect sizes being blink rate, heart rate, and cortisol for between-group comparisons. Additionally, in looking specifically at the atypical results, we found a significant difference in the mean for pupil size between all conditions, especially the Zoom condition versus the Live condition. We expected the statistical significance to be reduced because the subject pool was limited, especially for the atypical subjects. The pupil, blink rate and heart rate data showed the most variance for the between-group all visits and between-visit atypical group means.M.S.Includes bibliographical reference
C-section delivery alters the early life microbiome and neurodevelopment
No full textC-section (CS) delivery is associated with an increased risk of developing neurodevelopmental diseases, but mechanisms remain unknown. We hypothesize that birth mode affects neurodevelopment in a way that is reversible by microbial restoration. To test this hypothesis, we characterized brain development - hippocampus transcriptomics - and the gut microbiome in mice discordant to birth mode with and without microbial restoration after C-section birth. Restoration (CSR) was performed by exposure to the maternal vaginal microbiome at postnatal day 0 (P0). Experiments were performed on conventional B6129SF1/J and the 16p11.2del heterozygous mouse model of neurodevelopmental susceptibility. We collected gastrointestinal contents, dissected the hippocampus, and perfused whole brains at P7 and P21. We found significant effects of birth mode on the gut microbiome, although with small effect size, and partial restoration in the CSR group. At P7, there were alterations in 85 differentially abundant bacterial amplicon sequence variants (ASVs), of which 65% (55 taxa) were restored in the CSR group, mostly by ASVs shared between both vaginal and fecal communities. At P21, the CS-born mice showed altered the abundance of 203 ASVs, of which 53% (108 taxa) were restored in the CSR group. CS birth altered hippocampal gene expression, with an under expression of 69 genes and overexpression of 16 genes at P7, when compared with vaginally born and fostered animals. Gene ontology pathway analysis showed that CS increases cellular division/differentiation while decreasing synaptic plasticity. Microbial restoration after CS did not rescue gene expression. Overall, our findings show important early alterations in brain development caused by C-section. Although microbial restoration after C-section partially restored the microbiome, it was not enough to normalize brain gene expression at P7.Ph.D.Includes bibliographical reference