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CHARACTERIZING THE SPATIAL AND TEMPORAL T CELL EVOLUTION IN IMMUNOTHERAPY-TREATED PATIENTS WITH METASTATIC CANCER
No full textT cells are an essential component of the adaptive immune system and immune response, as through their T cell receptors (TCRs), they recognize and eliminate specific antigens. Immunotherapy is a promising cancer treatment that leverages this T cell function to improve anti-tumor response. Differences in the immune and tumor landscape can influence immunotherapy outcomes, and therefore, the analysis of T cell repertoire dynamics and composition could lead to key insights into the heterogeneity of the anti-tumor immune response and its effect on immunotherapy efficacy. In this work, we used bulk TCR sequencing to analyze the TCR repertoires of 52 samples from multiple disease sites and timepoints (baseline, post-treatment, resection, and autopsy) for a cohort of 7 patients with metastatic cancer and aimed to identify changes in dynamics and phenotypic composition that could explain the differential response to treatment across metastatic sites. This analysis revealed significant TCR repertoire heterogeneity across timepoints and anatomic locations of analyzed tumor lesions for each patient, with the baseline and primary disease sites being the most different compared to metastatic sites. Despite the overall heterogeneity, TCR repertoires from the analysis of metastatic sites from proximal anatomic locations shared similarities. To assess potential associations with immunotherapy response, we performed differential T cell expansion analysis at the clone and cluster level for each patient and phenotypic characterization of each site’s significantly expanded TCR clusters. This characterization revealed that despite the largely private expanded clusters in each patient, similar cluster dynamics were observed in regressing compared to progressing tumors while at the autopsy sites, clonality increased. Moreover, we observed expansions of TCR clusters attributed to T regulatory cells in progressing tumors at the time of rapid autopsy. Overall, this spatial and temporal TCR repertoire analysis allowed a better understanding of the evolving immune landscape and provided insights that can be leveraged to further examine immune and tumor heterogeneity and inform the development of more effective personalized treatment approaches
Analyzing Immunological Characteristics of Mice and Macaques Immunized Intranasally with Mip3α-RelMtb
Get PDFTuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a global health threat, particularly due to the capacity of Mtb to enter a persistent state that renders tolerance to antimicrobial therapies. The stringent response, regulated by the RelMtb enzyme, is central to this persistence. Building on prior work in mice showing the therapeutic efficacy of a DNA vaccine encoding the RelMtb gene, this study evaluates a vaccine construct that fuses the Mip-3α chemokine to relMtb, thereby targeting this antigen to immature dendritic cells for T-cell recruitment and activation. To assess its immunogenicity, this vaccine was administered intranasally to both mice and rhesus macaques.
In both species, Mip3α-RelMtb vaccination led to enhanced T-cell recruitment and reactivity in the lungs compared to the non-fused RelMtb vaccine. In macaques, we observed higher proportions of lung-infiltrating CD4+ and CD8+ T-cells producing IFNγ, TNFα, and IL-17A, together with increased levels of the chemokine CXCL10, a known T-cell chemoattractant. In mice, elevated levels of CXCR3+KLRG1- CD4+ T-cells and effector memory phenotypes suggest a more protective T-cell profile. These findings support the potential of Mip3α-RelMtb to generate improved T-cell immunogenicity compared to RelMtb vaccination alone and overcome historical limitations of DNA vaccines in non-human primates
QUANTIFYING THE EPIDEMIOLOGICAL IMPACT OF INVESTIGATING TUBERCULOSIS OUTBREAKS AMONG PERSONS EXPERIENCING HOMELESSNESS IN THE UNITED STATES
Get PDFThe World Health Organization designates the United States as a country with a low overall burden of tuberculosis, however people experiencing homelessness in the United States still face a disproportionate burden of disease compared to the general population. People experiencing homelessness have a higher prevalence of tuberculosis risk factors such as HIV, diabetes, smoking, and substance use disorders. Residence in homeless shelters and other congregate living environments can also increase tuberculosis transmission risk. This study employed an outbreak response modeling framework to estimate tuberculosis care cascade participation among people experiencing homelessness during outbreaks during 2025-2035. Our results indicate that outbreak investigations could prevent 4,560 tuberculosis cases among people experiencing homelessness over the ten-year prediction period. Raising the cluster size threshold for initiating outbreak investigations decreases the number of cases averted. The most influential factors for tuberculosis prevention in or model were the reproduction number, the percentage of case contacts evaluated, and the number of contacts per case. These findings support interventions that provide individual or small-group housing for people experiencing homelessness, implement universal masking or infectious disease screening protocols, and enhance outbreak response procedures to maximize contact evaluation coverage
MODELING ARTERIAL DISEASE AND INJURY USING ENGINEERED HUMAN ARTERIES-ON-A-CHIP
No full textArterial diseases affect the mechanical properties of blood vessels, which then impair their function via complex mechanisms. To develop and test effective treatments, microphysiological systems replicating the mechanics and function of human arteries are needed. Here, we establish an artery-on-a-chip (ARTOC) using vascular derivatives of human induced pluripotent stem cells (iPSCs) cultured with pulsatile flow on an electrospun fibrin hydrogel. ARTOCs have mature, laminated smooth muscle that expresses robust extracellular matrix and contractile proteins, contracts in response to pressure and vasoagonists, and exhibits tissue mechanics comparable to human small arteries. We monitor real-time distention and luminal pressure to inform computational fluidic modeling, and we can easily tune biomechanical cues using scaffold thickness and flow rate to promote survival and function of endothelial and smooth muscle cells in the ARTOC. To test the ARTOC as a disease modeling platform, we first use non-isogenic iPSC-derived smooth muscle cells (iSMCs) from a polycythemia patient, showing significantly altered cell phenotype and increased vessel wall stiffness compared to controls. We then test a novel isogenic disease model in ARTOCs using iPSCs CRISPR-edited with a Hutchinson-Gilford Progeria Syndrome LMNA mutation (LMNA G608G; LMNA-HGPS). LMNA-HGPS ARTOCs show extracellular matrix accumulation, medial layer loss, premature senescence, and loss of tissue elasticity and ductility. Finally, we use ionizing radiation as an injury model and show that exposure of ARTOCs to gamma rays and heavy ions induces a Senescence- Associated Secretory Phenotype that dysregulates transcript and protein expression, cytokine secretion, and tissue mechanics. We then partially rescue this phenotype in ARTOCs by targeting the AP-1 transcription factor with small molecule therapeutics. With this work, we establish the ARTOC as a translational platform to link cell phenotype and protein dysregulation to tissue mechanics and dysfunction in arterial diseases
Validation of the cough quality-of-life questionnaire in patients with chronic cough
No full textBackground: Chronic cough significantly affects patients’ quality of life. The Cough Quality-of-Life Questionnaire (CQLQ) was validated based upon a small single center study. The aim of this study is to assess the validity and reliability of the CQLQ in a larger, multicenter cohort.
Methods: Individuals with chronic refractory cough for 3 months or longer were allowed to enroll in the Chronic Refractory Cough Cohort (COCO) study. Internal consistency, concurrent validity, repeatability and minimal important difference (MID) were estimated. The Leicester Cough Questionnaire (LCQ) was used as the external gold standard to evaluate the ability to distinguish severe patients from those with mild or moderate cough. Questionnaires were completed at enrollment and after 4 weeks.
Results: 119 patients were enrolled into the study. Internal consistency was high for the total score (Cronbach’s alpha 0.93). Concurrent validity analysis showed strong correlations between total score (r = -0.82) and corresponding domains of the CQLQ and the LCQ. Test-retest repeatability was acceptable (intraclass correlation coefficient 0.69). The ROC curve yielded an AUC of 0.920, indicating excellent discriminative ability. An optimal cutoff score of 59 on the CQLQ was identified to distinguish patients with mild/moderate versus severe cough. MID was 7.78 calculated by distributional approach.
Conclusions: This study supports and expands the use of CQLQ as a valid and reliable cough related life quality measure in individuals with chronic refractory cough, based on a multicenter cohort study
Efficient Spatial Search via Modified Attractive-Repulsive Particle Swarm Optimization for Autonomous Unmanned Vehicles
Get PDFHeuristic stochastic algorithms are widely utilized to solve complex optimization problems. Of these, a particularly useful subset are swarm intelligence methods, inspired by mimicry of observed collective biological behaviors. While these algorithms often demonstrate versatile problem-solving capacities, their performance varies depending on the problem space. Thus, many specialized variants have been created to tailor results for specific domains. In the field of autonomous unmanned vehicle (AUV) operations, efficient search remains a challenge due to constraints of navigating complex environments, collision avoidance, and limited sensing abilities. As such, this thesis addresses this challenge using a novel modification to the attractive-repulsive particle swarm optimization (ARPSO) algorithm to guide a swarm of autonomous unmanned vehicles (AUVs) through an area searching for targets.
The proposed algorithm allows AUV swarms to perform localized searches compatible with configurable settings of swarm sizes, vehicle movement constraints, and sensor specifications. Swarm search behavior is influenced by tuning or adapting algorithm hyperparameters. Through extensive simulation across various swarm sizes and target distributions, a comparative analysis is performed against conventional search methods. Results demonstrate that this modified ARPSO method can outperform traditional methods in the cases studied here, showing improved search efficiency and reduced total search time.
This research contributes to enhancing autonomous vehicle search capabilities with immediate applications including mine detection, search and rescue operations, and surveying. Further, the findings demonstrate the value of adapting particle swarm optimization-like (PSO) algorithms to specific problem domains, showing potential for further exploration in domains such as spatial search problems and robotics
Evaluating the Performance of Epigenetic Gestational Age Clock Estimations in a Pediatric Sample and Assessing Epigenetic Age Associations with Autism
Get PDFBackground: Utilizing methylation levels at specific CpG sites in the genome, epigenetic clocks are widely used to assess how accelerated or decelerated aging relates to health outcomes. Despite their broad use in adults, there is limited understanding of their suitability for pediatric research. This study aims to (i) evaluate the performance of epigenetic clock algorithms for measuring gestational age at birth and (ii) examine whether gestational biologic age acceleration at birth is associated with prospective autism outcomes in early childhood.
Methods: We used extant data collected by the Study to Explore Early Development (SEED) network. Our analysis will focus on a subset of SEED, phase 1-2, participants recruited from the California site with Illumina array-based DNA methylation measures from dried blood spots collected at birth. Clock performance was evaluated for the Bohlin, Knight, and EPIC algorithms by computing Pearson correlations (r), concordance correlation coefficients (ccc), and mean absolute errors between the estimated epigenetic gestational age and reported chronological gestational age. Multivariable logistic regressions were used to test gestational age acceleration/deceleration associations with prospective autism case outcomes obtained between 2 and 5 years of age.
Results: A total of 171 SEED child participants met inclusion criteria, including 69 autism cases and 76 population controls. The Bohlin and EPIC gestational age clocks demonstrated the strongest performance (r = 0.634 for both; ccc = 0.443 and 0.518, respectively). The Knight clock exhibited the weakest performance (r = 0.464, ccc = 0.456). We observed sex-specific trends in the association between accelerated gestational epigenetic age and autism. Among males, accelerated gestational age was associated with decreased odds of autism, with suggestive associations for the EPIC (OR=0.46, p=0.027) and Bohlin (OR=0.37, p=0.005) clocks. Although not statistically significant after correction, females exhibited a consistent but opposite trend, with increased odds of autism across all three clocks.
Conclusions: In this pediatric autism case-control sample, the Bohlin and EPIC clocks demonstrated the strongest overall performance, while the Knight clock exhibited weaker performance. Multivariable logistic regressions suggest that epigenetic age acceleration at birth may be protective against autism in males, with potential sex-specific differences warranting further investigation
State Efforts to Address Eating Disorders
No full textEating disorders are the most fatal mental illness in the U.S. However, they have historically been overlooked in health policy. This study examines how state governments are considering and addressing eating disorders, as well as barriers to implementing eating disorder-related prevention, treatment, and recovery services. To accomplish this overarching goal, this dissertation: 1) Identifies state bills and laws related to eating disorders by conducting a legal mapping analysis (Manuscript 1); assesses the extent to which state agency leaders view eating disorders as a public health priority and characterizes how states are currently addressing eating disorders within the non-Medicaid/Medicare publicly-funded system (Manuscript 2); and 3) explores state officials’ and advocates’ perspectives on barriers to providing robust eating disorder services
(Manuscript 3). Through these three empirical manuscripts, this dissertation elucidates future policy opportunities and provides actionable steps that states can take to better serve those impacted by these serious disorders
LEVERAGING ELECTRONIC HEALTH RECORDS TO STUDY ENVIRONMENTAL DRIVERS OF ASTHMA EXACERBATION
Get PDFAsthma is a common respiratory disease affecting nearly 4.7 million (6.5%) children and 20 million (8.0%) adults in the United States. Asthma exacerbations are common—affecting over 50% of children and 40% of adults with current asthma—but are heterogeneous and difficult to predict.
Patients with eosinophilic asthma are thought to represent one high-risk subgroup with increased likelihood of asthma exacerbations. Characterization of this subgroup of patients offers opportunities to improve management of acute exacerbations. We leverage eight years of electronic health records data from a tertiary referral center to quantify the association between peripheral eosinophil count and exacerbation severity and duration.
In addition to identifying clinically relevant biomarkers, it is essential to understand which triggers increase exacerbation risk and identify vulnerable populations. However, studying the effects of environmental exposures in the presence of temporal trends presents significant statistical challenges. We propose an adjusted case-crossover conditional logistic regression model in which we explicitly adjust for temporal trends prior to estimating exposure effects. We evaluate the novel estimator in multiple simulated scenarios, varying the strength of the secular trend, the selection of matched controls, and the exposure effect size.
Lastly, we apply adjusted case-crossover conditional logistic regression to study the association between excess heat and asthma exacerbation. We incorporate effect modification by age and Area Deprivation Index to identify subgroups particularly susceptible to heat-induced exacerbations.
Overall, this work contributes to the growing effort to leverage observational health data to conduct robust research and improve our understanding of asthma exacerbation risk
MULTIPHYSICS MODELING FOR LONG-TERM NEURAL ORGANOID VIABILITY
No full textNeural organoids (NOs), derived from human-induced pluripotent stem cells, are microphysiological systems that recapitulate key aspects of neurodevelopment. They offer powerful in vitro models for studying brain development and disease mechanisms underlying disorders such as Alzheimer’s disease, microcephaly, and autism spectrum disorders. However, a major limitation of current NO models is the development of core necrosis, primarily due to oxygen and nutrient diffusion constraints. This necrosis restricts regional organization and functional complexity, limiting the fidelity of NOs. Although strategies such as orbital shaking and microfluidic culture have been explored to alleviate diffusion limitations, they have achieved only partial success, particularly for organoids exceeding ~800 μm in diameter.
In this thesis, I will present a 3D finite element model to simulate O₂ transport and consumption within NOs, incorporating Michaelis-Menten kinetics and the Damköhler number (Da) to capture oxygen-limited necrosis. Experimental measurements of necrotic regions using fluorescent viability staining were used to calibrate the computational model, allowing for accurate prediction of oxygen starvation under various culture conditions. Using this calibrated framework, we systematically compared static, orbital shaking, and flow-based microfluidic culture strategies, quantifying their relative impacts on necrotic progression.
Building on these insights, I propose a 3D spatial perfusion strategy using embedded microchannels to actively deliver oxygen throughout the NO. Parametric studies varying channel spacing, density, and insertion geometry revealed critical design parameters for achieving near-uniform oxygenation and minimizing necrosis. Additionally, we evaluated how variations in Da influence perfusion efficiency, offering a predictive guide for tuning culture conditions based on organoid-specific metabolic demands. Complementary simulations demonstrated oxygen diffusion dynamics in perfusion systems prior to consumption onset and explored the effects of increasing perfusion density by replicating arrays of fluidic channels within the organoid. Our findings not only advance the understanding of oxygen transport limitations in NOs but also provide a foundation for engineering next-generation microfabricated bioreactors and organoid culture platforms applicable to a broad range of 3D tissue models