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Disease Ecology in Prisons: Environmental Factors Influencing Covid-19 Transmission, Recovery, and Control Efforts in Maryland’s Correctional System
Get PDFThere are multiple environmental factors that can and have influenced the transmission of diseases and challenge recovery and control efforts across the globe, as was recently experienced during the Covid-19 pandemic. However, some communities who often bear the brunt of environmental injustices were impacted more than others, including carceral communities. Within correctional institutions, environmental factors such as cell spatial density, population numbers, air quality, and nutrition deficiency are believed to have played a pivotal role in the spread and symptom exacerbation of Covid-19. By creating a database to include statistics of the numbers of positive Covid-19 cases in inmates, the average prisoner populations, the volume of prisons, prison housing types, proximity to pollution facilities, and the number of days at subpar air quality, and performing fixed effect linear regression models, we can get a clear picture of the influence the environment had on Covid-19 in Maryland’s correctional facilities
METHODS FOR DECENTRALIZING PATHOGEN IDENTIFICATION AND ANTIMICROBIAL RESISTANCE TESTING
No full textThe importance of timely diagnostics for controlling infectious diseases has been highlighted by the COVID-19 pandemic. As we move forward, other diseases, such as RSV and the flu, are re-emerging. Infectious diseases, while presenting similar symptoms, can stem from various causes, making accurate diagnostics critical for appropriate treatment. Correct identification (ID) and antimicrobial susceptibility tests (AST) are essential for choosing effective treatments and curbing the rise of antibiotic-resistant bacteria. Traditional ID and AST methods, however, are slow and resource-intensive, hindering point-of-care (POC) applications. Technological advancements in clinical microbiology have improved the speed and sensitivity of diagnostics, with state-of-the-art labs employing tools like MALDI-TOF for ID and automated systems like the BD Phoenix for AST, providing faster results. Despite these improvements, diagnostics remain centralized due to the bulky and costly nature of the equipment required, limiting accessibility for many patients, especially in remote or low-income areas.
Magnetofluidics emerges as a potential solution, leveraging magnetic particles to automate and miniaturize diagnostic assays, simplifying sample-to-answer processes. While previous magnetofluidic implementations have shown success, challenges remain in accelerating assays, integrating controls, and enhancing multiplexing capabilities.
This thesis presents an exploration of magnetofluidics for diagnostics, aiming to speed up pathogen detection and improve multiplexing. It first looks at CRISPR for rapid SARS-CoV-2 detection (Chapter 2), then develops a ratiometric PCR assay for UTIs that identifies bacteria from urine samples in 30 minutes (Chapter 3). It also introduces a multiplexing approach for nucleic acid detection, focusing on a probe-based PCR melting assay for a drug-resistant STI (Chapter 4). The work culminates in a method that screens for STI pathogens and antimicrobial resistance genes simultaneously, showcasing the potential of magnetofluidics for comprehensive diagnostics (Chapter 5)
I’M NOT SURE WHAT JUST HAPPENED ESSAYS AND SHORT STORIES OF THE ABSURD
No full textThis collection of essays and short stories explores a variety of themes, such as the role of plot in a story, the necessity of character development, the toll of internal battles, and the ridiculousness of the mundane. Short stories “Thursdays” and “Empty” and “A Bloody Night on the Beat” all examine the role of suspense and climax for readers of fiction. Essays “Diagnosis” and “A Comedian’s Guide to Major Depressive Disorder” focus on the realities of mental illness and they, along with the humor piece “Educators in Extracurricular Activities (Or, The Penis Story),” all mock the absurdities those same readers may encounter off the page. These six collected texts feature characters and speakers with a strong interiority and an opportunity for the reader to study their own responses to the odd events, real and imagined, that they find within
Sound the alarmone: α-proteobacterial mechanisms of adaptation to stress
Get PDFBacteria occupy diverse niches and are thus exposed to various stressors, such as fluctuations in temperature and the availability of nutrients. To adapt to environmental challenges, bacteria must sense their surroundings and respond by re-wiring physiological processes to promote survival instead of growth until the stress is removed. For instance, Caulobacter crescentus and Rickettsia parkeri are two species of Gram-negative α-proteobacteria that are found in different habitats, yet each are exposed to changing environmental conditions and therefore must adapt accordingly. C. crescentus is an oligotrophic bacterium with a dimorphic life cycle that is regulated by the availability of nutrients: it can exist in either a motile “swarmer” cell stage when nutrients are unavailable, or as a “stalked” cell when resources are plentiful. In contrast, R. parkeri is a tick-borne obligate intracellular pathogen that can occupy a range of hosts, including ticks and a variety of mammals. While the mechanisms by which R. parkeri adapts to these various environments are relatively under-studied, it is conceivable that R. parkeri growth must also be regulated by the changing conditions within its different hosts. For these reasons, we use both C. crescentus and R. parkeri as models to study bacterial growth and adaptation during stress. Furthermore, since the processes that enable bacteria to adapt to stress are generally well-conserved, we are interested in using these models to uncover key mechanisms and factors in stress adaptation pathways that may also be found in various species of pathogenic bacteria, which could therefore inform the development of therapeutics to combat bacterial diseases
Integrating Electrochemical and Biological Carbon Dioxide Conversion: Adaptive Bacterial Evolution and Transcriptomics
No full textCarbon emissions from anthropogenic activities represent a significant risk to global welfare through their contributions to global warming. Carbon capture systems look to capture emissions, and new technologies have created novel uses for this captured carbon dioxide. One such use is as a novel feedstock for production of chemicals and bioproducts through electrochemical and biological conversion. Electrochemical systems are highly efficient at reducing carbon dioxide into other C1 compounds but struggle to create longer more complex carbon products. In contrast, biological systems are highly efficient at the metabolic conversion of many C1 compounds into complex molecules but struggle to utilize carbon dioxide. By integrating these two technologies, it may be possible to efficiently utilize carbon dioxide as a feedstock to produce bioplastics and other value-added chemicals, adding economic incentives to implement carbon capture systems. The methanotrophic bacterium Methylomicrobium alcaliphilum 20Z is a prime candidate for this integration. The bacterium is able to metabolize methanol, a C1 compound easily produced by electrocatalysis. Additionally, it is highly amenable to being genetically engineered. Development for high efficiency electrocatalytic conversion of carbon dioxide to methanol and engineering of M. alcaliphilum 20Z to produce useful biopolymers have been completed by collaborators. However, these processes have yet to be integrated to work together seamlessly. The largest barrier to integration is the incompatible buffer conditions of electrocatalytic reduction and biological conversion. Electrocatalysis must take place in a 1M sodium bicarbonate buffer, which is not compatible with the growth of the bacteria. Here, work was completed to integrate the two systems by adapting M. alcaliphilum 20Z to higher carbonate concentrations, allowing the bacteria to grow in the presence of the electrocatalysis products. Following adaptation, transcriptomics analysis was completed to determine the transcriptional changes that resulted in increased survivability. Adaptation was successful, and transcriptomics results show differential gene expression before and after adaptation. Additional study will identify specific pathways that are responsible for increased survivability. This study sets the stage for the completion of an integrated system for carbon capture, electrocatalysis, and biological conversion of carbon dioxide into high value biopolymers
PREDICTING MICRONUTRIENT DEFICIENCIES USING PROTEOMICS DATA VIA QUANTILE MATCHING
No full textMicronutrients play an essential role in human metabolism, health maintenance, and the prevention of illnesses. Despite their critical importance, more than 2 billion people worldwide suffer from micronutrient deficiencies (MNDs), particularly in impoverished countries. This thesis addresses the challenge of assessing micronutrient levels in populations where traditional measurement methods are prohibitively complex and expensive. By observing the correlation between specific micronutrients and plasma proteins, this project aims to develop predictive models for MNDs based on plasma protein levels. Utilizing data from 435 pregnant women in rural Bangladesh, we identified significant plasma proteins for nine essential micronutrients and applied the quantile matching technique for prediction. Our findings indicate that, comparing with linear regression models, quantile matching can enhance the accuracy of predicting micronutrient levels by closely capturing the distribution's mean and standard deviation when the data follows a specific distribution. However, the technique exhibits limitations in its application across diverse populations, highlighting challenges in generalizability and robustness.
This research emphasizes the potential of using plasma proteins as predictors for predicting MNDs and offers insights that we may need to study more on the associations between proteins and micronutrients and develop other methodologies for prediction
IMPACT OF EVOLUTION ON INFLUENZA A VIRUS FITNESS AND ANTIGENICITY DURING THE 2021- 2022 AND 2022-2023 FLU SEASONS
Get PDFInfluenza subtype dominance changes every season due to changes in antigenicity, fitness and even epidemiological factors allowing different subtypes to prevail during different seasons and geographical locations. The 2021-2022 and the 2022-2023 Influenza seasons were both H3N2 dominant seasons in the US. Sequences from circulating H3N2 viruses in the 2021-2022 flu seasons revealed significant genetic diversity leading to increased subclades undergoing parallel evolution. Fitness assays on representative viruses from Baltimore and Macha, including growth curves and plaque assays, revealed divergent plaque morphology. Phylogenetic analysis of viruses in the 2022-2023 influenza season revealed a possible reassortment event with mutations on important antigenic sites. No replication or plaque morphology changes were detected and circulating viruses were minimally drifted from the vaccine strain when tested against pre and post vaccination serum from healthcare workers. This indicates that these recent reassortment events and mutations have led to an expansion of genetic diversity to evolve from moving forward.
During 2022-2023 flu season the A5a.2 subclade was able to acquire several mutations within the HA segment that allowed it to bounce back and further diversify into A5a.2a and A5a.2a.1. These new subclades are marked by unique receptor binding and antigenic site mutations with A5a.2a.1 clade being additionally drifted from the vaccine. Representative viruses were characterized through plaque assays, low MOI growth curves and neutralization assays with serum from pre and post vaccinated healthcare workers. 2022-2023 circulating H1N1 viruses displayed similar or improved in-vitro fitness when compared to 2019 viruses. All 2022-2023 viruses were also antigenically drifted from the vaccine strain with A5a.2a.1 being additionally drifted. Single point mutations on the HA segment were introduced on the A5a.2 backbone to interrogate their individual contributions. All mutations other than Q189E proved detrimental to the in-vitro fitness of these viruses. To investigate whether Q189E compensates for detrimental mutations plaque assays of these paired point mutants showed that while Q189E did improve fitness it did so in a reduced amount when combined with K142R. This data encapsulates the constant give and take between fitness and antigenicity
“I HATED THAT PLACE”: DESIGNING LEARNING ENVIRONMENTS WHERE SYSTEM-IMPACTED STUDENTS THRIVE
Get PDFThis dissertation presents an analysis of recent data, highlighting the urgent and ongoing need to address the specific needs of system-impacted youth. This study reinforces the well-known but persistently unmet needs of this vulnerable population, by shedding light on the barriers to successful education re-entry. Despite federal mandates for rehabilitative services, significant disparities in the quality and consistency of these services across states contribute to poor educational outcomes and re-entry experiences for adjudicated youth and those involved with the criminal legal system Public education institutions exacerbate these challenges through exclusionary disciplinary practices that disproportionately affect Black, Brown, and Indigenous students, contributing to higher rates of juvenile arrests. System-impacted youth face significant barriers upon re-entering their communities, particularly in educational settings. Traditional K-12 schools often fail to provide supportive environments for these students, who frequently endure trauma and punitive measures, leading to negative associations with education. This dissertation employs containment theory and labeling theory to analyze the multifaceted challenges these students face and the systemic inefficiencies hindering their successful educational reintegration. The study aims to investigate the experiences of student disconnectedness, trauma, and stigma among system-impacted students enrolled in the EMERGE education re-entry program. It explores the correlation between trauma and school disconnection, as well as personal and school-related barriers to re-entry. The research reveals significant negative correlations between trauma levels and academic performance, highlighting the need for individualized academic support and trauma-informed teaching strategies. The findings emphasize the necessity for flexible school environments, familial support, and professional development for educators to create inclusive and supportive school cultures. However, despite the immense obstacles they face, these students demonstrate remarkable resilience, underscoring the urgent need for systemic change to support their educational and personal growth
SUPPRESSIVE EFFECTS OF THE COX-2/PGE2 PATHWAY ON HUMAN NK CELLS AND REVERSAL BY EP INHIBITORS TO OVERCOME TUMOR IMMUNE SUPPRESSION
No full textAbstract
Our laboratory previously found upregulation of the cyclooxygenase-2/prostaglandin E2 (COX-2/PGE2) pathway in the tumor microenvironment of cancer types that respond poorly to immune checkpoint blockade (ICB). We also reported that PGE2 can suppress human T cell and monocyte functions in vitro, which can be prevented by chemical inhibitors of its receptors EP2 and/or EP4. Studies by others have shown that IFN-g secreted from NK cells is critical to reversing ICB resistance in murine models of COX-2-expressing tumors. Therefore, here we explored the effects of PGE2 on human NK cells. NK cells were isolated from normal donor peripheral blood mononuclear cells (PBMCs) by negative selection and activated with IL-2 ± PGE2 in vitro. Cytolytic (CD16+CD56dim) and cytokine-secreting (CD16-CD56bright) NK subsets were gated by flow cytometry (FACS). Expression of NK receptors, checkpoint molecules, and a cytolytic marker were quantified with FACS. Proinflammatory cytokine and chemokine secretion was detected by ELISA. Cytolytic function was examined by the DELFIA EUTDA cytotoxicity assay. In some experiments, cells were pre-incubated with EP2 or/and EP4 inhibitors before PGE2 exposure. Regulatory and functional markers assessed by FACS showed different expression patterns on cytolytic vs cytokine-secreting NK cell subsets in resting and activating states. PGE2 reduced IL-2-induced expression of activating NK receptors (NKp44 and NKG2D) and GITR by 40-86%, suggesting a functionally suppressed state. Consistent with this, PGE2 significantly reduced the secretion of proinflammatory cytokines (IFN-g and TNF-a) and the dendritic cell (DC) attracting chemokine (XCL-1) from IL-2-activated NK cells. The NK cell cytotoxicity is also suppressed. These effects of PGE2 could be prevented by EP2i and/or EP4i or by the dual inhibitor TPST-1495. In contrast, expression of IL-2-induced immune checkpoints (TIM-3 and TIGIT), the inhibitory receptor NKG2A, and granzyme A was reduced by PGE2 to a lesser degree (15-50%) or showed no significant effect. Our results suggest that the COX-2/PGE2 pathway exerts immunosuppressive effects on NK cells, in addition to T cells and monocytes as previously characterized in our laboratory, providing a rationale to test immune checkpoint blockade in conjunction with COX-2 pathway inhibitors such as EP2/4 inhibitors in patients with cancer
Model Usefulness: Aligning Utility and Prevalence in Use and in Training of Clinical Machine Learning Models
Get PDFTranslating prediction models into practice and supporting clinicians’ decision-making demand demonstration of clinical value. Demonstration of usefulness requires accurate representation of human concerns across multiple layers of abstraction, from articulating the problem parameters to selecting the appropriate dataset that captures the said problem parameters to incorporating preferences and value tradeoffs. Furthermore, existing approaches to evaluating machine learning models’ performance emphasize discriminatory power, which is only a part of the medical decision problem. Our broader agenda is to question the alignment of machine values and human concerns, establishing coherence from model construction to evaluation. We provide a literature review on the larger alignment problem concerning the artificial intelligence community, the class imbalance problem, and the decision-theoretic basis of our work. We propose the Applicability Area (ApAr), a decision-analytic utility-based approach to evaluating predictive models that communicate the range of prior probability and posterior probability cutoffs for which the model is applicable or has broader potential use. We demonstrate through a simulated study as well as applying ApAr to three medical datasets that the typical area under the receiver operating characteristic curve metric (AUROC) is limited in its evaluation of model performance and satisfying the needs of decision makers. As an example, in the diabetes dataset, the top model identified by ApAr was ranked as the 23rd best model by AUROC. A typical model selection procedure would have overlooked any model with the 23rd-highest AUC. Yet, ApAr, by incorporating value tradeoffs, suggested otherwise. From the simulation study, we also highlighted potential disease contexts under which cost asymmetry is important to clarify. ApAr adds value beyond an AUROC analysis by incorporating utilities in its calculation and addresses the decision maker’s concerns: 1) is the model useful to begin with? and 2) when is the model useful? An ApAr reflects a model’s usefulness/applicability under different target population disease prevalence and predicted probability cutoffs. Decision makers looking to adopt and implement models can leverage ApArs to assess if the model is matched to the target population and its context. Towards the end, we also provide a brief exploration of alternative approaches to model evaluation, each with its strengths and limitations. Lastly, we outlined several considerations for future work