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MOLECULAR BASIS OF NPTX2 SYNAPTIC TRAFFICKING
Get PDFNeuronal pentraxin 1, 2, and R (NPTX1, NPTX2, and NPTXR) are expressed by excitatory neurons in brain. These related proteins form disulfide-linked heterooligomers and are functional when located at the plasma membrane of neurons via the transmembrane domain of NPTXR. NPTX2 is an immediate early gene expressed by pyramidal neurons and mediates an essential phase of homeostatic scaling whereby it enhances the excitatory drive of parvalbumin interneurons. Nptx2 is essential for the dynamic regulation of synaptic connections, particularly through its interaction with AMPA receptors which play a key role in synaptic plasticity and cognitive function.
Nptx2 is connected to a spectrum of neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, and schizophrenia, and was validated as a reliable biomarker. This thesis provides a comprehensive analysis of how Nptx2 is trafficked to synaptic sites and the molecular interactions that facilitate this process. Using proteomic techniques such as immunoprecipitation and proximity labeling (APEX2 and TurboID), this study maps the interaction network of Nptx proteins, identifying key candidate proteins involved in Nptx2 trafficking like SNARE and exocyst complex proteins.
Further, investigation into matrix metalloproteases (MMP), which are implicated in synaptic remodeling and plasticity, reveals their role in the cleavage and shedding of Nptx2 and Nptxr from the neuronal membrane. This process is essential for the modulation of synaptic strength, facilitating both the formation and retraction of synaptic connections in response to neuronal activity. The study also examines the role of Tumor Necrosis Factor-α Converting Enzyme (TACE) in this context, discussing alternative pathways for Nptx2 and Nptxr release that do not rely on TACE-mediated cleavage.
In conclusion, the findings of this thesis provide insights into the molecular basis of Nptx2 trafficking and its implications for synaptic function and neuronal health. This contributes to a deeper understanding of synaptic dynamics, offering potential therapeutic targets for treating neurodegenerative diseases
Contemporary Estimates of Lifetime Risk of Hypertension in the US
No full textLifetime risk estimations offer valuable insights into disease burden and inform preventive
strategies. To our knowledge, there is only one study estimating the lifetime risk of hypertension
using the contemporary definition in the US (systolic/diastolic blood pressure ≥130/80 mmHg),
with limited generalizability using three research cohorts and lacking data on Hispanics. Using National Health and Nutrition Examination Survey (NHANES) 1999-2018, we estimated the lifetime risk of hypertension (i.e., cumulative incidence from birth through age 80 years) by
sex and race/ethnicity (White, Black, and Hispanic), with Monte Carlo simulations (a simulated
cohort of 100,000 individuals). Overall, the lifetime risk of hypertension reached ~80-85% regardless of sex and race/ethnicity (i.e., Blacks ~85% and Whites and Hispanics ~80%-83%). However, the patterns to reach this level of lifetime risk of hypertension varied mainly by race/ethnicity. For example, the age reaching cumulative incidence of 50% (i.e., a half developing hypertension) was ~38 years in Black men, ~43 years in Black women, ~ 46-48 years in White and Hispanic men, and ~55 years in White and Hispanic women. Moreover, at any point in life, Black women had a higher cumulative incidence of hypertension than White and Hispanic men. Our study found that four in five Americans develop hypertension in their lifetime regardless of sex and race/ethnicity. However, Blacks tended to develop hypertension much earlier than the other racial/ethnic groups. Our findings further emphasize the need of public health interventions to prevent hypertension in the US, and such an intervention should reach Black youth and younger adults
Examining The Impact of Akt Inhibition on Artificial Antigen Presenting Cell Expanded Antigen-Specific CD8+ T Cells
No full textThe immune system is crucial to overall health and the prevention of diseases. However, for some conditions like cancer or autoimmune diseases, the immune response can be evaded, insufficient, or even harmful. Adoptive cell therapies aim to
resolve this by utilizing cellular engineering to help patients’ cells target specific antigens. An attractive cell type for these therapies is the central memory T cell, which
provides long lived immunity and a robust response when rechallenged by an antigen. One way to enhance the production of adoptive cellular therapies is to use biomaterial
based artificial antigen presenting cells (aAPCs). Nanoscale aAPCs are tunable magnetic nanoparticles presenting specific antigens and other activation signaling proteins. They have enabled unparalleled biodistribution, demonstrating enrichment and
expansion of antigen-specific T cell populations both in vivo and in vitro. Another way to enhance these efficacy of adoptive cell therapies is to modify metabolic pathways. The PI3K/Akt metabolic pathway is crucial for the differentiation of effector T cells. However, it is detrimental to the differentiation of memory T cells. By inhibiting Akt, an upstream protein in the pathway, differentiation of memory T cells can be enhanced. Akt inhibition
has not been used alongside aAPCs expansion in literature. This thesis reports that Akt inhibition and aAPCs expansion induces a central memory-like phenotype to murine
wild-type CD8+ T cells without impacting expansion and antigen specificity. TCR sequencing data analysis using sequence alignments and ImmunoMap show a reduction in dominant CDR3 sequence motifs and an increase in unique CDR3 sequence motifs. Akt inhibition may therefore increase the diversity of the TCR
repertoire, which may have beneficial implications revolving around TCR affinity maturation, cross-reactivity, and low affinity interactions. The combination of Akt inhibition and aAPCs expansion presents an exciting opportunity to not only enhance
cell production for adoptive cell therapies, but also advance the development of more durable and robust immunotherapies
Essays in international macroeconomics and finance
No full textThis dissertation contains three individual chapters that analyze the use of policy instruments to manage capital flows and exchange rates. Chapter one discusses how capital controls can be used to alleviate the sectoral trade-off of monetary policy, providing a theoretical explanation as to why many emerging market economies have a managed floating exchange rate regime. Chapter two analyzes how monetary policy is optimally used in response to sudden stops in a model with occasionally binding constraints. Chapter three shows how expected future exchange rate volatility can be beneficial as it increases how much the exchange rate responds to foreign exchange intervention today
The Role of Frizzled4 and Norrin in Maintaining BBB Integrity in Response to CCL2-induced Neuroinflammation
Get PDFThe Wnt signaling pathway plays a central in regulating the development and maintenance of the blood-brain barrier (BBB) under physiological conditions, and its disruption in diseases. Gpr124, a co-receptor of the Wnt ligands, has no effects on BBB integrity when conditionally knocked out in the endothelial cells of normal adult mice, but exacerbates BBB disruption under disease status like stroke and glioblastomas. This makes us wonder whether some genes in the Wnt signaling pathway are specifically responsible for maintaining BBB integrity in response to inflammations. In this study, we constructed the adeno-associated virus to deliver CCL2 into the brain as the inflammatory stressor. By comparing the differences in BBB integrity between infected regions labeled with GFP and the GFP-negative control in the same section, we confirmed the injection of AAV-CCL2P2A successfully delivered CCL2 and caused local neuroinflammation, identified by multiple markers showing astrocytes and microglia activation, and increased recruitment and adhesion in circulating monocytes. However, even in Frizzled4 and Norrin homozygous knockout mice, whose Wnt signaling is greatly weakened, no significant BBB breakdown nor increase in serum leakage was observed, suggesting the neuroinflammation caused by CCL2 alone is not sufficient to exceed the threshold and disrupt the BBB
Redox Assay Method Development And Optimization For Vaccine Production Process Characterization
Get PDFThe use of recombinant proteins is a practice that has several applications, particularly for the production of biotechnological and pharmaceutical products. The quality of the proteins that are being produced can be significantly affected by the intracellular metabolic environments such as redox. The redox environment in the cell can be affected by the production of metabolic cofactors that act as oxidizing and reducing agents. The purpose of this experiment was therefore to optimize a method to characterize the redox environment throughout the fermentation process to gain an understanding of how the redox ratio changes in different metabolic states. The process being evaluated in this study involves the production of a recombinant protein by using the expression system of Saccharomyces cerevisiae, also known as Baker’s yeast. During the production process, the yeast undergoes metabolic shifts, and this newly developed method was used to evaluate how the NAD+/NADH ratio changes in different metabolic states. The characterization results showed evidence that a more oxidative metabolic state causes a decrease in the NAD+/NADH ratio and a more fermentative state results in an increase in this ratio, which reflects potential redox influences on protein tertiary maturation (e.g. disulfide bond formation)
Supporting the Achievement of Autistic Students: Exploring Teacher and Student Perspectives
Get PDFAutistic students tend to experience lower academic achievement than predicted by their own intellectual capacities (Ashburner et al., 2008; Estes et al., 2011) as well as relative to their neurotypical peers (McLeod et al., 2020). Many factors contribute to the achievement of autistic students, ranging from the societal level to interactions at the individual level. This dossier includes a literature review examining the factors influencing autistic students’ academic achievement, utilizing Bronfenbrenner’s (1994) ecological systems theory to examine the various levels of influence. To further examine microlevel factors within a specific private learning context, this dossier also includes an exploratory case study needs assessment to examine the attitudes and beliefs of teachers toward supporting autistic students. In a final component of the dossier, a portraiture study was conducted to explore the cognitive, social/emotional, physical, and communicative needs of three autistic individuals with an accompanying discussion of how educators might support these needs to improve outcomes for autistic students. Taken together, the components of this dossier contribute to our understanding of the challenges faced by autistic learners, the perspectives of their teachers, and ways in which educators can accommodate the unique needs of autistic students. This work also contributes to a small but growing body of neurodiverse-affirming research around autism
PSYCHOSOCIAL DETERMINANTS OF CARDIOVASCULAR HEALTH AMONG SYRIAN REFUGEES AT THE ZAATARI CAMP: THE SYRIANS IN CAMP HEART STUDY (SYNC-HEART)
No full textBackground: Cardiovascular health (CVH) and its determinants are poorly understood among refugees who live in temporary settlements. This research investigates the prevalence of cardiovascular disease (CVD) risk factors and examines the association of psychosocial determinants and CVH among Syrian refugees residing at the Zaatari camp in Jordan.
Methods: A convergent mixed-method design was used. Syrian refugees (N=218) were recruited using a convenience sample from the King Salman Humanitarian Aid and Relief Primary Health Center. A purposive sub-sample of 13 participants completed a focus group discussion. Descriptive, chi-square tests and linear regression analyses were used. The total CVH score was derived by averaging eight health metrics, resulting in a composite score from 0 to 100. Scores of 80+ indicate high CVH, 50-79 indicate moderate CVH, and <50 indicate low CVH. Thematic analysis was used for qualitative data, which was analyzed separately. Results were then triangulated to interpret the convergence and divergence of findings.
Results: Participants scored low in diet diversity (50%), hypertension (61.8%), and obesity (49%). Males scored higher than females in body mass index (24.7%) and physical activity (70.3%), while females had higher scores in sleep (55.4%) and nicotine exposure (84.1%) (P 50), the presence of vulnerable household members, no education, depression, and anxiety were associated with lower CVH. Technical education versus high school and below and employment were associated with higher CVH. Barriers to CVH include financial constraints, lack of structured daily activities, remote access to sports facilities, unhealthy living conditions, long waiting times for medical care, chronic stress, and traditional gender roles with limited employment opportunities. Facilitators included personal efforts to stay active, home gardening, community advocacy, interactions with healthcare workers, using the internet for health information, evolving gender roles, and intra-community support.
Conclusion: Humanitarian organizations and stakeholders must implement interventions to improve diet, manage hypertension and obesity, and provide psychosocial support. Addressing these factors is vital for preventing further deterioration and promoting the overall well-being of CVH
Social Media is Killing Our Children: Examining the Neurobiological Damage of Addiction in Adolescents due to Unregulated Social Media Use
Get PDFSocial media has become an integral part of modern life, with its prevalence
increasing rapidly among adolescents. However, this surge in social media use
coincides with a concerning rise in mental health crises among teenagers, including depression, self-harm, and suicidal ideation. Numerous studies have revealed a direct correlation between excessive social media use and poor mental health outcomes in this vulnerable population. The root cause of this issue lies in the neurobiology of adolescent brain development. During this critical period, the emotional and reward-seeking regions of the brain mature before the decision-making and impulse-control centers. Social media platforms exploit this vulnerability by employing addictive tactics, such as variable reward schedules and targeted advertising, to maximize user engagement and revenue.
To address this crisis, a multifaceted approach is necessary. Firstly, pediatricians should incorporate mandatory social media use screenings during annual check-ups, allowing for personalized interventions and recommendations. Secondly, comprehensive social media education programs should be implemented in schools, akin to existing sex education curricula. These programs would educate adolescents on the risks of excessive social media use, healthy coping strategies, and the manipulative tactics employed by tech companies.
Parental involvement is crucial in this endeavor. Parents should receive
educational resources to facilitate open communication with their children about
responsible social media use and role-model healthy digital habits. Additionally,
providing alternative recreational activities and after school programs can reduce adolescents’ reliance on social media. While federal regulations are necessary to curb the predatory practices of tech companies, immediate interventions through the medical, educational, and parental communities are imperative to protect adolescents from the neurological and psychological consequences of unregulated social media use. By addressing this issue proactively, we can mitigate the mental health crisis and ensure the well-being of future generations
Efficient In- and Near- Memory Computing System With Hardware and Software Co-Design
Get PDFOver the past decades, we have entered the big data era, where increasing amounts of data are generated daily, requiring processing and analysis by computing systems. However, modern computing systems suffer from power-hungry data transfer and processing due to the separate design of storage and processing units. This separation leads to a significant gap between supply and demand when processing large amounts of data, especially on resource-limited devices such as IoT (Internet of Things) devices. Motivated by this, this dissertation focuses on software and hardware co-design across different layers (device, circuit, architecture, algorithm) to develop energy-efficient and high-performance in-/near-memory computing systems, accelerating data-intensive applications such as deep learning and bioinformatics. This dissertation explores how designing memory and logic through innovations in devices, circuits, and architecture can overcome existing memory and power walls. Additionally, hardware-aware algorithm design further optimizes hardware utilization, significantly enhancing the computing efficiency of modern non-Von Neumann systems.
This dissertation begins by introducing circuit and algorithm optimizations to enhance the energy efficiency of RRAM-based in-memory computing architectures for on-device multi-task adaptation in neural networks. Here, the utilization of Resistive RAM (RRAM) takes the form of a 1 transistor 1 resistor (1T1R) crossbar array, enabling the integration of dot-product operations within the memory itself. This approach not only minimizes energy consumption during memory access but also boosts the throughput and energy efficiency of dot-product operations. The column-wise mask-based method has been proposed to avoid the high reprogramming energy consumption of RRAM for on-device multi-task learning. Through hardware-aware design innovation, the necessary masking operation to adapt to a new task can be seamlessly implemented in existing crossbar-based convolution engines with minimal hardware and memory overhead. More importantly, this approach significantly reduces power-hungry cell reprogramming while providing a trade-off between accuracy and energy consumption.
The next focus of this dissertation involves machine learning accelerator designs utilizing hybrid memory technologies for on-device continual learning. By integrating processing elements (PEs) made with different memory types (such as SRAM, RRAM, and MRAM) and distributing operations among these varied PEs, the design effectively mitigates the drawbacks associated with using a single-memory PE, such as high write energy, latency, and instability. Moreover, the hybrid design not only reduces area and power consumption but also maintains high accuracy, offering a scalable and versatile solution for on-device continual learning.
Finally, the dissertation presents designs for other data-intensive applications such as Min/Max searching and accelerating genome processing tasks, leveraging both volatile and non-volatile memories. For genome processing, an RRAM-based macro prototype is fabricated using the monolithic integration of HfO RRAM and 65-nm CMOS technology, achieving remarkable energy efficiency metrics of 2.07 TOPS/W (Tera-Operations Per Second per Watt) and 2.12G suffixes/Joule at 1.0V. This represents the most energy-efficient solution to date for genome processing tasks