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Rational Design of Selective Protein Therapeutics for Structurally and Functionally Complex Targets
No full textProtein biologics have transformed modern drug discovery and development by offering high selectivity and reduced off-target effects, prolonged serum half-lives, and the ability to modulate cellular processes. However, many clinically relevant targets remain intractable due to limited structural or mechanistic information, selectivity issues, or the need to modulate multiple pathways simultaneously. This work presents two distinct case studies in engaging challenging targets using rationally designed bispecific protein therapeutics and Fc fusion proteins. In Chapter 1, I describe the successful design and characterization of the first non-EPO-based, bispecific agonists for the tissue-protective receptor, EPO-R/CD131. We generated a structural model of the EPO-R/CD131 complex using AlphaFold and available structures of EPO-R and CD131 individually bound to single chain variable fragments (scFvs). Using this model, we designed several tandem scFvs and a bispecific antibody that selectively activated EPO-R/CD131 and not the related receptor, EPO-R/EPO-R. These proteins serve as a foundation for future studies of EPO-R/CD131 biology or for the development of safer, more selective therapeutic candidates for cell-protection applications, such as neurodegenerative diseases. In Chapter 2, I detail the design and early stage testing of several mono- and bi-specific Fc fusion proteins for the treatment of dysfunctional and inflammatory pain. Using similar design principles, I generated Fc fusions to peptides that inhibit the voltage-gated sodium channels Nav1.7 and Nav1.8 and Fc fusions to neprilysin, an enzyme that degrades the neuroinflammatory peptide, substance P. Altogether, this work provides novel approaches to the modulation of these challenging targets and insights about future design considerations and possible solutions to further the development of protein therapeutics for cell-protection and chronic pain.Systems Biolog
Driving Emissions Abroad? The Relationship Between Green Vehicles and Used Vehicle Exports to Developing Nations
No full textDeveloped countries have begun pursuing green industrial policy as a strategic
means to accelerate technological change and economic transformation towards more
sustainable economies. These shifts raise important questions concerning how green
industrial policies might interact with greenhouse gas flows through international trade.
Policies aimed at reducing transportation emissions are particularly important as the
sector is lagging others in decarbonization. As populations rise and economies develop
within developing countries, vehicular transportation emissions are projected to escalate
without policy interventions.
My research aimed to understand if used vehicle exports from developed
countries are part of a system preventing decarbonization in developing countries by
shifting emissions abroad. Do green industrial policies in developed nations drive the
export of used conventionally fueled vehicles to developing countries? How might this
apply to a region experiencing rapid urbanization and population growth, considering
sub-Saharan Africa (SSA) is poised for rising transportation emissions that could
undermine global climate goals (Booysen et al., 2021; Rajé et al., 2018)?
Through quantitative analysis of two decades of customs data, my research
evaluated connections between major exporters' green vehicle policies and used vehicle
exports. Using a cross-national panel regression analysis, the effects of used vehicle trade
on CO2 fuel emissions were analyzed. This analysis explored associations between major
transport emissions sources in core countries transitioning to green vehicle fleets and
periphery nations continuing conventionally fueled imports.
This research draws on Eco-dependency theory literature and hypothesized and
found that: 1) The relationship between used vehicle trade flows and associated CO2
emissions demonstrates stronger alignment with Eco-dependency theory than Neoliberal
theoretical frameworks in the Global and Latin America regressions; and 2) the regions
of SSA, Latin America, and Southeast Asia, predominantly comprised of countries with
low and medium HDI, support Eco-dependency theory through positive correlation
between used passenger vehicle exports and CO2 fuel emissions. However, only the
region of Latin America showed support for Eco-dependency theory.
The analysis provided some empirical support for green industrial policy serving
as a potential new mechanism by which core countries maintain technological
dependencies with peripheries in Latin America. However, this relationship did not hold
in the cases of SSA and Southeast Asia. This casts doubt upon the relevance of Ecodependency theory and calls for further research on understanding how green industrial
policies interact with international development processes and prevent periphery
countries from decarbonizing. The link was not found in SSA and Southeast Asia,
challenging aspects of Eco-dependency theory by suggesting green development does not
inherently affect the environment in the way the theory proposes outside of Latin
America.
Policy makers should note that these unintended global emission flows through
international trade risk eroding emissions reductions achieved domestically in developing
countries, and hamper net zero efforts globallyExtension Studie
The effect of Deep Brain Stimulation on Sleep-Related Symptoms
No full textDeep brain stimulation (DBS) is an established neuromodulatory intervention for movement disorders, but its impact on sleep in Parkinson’s disease (PD) remains unclear. To address this gap, we conducted a single, integrated investigation combining a systematic review and meta-analysis of published studies with a secondary data analysis of the Parkinson’s Progression Markers Initiative (PPMI).
First, we systematically reviewed all peer-reviewed reports of sleep outcomes following DBS across various targets and clinical populations. Random-effects meta-analysis revealed small, inconsistent changes in subjective sleep measures, with high between-study heterogeneity (I² > 70%) and mixed results in PD cohorts, indicating a lack of consensus on the direction and magnitude of DBS effects on sleep.
Next, we analyzed cross-sectional data from 970 PD participants in PPMI—102 with chronic DBS (≥ 6 months post-implant) and 868 without stimulation. Subjective sleep was assessed via the Epworth Sleepiness Scale (ESS) and three MDS-UPDRS Part I items (sleep problems, daytime somnolence, and fatigue). We applied inverse probability-weighted linear and logistic regression models, adjusting for age at onset, Hoehn & Yahr stage, MDS-UPDRS III motor score, levodopa equivalent daily dose, psychiatric comorbidity, pain, urinary incontinence, and sex. Sensitivity analyses—including propensity score matching and ridge regression—confirmed the robustness of our findings.
Across both components, DBS was associated with modestly higher sleepiness (mean ESS increase of 1.06 points, 95% CI 0.08–2.35), greater sleep problem scores (0.53; 0.19–0.78), and increased fatigue (0.33; 0.12–0.62), with a non-significant trend for daytime somnolence (0.13; –0.06–0.43). Notably, urinary incontinence modified the effect, suggesting autonomic dysfunction as an important effect modifier.
These integrated results indicate that DBS may subtly exacerbate certain sleep-related symptoms in PD, with interindividual factors such as autonomic impairment influencing outcomes. Future longitudinal research employing objective measures (polysomnography, actigraphy) is needed to clarify causal pathways and optimize stimulation protocols to minimize adverse sleep effects.Medical Scienc
Adaptive Innovation in the Octopus Ribosome
No full textThe ribosome is the universal machine for protein synthesis across all life. All ribosomes consist of a conserved core of ribosomal proteins and RNAs (rRNAs) that mediate accurate decoding of mRNAs to synthesize functional proteins. In agreement, biochemical or genetic disruptions to translation fidelity cause cellular death and severe cognitive or aging related defects.
In this thesis, I describe a completely serendipitous discovery, where we find that the 28S rRNA of the octopus contains a novel “break” in the highly conserved catalytic ribosomal RNA (rRNA) core of the ribosome. This rRNA break is unique to octopus species and not found among all analyzed animals, including closely related squid or cuttlefish, or distant mollusks, invertebrates, or vertebrates. By obtaining a cryo-EM structure of the O. bimaculoides ribosome, we find that the octopus rRNA break is found in the E-site near the site of deacylated tRNA binding. We then postulate that octopus rRNA break enhances translation fidelity by allosterically decreasing A-site tRNA binding affinity during decoding.
Later studies focused on how evolution of this break ultimately supports novel traits which emerged in octopuses. We find that the increased accuracy leads to less protein misfolding and aggregation and a reduced basal unfolded protein response in vivo in octopus compared to other cephalopods or mollusks. This advantage for proteostasis supports the expanded nervous systems of the animal. Notably, we also observe that the octopus ribosome innovation contributes to organismal plasticity. Octopus and squid exhibit unusually high levels of ADAR editing, with extensive adenosine-to-inosine recoding in the coding regions of transcripts. Editing increases in response to the environment, and has been hypothesized to contribute to protein recoding. We find that the octopus rRNA break controls how inosines are decoded during mRNA translation. This allows octopus to have higher organismal plasticity and regulation of the proteome than squid upon exposure to changes to environmental conditions such as cold temperature.
In summary, our findings reveal how evolution of the ribosome allows for organismal-specific adaptations to protein synthesis. While much of biology has demonstrated how the genetic code drives evolution, it is less understood how evolution can be driven by adaptations in other components of the central dogma. Here, we discover how the octopus uses modifications in the core protein synthesis machinery to drive biological novelty, a strategy which could support the evolution of unique organismal traits across life.Medical Science
Holding Ground in Fields Corner: Queer Businesses' Role in Resisting Displacement
No full textExtensive literature explores queer residential neighborhoods and gentrification, yet urban planning research offers little analysis of queer businesses’ role in stabilizing neighborhood identity and mitigating displacement pressures. This study examines how queer businesses in Fields Corner, a neighborhood in Dorchester, Boston, counteract gentrification-driven displacement. Using longitudinal analyses of shifting land and property values, along with archival documents and semi-structured interviews with queer business owners, the study investigates their sense of belonging, strategies for resistance or adaptation, and contributions to the area’s physical, social, cultural, and economic fabric. Findings offer insights into the intersections of queer identity, commerce, and urban change, culminating in planning strategies to strengthen queer businesses’ presence and curb displacement pressures in the face of gentrification.Department of Urban Planning and Desig
Causal Inference Beyond Standard Assumptions: Learning Policies and Treatment Effects in Complex Environments
No full textCausal inference aims to uncover cause-and-effect relationships from data and has seen widespread application and rapid methodological development across scientific disciplines. While recent methodological advances --- driven by increasingly rich and diverse data ---- has expanded the scope of causal analysis, practical applications often involve complexities that violate the core assumptions underlying standard approaches. These include lack of overlap between treatment and control groups, interference among units, and distributional shifts across populations. Addressing these challenges is crucial for ensuring the validity and reliability of causal conclusions in real-world settings.
This dissertation develops novel methodological frameworks for robust, efficient, and interpretable causal inference in complex environments. Each chapter addresses a unique violation of standard assumptions, with an overall focus on two key areas: policy learning and heterogeneous treatment effect estimation.
Chapter 1 considers safe policy learning in regression discontinuity designs, where treatment assignment is deterministic and requires robust extrapolation beyond observed data. Chapter 2 focuses on the evaluation and learning of individualized treatment rules under clustered network interference, where spillover effects exist and may vary across units within a cluster. Chapter 3 investigates the generalization of heterogeneous treatment effects with multisite data, where distributional shifts across populations challenge the validity of pooled or site-specific estimators.Statistic
Engaging the Next Generation: Connecting Students with Collective Impact Organizations
No full textOne common challenge that organizations engaged in collective impact (Kania & Kramer, 2011) face is a growing need to reach broader audiences and inspire new leaders to advance this work. This capstone explores strategies to expand student engagement with organizations practicing collective impact, through the lens of The EdRedesign Lab (EdRedesign) at the Harvard Graduate School of Education. I leveraged the organization’s senior fellowship program, which supports best-in-class leaders, to introduce students to EdRedesign and the collective impact field.
A pivotal moment came when survey data revealed that this emergent field’s vocabulary may create a barrier to entry for students and other professionals. Findings showed widespread unfamiliarity with key terms such as collective impact, cross-sector work, backbone organization, among others. To address this communication barrier, I launched an informal awareness campaign using storytelling to explain collective impact work, demystifying the vocabulary and increasing accessibility.
To generate student engagement, I leveraged my connections at Harvard through my roles as a doctoral student, first-year experience residential proctor, and fellow. These efforts contributed to the creation and launch of a new pilot program, the Cradle-to-Career Summer Fellowship, aimed at providing undergraduate students with summer experiential learning at a collective impact organization. The fellowship may serve as a model for organizations across the country to adopt in their efforts to engage undergraduate students.
I make concrete recommendations to address both technical and adaptive challenges (Heifetz, 1994) that organizations may encounter when implementing similar practices. I also identify implications for my leadership and the sector at large.
Through this engagement project, I experienced managing from the middle, aligning my workstyle with the organization’s culture, and deepening my understanding of the collective impact ecosystem. My experience as a resident allowed me to learn from a strategic-minded team, reflect on my leadership style, and practice my immunity-to-change goals (Kegan & Lahey, 2009). On a broader level, this work reinforced the importance of intentionally developing a culture of mentorship to scale leadership and ultimately increase impact.Educatio
Essays on the Labor Market
No full textThis dissertation studies how firms set wages. The first essay, coauthored with Corey Allan, studies the restrictions that governments place on migrants' job options. We find that firms account for migrants' weaker job options when setting wages. However firms don't specifically discriminate against migrants, but rather pay lower wages to all their workers. As such, restrictions on migrants' job options also reduce the wages of many non-migrants. The second chapter, coauthored with Jesse Silbert, is theoretical. We study a labor market in which firms do not price discriminate among their workers. We characterize when and how such a labor market will allocate workers inefficiently, and we show who benefits from these inefficiencies. The third chapter, also coauthored with Jesse Silbert, studies wage inequality within occupations. Every occupation in our data exhibits substantial wage inequality. By studying how firm profits are affected by the separation of individual workers, we show that much of this inequality cannot be explained by productivity differences between workers.Business Economic
Bioaerosol Sampling for Viral Detection in Public Spaces: Application of Bioaerosol Sampling Devices in Long-Term Monitoring of Airborne Pathogens in a Railway Station and a Subway Station
No full textThis thesis investigates the effectiveness of the BC500 impact-based bioaerosol sampling device for detecting airborne viruses in both laboratory and real-world environments. By optimizing sampling and post-processing conditions, the BC500 demonstrated an impressive detection limit as low as 0.35 copy/L for airborne viruses during laboratory evaluation. In field applications at high-traffic public spaces, such as Beijing Railway Station and Xidan Subway Station, the device successfully detected SARS-CoV-2, Influenza A, and Influenza B. Specifically, SARS-CoV-2 was found in 52.9% of samples at Beijing Railway Station and 44.4% at Xidan Subway Station. Influenza A was detected in 47.1% of samples from the railway station and 18.5% from the subway station, while Influenza B appeared in 23.5% and 7.4% of the samples respectively. These findings underscore the widespread presence of airborne viruses in crowded environments, demonstrating the value of BC500, a non-intrusive and highly sensitive tool for public health surveillance.
The significant detection rates of multiple pathogens in this study highlight the need for enhanced public health measures, including regular bioaerosol monitoring and improved ventilation, to mitigate airborne transmission in densely populated areas. Furthermore, integrating bioaerosol sampling into existing surveillance frameworks could enable early outbreak detection, supporting timely responses to emerging health threats. This research contributes to the standardization of bioaerosol sampling practices and underscores its vital role in strengthening public health monitoring and response efforts
Harnessing UniAnalytics: Exploring the Role of Engagement and Collaboration in Student Success in Jupyter Notebook Environments
No full textWhether and how students engage, and the ways in which they collaborate during learning activities, are critical determinants of academic success. These factors become even more significant in computational learning environments where digital tools mediate interactions. In this thesis, we examine the relationship between student engagement, collaboration, and academic success in a Jupyter Notebook-based learning environment. We utilize regression and multilevel models to identify key engagement and collaboration behaviors observing their impact on three key measures of student success: performance on assignments, on the final exam, and overall course grade. From our analyses, we find that certain engagement metrics such as execution frequency are strong predictors of success. We also found that other metrics such as higher error rates and prolonged idle time are negatively associated with all 3 of our measures of success. Our chosen collaboration metrics do not show significant correlations with student success, raising questions about how collaborative learning is assessed in digital environments. This thesis hopes to contribute to the growing field of learning analytics by providing empirical evidence on how digital engagement behaviors impact student success. The ultimate goal of this work is to offer insights that can enhance teaching strategies and educational outcomes in computational classrooms that rely on digital tool such as Jupyter Notebook.Applied Mathematic