VictorJuiz/thesis huggingface dataset:
Membrane proximal F-actin as a master regulator of cell polarity, signaling dynamics, and protrusion during migration

Balanced regulation of cell migration is critical for all stages of the human life cycle. Furthermore, aberrant or inhibited motility can cause dire consequences ranging from embryonic lethality to metastasis. Despite the diversity and plasticity of cell migration, almost all forms of motility depend on dynamic regulation of F-actin cytoskeleton. While there has been a lot of effort to understand the underlying signaling of prominent F-actin pools such as lamellipodia, filopodia, and stress fibers, much less is known about the role of membrane proximal actin (MPA) and membrane adhesion has on cell migration and polarization. We currently lack the tools to resolve MPA from other F-actin pools in the cell with high spatio temporal resolution. In this thesis we first develop a fluorescent biosensor to measure the density of membrane proximal F-actin, here termed MPAct. MPAct can be used to investigate the absolute differences between conditions using FRAP and lateral diffusion measurements, or as ratiometric reporters of relative MPA distribution within the same cell. Using the MPAct sensor we then made the unexpected observation that MPA was higher in the rear of cells migrating in 1D, 2D, and 3D, unlike global F-actin concentration under these same conditions. We further demonstrated this observed gradient was due to the underlying F-actin architecture and that MPA gradients strengthened existing polarity by biasing nascent protrusions to areas with low MPA. Finally, we found that increased Cofilin-mediated F-actin turnover at the front contributed to the observed gradients. These results provide a framework to understand directional persistence from a biomechanical point of view: cells will continue protruding from the existing cell front thereby creating directional "inertia." Based on the results from this study we further investigated if MPA gradients could create other types of signaling and biomechanical polarity during migrations. We found that EGFR dynamics, ERM localization, Focal adhesion turnover, and Cdc42 activity showed distinct behavior based on local MPA. These follow-up studies demonstrate how MPAct and MPA gradients can be used to clarify signaling dynamics at the plasma membrane. This work provides a new tool, the MPAct sensor, for probing the role of membrane adhesion in a variety of contexts. We further uncovered a novel role for MPA in unifying migration polarity signaling and a global and local level

Keywords: Chemical and Systems Biology.
Advisor: Meyer Tobias
Dunn Alexander Robert
Ferrell James Ellsworth
O'Brien Lucy Erin
Memory-efficient optimization over positive semidefinite matrices

We present an extension of the conditional gradient method to problems whose feasible sets are convex cones which we call conic descent. We provide a convergence analysis for the method and for variants with non-convex objectives, and we extend the analysis to practical cases with effective line search strategies. For the specific case of the positive semidefinite cone, we present a memory-efficient version based on randomized matrix sketches and advocate a heuristic greedy step that greatly improves its practical performance. Numerical results on phase retrieval problems indicate that our method delivers results of a specified accuracy in approximately half as many iterations as required by the conditional gradient method. Building off this foundation, we next use the augmented Lagrangian technique to enable the incorporation of equality constraints. This immediately leads to applying the memory-efficient version of conic descent over the positive semidefinite cone to the solution of large scale semidefinite programs. Numerical results on solving graph maximum cut problems demonstrate its usefulness and advantages over traditional Burer-Monteiro approaches. In a sensor network localization (SNL) problem, we attempt to determine the two- or three-dimensional layout of a network of sensors from some of their pairwise distances. We present an efficient projected gradient method to approximately solve the SNL problem if a good initial guess of the sensor locations is available. When the sensors are not static, our method is an efficient way to update the estimate of their positions and so provides a way of tracking the sensors as they move. Along the way, we present an analysis of the projected gradient method for arbitrary feasible sets onto which we can project exactly, which is of independent interest. Numerical results demonstrate the practical efficacy and robustness of our method

Keywords: Electrical Engineering.
Advisor: Duchi John
Lall Sanjay 
Ye Yinyu
Methodologies for uncovering hidden information at molecular and cellular scales

The reductionism of molecular biology has been incredibly fruitful and instrumental in scientific advancement. The advent of high-throughput technologies and improved measurement techniques has allowed systems biology and quantitative biology to further revolutionize biology in the last half-century. A quantitative, systems biology approach allows scientists to uncover unknown unknowns by performing large-scale experiments in an unbiased manner. For example, DNA/protein sequencing, growth curve measurements, and microscopy are information rich, and the latter two are highly tunable to interrogate the relationship between environment and physiology. However, to fully exploit these advances, it is important to optimize these precise, quantitative measurements and understand how to interpret the data. Furthermore, it has become increasing important and feasible to develop algorithms to exploit the large amount of data that is being generated. This dissertation describes two such methodological advances that involve new methods for disentangling signal from noise. Chapter 2 describes a novel framework for analyzing protein coevolution to gain functional understanding of a protein. Chapter 3 describes refined methods for optimizing the measurement of bacterial growth parameters by carefully considering cellular physiology and environmental conditions. Chapter 4 provides concluding thoughts on future directions for using these methods. Taken together, my PhD work showcases the importance of developing methods to link molecular and structural biology with the ongoing systems and quantitative biology revolution

Keywords: Chemical and Systems Biology.
Advisor: Huang Kerwyn Casey
Jarosz Daniel
Wang Bo (Researcher in bioengineering)
Altman Russ
A methodology to align the logistical requirements of prefabricated wall panels

Stacking plans of prefabricated wall panels provide the logistics information that connects the stacking, transportation, and installation processes, and thus need to be generated with careful consideration of logistical requirements. Any conflicts on these plans due to the different foci of each process can cause costly logistical problems, such as panels requiring reshuffling work on site or unstable stacks that require additional bracing work. Therefore, these plans are important deliverables from the planning process that are directly associated with the cost-effectiveness of the wall panels. This dissertation formalizes two metrics to assess stacking plans: reshuffling effort to measure the efficiency of installation and panel/stack stability to measure the stability of panel stacks during transportation enabled by a stacking plan. Applying these metrics to two projects showed that current stack planning methods do not generate stable stacks that can be installed efficiently. In fact, for stacking planners, carefully considering the logistical requirements when generating stacking plans is often laborious and on an ad hoc basis because they do not have a formal methodology to do so. This dissertation presents a methodology that enables stacking planners to generate stacking plans for prefabricated wall panels rapidly and systematically considering the requirements of reshuffling effort, panel stability, and the number of required trailers. Panel Stacking Plan Generator (PSPG), a software prototype, was developed to automate the steps of the methodology. Compared to conventional manual practice, the three case studies with the prototype showed that the methodology allows stacking planners to generate stacking plans with no reshuffling effort and higher panel stability while not increasing the number of required trailers, which led to logistics cost savings. Results were obtained approximately 6 times faster than the conventional manual method including data preparation and computation time. Future research should focus on considering additional factors that affect the logistics of the wall panels (e.g., on-site laydown space availability), including installation plans to optimize the logistics and installation processes holistically, and studying additional objectives and criteria (e.g., sustainability) to understand the advantages and challenges of the wall panels more fully

Advisor: Fischer Martin
Ashlagi Itai 
Kim Jung In
Methods for measuring selection on coding regulatory elements and gene expression divergence between human and chimpanzee brain development in vitro

In this dissertation, I explore the impact of gene expression changes on human evolution in two distinct contexts. In chapter 2, I describe a method of quantifying the relative contributions of coding and non-coding changes in driving selection at three regulatory loci in the human genome. In chapter 3, I describe a novel system for quantifying cis- regulatory gene expression divergence between the human and chimpanzee genomes during fetal brain development in vitro. Overall, this body of work highlights the importance of precise methodology for understanding the role of gene regulation in human evolution

Keywords: Genetics.
Advisor: Fraser Hunter B.
Baker Julie (Professor of genetics)
Montgomery Stephen
Pritchard Jonathan (Jonathan K.)
Microfluidic devices for studies of single cell wound repair, regeneration, and other biological phenomena

Microfluidics has enabled a wide range of biological studies. The objective of my thesis dissertation is to apply microfluidics for studies of wound repair and regeneration, as well as to use droplet microfluidics to study stochastic biological phenomena. My thesis covers three parts: In Chapters 2 and 3, I develop the microfluidic guillotine for high-throughput studies of wound repair in Stentor coeruleus. We were able to bisect over 150 cells in 3 minutes, which is 200 times faster than current methods, while achieving approximately 95% cell survival. I also develop quantitative and qualitative assays to assess wound repair. With these tools, we measured the wound repair time in Stentor and discovered the occurrence of three mechanical modes of wound repair, as well as Ca2+ activated wound repair processes. In Chapters 4 and 5, I further develop the microfluidic guillotine to bisect multicellular structures and show that organoids bisected by the guillotine can also regenerate. Furthermore, I optimize cutting performance by developing a method using the Nanoscribe, a sub-micron resolution 3D printer, to fabricate the blade at an angle. My work on the microfluidic guillotine in Chapters 2 -- 5 has been patented and we are in the process of commercializing the technology. Finally, in Chapters 6 and 7, I used the uniquely high-throughput, low volume nature of droplet microfluidics to study stochastic biological phenomena. I developed theory to understand the impact of drop-to-drop variance in studies of single cell phenotypic heterogeneity. Using droplet microfluidics also lead to the discovery of hundreds of novel RNAs that can be replicated by T7 RNAP, whereas before only five were known. This lead to my collaborator discovering the origin and replication mechanism of these replicating RNAs. We have submitted a provisional patent on this technology

Keywords: Mechanical Engineering.
Advisor: Tang Sindy (Sindy K.Y.) 
Chaudhuri Ovijit 
Marshall Wallace F.
Microfluidics meet ionizing radiation : drop-based flow radiocytometry and liquid sheet jet-based for X-ray spectroscopy

This thesis is focused on the development of two microfluidic platforms for multiphase sample delivery in assays involving ionizing radiation. In the first part of the work, a water-in-oil droplet microfluidic platform was designed and built for single-cell radiopharmaceutical studies. Radiotracers are widely used to track molecular processes with high sensitivity and specificity. However, most radiotracer detection methods have spatial resolution inadequate for single-cell analysis and cannot probe cellular heterogeneity, one of the most important challenges in cancer therapeutics. Here we introduce a robust, high-throughput single-cell radiometry based on radiofluorogenesis and droplet optofluidics. As a proof-of-concept application, we quantified [18F]fluorodeoxyglucose radiotracer uptake in single human breast cancer cells to assess glucose metabolism at the single-cell level. The second multiphase sample delivery system is a microfluidic nozzle designed to create liquid jet in air for X-ray spectroscopy analysis. We created stable free-surface liquid sheet jets with a width and length on the order of millimeters and sheet thickness on the order of microns and even sub-micron. These large aspect ratios provide a large target for the X-ray beam while minimizing background signal associated with line-of-sight integration of the detection. We conducted an experimental and numerical study to understand how fluid properties, pressure, momentum fluxes, surface tension, and nozzle geometry all interact to determine flow structures. The work developed scaling theories that predict sheet jet thickness, width, and length strictly from nozzle geometry, flow rate, and thermophysical fluid parameters. Interestingly, given this scaling analysis, no computer-aided simulations are needed for accurate flow structure prediction. Together the device design and theories provide a clear path to the rapid and efficient design of liquid sheet jets

Keywords: Mechanical Engineering.
Advisor: Pratx Guillem
Santiago Juan G. 
Tang Sindy (Sindy K.Y.)
The microfoundations of identity politics in Pakistan's megacity

How do we make multi-ethnic, conflict-prone cities "work"? Urbanization offers an enormous opportunity to revive stagnating economics and lift millions out of poverty. This potential, however, can only be realized if proper attention is paid to the question of how best to manage such growth. If the growth of cities depends necessarily on in-migration of new populations, the causes and consequences of such migration deserve considered attention. One consequence of rapid urbanization and demographic change is the development of ethnic political parties that promise to advocate for the rights of particular identity groups. What accounts for the success or failure of ethnic parties in mobilizing urban populations in diverse cities? And what are the governance consequences of this form of politics? The three papers that constitute this dissertation project aim to answer these questions by exploring in-depth the megacity of Karachi, Pakistan. A central concept linking all three papers is that of descriptive ethnic representation. Chapter 1 shows that the demand for descriptive representation can systematically differ between urban ethnic groups based on their reason for migration to the city. Chapter 2 shows that once ethnic parties successfully leverage a demand for descriptive representation, they are better able to avoid accountability for poor governance on material dimensions -- such as on the provision of basic public goods. Chapter 3 shows that the relationship between coethnicity and citizen expectations of police bias is moderated by the level of perceived descriptive representation in the police forces. Altogether, these papers illustrate the abundant and as yet underexplored within-urban variation in the workings of ethnic politics, thereby enriching our pool of knowledge on how ethnicity structures the political landscape of cities in the global south

Keywords: Political Science.
Advisor: Fearon James D.
Laitin David D.
Magaloni Beatriz
Scheve Kenneth F.
Weinstein Jeremy M.
microRNA controls over cortical projection neuron development

Corticospinal motor neurons (CSMN), residing in layer V of the neocortex, are the brain component of the multi-neuron circuitry controlling voluntary movement in mammals. CSMN are closely related to deep layer callosal projection neurons (CPN) and have the same embryonic birthdate during development, however very different projection targets and functions. While several transcription factors important for specifying both CSMN and CPN have been identified, much of the molecular regulation of this process remains incompletely understood. MicroRNAs are post-transcriptional gene regulators that are ideally suited to control developmental programs, as multiple microRNAs can converge on multiple targets to repress translation. While microRNAs have been shown to play a role in the earliest stages of cortical development, their role in cortical projection neuron development and diversity is unknown. A differential microRNA expression analysis of CSMN vs. CPN revealed 19 microRNAs that are more highly expressed by CSMN vs. CPN at post-natal day 1 (P1) mouse. miR-409-3p, is enriched in CSMN compared to CPN at P1. Predicted gene targets of miR-409-3p include LMO4, a transcriptional regulator important for specifying CPN and associative projection neuron development. Gain- and loss-of function studies demonstrate that miR-409-3p can control cortical projection neuron fate in both embryonic cortical cultures, in part through repression of the CPN-expressed transcriptional regulator LMO4. In utero electroporation experiments during development demonstrate alteration in axon projection trajectory and projection neuron cell fate. Characterizing cluster-encoded microRNA controls on CSMN development may inform stem cell-based regenerative therapies for paralysis in clinically relevant conditions, including spinal cord injury

Advisor: Palmer Theo
Tharin Suzanne
Buckmaster Paul S.
Sarnow P. (Peter)
Mindality

For individuals with moderate to severe depression, it can be difficult to manage decisions in everyday life. Research shows that depression reduces quality of life through cognitive distortions––biased perspectives that are considered irrational about oneself and the external world, creating damaging thought patterns and false beliefs. Such disparaging distortions make it especially important to be connected to supportive friends and family. Mindality is a platform that helps learners generate explanations of their day-to-day struggles. The goal is to enhance an individual’s capacity to effectively understand their own needs and communicate them to loved ones or licensed professionals in order to get support––and these self-generated explanations can leverage a variety of media, such as audio, text, and visual. The multimodal availability of expressing common symptoms found in depression and suicidal ideation proposes that this practice can potentially support mental health understanding, communication, and literacy for those impacted by mental health, both directly and indirectly. This report provides the reader with some research perspectives on major depressive disorder and its relationship to the effectiveness that multimedia can leverage for expression, communication, and support.

Keywords: Learning Design and Technology
LDT
Graduate School of Education
GSE
Thesis
Minds, groups, and populations : harnessing the latent structure of social information

Choices are woven into the fabric of social life: We buy things that have received glowing reviews, watch shows recommended by our friends, and assess a potential date based on their taste in music. Observing others' choices provides valuable insights into both the world and into the person doing the choosing. How do observers extract so much information from everyday, seemingly arbitrary choices? In this dissertation, I propose that observers make rich inferences from others' choices by harnessing structured representations of the physical world, of the contents of others' minds (e.g., their knowledge and preferences), and of the social world (e.g., of relationships and similarities between individuals). Chapters 2--3 examine how adults harness representations of other minds to recover information about the value of unexplored choice options. These studies find that adults do not simply imitate or ignore others' choices, but rather actively infer the latent mental states—such as beliefs and strategy—that gave rise to them. Chapters 4--5 examine how children and adults harness representations of the social world to learn about new individuals. This work finds that preschool-aged children and adults use minimal statistical information about how choices are distributed across individuals to judge their potential compatibility with new individuals (Chapter 4) and make inductive inferences about them (Chapter 5)

Keywords: Psychology.
Advisor: Gweon Hyowon
Goodman Noah (Noah D.) 
Zaki Jamil
Misrepresented : understanding the gap between US public opinion and policy on climate change

The US federal government and most state governments have failed to pass legislation aimed at achieving large-scale greenhouse gas (GHG) emissions reductions despite nationwide popular support for those reductions. This dissertation examines three potential causes of this democratic deficit with respect to climate policy: (1) each policymaker is representing their own constituency's preference; (2) policymakers are not aware of their constituents' preferences; (3) constituents need to send stronger signals about their preferences to policymakers. I address cause 1 by predicting state-level climate change opinion to determine whether support for reducing GHG emissions is clustered in a few states or is present in a majority of states. My results indicate that states overwhelmingly support reducing GHG emissions. I conduct survey experiments on state and local policymakers to study cause two. I find that policymakers consistently underestimate how popular climate policy is among their constituents. I also find that policymakers support slightly stronger emissions reductions policies when they learn that the policies are in fact popular. However, policymakers might not respond to public opinion polls alone, because they might believe that constituents' preferences for climate policy are very weak. Thus, to address cause three, I study the factors that motivate environmental political activism. Through a series of survey experiments, I show that Americans who are in favor of climate policy are most likely to also engage in political activism when they learn that millions of other Americans are doing the same. Overall, my research suggests that climate policy is more popular than we all, including policymakers, tend to believe. However, informing the public and policymakers about its true level of popularity does not seem to be sufficient to motivate the necessary scale of policy action on climate change

Advisor: Krosnick Jon A.
Willer Robert Bartley
Broockman David E.
Malhotra Neil Ankur