VictorJuiz/thesis huggingface dataset:
NLGN3 interacts with CSPG4 through regulated intramembrane proteolysis, driving glioma growth and maintaining OPC stemness

Pediatric high-grade glioma (pHGG) is a category of lethal brain cancers, many of which are inoperable and have no specific approved treatments. Oligodendrocyte precursor cells (OPCs), the putative cell of origin for these tumors, undergo a mitogenic response to active neurons. Previous work has identified that neuronal activity increases pHGG proliferation and growth in vivo through the activity-dependent release of soluble neuroligin-3 (sNLGN3). Furthermore, previous unbiased proximity labeling and mass spectrometry has identified the proteoglycan and OPC marker chondroitin sulfate proteoglycan 4 (CSPG4) as a candidate binding partner. Here, CSPG4 as the receptor for NLGN3 on glioma cells is validated and a role for this signaling axis in healthy OPC physiology and differentiation is established. Membrane pulldown assays combined with mass spectrometry further establish CSPG4 as the NLGN3 binding partner. An in vitro protein shedding assay shows that NLGN3 interacts with CSPG4 and the complex undergoes two rounds of cleavage by the proteases ADAM10 and gamma secretase through a mechanism known as regulated intramembrane proteolysis. The resulting intracellular cascade is responsible for the mitogenic effects of NLGN3. Additionally, NLGN3 maintains OPC stemness when growth factors are withdrawn, and suppressing the NLGN3-CSPG4 axis with gamma secretase inhibition results in increased differentiation. These results identify new druggable targets in a pathway important to pHGG growth and shed light on the understudied mechanism of glial differentiation.

Keywords:  Department of Biology
Biology
Cancer
Neurosciences
Neuroglia
Oligodendroglia
Gliomas
Text
Thesis
Advisor: Monje Michelle
Luo Liqun
Nonlocal games, distributed storage, and quantum error correction : excursions in fault-tolerant computation

In this thesis, we consider three computing systems afflicted by noise, which causes their behavior to deviate unpredictably from idealized theoretical models. In each system, we model the effects of noise, and characterize the extent to which fault-tolerance techniques allow the computation to proceed efficiently despite the presence of the noise. First, we consider two parties who wish to implement a computation with little communication by making use of nonlocal correlations, a task called nonlocal computation. Second, we investigate a data center computing scenario where data are stored across many nodes in an error-correcting code, and we wish to evaluate functions of this data despite unpredictable node failures. Third, we consider building a fault-tolerant quantum computer using near-term hardware, in which qubits are afflicted by a high rate of noise, and two-qubit gates are constrained to act on pairs of nearby qubits in a planar layout. A common theme in these three settings is that, in each case, the data are encoded in some code. In the nonlocal computation setup, this encoding takes the form of linear shares or distributed bits, and arises as a result of the distributed nature of the computation. In the data center computing setting, the encoding is a Reed-Solomon or other linear error-correcting code, whose purpose is to protect against catastrophic data loss due to worst-case node failures. In the fault-tolerant quantum computer, the data are encoded in quantum error-correcting codes, which protect the encoded quantum information from the unpredictable noise of the underlying hardware. We measure our fault-tolerance techniques by various notions of efficiency. In the first two systems, we aim to minimize the communication cost. In the third system, we aim to minimize the space and time overhead cost. We show both positive and negative results that better characterize the trade-off between noise level and efficiency in these three systems

Keywords: Physics.
Advisor: Hayden Patrick (Patrick M.)
Wootters Mary
Rubinstein Aviad
Tan Li-Yang
Nonparametric perspectives on empirical Bayes

In an empirical Bayes analysis, we use data from repeated sampling to imitate inferences made by an oracle Bayesian with extensive knowledge of the data-generating distribution. Existing results provide a comprehensive characterization of when and why empirical Bayes point estimates accurately recover oracle Bayes behavior---in particular when the likelihood of the individual statistical problems is known and all problems are relevant to each other. In this thesis, we build upon advances in the theory of nonparametric statistics, machine learning, and computation to make three-fold contributions to the empirical Bayes literature: 1) We develop flexible and practical confidence intervals that provide asymptotic frequentist coverage of empirical Bayes estimands, such as the posterior mean or the local false sign rate. The coverage statements hold even when the estimands are only partially identified or when empirical Bayes point estimates converge very slowly. 2) We show that it is possible to achieve near-Bayes optimal mean squared error for the estimation of n effect sizes in the setting where both the prior and the per-problem likelihood are unknown. The requirement of our method is that we have access to replicated data, that is, each effect size of interest is estimated from K> 1 noisy observations. 3) We tackle the issue of relevance in empirical Bayes estimation of effect sizes. We propose a method that shrinks toward a per-problem location determined by a machine learning model prediction of the effect given side-information. We establish an extension to the classic result of James-Stein, whereby our proposed estimator dominates the sample mean for each problem under quadratic risk; even if the side-information contains no information about the true effects, or the machine learning model is arbitrarily miscalibrated. Taken together, these results broaden the applicability of empirical Bayes methods in areas such as genomics, and large scale experimentation, and demonstrate that it is fruitful to revisit traditional ideas in the empirical Bayes literature through a modern lens. The above results largely draw upon the following papers: Ignatiadis and Wager (2019, 2022) and Ignatiadis, Saha, Sun, and Muralidharan (2021)

Keywords: Statistics.
Advisor: Wager Stefan
Candès Emmanuel J. (Emmanuel Jean)
Tibshirani Robert
Not just hopeful monsters : phenotypic and evolutionary properties of very large adaptive mutations

Understanding which mutations drive adaptation and mapping these mutations to their phenotypic and fitness consequences is a major goal of evolutionary biology. In particular, constructing these genotype-phenotype-fitness maps of adaptive mutations has the promise to answer numerous puz- zles in the field of evolution. One especially tricky puzzle is the existence of examples of very large adaptive mutations. Theoretical work, alongside evidence from quantitative genetics, suggests that organisms are integrated entities and mutations of very large effect should be doomed to be very strongly deleterious. However, there are numerous examples of very large adaptive mutations in nature. In this thesis, I tackle this apparent paradox by leveraging barcode lineage tracking technology to measure the fitness of very large adaptive mutations that arose in an evolution ex- periment conducted with yeast. First, I test the limits of this technology to measure fitness, finding a major source of technical variation that affects many technologies that use sequencing data as a quantitative measure. However, after accounting for this and other technical variation, we find that substantial variation persists between replicate experiments conducted on different days, which represents strong context-dependency in fitness. Second, I leverage this context dependency by conducting fitness measurement experiments in a large collection of subtly varying environments. We then use these data to gain insight into the structure of the genotype-phenotype-fitness maps for these very large adaptive mutations. We find that these mutations are able to exist because they are locally modular - affecting a small number of phenotypes that contribute to fitness in the environment they evolved in. However, these mutations are also globally pleiotropic - affecting many phenotypes that contribute to fitness in other environments. Altogether, this in-depth study of very large adaptive mutations reveals a diversity of phenotypic and evolutionary properties hidden from mere glances at a mutation's fitness, or the gene or pathway the mutation affects

Keywords: Biology.
Advisor: Petrov Dmitri Alex
Geiler Samerotte Kerry 
Palacios Roman Julia Adela
Rosenberg Noah
Sherlock Gavin
Novel complex oxide structures using deintercalation

The discovery of novel materials brings diverse scientific opportunities by introducing novel physical phenomena, opening ways to verify and formulate theories, and enabling revolutionary industrial applications. Stabilization of novel structures in complex oxide materials is in particular of strong interest, as these materials display a broad spectrum of physical and chemical properties, along with dramatic variations in the material properties upon subtle changes in their structures. The stabilization of a material is largely governed by thermodynamic variables such as temperature, pressure, and chemical potential. Hence, stabilizing a novel, unconventional material usually requires that one or more of these thermodynamic variables are maintained at values far from the standard conditions. Epitaxial thin film growth, in which the target material is artificially exposed to large effective pressure due to the forced geometrical match with an underlying substrate with different unit cell dimensions, is a well-established example that satisfies this criterion. Another relevant example is ion intercalation, where relatively small ions such as lithium are inserted into a material (usually a two-dimensional van der Waals material) by electrochemically tuning the chemical potential of the ions, thereby changing the material's physical and chemical properties. In this work, I will show that controlled ionic modification via deintercalation can be an effective approach to stabilize novel complex oxides and demonstrate this in two material systems. First, I will discuss the meta-stable formation of IrO$_{x}$ via deintercalation of strontium in SrIrO$_{3}$, which demonstrates high oxygen evolution reaction (OER) activity and good chemical stability in acid. This motivates design strategies for high-activity OER catalysts such as the stabilization of a novel columbite polymorph of IrO$_{2}$, which I demonstrate can be achieved via epitaxial thin film growth. Second, I will show that oxygen deintercalation of perovskite nickelate stabilizes infinite-layer \textit{Ln}NiO$_{2}$ (\textit{Ln} = lanthanide), which upon hole-doping hosts unconventional superconductivity and shows striking similarities in the superconducting phase diagram to that of the cuprates despite marked differences in the two systems. Overall, this work highlights deintercalation as a powerful technique to stabilize novel complex oxides that is widely applicable to various material systems. As this approach has been rather underutilized relative to other conventional methods, there is great potential to further discover novel materials using this technique

Keywords: Physics.
Advisor: Hwang Harold Yoonsung
Cui Yi
Raghu Srinivas
A novel search for exotic decays of the Higgs Boson with the ATLAS detector and enhancing the physics potential of the large hadron collider and atom interferometers with new techniques

Fundamental physics research aims to understand the theory of particle interactions, the Standard Model (SM) of particle physics being the current best theory of the electroweak and strong forces. Modern efforts seeks to explain phenomenon like the matter antimatter asymmetry of the universe and the nature of dark matter using various experimental modalities such as terrestrial particle colliders like the Large Hadron Collider (LHC). The ATLAS detector on the LHC is conducting a diverse physics program of precision SM measurements and searches for Physics beyond the SM using deeply inelastic scattering products to study fundamental physics. The original research presented here uses proton collision data from the ATLAS detector to search for an exotic decay mode of the Higgs boson coupling to a new light scalar field. Additionally, two research projects are presented to improve the performance of the ATLAS detector. The first introduces a novel algorithm to improve the efficiency of locating interesting physics within saved events. The second improves the jet calibration procedure by enabling the use of gradient based regression with a novel objective function along with a unified neural network based framework. Additionally, a network of quantum sensors are in development to enhance the physics reach of modern detectors and expand the set of models of new physics that can be experimentally probed. One such technology is atomic gradiometer interferometric sensors, like the MAGIS-100 experiment, that utilize matter waves to search for ultralight bosonic dark matter. The research and development of a novel light field imaging device is presented here for the MAGIS-100 experiment, as part of a burgeoning collaboration between the high energy physics (HEP) and the atomic, molecular, and optical (AMO) physics communities

Keywords: Physics.
Advisor: Schwartzman Ariel G.
Burchat P. (Patricia)
Tompkins Lauren Alexandra
Novel Techniques to Measure Micron-Scale Gravity

The gravitational force, while understood precisely at large distances, has not been measured on scales below a few tens of microns. Recently, the use of optically levitated sensors has shown promising results as a technique to probe parameter space at these scales.
However, the sensitivity of these experiments seems currently to be limited by backgrounds. These backgrounds are inherent to current measurement schemes that rely on density-modulated attractors driven sinusoidally in close proximity to an optically-levitated dielectric microsphere to induce and measure a time-varying gravitational signal. Three limitations of this technique can be connected to the sinusoidal motion: mechanical backgrounds from the acceleration of the attractor, electrostatic backgrounds coupling to the microsphere’s permanent dipole moment, and optical backgrounds from scattered light.
One path towards eliminating these backgrounds is to use a rotating disk with various built-in density modulations. Here, I report on the efforts of understanding and implementing such a rotary attractor in our existing system. Specifically, I build a signal model using a FEM simulation which informs optimal density profiles for manufacturing, use microscopic video registration to characterize the stability of hardware, and outline the steps needed for a full implementation.

Keywords: Physics
Optically-Levitated Microspheres
Gravity > Measurement
Computer simulation
Hardware
Text
Thesis
Advisor: Gratta Giorgio
Hollberg Leo
Numerical simulation of hot surface ignition and combustion of fuel sprays

Due to their high energy density and ease of transportation, liquid fuels continue to be used in a variety of combustion systems, including in aerospace, automotive and industrial applications. Analysis of the underlying physics of multiphase combustion phenomena, particularly as it pertains to ignition, contributes to improved physical understanding and supports greater system reliability and safety. High-fidelity numerical simulations are particularly effective in supporting improved fundamental understanding, but detailed simulations of practical multiphase combustion configurations are highly computationally costly. The study of accidental ignition of liquid fuels and the development of computationally efficient means of performing physically accurate multiphase combustion simulations are therefore important avenues of scientific inquiry. This dissertation considers the problem of the ignition and combustion of a wall-impinging fuel spray using four complementary approaches. First, to analyze the long-term wall heat flux caused by a wall-stagnating spray flame, a steady, one-dimensional, multi-continuum formulation is developed with consideration given to conjugate heat transfer effects. Second, an unsteady, one-dimensional, multi-continuum formulation is developed and a broad parametric study of the hot surface ignition of wall-stagnating fuel sprays is conducted. Third, high-fidelity three-dimensional large-eddy simulations are performed in an Eulerian-Lagrangian formulation using a finite-rate chemistry model. Fourth, the substantial computational cost of the high-fidelity simulations performed motivates the development of a computationally efficient spray combustion modeling framework. This dissertation extends the Pareto-efficient combustion (PEC) modeling framework to spray combustion through a rigorous analysis of the governing equations. The spray-augmented PEC formulation is applied to the high-fidelity simulation of a wall-stagnating spray flame and to the simulation of a realistic gas turbine combustor to demonstrate improved physical fidelity compared to tabulated chemistry, while reducing computational cost compared to monolithic finite-rate chemistry

Keywords: Mechanical Engineering.
Advisor: Ihme Matthias
Boettcher Philipp (Philipp Andreas)
Bowman Craig T. (Craig Thomas)
Lele Sanjiva K. (Sanjiva Keshava)
Numerical study of excitonic orders in strongly correlated systems

Harnessing unconventional phases of matter in strongly-correlated electron systems holds great promise for the functionalization of quantum properties of materials. Soon after the prediction of Bose-Einstein condensation, it was realized that the concept of condensation can be generalized to arbitrary systems of bosonic quasiparticles, including excitons -- bound pairs of electrons and holes. Understanding the emergence of excitonic instabilities from strong electronic interactions has remained challenging for numerical methods, including determinant quantum Monte Carlo (DQMC), due to the notorious sign problem. In this thesis, I present sign-free DQMC studies of excitonic orders in multi-band Hubbard-like models. First, I show results for a bilayer Hubbard model with equal and opposite electron-hole doping in the two layers, which is proposed to be an ideal platform to study excitonic orders due to suppressed recombination of inter-layer electrons and holes. Here, our study demonstrates convincing evidence for the existence of the bi-excitonic condensation phase in the vicinity of the high-symmetric point at finite electron-hole doping, as well as a competing (pi, pi) charge density wave (CDW) state. Furthermore, we analytically investigate the strong coupling limit of the model, providing physical insight underlying the emergence of the bi-excitonic condensation phase. Second, I discuss a half-filled two-orbital Hubbard-Kanamori model with broken orbital degeneracy, which accounts for the role of Hund's coupling in transition-metal compounds and other materials of multi-orbital nature. For strong inverted (negative) Hund's coupling, we find numerical evidence for the emergence of a Z2 symmetry breaking excitonic density order, which competes with an anti-ferro-orbital (AFO) order as a function of orbital splitting and Hund's coupling

Keywords: Applied Physics.
Advisor: Devereaux Thomas Peter
Heinz Tony F.
Kivelson Steven
Oceanic influence and sustainable development of large ocean states

Certain developing countries disproportionately rely on the ocean for their sustainable development. Yet, the technical and financial assistance they receive from the international development community through country classifications, a mechanism that groups countries based on common development constraints, falls short of addressing their specific ocean-based needs. This is resulting in ineffective investments and weak coordination at a time when most countries are struggling to achieve multiple ocean-based international sustainable development priorities, including the United Nations Sustainable Development Goals. In three chapters, this dissertation examines these issues by drawing on global and publicly available datasets to propose a way forward. The first chapter identifies critical ocean policy gaps with current country classifications within the context of countries increasingly self-identifying as 'large ocean states' to illustrate the need for a new Large Ocean State country classification. The second chapter investigates how climate change is impacting fisheries, a key sector for many ocean-based developing countries, by analyzing the plausible causal effect of changing ocean seasonality on global fisheries harvests using fixed effect regression. The third chapter builds on the previous chapters to articulate a new Large Ocean State country classification using unsupervised machine learning. Collectively, the dissertation provides actionable solutions to support large ocean states and promote a healthier ocean

Advisor: Dunbar Robert B.
Leape James P.
Micheli Fiorenza
Oleson Kirsten
Odd Correlations and their Gravitational Duals in the SYK Model

We investigate two-point correlation functions on the Sachdev-Ye-Kitaev (SYK) model. SYK describes a system of N-Majorana fermions with random all-to-all q-couplings. In the low energy limit SYK becomes a nearly conformal theory (NCFT), which in turn has an approximate holographic dual in a nearly AdS2 or NAdS2 spacetime described by Jackiw-Teitelboim (JT) gravity. Drawing on black hole information theory guides the addition of various topological effects in the genus expansion for thermal expectation values. We compare these expected results with numerical simulations of two-point correlations for varying values of N mod 8. We see that previous correlation calculations almost perfectly account for all numeric phenomena save for an anomalous bump in the N = 4 mod 8 case and an unexpectedly high correlation plateau for N = 3 mod 8. These calculations imply the need to include higher order topologies when calculating boundary observables.

Keywords: Physics
SYK
JT
Jackiw-Teitelboim
Sachdev-Ye-Kitaev
Quantum gravity
Text
Thesis
Advisor: Stanford Douglas
Susskind Leonard
Oddball realizations of "geometry = entanglement"

The four chapters of this thesis consist of three published papers to which I contributed, as well as a draft of a theorem & proof that I will be contributing to a forthcoming paper. The four subjects presented here all have, as their ur-ancestor, Mark Van Raamsdonk's observation that in holographic theories of quantum gravity, entanglement in the boundary state seems to be a prerequisite for connected geometry in the bulk state. The common goal of the four chapters of this thesis is to sniff out concrete, specific, and weird realizations of this principle

Keywords: Physics.
Advisor: Hayden Patrick (Patrick M.)
Shenker Stephen Hart
Stanford Douglas