VictorJuiz/thesis huggingface dataset:
Transcriptional, proteomic, and functional analysis of cytokine secreting plasmacytoid dendritic cells [electronic resource]

Plasmacytoid dendritic cells (pDCs) are a rare subset of immune cells characterized by their ability to secrete large amounts of interferon alpha (IFN[alpha]) in response to Toll Like Receptor (TLR) activation by viral and endogenous nucleic acids. In these studies, we developed novel techniques that fundamentally change how cellular biologists can detect and assess protein and gene expression in cells based on function instead of phenotype. These techniques, which allow for transcript profiling of cells sorted by intracellular cytokine staining, and high throughput single cell detection of RNA transcript, were used to examine the role of pDC subsets that differ by IFN[alpha] and TNF secretion. Transcript profiling of these subsets revealed that after activation, there are two subsets of pDCs; cytokine secreting pDCs which express inflammatory and tolerogenic mediators, and quiescent noncytokine secreting pDCs, which maintain mRNA profile of unstimulated pDCs. Single cell RNAflow demonstrated that gene expression in subsets of pDCs from FLT3L DC (FLDC) cultures, bone marrow, and spleen correlates with cytokine staining. From our transcript profile data, we generated a list of candidate surface markers for cytokine secreting pDCs, which we screened by CyTOF and present here. Finally, we performed functional analysis of CD4- and CD4+ pDC subsets, and demonstrated that CD4- pDCs contain more activateable pDCs which take up antigen and induce antigen specific T cell proliferation. Taken together, these studies suggest that upon TLR activation, concomitant expression of rate limiting signaling genes leads to stochastic pDC expression of IFN[alpha] and TNF, leaving a larger pool of non cytokine secreting pDCs that maintain their pDC phenotype and expression pattern, and which may be activated at a later time. These studies also demonstrate the utility of screening based on function (cytokine secretion) instead of phenotype, which in this case, allowed for more complete assessment of variation between cells of different function.

Keywords: Immunology.
Advisor: Utz Paul primary advisor. Thesis advisor
Engleman Edgar G. advisor. Thesis advisor
Nolan Garry P. advisor. Thesis advisor
Robinson William (William Hewitt) advisor. Thesis advisor
Steinman Lawrence advisor. Thesis advisor
Treating neuroinflammatory diseases via pharmacological modulation of microglia [electronic resource]

Microglia are the resident tissue macrophages of the central nervous system (CNS) parenchyma. While less than 20% of the cellular composition of the CNS is made up of by microglia, they play many roles in the CNS ranging from tissue remodeling, maintenance and repair to protecting the CNS against insults, both foreign- and self-derived. It is not surprising that microglia dysfunction has been shown to contribute to major neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease and Multiple Sclerosis (MS) as well ass lesser-known diseases such as Nasu-Hakola disease. Unfortunately, the ability to modulate microglia to beneficially modify neurodegenerative diseases remains limited. This dissertation illustrates how an antiviral and a hypertension medication ameliorate disease in animal models of neuroinflammation and neurodegeneration by modulating the cellular and molecular functions of microglia.

Advisor: Wyss-Coray Anton primary advisor. Thesis advisor
Buckwalter Marion
Chawla Ajay advisor. Thesis advisor
Steinman Lawrence advisor. Thesis advisor
Trophic ecology of invertebrates in an intertidal seagrass community: spatial and functional variability in the importance of primary producers

This project aimed to understand the relationship between marine invertebrates associated with the intertidal seagrass Phyllospadix scouleri, and the greater intertidal community. I hypothesized that individual invertebrate species would show distinctive feeding ecologies due to differences in proportional utilization of primary producer organic matter. I also predicted that species would show shifts in their resource utilization between the wave-protected and wave-exposed sites. Stable isotope analysis offered a method for determining their food sources, since they are difficult to observe. Combined with the mixing model analysis completed by the program MixSir, I was able to track both which food sources were utilized, and whether this varied with location, for each invertebrate. I found that all the consumers relied on a variety of food resources, appearing to be generalists rather than specialists, and that they utilized the resources differentially based on the location they were collected from. This likely derives from the differences in wave exposure of the two sites, and the change in the bioavailability of organic matter as a food resource between the two sites studied.

Keywords: Hopkins Marine Station
Stanford Biology Department
surfgrass
surf grass
seagrass
Phyllospadix scouleri
Thesis
Advisor: Micheli Fiorenza
Dirzo Rodolfo
Tunable photonic crystal biosensors for portable label-free diagnostics [electronic resource]

Although there is a pressing global need for widely-deployable disease detection and monitoring systems, today's options for biochemical analysis are often bulky, slow, expensive, and reliant on trained medical personnel. In contrast, the miniaturization and integration of devices based on arrays of sources, detectors, and active or passive biosensing surfaces provides a means to achieve handheld diagnostic capabilities with a "lab-on-a-chip" that would be vastly less expensive and fully automated. In this thesis, we design, fabricate, and characterize tunable biosensors with compact and low-cost Vertical Cavity Surface Emitting Lasers (VCSELs), integrated detectors, Peltier coolers, photonic crystal slab resonators, and polymer microfluidics. All of the components utilize scalable semiconductor and soft-lithography techniques to significantly reduce the required device footprint, simplify system assembly, and enable large-scale, economical manufacturing. The sensors operate in the visible to near-infrared 650-900 nm wavelength range for low absorption of water, hemoglobin, and other background elements found in tissue or aqueous samples. Moreover, the 670 nm label-free sensors we demonstrate are designed for compatibility with previously characterized monolithically integrated fluorimeters that capitalize on emerging deep-red fluorescent proteins and molecular probes approved for pre-clinical use by the Federal Drug Administration.

Keywords: Electrical Engineering
Advisor: Harris J. S. (James Stewart)
Fan Shanhui
Hesselink Lambertus advisor. Thesis advisor
Tunneling contacts for novel semiconductor devices [electronic resource]

While the continued scaling of transistors faces severe limitations, novel devices incorporating new materials, new transport mechanisms and new state variables are emerging as a strong contender for future logic and memory. This thesis describes the modeling and simulation of three such devices. The first of these is the metal-insulator-semiconductor (MIS) contact to achieve low contact resistance. A contact resistance simulator for MIS structures is developed and quantitative predictions are made of the achievable contact resistance using different insulator materials. $\mathrm{TiO}2$ is predicted to be a suitable interface material. The second device is the spin MOSFET using ferromagnetic source and drain contacts. An efficient framework is developed to simulate spin transport in semiconductors coupled with a tunneling model for spin injecting contacts. The important effects of electric fields, the voltage dependence of magnetoresistance (MR) and the effect of parameters such as tunnel oxide thickness, semiconductor channel length and doping density on MR are investigated. The third device is the magnetic tunnel junction which uses spin selective MgO tunnel barriers. An extended Huckel theory (EHT) atomistic simulator coupled with non-equilibrium Green's function (NEGF) formalism for transport is implemented. Through these EHT-NEGF simulations the reduction of magnetoresistance due to Fermi level pinning is demonstrated. An approximate approach for the simulation of CoFe alloy electrodes is developed.

Keywords: Electrical Engineering
Advisor: Saraswat Krishna primary advisor. Thesis advisor
Nikonov Dmitri
Nishi Yoshio
Two-step laser mass spectrometric investigations of terrestrial and extraterrestrial samples [electronic resource]

The studies detailed in this thesis center around the application of laser mass spectrometry to a variety of terrestrial and extraterrestrial samples and their polycyclic aromatic hydrocarbon (PAH) contents. Though PAHs are ubiquitous in space, on Earth and, indeed, in our everyday lives, determination of characteristic PAH signatures in samples of interest can provide important clues to the mechanisms of asteroid interactions, answer questions about experimental contamination, and even help to decipher the riddles of extraterrestrial life. Specifically, this thesis describes the use of two-step laser desorption laser ionization mass spectrometry (L2MS) to: (i) determine that photochemical reactions are not a source of contaminating aromatics in NASA's Stardust mission; (ii) confirm that meteorites collected in the area of a witnessed near-Earth object (NEO) impact were indeed part of the parent asteroid; (iii) contribute to the on-going question of biotic or abiotic formation of carbonate/magnetite globules in mineralogical formations; and (iv) show that L2MS is a promising alternative to laser desorption/ionization mass spectrometry (LDI-MS) for analytes prone to gas-phase aggregation.

Keywords: Chemistry
Advisor: Zare Richard N. primary advisor. Thesis advisor
Andersen Hans
Boxer Steven G. (Steven George)
TypeVote algorithm [electronic resource] : theory, computation, extensions and applications

This thesis is devoted to describe an algorithm --- TypeVote algorithm that enables us to compute more accurate probability distribution estimators (both probability mass and density estimators) in the presence of missing data of which the missing pattern is MCAR (missing completely at random). We first review some of the background literatures of MCAR data analysis and present a number of motivating heuristics underneath the algorithm design. Then we elaborate the generic TypeVote algorithm right after introducing two related concepts: vagueness and type graph; there are two parts of the algorithm: the typing process which standardizes the raw data and the voting process which is an EM algorithm that finds the maximum likelihood estimator by using both completely and incompletely observed data entries. Subsequently, we prove the properties of the generic TypeVote algorithm such as the convergence condition, the convergence rate and the superiority to the classical multinomial estimator that only use completely observed data entries in terms of asymptotic efficiency and some others. We also cover the computational aspects of the generic TypeVote including the run-time data structure, scalability and flexibility. Additionally, we provide a simulation-based numerical experiment to support the theory. We then extend the study to categorical data and furthermore we derive TypeVote kernel density estimator (TV-KDE) which is more accurate than the classical KDE by taking both completely and incompletely observed data entries into account. Overall, TypeVote algorithm not only gives us an unprecedented methodology on how to handle probability distribution estimation with MCAR data, but also opens some new opportunities for us because a number of acclaimed multi-step estimators employing probability distribution estimators as one critical step. Practically, probability distribution estimation with MCAR data (MCAR data is getting prevalent in the computational era) is one of the key problems in the realm of applied statistics.

Advisor: Hong Han primary advisor. Thesis advisor
Papanicolaou George advisor. Thesis advisor
Ye Yinyu advisor. Thesis advisor
Ultrafast photovoltaic responses in ferroelectric thin films [electronic resource]

The interaction of ultrashort light pulses with the medium of the ferroelectric is a fundamental question for photonics and photovoltaic applications. I report two advances toward our understanding of this family of materials in the ultrafast regime: (1) Using femtosecond time-resolved x-ray scattering to observe changes in the unit-cell tetragonality of thin films of the prototypical ferroelectric lead titanate, PbTiO3, we show the direction, magnitude and physical mechanisms underlying the photocurrents generated by femtosecond near-bandgap photoexcitation. These findings elucidate the ultrafast photovoltaic response in these ma- terials, illustrate the intrinsic coupling between their electronic and structural degrees of freedom, and show that light can enhance the functional properties of ferroelectrics on nanosecond timescales. In addition, we observe that femtosecond optical pulses can reversibly switch the ferroelectric phase to the non-polar paraelectric phase. (2) In order to further investigate mechanisms for using light to manipulate the ferroelectric polarization, a terahertz (THz) pulse source based on coherent transition radiation has been commissioned, which generates single-cycle pulses lasting roughly 100 fs with peak fields greater than 20 MV/cm and energies in excess of 100 uJ. These pulses contain frequencies resonant with the "soft mode" reaction coordinate of the ferroelectric-paraelectric phase transition, and their high peak fields drive strong nonlinear optical responses in materials. As a first demonstration, I show that this source drives an all-THz response in a silicon photodiode. Recent work shows that such pulses should permit purely optical steering of the ferroelectric polarization.

Keywords: Chemistry
Advisor: Lindenberg Aaron Michael primary advisor. Thesis advisor
Chidsey Christopher E. D. (Christopher Elisha Dunn)
Reis David A.
Ultralow threshold electrically pumped photonic crystal lasers [electronic resource]

The advantages of shrinking the cavity of a semiconductor laser to volumes on the order of the wavelength of light and below were realized more than 20 years ago. Within the last decade there has been extensive work developing techniques for confining light in nanoscale cavities such as photonic crystals and plasmonics. It is now considered relatively easy to demonstrate semiconductor nanocavity lasers where greater than 10% of the spontaneous emission is coupled to the laser mode, and researchers have recently been able to demonstrate nanolasers where the active volume consists of a single quantum dot. It has been predicted that these lasers will open up many applications such as on-chip optical interconnects, optical computing, photonic integrated circuits, high sensitivity optical sensors, in addition to novel physics. Before the work described in this thesis, the performance of optically pumped nanolasers was orders of magnitude better than electrically pumped devices due to the difficulty of efficient electrical pumping of nanoscale optical cavities. The main result of this thesis is the development of a practical and efficient way to electrically pump photonic crystal nanocavity lasers and other photonic crystal nanocavity devices (modulators, resonant cavity LEDs etc). Using this technique we were able to demonstrate a laser with a threshold of only 181nA at 50K, the lowest threshold ever observed in any type of electrically pumped laser. The design shows great promise for high speed operation, and we experimentally show that quantum dot photonic crystal lasers can achieve modulation rates of 30GHz and study the factors limiting the maximum modulation rate.

Keywords: Electrical Engineering
Advisor: Vuckovic Jelena primary advisor. Thesis advisor
Harris J. S. (James Stewart)
Miller D. A. B. advisor. Thesis advisor
Unbeamed extragalactic emitters and the origin of the isotropic diffuse gamma-ray background [electronic resource]

The extragalactic background light is the total radiative output from the edge of our Galaxy to the edge of the observable Universe. In the gamma-ray band, this background becomes a census of high energy phenomena throughout cosmic time. Gamma-ray telescopes have now detected approximately one-thousand individual extragalactic sources, as well as a diffuse all-sky component which is isotropic on large angular scales -- the Isotropic Diffuse Gamma-ray Background (IGRB). The collective emission of unresolved extragalactic sources is a guaranteed contribution to the IGRB, and truly diffuse processes and Milky Way foregrounds must also be present at some level. While the great majority of individually resolved extragalactic sources are active galactic nuclei (AGN) whose apparent emission is enhanced by relativistic beaming, observations with the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope (Fermi) have started to reveal new types of extragalactic sources. This Dissertation describes how Fermi is helping us to better understand faint extragalactic sources including non-AGN star-forming galaxies, galaxy clusters, and AGN lacking powerful relativistic jets, as well as the contributions of these populations to the IGRB intensity budget. Ongoing studies of atmospheric particle backgrounds in low-Earth orbit and their influence on the LAT IGRB measurement will also be presented. Finally, we consider areas for further exploration regarding the IGRB origin and the physics of cosmic rays in the interstellar and intergalactic medium.

Keywords: Physics
Advisor: Funk Stefan
Allen Steven W. (Steven Ward) advisor. Thesis advisor
Blandford Roger D. advisor. Thesis advisor
Wechsler Risa H. (Risa Heyrman) advisor. Thesis advisor
Uncertainty quantification in high dimensional model selection and inference for regression [electronic resource]

Recent advances in ll_1$-regularization methods have proved to be very useful for high dimensional model selection and inference. In the high dimensional regression context, the lasso and its extensions have been successfully employed to identify parsimonious sets of predictors It is well known that the lasso has the advantage of performing model selection and estimation simultaneously. It is less well understood how much uncertainty the lasso estimates may have due to small sample sizes. To model this uncertainty, we present a method, called the "contour Bayesian lasso" for the purposes of constructing joint credible regions for regression parameters. The contour Bayesian lasso is an extension of a recent approach called the "Bayesian lasso" which in turn is based on the Bayesian interpretation of the lasso. The Bayesian lasso uses a Gibbs sampler to generate from the Bayesian lasso posterior and is thus a convenient approach for quantifying uncertainty of lasso estimates. We give theoretical results regarding the optimality of the contour approach, study posterior consistency and the convergence of the Gibbs sampler. We also analyze the frequentist properties of the Bayesian lasso approach. A theoretical analysis of how the convergence of the Gibbs sampler depends on the dimensionality and sample size is undertaken. Our methodology is also illustrated on simulated and real data. We demonstrate that our posterior credible method has good coverage, and thus yields more accurate sparse solutions when the sample size is small. Real life examples are given for the South African prostate cancer data and the diabetes data set.

Keywords: Statistics
Advisor: Rajaratnam Balakanapathy primary advisor. Thesis advisor
Efron Bradley advisor. Thesis advisor
Johnstone Iain advisor. Thesis advisor
Romano Joseph P.
Uncovering the neural correlates of intersubjective avoidance in a novel rat model [electronic resource]

Over half of all violent crimes are committed by only about 5% of offenders. While most healthy people feel strong aversion to seeing other people in pain, fear, or sadness, a phenomenon I define as "negative intersubjectivity", these persistent violent offenders (PVOs) have blunted reactions to other people's distress and the strength of their negative intersubjectivity deficit correlates with how much violence they ultimately perform. This suggests that if we could learn how to enhance PVOs aversion to other people's distress, we could decrease their violent behavior. In this dissertation, I describe a new rat model that can be used to study the neural mechanisms underlying negative intersubjectivity. I demonstrate that Observer rats will overcome their innate aversion of bright light to consistently avoid a dark, safe space if entering that dark space is paired with another Receiver rat getting shocked, a behavior called "intersubjective avoidance". In Chapter 2, I describe the relatively poor intersubjective avoidance behavior of mice. In Chapter 3, I describe the comparatively strong intersubjective avoidance behavior of rats, and show that rats' intersubjective avoidance is enhanced by personal experience with shock. In Chapter 4, I use patterns of expression of the immediate early gene c-Fos to determine whether activity in candidate brain regions correlates with intersubjective avoidance. I provide evidence that many brain regions--including the anterior cingulate, anterior insula, infralimbic cortex, and central amygdala--are active both when observing shock in another and when receiving shock to oneself, similar to what has been shown by fMRI studies of humans observing others in pain. However, within these areas, only activity in the anterior cingulate robustly correlates with how much intersubjective avoidance each individual Observer rat performs, perhaps analogous to how fMRI studies in humans have show that anterior cingulate activity correlates with humans' self-reports of "empathy". These results validate the rat model of intersubjective avoidance as model of negative intersubjectivity in humans, and highlight the anterior cingulate as a potential target for negative intersubjectivity interventions. In Chapter 5, I describe future experiments and discuss how research using this new behavioral paradigm may help develop treatments for not only PVOs, but all anti-social behavior.

Keywords: Neurosciences.
Advisor: Newsome William T. primary advisor. Thesis advisor
Lecea Luis de primary advisor. Thesis advisor
Fernald Russell D. advisor. Thesis advisor
Knutson Brian advisor. Thesis advisor
Parker Karen J. advisor. Thesis advisor