VictorJuiz/thesis huggingface dataset:
The household thru time : the paracas to nasca transition at Uchuchuma, Aja Valley, Peru
Keywords: Anthropology.

This dissertation focuses on the emergence of the prehispanic Nasca (AD 1-- 700) culture during the transition from the Late Terminal Formative (200 BC -- AD 1) to the Early Intermediate Period (AD 1 -- 700) in the Rio Grande de Nasca Region, Peru. The Paracas culture (800-100 BC), a federation of various ethnic groups from the Ica region that shared pottery, textile, and funerary practices, migrated to the Nasca region sometime during the Late Terminal Formative. Andean archaeologists suggest that Paracas groups living in the Nasca region came together to form a centralized society and ethnicity -- Nasca -- that shared a common religion and pottery style. To better understand the nature of this transition from Paracas to Nasca from a household perspective, my project systematically compared both Paracas and Nasca domestic practices (e.g. ceramic production, stone tool making and food consumption) using data from a residential archaeological site called Uchuchuma, located in the Aja Valley, Peru. While my excavations confirm a Paracas and Nasca occupation at Uchuchuma, they also demonstrated that these occupations were not continuous and that the two groups lived in different areas of the site. Artifact analyses demonstrate that food consumption, stone tool making, and ceramic production were much more varied in Paracas households, while Nasca households were more homogeneous. I conclude that Paracas people living at Uchuchuma were highly influenced by the broader social changes occurring in the Nasca region, as architecture, pottery styles, and stone tool making traditions were abandoned and replaced with new ones. I argue that the abandonment of certain Paracas traditions such as house form and ceramic technology were abandoned intentionally, as participation in the developing Nasca architectural and pottery style would have connected this community with a broader network of interaction. Finally, I suggest that the continuation in settlement, some pottery forms, and plaza use were subtle practices that allowed the Uchuchuma community to maintain ties with their past.
How mechanical properties of the pancreas signal the immune system in type 1 diabetes
Keywords: Materials Science and Engineering.

Inflamed tissues experience a change in stiffness compared to their healthy state. This could be partially a result of accumulation of the glycosaminoglycan hyaluronan (HA). T cells can sense external mechanical forces, as seen in stiff and soft matrix. The goal of this work is to investigate the role of mechanobiology in type 1 diabetes (T1D) using HA-based hydrogels that mimic the physiological mechanics and biophysical cues in pancreatic islets.
How prepared do I have to be for a job? : gender differences in the desire for preparedness
Keywords: Psychology.

While some people jump into taking on a new challenge, others feel like they need to be more "prepared" before they take the first step. Such a desire to be highly prepared could hold one back from embarking on a new journey, such as applying for a new job. Is there a gender difference in how much people want to be prepared for a job before applying? In this dissertation, I systematically examine this phenomenon and seek a solution that could reduce the gender difference. Study 1a and 1b revealed that women wanted to have a greater level of job-related knowledge and skills before applying than men. Studies 2-4 explored boundary conditions for the gender difference in the desire for preparedness. Study 2 investigated whether women would believe other women should also be highly prepared. Women wanted a high level of preparedness for themselves but not for others, and the gender difference disappeared when people made judgments about others rather than themselves. Study 3 presented jobs in gender-typed and gender-neutral industries to test whether the gender difference varied across jobs in different fields. The gender difference was not significant overall, but both women and men wanted to be more highly prepared for male-typed jobs than female-typed jobs. Study 4 presented jobs that varied in level of career-related risk. Both women and men wanted to be prepared to an equal extent, not only when the job was explicitly described as safe, but also when it was described as risky. The difference was significant only when there was no overt mention of a risk involved. Finally, Study 5 tested a potential solution for organizations to reduce the gender difference. I presented job descriptions that portrayed the recruiting company as valuing either employees' learning, ability, or health (control). When the company valued learning, compared to health, women's desire for preparedness decreased, and the gender difference was closed. This research suggests that women may set a higher standard than men early in their career when they consider applying for jobs. Importantly, this work proposes a practical organizational solution that may equalize the psychological standing of women and men when they apply for a job and encourage women to take opportunities they might be well qualified for.
Human Induced Pluripotent Stem Cells Reveal Mitophagy as an Essential Process Against Diabetic Cardiomyopathy
Keywords:  Department of Bioengineering
Stanford School of Engineering
Department of Bioengineering
Stanford Cardiovascular Institute
Undergraduate Advising and Research (UAR) Major Grant
stem cell
diabetes
diabetic cardiomyopathy
cardiology
mitophagy
proteomics
Thesis

Diabetic cardiomyopathy is a common consequence of diabetes and is associated with mitochondrial pathology. Using human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) as an in vitro model of diabetes, we sought to understand the role of mitophagy, a process that selectively degrades mitochondria through the autophagy-lysosome pathway, as a crucial quality control pathway against diabetic cardiomyopathy. We first showed that iPSC- CMs exposed to a diabetic milieu demonstrated increased hypertrophy, impaired calcium signaling, and higher oxidative stress. Flow cytometry analysis of iPSC- CMs subjected to diabetic conditions revealed two distinct populations of cells (normal and hypertrophied), suggesting a heterogeneous response to hyperglycemia. In these cells, hypertrophied iPSC-CMs were found to have reduced mitophagy compared to normal cells when exposed to hyperglycemia. In addition, we showed that mitochondrial fragmentation was also decreased in the hypertrophied iPSC-CMs compared to normal cells upon exposure to hyperglycemia, demonstrating a link between mitochondrial fragmentation and mitophagy. Surprisingly, pretreatment of iPSC-CMs with a non-selective antioxidant, N-(2-mercaptopropionyl)-glycine, not only failed to limit the deleterious effects of hyperglycemia but actually led to increased hypertrophy and cell death. We found that mitophagy was significantly reduced in iPSC-CMs following antioxidant treatment, suggesting the need for mild oxidative stress as a trigger for mitophagy. Future studies are warranted to further investigate the association between oxidative stress, mitochondrial fragmentation, and mitochondrial fission as targets against diabetic cardiomyopathy.
Hunting down host targets for host-directed therapies through forward genetic screens
Keywords: Microbiology and Immunology.

Infectious diseases have plagued humans for centuries, and with the rise in antimicrobial resistance, there is a pressing need to develop novel strategies for combating pathogens. Host-directed therapies offer a promising alternative to traditional antimicrobials that directly target the pathogen. Furthermore, the identification of targets for the development of host-directed therapies has been accelerated by the advent of next-generation screening technology. This thesis presents examples of applying forward genetic screens to the identification of novel and attractive host targets for the development of host-directed therapies.
The hybrid mobile instrument : recoupling the haptic, the physical, and the virtual
Keywords: Music.

The decoupling of the "controller" from the "synthesizer" is one of the defining characteristic of digital musical instruments (DMIs). While this allows for much flexibility, this "demutualization" (as Perry Cook termed) sometimes results in a loss of intimacy between the performer and the instrument. In this thesis, we introduce a framework to craft "mutualized" DMIs by leveraging the concepts of augmented mobile device, hybrid instrument design, and skill transfer from existing performer technique. Augmented mobile instruments combine commodity mobile devices with passive and active elements that can take part in the production of sound (e.g., resonators, exciter, etc.), while adding new affordances to the device and changing its form and overall aesthetics. Screen interfaces can be designed to facilitate skill transfer, accelerating the learning and the mastery of such instruments. Hybrid instrument design mutualizes physical and "physically-informed" virtual elements, taking advantage of recent progress in physical modeling and digital fabrication. This design ethos allows physical/acoustical elements to be substituted with virtual/digital ones and vice versa (as long as it is physically possible). A set of tools to design hybrid mobile instruments is introduced and evaluated. Overall, we demonstrate how this approach can help digital luthiers to think about DMI design "as a whole" in order to create mutualized instruments. Through a series of case studies, we discuss aesthetic and design implications when making such hybrid instruments.
Hybrid PSO - adjoint-gradient Procedure for Well Control Optimization
Keywords:  Energy Resources Engineering
School of Earth Energy &amp; Environmental Sciences
Energy Resources Engineering
Production optimization
well control optimization
Particle swarm optimization
Adjoint-gradient optimization
Hybrid optimization
Reservoir simulation
Compositional simulation.
Thesis

Compositional simulation is commonly applied to evaluate enhanced oil recovery and carbon storage processes. Compositional simulation is expensive because the models may include multiple components along with complex phase behavior. Thus, when compositional systems are optimized, the optimization algorithms must be robust and efficient. In this work, we assess different procedures for well control optimization in oil-gas compositional systems. The optimization algorithms considered include a standalone adjoint-gradient-based method, a standalone particle swarm optimization (PSO) procedure, and several hybridizations of these two approaches. We introduce and evaluate two criteria for switching from PSO to adjoint-gradient-based optimization in the hybrid procedures. These approaches are referred to as deterministic switching, where we switch after a specified number of PSO iterations, and adaptive switching, where the algorithmic switch is based on PSO performance. All methods are implemented and run within Stanford’s Unified Optimization Framework (UOF).
The performance of the standalone and hybrid procedures is assessed for two example cases involving well control optimization in Gaussian and channelized geological models. The time-varying bottom-hole well pressures are treated as the optimization variables, and net present value (NPV) is optimized. Each method under consideration is run at least nine times to account for the stochastic nature of PSO and the sensitivity to the initial guess in the adjoint-gradient method. This allows us to draw meaningful conclusions on the relative performance of the various procedures. The two example cases presented in this study demonstrate that the hybrid PSO-adjoint-gradient procedure utilizing adaptive switching outperforms the standalone algorithms in terms of average optimal NPV. By plotting the average optimal NPV versus computational effort for the different methods, we can construct a Pareto front. For both cases, the Pareto-optimal procedures include standalone PSO (which provides lower average NPV but requires less computation) and the hybrid PSO-adjoint-gradient method using adaptive switching. The latter gives higher average NPV but at the cost of increased computational effort.
Hydrocarbon combustion reaction models from both ends--the foundational fuels and JP10
Keywords: Mechanical Engineering.

Due to the hierarchical nature of high-temperature hydrocarbon oxidation, modeling the combustion chemistry of higher hydrocarbon fuels typically requires a fuel-specific reaction model that describes the fragmentation of the fuel to small species, and a foundational fuel chemistry model that describes the oxidation of these species. Shared by the combustion of large hydrocarbons, the foundational fuel chemistry is also the rate-limiting step and therefore a crucial part for constructing reliable combustion models for any higher hydrocarbons. The dissertation studies the aforementioned problems from both ends. A detailed reaction kinetic model of the foundational fuel combustion is comprised of elementary chemical reactions and their associated rate coefficients. Each of the rate coefficients comes with some uncertainty. The inherent uncertainties of the rate parameters propagate into model predictions and need to be properly quantified. Without characterizing the uncertainty, a reaction model merely represents a feasible combination of rate parameters within a high-dimensional uncertainty space. The Foundational Fuel Chemistry Model (FFCM) is an effort directed at developing a reliable combustion model for the foundational fuels with rate parameters optimized and uncertainty minimized. The first version, FFCM-1, optimized for H2, H2/CO, CH2O and CH4 combustion was constrained with carefully evaluated fundamental combustion data that includes laminar flame speeds, shock tube ignition delay times, shock tube species profiles, and flow reactor species profiles. It has been shown that the model reconciles all the experimental targets chosen and has significantly reduced prediction uncertainties. The remaining kinetic uncertainties in FFCM-1 were further analyzed with extinction and ignition residence time predictions in perfectly-stirred reactor conditions. The reactions that were responsible for the remaining prediction uncertainties were studied with an impact factor analysis over a wide range of temperature, pressure and equivalence ratio. The optimization and uncertainty quantification procedure was then extended to also include temperature dependency by considering the joint optimization of pre-exponential factors and activation energies. An effective temperature was defined for every target and utilized in the response surface derivation. The resulting temperature-dependent uncertainties of key reactions in H2/CO flames in a test problem were discussed. JP10 was studied as a single-component large-fuel example, using the Hybrid Chemistry (HyChem) approach. The HyChem approach assumes a decoupled fuel pyrolysis and oxidation of pyrolysis products. The pyrolysis model is described with highly-lumped steps and optimized against experimental data from shock tube and flow reactor species profiles and shock tube ignition delay. Special attention was paid to the unique molecular structure of the fuel in the lumped pyrolysis reactions, and the overall performance of the model is shown to be satisfactory.
Hydroxychloroquine use and adverse events in Lupus pregnancy: A Stanford Experience
Keywords:  Department of Health Research & Policy
Systemic lupus erythematosus
SLE
lupus
preeclampsia
preterm birth
hydroxychloroquine
plaquenil
Department of Health Research &amp; Policy
Stanford University
Stanford School of Medicine
Obstetrics
Gynecology
Rheumatology
Thesis

Background: Relatively recently, women with lupus would be advised against pregnancy. However, with improved diagnosis and management, complicated SLE and history of any organ involvement is not a strict contraindication for future pregnancy. As the literature providing evidence for the safety of hydroxychloroquine (HCQ) use during pregnancy in women with lupus grows, it has become increasingly important to evaluate the changes this intervention has introduced in regard to adverse events in pregnancy.
Aim: To evaluate the association between HCQ use and preterm birth (PTB) and preeclampsia (PE) in pregnant women with lupus.
Methods: A retrospective cohort of 129 pregnancies from 110 women with lupus was formed from 2000-2017 from a single center, Stanford Healthcare. Lupus diagnosis was evaluated and confirmed via medical record review. Data were collected regarding demographics, lupus disease, current pregnancy, delivery, and reproductive history characteristics. HCQ exposure was determined by care plan, physician notes, and prescriptions. Use of low dose aspirin (ASA), a secondary exposure, was also collected during chart review. Logistic regression was used to estimate odds ratios and 95% confidence intervals adjusting for potential confounders.
Results: Due to the limited sample size, statistical analyses were underpowered. However, the association between HCQ use during pregnancy and preeclampsia and preterm birth appeared protective in unadjusted and adjusted analyses accounting for maternal age and race, renal involvement, and antiphospholipid antibody positivity and syndrome (crude OR for HCQ-PTB=0.6, 95% CI=0.3-1.4 crude OR for HCQ-PE=0.4, 95% CI=0.2-1.1). Observed effects were not consistent in ASA analyses, for example the crude OR for ASA-PTB was 1.5, 95% CI (0.6-4.1) and the crude OR for ASA-PE was 0.6 95% CI (0.2-2.1).
Conclusion: While our study does suggest protective effects with HCQ use during pregnancy against preeclampsia and preterm birth in women with lupus, our sample size limitations hindered our ability to fully investigate potential effect modification by parity. Additional research is required to achieve sufficient power to adequately investigate effect modification by factors such as antiphospholipid antibodies (aPL) and antiphospholipid syndrome (APS).
Hypothesis testing using multiple data splitting
Keywords: Statistics.

Data splitting, a tool that is well studied and commonly used for estimation problems such as assessing prediction error, can also be useful in testing problems where a portion of the data can be allocated to make the testing problem easier in some sense, say by estimating or even eliminating nuisance parameters, dimension-reduction, etc.. In single or multiple testing problems that include a large number of parameters, there can be a dramatic increase of power by reducing the number of parameters tested, particularly when the number of non-null parameters is relatively sparse. While there is some loss of power associated with testing on only a fraction of the available data, carefully selecting a test statistic may in turn improve power, though it remains unclear whether the reduction of the number of parameters under consideration can outweigh the loss of power from splitting the data. To combat the inherent loss of power seen with data splitting, methods of combining inference across several splits of the data are developed. The power of these methods is compared with the power of full data tests, as well as tests using only a single split of the data.
Identification of biogenesis factors and drug targets in the apicoplast proteome of malaria parasites
Keywords: Microbiology and Immunology.

Malaria, caused by apicomplexan parasites of the genus Plasmodium, is a devastating disease of global importance, with over 200 million yearly cases leading to more than 400,000 annual deaths. Emerging resistance to current frontline treatments necessitates continued identification of new, parasite-specific drug targets with mechanisms-of-action orthogonal to current treatments. One key source of novel targets is the apicoplast, a nonphotosynthetic, 4-membraned plastid that performs critical metabolic functions throughout the parasite life cycle. Apicoplast maintenance and biogenesis are essential processes and validated drug targets, but our limited molecular understanding of apicoplast organelle biology has hindered the discovery and development of chemotherapies that exploit these unique pathways for antiparasitic treatment. The work described in this dissertation addresses two aspects related to identifying and drugging apicoplast biogenesis factors. First, the full complement of apicoplast-localized proteins is poorly characterized, and this lack of a reliable apicoplast proteome has limited our ability to mechanistically interrogate the most novel aspects of apicoplast biogenesis. Using a combination of proximity biotinylation-based mass spectrometry and machine learning, I report a high-confidence apicoplast proteome that is rich in novel and essential functions. Critically, many of these novel proteins are parasite-specific and will likely yield new insights into mechanisms of apicoplast biogenesis. Second, even given a high-confidence proteome, methods for prioritizing the most promising candidates for drug discovery efforts are limited. This is especially so given the context that some inhibitors of apicoplast biogenesis cause an undesirable "delayed-death" phenotype resulting in a slow onset-of-action that limits the clinical utility of these drugs. Using a chemical biology approach designed to selectively disrupt apicoplast protein import, I show that this particular biogenesis pathway appears to avoid the delayed-death phenotype. This suggests that targeting apicoplast protein import may yield clinically useful antimalarials and that protein-level conditional tools are valuable resources for characterizing apicoplast biogenesis pathways. Altogether, the results of these studies will facilitate detailed investigation of the mechanisms and chemical inhibition of apicoplast biogenesis.
Identification of genetic modifiers of neurodegenerative diseases using CRISPR-Cas9 screens
Keywords: Genetics.

Neurodegenerative diseases, such as Alzheimer's disease and Amyotrophic lateral sclerosis (ALS), pose one of the greatest risks to human health. Progress towards medical interventions is hindered by a lack of understanding of the underlying cellular and molecular causes of these diseases. In this work, I describe novel CRISPR-Cas9 screening approaches in human cells and primary neurons to understand neurodegenerative diseases. Through genome-wide CRISPR-Cas9 knockout screens in human cells, I describe hundreds of genetic modifiers of the toxic dipeptide repeat proteins (DPRs) associated with the C9orf72 repeat expansion, the most common cause of ALS. The genetic modifiers discovered in the human genome-wide screens are validated in the first reported CRISPR-Cas9 knockout screen in primary mouse neurons. Together, these screens revealed a novel therapeutic target for ALS, the ER resident protein TMX2. Additionally, I describe the development of a rapid genome-wide phenotypic screens for substrate specific regulators of phagocytosis, a process recently implicated in Alzheimer's disease. By conducting eight human genome-wide CRISPR knockout screens for regulators of phagocytosis of distinct substrates, I describe the discovery of a novel universal phagocytosis regulator, the previously-uncharacterized gene NHLRC2. Lastly I show that the previously-uncharacterized Alzheimer's disease-associated gene TM2D3 can selectively influence the phagocytosis of A aggregates. Together this work describes a novel approach to studying neurodegenerative diseases using human genome-wide knockout screens to reveal the cellular mechanisms and potential therapeutic targets for neurodegenerative diseases.