VictorJuiz/thesis huggingface dataset:
Racial/Ethnic Disparities in Severe Postpartum Depression
Keywords: Racial and ethnic disparities
Postpartum depression
Major depression after delivery
Hospital care for postpartum depression
Postpartum hospitalization for depression
Department of Health Research &amp; Policy Epidemiology &amp; Clinical Research School of Medicine Stanford University
Thesis

Importance: A recent report shows upward trends of maternal hospitalizations for depression. Given the expanding non-white population and two major national obstetric priorities in the United States to improve maternal mental health and reduce disparities in maternal care, there is a pressing need to examine whether racial/ethnic disparities exist in severe postpartum depression.
Objective: To determine whether the risk of hospital based care for postpartum depression differs according to maternal race and ethnicity.
Design: A retrospective cohort study
Setting: Analysis was based on the linked data containing hospital discharge and birth certificate data from the Office of Statewide Health Planning and Development (OSHPPD) in California.
Participants: Primiparous mothers aged 15-50 years who delivered in California hospitals between 2008 and 2012.
Exposure: Race and ethnicity
Main Outcomes and Measures: Hospital encounters for postpartum depression in the first 9 months after delivery
Results: Our cohort comprises 984,167 first-time mothers. The overall cumulative incidences over the first 9 months after delivery for a principal diagnosis and a principal or secondary diagnosis of depression are 15.9 and 53.6 per 10,000 deliveries respectively. Non-Hispanic black women had the highest incidence of postpartum admission for depression and non-Hispanic Asian women had the lowest incidence. When compared to the non-Hispanic white, the risk was 2-fold higher in black women while Asian and Hispanic women had a lower risk by 20-60%. In our sensitivity analyses, similar findings were observed after excluding women with antepartum depression, or under different scenarios where women underwent postpartum hospitalization or assessment only in the emergency room. Mediation analyses revealed maternal education and insurance status may contribute to the differences up to 80%.
Conclusions and Relevance: Non-Hispanic black women may be one of the most susceptible groups that warrant more attention to monitoring and/or treating the depressive symptoms at the community setting. Further research is needed to determine causative factors for these disparities and identify ways to improve mental health care and support for African-American women after delivery.
Radio-frequency penetrable positron emission tomography (PET) insert for simultaneous PET and magnetic resonance imaging
Keywords: Applied Physics.

Combining medical imaging modalities that measure complementary, multi-parametric information such as anatomy and biochemistry about a patient's disease has been proven to provide tremendous clinical value. In recent years, hybrid positron emission tomography (PET)/magnetic resonance imaging (MRI) has risen to the cutting edge of multi-modality medical imaging technology. Unfortunately, the cost of purchasing a commercially-available integrated PET/MRI scanner is unaffordable for most healthcare providers, therefore limiting the dissemination of PET/MRI and its long-term potential. This dissertation presents the development of a radio-frequency (RF)-penetrable PET insert that can be placed into any existing MRI system to acquire simultaneous PET and MRI images. The insert approach can reduce the cost barrier for an existing MRI site to offer PET/MRI scans by leveraging its existing infrastructure. A brain-sized prototype PET insert with a 2.8-cm axial field-of-view (FoV) has been developed and its performance (energy, timing, spatial, system stability, and count rate) evaluated. Tomographic images of resolution and 3-D Hoffman brain phantoms have been acquired with the PET insert both outside and inside and simultaneous running with a 3T MR system. A second-generation RF-penetrable PET insert with an extended axial field-of-view (16 cm) and a coincidence timing resolution (< 300 picosecond full-width-at-half-maximum) capable of time-of- flight (TOF) measurement is currently under development. Two out of a total of sixteen detector modules have been developed and their performance evaluated. A novel PET detector design based on a phoswich configuration capable of both excellent coincidence timing resolution and photon depth-of-interaction measurements has also been developed and tested to improve spatial resolution uniformity of the insert.
Radiomic Biopsies: Segmentation Invariant Feature Extraction for Quantitative Imaging
Keywords:  Department of Biology
radiomics
radiomic biopsy
machine learning
chromophobe renal cell carcinoma
oncocytoma
non-small-cell lung carcinoma
recurrence
Biology
Thesis

Radiomics aims to radically improve cancer detection through automating the evaluation of potentially cancerous masses in medical images. Early evaluation of cancer is crucial to treatment decisions and to eventual survival outcomes. Radiomics approaches compute quantitative descriptors (shape, size, intensity, texture, etc.) of regions of interest in images and then build predictive statistical models from these numerical data. Computational techniques require radiologists to define regions of interest (ROI) in a process called segmentation. Radiologists often disagree on the exact outline of ROIs, which leads to unreliable data and poor models. We propose a new paradigm called “radiomic biopsies” that focuses on a spherical sample of the ROI. For intensity and texture features robust to variation in segmentation, radiomic biopsies produce samples of these features without the laborious segmentation process. Radiomic biopsies have proven to produce reliable features, but their application to predictive modeling has never been tested. To explore the application of radiomic biopsies to different disease types, we conducted a simulated case study in predicting non-small-cell lung carcinoma recurrence from chest CT scans. We then designed and implemented a novel 3D Radiomic Biopsy Tool for differentiating oncocytoma and chromophobe renal cell carcinoma. Across both studies, we showed that radiomic biopsies perform similarly to full segmentations on proven predictive tasks and can successfully differentiate subtypes in novel tasks.
Raman Spectroscopy Deconvolution Using Machine Learning
Keywords: Raman spectroscopy
Convolutions (Mathematics) > Data processing
Machine learning > Mathematical models
Text
Thesis

Proper characterization of a tumor is essential for informing treatment and assessing prognosis for the patient. The concentration of certain biomarkers, presence or absence of specific mutations, and even the pattern of distribution of biomarkers throughout the tumor can be extremely important in determining the aggressiveness of the tumor. For example, tumors that are more homogenous tend to be less aggressive and have a better prognosis than those that are more heterogenous. Therefore, we seek to image multiple biomarkers in vivo using targeted dyes.
However, imaging the tumor multiple times in series without an invasive biopsy is much too time consuming. Usually, for these targeted dyes, imaging occurs 5-7 days after the imaging agent is administered, meaning that imaging any more than one or two biomarkers would be prohibitively lengthy, possibly affecting timely treatment of the tumor. Therefore, we can utilize unique surface-enhanced resonance Ra- man scattering (SERRS) particles to target distinct biomarkers. In order to determine the concentration of each particle at each point, the individual spectra need to be deconvolved from the multiplexed spectra.
Conventional methods for separating the spectra, nonnegative least squares (NNLS), have been successful for low numbers of spectra. However, NNLS must calculate the pseudoinverse, and as the number of spectra increases, the condition number for that matrix increases quickly. Thus, past five spectra or so, using NNLS to deconvolute the spectra becomes untenable. Thus, we aim to use machine learning as an alternative to NNLS, with the potential to expand spectral deconvolution to more spectra accurately and quickly during run time.
Rational design of ribozyme switches through big data and machine learning
Keywords: Bioengineering.

RNA switches are a broad class of functional RNAs that support conditional regulation of gene expression. These genetic switches have broad application in creating biological systems responsive to changes in their environment - a situation that occurs frequently in the fields of metabolic engineering, environmental sensing, and therapeutics. These switches gain their function from both their structural conformation and their sequence of functional regions, implying that an improved elucidation of relationships between structure, sequence, and function can be used to improve our capacities for de novo design. One type of RNA switch is the ribozyme switch, which changes its self-cleavage activity based on the presence of the target ligand. Here we leverage sequencing data and machine learning to relate the sequence and structure of biological molecules to their function and develop models that predict the function of novel ribozyme switches. In the course of our work, we generated data on the activity of hundreds of thousands of ribozyme switch sequences. Using automated structural analysis and machine learning, we leveraged this wealth of sequence data to develop predictive models that forecast the in vivo activity of a functional RNA sequence using the sequence of functional regions. We have used these models for the de novo design of novel ribozyme switches that exhibit changes in expression activity upon introduction of a target ligand. Our work demonstrates how to use computational tools to turn RNA sequences into quantitative features that represent important sequence and structural motifs and how to use those features to develop models that can learn how the interactions of these motifs translates to device function. We have integrated the model for predicting switch activity into design software that will provide a broadly accessible tool for designing custom ribozyme switches.
Ready, Set, Bio (Jet): A Policy Recommendation for Indian Commercial Aviation
Keywords:  Public Policy Program
Stanford University
Humanities and Sciences
Public Policy Program
biofuels
civil aviation
emissions
traditional fuel
routes
short haul
medium haul
long haul
taxation structure
jatropha
Thesis

India is a country with tremendously rich culture, history and economic growth. India’s aviation industry is the fastest growing in the world. However, it is also responsible for a large share of overall greenhouse gas emissions – an especially relevant problem in a country where a many people are dying due to air pollution every year. This proposal contains a cost-benefit analysis of adopting biofuel, also known as Sustainable Aviation fuel (SAF), in the commercial aviation sector as a replacement to Aviation Turbo Fuel (ATF) which is currently used. A thorough investigation shows that the adoption of biofuel will significantly reduce the aviation sector’s contribution to greenhouse gas emissions, specifically CO2, HC, CO and SOx emissions, under certain taxation assumptions. This will allow India’s aviation industry to play a role in reducing air pollution and ensuring that the country’s population remains healthy and is able to contribute to India’s economic growth. The spillover benefits of adopting biofuels also exceed the costs, therefore contributing positively to work-force participation and productivity.
The real-alternative school paradox : a California continuation high school's struggle to be something different in a universe of real schools
Keywords: Education.

Though they serve upwards of 100,000 students in a given school year, California continuation high schools remain marginal to both educational research and practice. As California's primary dropout prevention response for "at-risk" high school youth, continuation high schools allow students acquired into persistent school failure a second chance at obtaining a high school diploma. They have served various functions throughout their one-hundred-year existence, but remain largely invisible, acting as convenient depositories for the problems created by an American schooling system rooted in competition and social sorting. My dissertation examines the paradoxical question of what it means to be a "real-alternative" school. It pursues answers via the presentation of an institutional history of the California continuation high school system, through theoretical examination of what it means—in the words of Mary Metz (1989)—to be and not be "real school, " and via a descriptive case study of Bridgeview High School, a continuation school whose staff attempts to balance the pull of being "real" with the promise of being "alternative" through the creation and practice of social justice inspired project-based learning. The study concludes with practical recommendations for educational researchers, state and district-level policymakers, and an impractical recommendation for teachers: to teach absurdly.
Reciprocity and legislative organization
Keywords: Business.

I explore the implications of a novel assumption about legislators' preferences: that they, like most human beings, have a preference for reciprocity. That is, they like to help those who have helped them in the past and harm those who have harmed them in the past for its own sake. The first chapter highlights that the preference for reciprocity implies congressional parties face a tradeoff between giving their leaders the resources necessary to produce collective goods and ensuring that ineffective leaders can be removed from office. The second chapter shows that the legislature faces a tradeoff between ensuring allocative efficiency by using discretionary authority and minimizing costly interpersonal conflict through deference to rules. The third chapter provides empirical evidence for the preference for reciprocity by studying how legislators behave immediately before they exit the chamber.
Reconsidering the electron-phonon problem
Keywords: Physics.

One of the most important interactions in a solid is that between electrons and the vibrational modes of the underlying lattice (phonons). This interaction determines many of the familiar features of conventional metals, e.g. resistivity at elevated temperatures, as well as their superconducting transition temperature, Tc. From a theoretical standpoint, the electron-phonon problem was considered to be solved 60 years ago, thanks to the pioneering work of Migdal and Eliashberg. We have revisited this problem using a combination of numerical and analytic techniques, and I will show that this "solved" problem harbors basic features that have not been properly understood. I will show that the Migdal-Eliashberg approach works remarkably well for sufficiently weak coupling but breaks down entirely as the coupling strength is increased (even while the nominal condition for its validity remains intact), giving way to a qualitatively new regime of strong coupling physics. I will discuss the implications of these results for superconductivity and argue they suggest an approximate, universal upper bound on Tc in conventional metals.
Reconstitution of B cell somatic hypermutation in yeast for directed evolution
Keywords: Bioengineering.

Targeted mutagenesis is a powerful technique used by nature and scientists to generate biological diversity and evolve diverse biological properties of proteins such as enzymes and antibodies. In vivo targeted mutagenesis enables rapid and continuous evolution of desired phenotypes directly in a host organism. However, existing in vivo mutagenesis tools are limited by low mutation rates and arduous gene specific gRNA expression. We describe a new method for TaRgeted In vivo Diversification ENabled by T7 RNAP (TRIDENT). TRIDENT is a platform for targeted, continual, and inducible diversification at genes of interest in yeast at mutation rates up to one-million fold higher than natural genomic error rates. TRIDENT targets natural and engineered mutagenic deaminase enzymes to precise genetic loci by fusion to T7 RNA polymerase, resulting in mutation tracks of controllable size from tens to thousands of base pairs, dependent on the positions of a T7 promoter sequence. Mutation diversity is further increased by targeting of DNA repair factors to the sites of deaminase-driven mutation, enabling sustained mutation of all four DNA nucleotides at rates greater than one substitution mutations per thousand bp, a more than 10-fold improvement over recent state-of-the art in vivo mutagenesis systems. We demonstrate application of TRIDENT to entirely replace ex vivo mutagenesis by applying it to correct point mutations in enzymes, fluorescent proteins, and evolve a red-shifted fluorescent protein. TRIDENT is a powerful in vivo mutagenesis platform and will accelerate protein engineering.
Regulation & control of multicell behavior : interactive swarm control, collective migration, and synthetic aggregation
Keywords: Bioengineering.

This thesis covers three separate projects investigating the mechanisms and applications of multicellular systems. The first project is a pioneering study in the application of swarms of the protist Euglena gracilis in developing interactive and educational biotechnology. I demonstrate we can control the taxis of these single-celled phototactic organisms with directional light stimuli. Furthermore, I discuss the utility of this phenomena in STEM education through the LudusScope - a do-it-yourself (DIY) platform that includes lessons in electronics, fabrication, programming and biology. I also report on the feedback from both students and teachers about the applicability of the platform in education. The second project discusses the role of the Epithelial Cell-Adhesion Molecule (EpCAM) on migration of multicelluar sheets of epithelial cells. I describe the phenotypic change in sheet migration due to over and under-expression of EpCAM, and report on several protein-protein interactions that are responsible for mediating this change in phenotype. In the last project I discuss the application of synthetic cell-cell adhesion proteins on pattern formation in multi-cell swarms of Escherichia coli. I describe the types of patterns formed by different kinds of cell adhesions, as well as the dynamics of this phenomena. Finally I discuss theoretical models of the phenomena explored through numerical simulations.
Regulation and function of transcription factor dynamics during adipogenesis
Keywords: Chemical and Systems Biology.

A healthy metabolism requires proper fat tissue function. Thus, the generation of new fat cells through the process of adipogenesis is a critical component in the regulation of metabolic homeostasis and change. Prior work has established an extensive list of key transcriptional regulators of the adipogenic differentiation process including the important early regulator, CEBPB, and the master regulator, PPARG. However, the expression and activation dynamics of these transcriptional regulators along with the functional consequences of the dynamics remain poorly studied. A main challenge has been the lack of tools and techniques to study the dynamics in single cells in the context of adipogenesis. In this thesis, I aimed to overcome these challenges and address the important question of how the dynamics of key transcription factors regulate the process of adipogenesis. I present two works that introduce new fluorescent cell lines and live cell imaging pipelines that enable the quantitative analysis of transcription factor dynamics during adipogenesis. I first demonstrate that slow PPARG dynamics enable pre-adipocyte cells to regulate the degree of fat cell differentiation in response to different patterns of stimulus application. I show that this regulation depends on combination of fast and slow acting positive feedback loops centered on PPARG. This network architecture allows cells to discriminate between pulsatile and continuous stimulus patterns and may explain why loss of pulsatile glucocorticoid patterns in the body is so closely associated with obesity. I then used measurements of PPARG dynamics over the course of the cell cycle to identify a time range during adipogenesis when the decision to proliferate competes with the decision differentiate. Moreover, dynamic measurements enabled me to measure the point in time where cells committed to the differentiated state and I show that this commitment point corresponds to when differentiating cells permanently withdrew from the cell cycle. Taken together my work demonstrates how measuring the dynamics of key regulators of adipogenesis suggested new models for how the number of adipocytes is controlled in fat tissue. Importantly, our findings have more general implications for how other tissues can control the number of terminally differentiated cells since both the response to pulsatile hormonal signals and cell cycle control are general features shared by cells throughout the body.
Relationships between Memory Retrieval, Media Multitasking, and Attention: An EEG/Pupillometry Approach
Keywords: Symbolic Systems Program
Stanford University
Thesis

When an individual retrieves a memory, trial-level fluctuations between attention lapses, and memory may interact with subject-level differences in constructs such as media multitasking and sustained attention. I will present data and reflections on my master’s research project that lend support to this theoretical framework. Concurrent EEG+pupillometry was recorded during an encoding/retrieval task with 80 young adults to examine how (a) multimodal trial-level indices of attention lapsing relate to goal coding and memory, and how (b) trait differences in self-reported media multitasking and task-based sustained attention may contribute to these interactions. Pre-trial lapses of attention as recorded by tonic changes in alpha and theta oscillatory power and pupil diameter predicted retrieval accuracy; decreases in pupil diameter and theta power and increases in alpha – assays of lapsing – predicted retrieval misses vs. hits. Subject-level increases in media multitasking were related to decreases in sustained attention and retrieval accuracy using continuous and extreme group approaches. These results suggest that trial-level interactions in attention-control-memory and subject-level differences in media multitasking and sustained attention may help explain how an individual remembers.