VictorJuiz/thesis huggingface dataset:
Designing integrated infrastructure for sustainability

Increasing sustainability of energy systems in urban and suburban environments are a multifaceted problem with numerous approaches. Much research has been devoted to focusing on either the supply or demand side of a single infrastructure system, while limited work has been done on the co-optimization of the energy system. This paper tailors the proven urban optimization system to a suburban environment using an idealized military base near Helena, MT as case study. This research focuses on the concurrent design of optimal building mix and the systems supplying heating, cooling, and electricity in a constrained suburban environment. Using a Genetic Algorithm to develop over 400,000 base designs, the model incorporates 21 generic and 13 military specific building types, 32 combined heating and power engines, and 16 chillers. The results show the ability to obtain a variety of designs that fit within the required community building use needs while minimizing the life cycle cost and social cost of carbon

Advisor: Lepech Michael
Determining the bacterial response to environmental stresses

Bacteria are highly resilient to environmental insults due to their sophisticated abilities to adapt to diverse stressors. As a primary level of response, they carefully regulate thousands of genes in response to changes in their surroundings. Moreover, evolution can provide genetic enhancements to stress adaptation. Perhaps less appreciated are physiological adaptations, often occurring on short time scales that improve growth and survival in dynamic environments. Most experimental studies of bacteria are carried out in near ideal conditions for growth, which are ultimately poor replicas of the harsher natural environments in which cells typically exist. Expanding our knowledge of how bacteria function in inhospitable and dynamic environments is crucial to understanding and capitalizing on bacterial physiology. In this thesis, I provide multiple novel perspectives on physiological adaptation to stress in bacteria. Chapter 1 provides an introduction to the ways bacteria can adapt to environmental conditions and methods for measuring adaptation. In chapter 2, I investigate how starvation introduces heterogeneity in a populations of cells, in which different subpopulations exhibit vastly different potentials for growth. In chapter 3, I explore the genetic mechanisms by which bacteria adapt to a variety high osmolarity conditions in a long-term laboratory evolution experiment. Chapter 4 concludes with a summary of my work and a discussion of future directions with broad impacts for the microbiology field

Keywords: Microbiology and Immunology.
Advisor: Huang Kerwyn Casey
Amieva Manuel
Fischbach Michael 
Sonnenburg Justin
Determining the Role of the Nlgn3 Mutation R451C on Myelin-forming Cell Dynamics in Autism Spectrum Disorders

Autism Spectrum Disorders (ASDs) are a broad spectrum of neurodevelopmental conditions with high prevalence but no effective therapy. Recently, mutations in the synaptic protein neuroligin-3 (Nlgn3) have been associated with ASDs, resulting in disrupted neuronal connectivity and altered neural circuit function. Although decreased white matter especially in the corpus callosum (CC) has been observed in patients with autism, the effect of autism-related mutations such as Nlgn3R451C on myelination by myelin-forming glial cells called oligodendrocytes has never been studied. Previous work has shown that this mutation leads to decreased Nlgn3 protein levels by 90% at the synapse, suggesting that it may disturb synapse formation between neurons and oligodendrocyte precursor cells (OPCs). In this work, we aim to determine how Nlgn3R451C alters myelination and OPC dynamics and to establish whether this mutation affects the adaptive proliferative response of OPCs to neuronal activity. Using immunostaining and fluorescence confocal microscopy in a conditional knock-in endogenous mouse model, this study reveals that Nlgn3R451C does not alter CC white matter volume. Furthermore, Nlgn3R451C is found to decrease the number of OPCs in white matter CC, but not in gray matter cortex, suggesting particular vulnerability for white matter OPCs. The OPC response to optogenetically increased neuronal activity shows unaltered proliferation despite potential disruption in neuron-to-OPC synapses in Nlgn3R451C. This study sheds light on the link between autism and myelin dynamics and establishes Nlgn3R451C-related myelin impairments that contribute to autism pathology.

Keywords:  Department of Biology
oligodendrocyte
myelination
neuroligin-3
Autism Spectrum Disorders
myelin plasticity
Thesis
Advisor: Monje Michelle
Shen Kang
Developing computational and experimental tools to understand chromatin dynamics and regulation

The human genome is condensed yet accessible, allowing cells to execute complex logic needed for cellular programs. The dynamic physical organization of the genome is connected to its instantaneous transcriptional profile. Current sequencing technologies can only recover a static and highly-averaged picture of these dynamic processes. Identification of dynamic signatures from chromatin motion requires an imaging and analysis platform for simultaneous tracking of genes and their transcriptional state in live cells. Advances in microscopy have provided a great opportunity to obtain such information. Unfortunately, segmenting overlapping nuclei is still a major challenge for single cell microscopic measurement. We first reported a deep-learning based model 'Nuclear Segmentation Tool' (NuSeT) that accurately segments multiple types of nuclei from imaging data. Using a hybrid architecture that consists of U-Net and Region Proposal Networks (RPN), followed by watershed processing, NuSeT has achieved superior performance in delineating nuclear boundaries in images of varying complexities. NuSeT further improves nuclear detection and reduces false positives by employing foreground normalization and additional training on synthetic images containing non-cellular artifacts. NuSeT also addresses common bottlenecks in nuclear segmentation such as limited training samples, variability in nuclear signal and shapes, and sample preparation artifacts. NuSeT consistently fares better in generating accurate segmentation masks and assigning boundaries for touching nuclei compared with other state-of-the-art segmentation models. Next, we developed an imaging platform for simultaneous real-time visualization of locus dynamics and transcriptional output. Using a CRISPR/Cas9 based gene knock-in strategy, we have introduced MS2 hairpin cassettes into native genes of interest, which can reveal their transcriptional states. To track these loci for extended periods of time at high spatiotemporal resolution, we have generated optical tag ArrayG/N fusions of the nuclease deactivated Cas9 (dCas9) and a polycistronic cassette of repeating tRNA-sgRNA delivered by lentivirus. This platform enables sustainable tracking of non-repetitive genomic loci. We have further modified ArrayG/N tags to recruit chromatin effectors at selected genomic sites that makes this experimental platform particularly well suited for dynamic monitoring of epigenetic manipulations on selected genes. Using this platform, we have measured dynamic signatures of chromatin accessibility. We have also shown that the motion of gene loci are further constrained when they are transcriptionally active. These image analysis and cellular engineering tools can be used to answer other outstanding questions about the chromatin and gene regulation dynamics

Keywords: Bioengineering.
Advisor: Liphardt Jan 
Bintu Lacramioara 
Covert Markus 
Spakowitz Andrew James
Developing functionalized virus like particles for circulating tumor cell detection and enumeration

Circulating Tumor Cells (CTCs) are released from a primary tumor and circulate in the vasculature to form seeds for metastatic colonization at distant locations. There is strong evidence for their use as prognosis markers to indicate the extent of disease progression in cancer patients. For example, the accurate enumeration of CTCs could provide a minimally invasive method to frequently monitor how the cancer responds to therapeutic interventions. Currently there is only one FDA approved CTC assay, CellSearch, but its clinical acceptance has been limited. We seek to develop a point-of-care assay that would detect CTCs based on tumor specific markers. As a model system, we are targeting prostate specific membrane antigen (PSMA), a glycoprotein that is overexpressed on a majority of metastatic prostate cancer cells. The Swartz Lab has developed virus-like particles (VLPs) derived from the Hepatitis B core protein. The VLPs have been stabilized by an engineered disulfide network and display a non-natural amino acid for precise surface augmentation. Using this VLP as a scaffold, nanoparticles (NP) have been developed that can specifically target prostate cancer cells. These NPs are surface functionalized by: a) scFv antibody fragments derived from the PSMA targeting J591 antibody and b) the Gaussia princeps luciferase to provide a luminescent signal. We present work showing feasibility for a point-of-care, highly parallel CTC assay based on these highly engineered VLPs. This technology can facilitate frequent monitoring of cancer patients to ensure that the best possible interventions are employed

Keywords: Chemical Engineering.
Advisor: Swartz James R. 
Dunn Alexander Robert
Developing high-performing business models

Strategy and innovation scholars point to the rising importance of business models for firm performance. While prior research offers some insight into high-performing business models, it largely focuses on established firms with stable business models. Yet, this overlooks how entrepreneurial ventures develop and scale novel business models. This dissertation addresses this gap with three closely linked studies. The first is a comprehensive review of prior literature linking business models to firm performance. The second uses a novel theory-building methodology — machine learning and multiple cases -- to fit revenue models (i.e., value capture) with underlying activities (i.e., value creation) in high-performing business model configurations. The third is a longitudinal multiple-case theory-building study that unpacks how entrepreneurs build scalable business models in nascent markets. Jointly, the studies in this dissertation offer rich theory regarding how entrepreneurs can effectively develop and scale novel business models. Overall, this research contributes to literature on strategy, innovation, and entrepreneurship, as well as to practice

Keywords: Management Science and Engineering.
Advisor: Eisenhardt Kathleen M.
Byers Thomas (Thomas H.)
Eesley Charles 
Katila Riitta
Developing rational combination therapeutic strategies for diffuse intrinsic pontine glioma

Diffuse intrinsic pontine glioma (DIPG), recently reclassified as diffuse midline glioma (DMG), H3K27M mutant, is a universally fatal disease. Despite decades of clinical efforts, radiotherapy remains the only transiently effective therapy. Currently, median survival remains 11 months with 90% of children dying within 2 years of diagnosis. In search of effective therapeutic strategies, we developed a method to generate patient-derived DMG cell cultures from early post-mortem tissue donations. Using these cultures, we performed systematic quantitative high-throughput screens (HTS) of 2,706 approved and investigational drugs. This effort generated 19,936 single-agent dose responses and inspired HTS-enabled drug combination assessments encompassing 9,195 drug-drug assays. Top combinations were validated in vitro across patient-derived cell cultures representing the major DMG genotypes and in vivo across patient-derived xenograft models. The combination of the multi-histone deacetylase (HDAC) inhibitor panobinostat and the proteasome inhibitor marizomib emerged as a promising therapeutic combination. Transcriptional and metabolomics surveys demonstrated an NAD-dependent metabolic catastrophe driving the combination-induced cytotoxic response. These studies provide comprehensive single- and combination-agent drug screening data for DIPG and identify a candidate therapeutic strategy for clinical translation. We also explored the immune cell microenvironment of DIPG in comparison to adult glioblastoma (aGBM) using primary tumor tissue donations. Previous studies found that primary DIPG tissue contains numerous tumor-associated macrophages, and substantial work has demonstrated a significant pathological role for adult glioma-associated macrophages. However, pediatric and adult glioblastoma are molecularly and genomically distinct, raising the question of whether they also have distinct interactions with the tumor immune microenvironment. We found that the leukocyte (CD45+) compartment in primary DIPG tissue is predominantly comprised of CD11b+ macrophages, while other cells (e.g. CD3 lymphocytes) can be found in aGBM. RNA sequencing of isolated tumor-associated macrophages revealed common gene programs related to extracellular matrix remodeling and angiogenesis, but demonstrated that DIPG-associated macrophages express fewer inflammatory factors. We also found that patient-derived DIPG cell cultures secrete fewer cytokines and chemokines than patient-derived aGBM cultures, and confirmed the low to absent expression of these factors in DIPG bulk and single-cell RNA sequencing data. These observations suggest an ineffective inflammatory response by DIPG-associated macrophages, which may be related to the low inflammatory signature of DIPG tumor cells. These findings also highlight that differences between DIPG and aGBM extend into their immune microenvironment, which carries implications for the development and application of immunotherapy-based treatments for DIPG

Advisor: Monje-Deisseroth Michelle
Engleman Edgar G.
Palmer Theo
Wyss-Coray Anton
Developing tools for pluripotent stem cell-based therapies using AAV6/Cas9-mediated genome editing

The application of AAV6/Cas9-mediated genome editing to human pluripotent stem cells (hPSCs) offers the opportunity for efficient in vitro disease modeling, correction of disease-causing mutations, and a platform for engineering novel properties for clinical applications. Here we describe how to edit the genome of hPSCs, ranging from modifying single base pairs to the integration of large transgene cassettes. We then show how with this protocol we can build safety systems to minimize the risk of hPSC-derived teratoma formation. We show how orthogonal safety switches can be used prevent and intervene in the case of an adverse event following the transplantation of hPSC-derived cells. We also demonstrated the utility of this technology by creating isogenic series of the Huntington CAG repeat to model the pathogenic phenotype in vitro. Finally, we show how we can engineer hPSCs to secrete neurotrophic factors such as BDNF and GDNF that have been shown to ameliorate the symptoms of the disease

Keywords: Stem Cell Biology and Regenerative Medicine.
Advisor: Porteus Matthew H.
Cyert Martha S.
Loh Kyle
Palmer Theo
Development and application of an intercellular immune interaction network

This dissertation describes the development of ImmunoGlobe, a manually curated intercellular immune interaction network extracted from the Janeway's Immunobiology textbook. I show that ImmunoGlobe recapitulates known features of the immune system and can be used to discover novel immune pathways as well as to predict the responses of immune cells to stimuli. I then use ImmunoGlobe to perform network analysis of SARS-CoV-2 infection, which reveals immune mechanisms characteristic of general COVID-19 infection and further identifies active immune pathways that differentiate COVID patients based on severity and gender. Finally, I describe the results of two studies of antitumor immunity in mouse models of lymphoma. Assessing the findings in the context of the ImmunoGlobe network reveals previously unnoticed similarities in the immune response across both studies, suggesting a common immune mechanism and illustrating the ability of network analysis to provide novel insight into existing immune data. We have made the ImmunoGlobe network publicly available as an interactive network and fully computable graph, and have demonstrated its utility in extracting mechanistic insight both from high-throughput and traditional immunologic studies. Collectively, this work will enable the creation of systems immunology tools that will allow us to predict the outcome of complex immune interactions, providing mechanistic insight that allows us to precisely modulate immune responses in health and disease

Advisor: Engleman Edgar G.
Mallick Parag
Bendall Sean
Gentles Andrew J. 
Graves Edward (Edward Elliot)
Development of accessible quantum chemistry through virtual reality and cloud computing

The key bottleneck in many ab initio computational chemistry calculations is the electronic structure, i.e. what are the electrons doing in response to the atomic nuclei and/or other external influences. This is particularly problematic when considering that many electronic structure calculations are needed in most workflows, such as geometry optimization or molecular dynamics trajectories. As a result, many large or accurate calculations rely on high-performance computing (HPC) systems, such as large distributed systems (e.g. supercomputers with many compute nodes) or specialized coprocessors [e.g. graphical processing units (GPUs)]. The current state of scientific software for quantum chemistry centers on monolithic packages designed to run on remote clusters with batch job submission; however, this strategy limits the speed of method development and creates a significant barrier for educating aspiring chemists and the general public. In line with recent trends of code abstraction and encapsulation in the community, I present my work on a new socket-based interface for our GPU-accelerated electronic structure package, and furthermore my development of a cloud-based framework for distributing electronic structure calculations (on either academic HPC systems or renting commercial cloud resources) utilizing this new interface. I will demonstrate how this platform was applied to several key quantum chemistry workflows that require high-throughput calculations, including dataset generation, excitation energy transfer in multichromophoric systems, and automated reaction network discovery. Additionally, I detail the advancements made in real-time ab initio interactive molecular dynamics (AI-IMD) simulations to use virtual reality (VR) headsets to provide a virtual playground for interacting with quantum chemistry for students and other non-expert users

Keywords: Chemistry.
Advisor: Martinez Todd J. (Todd Joseph)
Chidsey Christopher E. D. (Christopher Elisha Dunn)
Markland Thomas E.
Development of DARS II for the measurement of pressure dependent quality factor and compressibility of small rock samples

Sample quality factor remains largely ignored due to difficulties in quantifying and repeating results. This thesis describes a Differential Acoustic Resonance Spectroscopy system, (DARS II), an acoustic method developed to study sample quality factor as a function of confining pressure at a kilohertz frequency scale. The work is subdivided into five parts: A review of the proof-of-concept system, DARS I; DARS II design and construction; DARS II empty-system characterization; Non-porous sample compressibility and attenuation estimates as a function of pressure; and Shale sample quality factor and attenuation estimates as a function of pressure. The primary contribution of this study is the design and construction of a system which estimates the resonant frequency, amplitude, and linewidth of porous and non-porous media with variable confining pressure at about 1000 Hz. The DARS II resonant frequency and linewidth measurements are used to estimate sample compressibility and quality factor with change in pressure measured at low frequencies. The method may be applied to regular or irregular shaped non-porous and porous samples

Keywords: Geophysics.
Advisor: Harris Jerry M.
Dvorkin Jack
Mukerji Tapan
Zoback Mark D.
Development of instaFLARE Technology for Immediate Cell Activation Reporter Signal

Changes in intracellular calcium are a hallmark of many cellular processes, including spiking activity in neurons, activation of G-protein coupled receptor cascades, or metabolic regulation in the mitochondria. It would be beneficial to have a technology that can rapidly and stably label cells exhibiting an increase in intracellular calcium following some stimulus. These cells could then be processed and analyzed to reveal calcium-dependent changes in gene expression or protein localization. There are various biotechnological tools that label activated cells after elevated intracellular calcium with a stable read-out, such as photo- conversion of a calcium-sensitive fluorophore (CaMPARI) or a calcium-dependent transcriptional reporter (FLARE); however, these tools either have limited sensitivity or require approximately 9 hours to provide the transcriptional read-out of activity. An efficient cell labeling tool that generates a stable signal within minutes would benefit researchers interested in investigating dynamic processes in cells that take place quickly after periods of high intracellular calcium. Here, we present instaFLARE, a novel technology that addresses the need for rapid and stable reporter expression; by using a reconstitutable, split infrared fluorescent protein (Split-IFP) instead of a transcription-initiated reporter gene, it is possible to engineer a tool that has much faster kinetics of reading out cells undergoing high intracellular calcium. instaFLARE’s faster time scales of activation and cell labeling has been tested by introducing the engineered proteins into HEK293 cells, exposing the cells to blue light and calcium at the same time, followed by subsequent imaging of the reconstituted IFP reporter at different time stamps after light and calcium introduction. In the future with further engineering, instaFLARE will allow for quick labeling of activated cells, which will enable researchers to investigate dynamic changes in the cell after rises in calcium that would otherwise be undetectable.

Keywords:  Department of Biology
fluorescent labeling
calcium labeling
split infrared fluorescent protein
biology
Thesis
Advisor: Ting Alice Y.
Gitler Aaron D.
Shen Kang
Development of Subject Matter Knowledge and Pedagogical Content Knowledge Through High-Level Cognitive Mathematics Tasks: The Case of a Teacher Education Program in Chile

This study seeks to understand whether the use of high-level cognitive mathematics tasks supports the development of subject matter knowledge (SMK) and pedagogical content knowledge (PCK) in pre-service teachers. It analyzes curriculum materials implemented in the content-focused mathematics methods courses in a teacher education program in Chile. In comparing the curriculum materials across the five courses, inconsistencies are found among the PCK components covered. Another result is that the Chilean curricular and teacher education standards are present in all the analyzed syllabi; however, they are not equally operationalized in the in-class tasks or the graded assignments of those same courses. This study also shows that there is little connection between the level of cognitive demand and the type of mathematics in-class tasks in the courses analyzed. Finally, the data reveal that the easier the mathematics content of the course, the larger the percentage of components related to PCK. In order to improve the effectiveness of teacher education programs for future mathematics teachers, Chilean education policies should more explicitly specify how to connect SMK and PCK in those programs and courses.

Keywords: Chile
teacher education
pedagogical content knowledge
subject matter knowledge
curricular standards
Stanford Graduate School of Education International Education Policy Analysis
Thesis