Robust 6D Fluorescence Microscopy

Single-Molecule Orientation Localization Microscopy (SMOLM) measures the positions and orientations of single fluorophores precisely, approaching fundamental classical and quantum limits. However, a disadvantage of SMOLM is the time-consuming nature of its acquisition and reconstruction processes. In my thesis, I introduce an innovative framework that simplifies the detection and estimation algorithms used in SMOLM into a computationally efficient high-dimensional deconvolution algorithm. This framework extracts six-dimensional information of continuous biological structures from just a single camera image (i.e., a single shot). While this method is diffraction limited, unlike conventional SMOLM algorithms, it nevertheless offers accurate and precise estimations of the orientations of collections of molecules. Crucially, it is suitable for capturing dynamic changes in biological structures, thereby broadening its applicability in scientific investigations

Learning to Disagree: The Surprising Path to Navigating Differences with Empathy and Respect

Are you discouraged by our divided, angry culture, where even listening to a different perspective sometimes feels impossible? If so, you\u27re not alone, and it doesn\u27t have to be this way. Learning to Disagree reveals the surprising path to learning how to disagree in ways that build new bridges with our neighbors, coworkers, and loved ones--and help us find better ways to live joyfully in a complex society. In a tense cultural climate, is it possible to disagree productively and respectfully without compromising our convictions? Spanning a range of challenging issues--including critical race theory, sexual assault, campus protests, and clashes over religious freedom--highly regarded thought leader and law professor John Inazu helps us engage honestly and empathetically with people whose viewpoints we find strange, wrong, or even dangerous. As a constitutional scholar, legal expert, and former litigator, John has spent his career learning how to disagree well with other people. In Learning to Disagree, John shares memorable stories and draws on the practices that legal training imparts--seeing the complexity in every issue and inhabiting the mindset of an opposing point of view--to help us handle daily encounters and lifelong relationships with those who see life very differently than we do. This groundbreaking, poignant, and highly practical book equips us to: Understand what holds us back from healthy disagreement Learn specific, start-today strategies for dialoguing clearly and authentically Move from stuck, broken disagreements to mature, healthy disagreements Cultivate empathy as a core skill for our personal lives and our whole society If you are feeling exhausted from the tattered state of dialogue in your social media feed, around the country, and in daily conversations, you\u27re not alone. Discover a more connected life while still maintaining the strength of your convictions through this unique, often-humorous, thought-provoking, and ultimately life-changing exploration of the best way to disagree

Voting Under the Federal Constitution

There is no explicit, affirmative right to vote in the federal Constitution. At the Founding, States had total discretion to choose their electorate. Although that electorate was the most democratic in history, the franchise was largely limited to property-owning White men. Over the course of two centuries, the United States democratized, albeit in fits and starts. The right to vote was often expanded in response to wartime service and mobilization.A series of constitutional amendments prohibited discrimination in voting on account of race (Fifteenth), sex (Nineteenth), inability to pay a poll tax (Twenty-Fourth), and age (Twenty-Sixth). These amendments were worded as anti-discrimination provisions with nearly identical language. Although they vastly expanded who was eligible to vote, these constitutional amendments’ negative framing permits States to disenfranchise voters through facially neutral requirements, such as felon disenfranchisement laws.Starting in the 1960s, the Supreme Court relied on the Equal Protection Clause—rather than the voting rights amendments themselves—to protect the “fundamental” right to vote, applying strict scrutiny to voting qualifications. This line of cases comes closest to recognizing an affirmative right to vote that receives protection even absent an invidious facial classification. These decisions, combined with the Voting Rights Act of 1965 (VRA) and the civil rights movement, helped eradicate Jim Crow.This chapter charts how the United States democratized, and its focus is on voting qualifications under the federal Constitution. As this chapter demonstrates, democratization has been accomplished through federal constitutional amendments, state-law changes, judicial decisions, and popular support during or shortly after wartime

ERISA Principles

ERISA, the detailed and technical amalgam of labor law, trust law, and tax law, directly governs trillions of dollars spent on retirement savings, health care, and other important benefits for more than 100 million Americans. Despite playing this central role in the US economy and social insurance systems, the complexities of ERISA are often understood by only a few specialists. ERISA Principles elucidates employee benefit law from a policy perspective, concisely explaining how common themes apply across a wide range of benefit plans and factual contexts. The book\u27s non-technical language and cross-cutting conceptual organization reveal latent similarities and rationalize differences between the regulatory treatment of apparently disparate programs, including traditional pensions, 401(k), and health care plans. Important legal developments - whether statutory, judicial, or administrative - are framed and analyzed in an accessible, principles-centric manner, explaining how ERISA functions as a coherent whole

Leveraging protein dynamics to drug filovirus protein-nucleic acid interactions using simulations and experiments

Drug discovery targeting protein nucleic acid (PNI) and protein-protein interactions (PPI) remains a difficult task. How to identify druggable conformations and discover compounds binding to these conformations is an unsolved problem. Here, I describe how we apply computational and experimental approaches to probe the conformational landscape of a key immune antagonist protein from the Zaire ebolavirus. Viral Protein 35 (VP35) binds to the viral pathogen associated molecular pattern, double stranded RNA (dsRNA), and blocks activation of the interferon (IFN) response. Long time scale molecular dynamics simulations reveal that VP35 adopts an alternative conformation which opens a pocket absent in experimental structures, a cryptic pocket. Simulations predict and we experimentally validate that this pocket exists and is allosterically coupled to the dsRNA binding site. High throughput screening identified new chemical matter that inhibits dsRNA binding. Subsequent structural and biochemical studies show that the inhibitors target the dsRNA binding site. One inhibitor also binds to the VP35 cryptic pocket. Our data shows the usefulness of considering protein conformational heterogeneity for drug discovery targeting PNIs and PPIs

Parent and Child Wellbeing in a Humanitarian Context By Flora Cohen,

There are increasingly more children and families affected by conflict and displacement. Conflict and displacement can cause severe mental health challenges and social fragmentation. Programs that support the mental health and wellbeing of communities and families living in humanitarian contexts are vital to improving future outcomes. This dissertation utilizes evidence from a psychosocial support intervention designed to support caregivers living in Kiryandongo refugee settlement, Uganda. Findings from this study highlight the importance of utilizing children’s voices in the development of programs, equipping researchers with instruments that have been tested for reliability and validity in differing contexts, and evaluating differing program outcomes for population subgroups. Study findings are vital to enhancing mental health and psychosocial policies, programming, and research for the burgeoning population experiencing forced displacement

Wide-field optical imaging of neurological disorders and sleep in mice

Neuroimaging has revolutionized the way in which we understand the hierarchical organization of the amazingly complex, interconnected human brain. Neuroimaging techniques, like functional magnetic resonance imaging (fMRI), have provided high quality structural and functional data, providing multiple in-depth analyses and biomarkers of disease processes. In animal models, mechanistic studies can uncover root pathologies that aren’t explorable in humans. In mice, brain functional connectivity (FC) can be measured via Optical Intrinsic Signal (OIS) imaging – a modality that measures vascular reactivity as a surrogate for neural activity via quantification of fluctuations in oxygenated-hemoglobin (similar to the blood oxygen level dependent (BOLD) signal used in fMRI). Another advantage of optical neuroimaging in mice is the expression of genetically encoded calcium indicators (GECIs), which provide cell-specific and network-level functional imaging of brain activity at speeds up to at least 4Hz. Imaging in higher frequency bands (compared to \u3c0.2Hz in fMRI or other hemoglobin-based imaging modalities) allows for resolution of neural specific phenomena on the order of milliseconds, such as the global ∼1Hz slow oscillation that is characteristic of anesthesia and non-rapid eye movement (NREM) sleep. We imaged mice expressing the GECI GCaMP6 in excitatory neurons while awake, in NREM (verified by EEG), or under ketamine/xylazine (K/X) or Dexmedetomidine (Dex) anesthesia and reconcile discrepancies between activity dynamics observed with hemoglobin vs. calcium (GCaMP6) imaging. Alterations in correlation structure were most obvious in delta band calcium NREM and anesthesia data, resulting in maps with large regions of polarized positive and negative correlations covering the field-of-view (FOV). We use principal component analysis (PCA) to provide evidence that the slow oscillation superimposes on FC rather than replaces FC patterns typical of the alert state. While consciousness state can oscillate on the order of seconds, many studies of disease processes are most informative across a longer period of time. Surgical preparations coupled with optical imaging allow for longitudinal experiments on varying timescales. For example, sequalae of subarachnoid hemorrhage (SAH) include vasospasm, microvessel thrombi, and other delayed cerebral ischemic (DCI) events around 3 days post SAH. These DCI events have been shown to coincide with up-regulation of the neuroprotective peptide Sirtuin1 (SIRT1), using an endovascular perforation mouse model. Here, we display global FC disruption caused by SAH and DCI events in parallel with behavioral deterioration. Normal brain connectivity and behavior was maintained during SAH and DCI via two different treatments targeting SIRT1 activation. SIRT1-specific (resveratrol) and non-specific (hypoxic conditioning) treatments both protected against the FC deficits induced by SAH and DCI, with the latter providing the largest protective effect. This indicates that conditioning-based strategies targeting SIRT1-directed mechanisms provide multifaceted neurovascular protection in experimental SAH – data that further supports the overarching hypothesis that conditioning- based therapy is a powerful approach with great potential for improving patient outcome after aneurysmal SAH. Studies involving focal injury (e.g., stroke, SAH) usually exhibit functional deficits surrounding the injured tissue, however, it is less clear how diffuse processes, such as novel models of acute septic encephalopathy (i.e., Delirium), and encephalitis caused by Zika virus infection, alter brain dynamics. Septic encephalopathy leads to major and costly burdens for a large percentage of admitted hospital patients. Elderly patients are at an increased risk, especially those with dementia. Current treatments are aimed at sedation to combat mental status changes and are not aimed at the underlying cause of encephalopathy. Indeed, the underlying pathology linking together peripheral infection and altered neural function has not been established, largely because good, acutely accessible readouts of encephalopathy in animal models do not exist. In-depth behavioral testing in animals lasts multiple days, outlasting the time frame of acute encephalopathy. Here, we propose optical fluorescent imaging of neural FC as a readout of encephalopathy in a mouse model of acute sepsis. Imaging and basic behavioral assessment was performed at baseline, Hr8, Hr24, and Hr72 following injection of either lipopolysaccharide (LPS) or phosphate buffered saline (PBS). Neural FC strength decreased at Hr8 and returned to baseline by Hr72 in somatosensory and parietal cortical regions. Additionally, neural fluctuations transiently declined at Hr8 and returned to baseline by Hr72. Both FC strength and neural fluctuation tone correlated with behavioral neuroscore indicating this imaging methodology is a sensitive and acute readout of encephalopathy. Zika virus (ZIKV) emerged as a prominent global health concern due to the severe neurologic injury in infants born to adults who had ZIKV infection during pregnancy. However, neurologic manifestations in healthy adults were subsequently reported during Zika pandemics in South America and Southeast Asia. In this population, infection can result in severe cases of encephalitis and have lasting impacts on cognition, and learning and memory, even after recovery from acute infection. Recent studies have uncovered extensive ZIKV- related neural apoptosis within the trisynaptic circuit involving the entorhinal cortex, the cornu ammonis, and the dentate gyrus of the hippocampus in adult mice. However, there are many contributing regions and circuits involved in cognition and learning and memory outside of this trisynaptic circuit. Communication within the cortex and between the cortex and hippocampus is necessary for a variety of neurological processes, such as performing cognitive tasks or for memory consolidation during sleep. Here, we investigate cortical networks and connectivity utilizing wide-field optical fluorescence imaging. We demonstrate that functional deficits congregate in regions of cortex that are highly communicative with hippocampus, such as somatosensory and retrosplenial cortices. Further, we prove that these functional imaging deficits are correlated with other metrics of disease severity, such as encephalitis score and increased delta power, providing a potentially useful clinical biomarker of disease. Finally, these imaging deficits resolve after recovery from acute infection. While optical methods have obvious advantages when used to study animal models, the technique is relatively novel (compared to fMRI) therefore, there are many avenues for data processing algorithms to improve. Similar to fMRI, historically, optical methods use a remarkably simple bivariate Pearson-based approach to mapping FC, leading to quick and easy-to-interpret models of brain networks but also susceptibility to global sources of variance (e.g., motion, Mayer waves). Previously, we demonstrated the binarizing effect of the slow oscillation on FC during NREM and K/X anesthesia. While PCA effectively removed the slow oscillation, it is reasonable to assume that a biological process cannot be completely explained in algebraically orthogonal components. Therefore, we pioneer a multivariate approach to imputing individual neural networks from spontaneous neuroimaging data in mice in an effort to map connectivity with less susceptibility to confounding variance. Calcium dynamics in all brain pixels are holistically weighted via support vector regression to predict activity in a region of interest (ROI). This approach yielded remarkably high prediction accuracy, suggesting the optimized pixel weights represent multivariate functional connectivity (MFC) strength with the ROI. Additionally, MFC maps were largely impervious to the slow oscillation. Moreover, MFC maps more closely aligned with anatomical connectivity as modeled through axonal projection images, than FC maps. Lastly, MFC analysis provided a more powerful connectivity deficit detection following stroke compared to standard FC. These results show that MFC has several performance and conceptual advantages over standard FC and should be considered more broadly within the FC analysis community. Further, with study of diffuse processes (e.g., LPS and ZIKV infection), statistical developments are crucial to solve the multiple comparisons problem when examining all cortical regions within the FOV. Therefore, part of this thesis focuses on the development of a streamlined, open source, user friendly data processing toolbox that contains multiple statistical approaches to make the aforementioned studies possible. Together, the following presents the multiple ways wide-field optical imaging can be used to learn more about the brain’s functional architecture in health and disease

The Application of Dynamic Models in Operations Management

The dynamic program is a principal method for analyzing stochastic optimization problems. This dissertation studies three operations management problems that arise in the dynamic environment. The principal motivation behind these comes from the applicability in three areas: the agricultural supply chain, the container shipping industry, and supply chain financing. In the first chapter, we consider the hog production industry, where the hog raising farm should decide the selling strategy among several selling options. The farm also faces the uncertain yield of different weights of hogs and spot price volatility from other interactive markets. In the second chapter, we formulate a blockchain-based cargo reservation system, where a token is designed to be used as a booking deposit to compensate the contractual party if the other side fails to honor the booking, i.e., the overbooking from the service provider and customer no-show. In the third chapter, we study advance payment as a financing instrument in a multitier supply chain to mitigate the supply disruption risk and compare the traditional system (with limited visibility) with the blockchain-enabled system (with perfect visibility). The main goal of this chapter is to shed light on how blockchain adoption impacts agents\u27 operational and financial decisions and profit levels in a multitier supply chain. We apply the genre of dynamic models to formulate all three problems, but we address them by different methodologies because of the difference in the contexts. The first two problems possess structural properties adequate to find the optimal structural policy for a dynamic program, whereas the last problem can be applied to game theory. In the hog production chapter, we find that the optimal selling strategy for the hog farm is non-monotone. The counter-intuitive situation, namely, the farm does not fulfill the long-term contract but sells to the open market to speculate the high spot price, happens when the open market is good enough. We also propose a newsvendor-like heuristic policy that improves the profit of the hog farm by over 25%. We find the service provider has different acceptance strategies for the maritime container shipping problem with and without overbooking. He always prefers reliable customers without overbooking but prefers unreliable customers with overbooking in some circumstances. In the deep-tier supplier chain finance, take a game-theoretic approach to compare how blockchain-enabled deep-tier financing schemes affect a financially constrained supply chain\u27s optimal risk-mitigation and financial strategies. We find that although improved visibility via blockchain adoption can help the manufacturer make informed supply chain financing decisions, whether it can benefit all supply chain members depends on the financing schemes in use. Blockchain-enabled delegate financing increases risk-mitigation investments and benefits all three tiers of the supply chain only when tier-2 is severely capital-constrained with the working capital below a threshold. Because delegate financing endows the intermediary tier-1 supplier leverage over the manufacturer, the inefficiency inhibits an all-win outcome when the tier-2 is not severely capital-constrained. Blockchain-enabled cross-tier direct financing exhibits a compelling performance as it always leads to win-win-win outcomes (and thus ubiquitously implementable) regardless of the supplier\u27s working capital profile

Investigating Disease Progression and Therapeutic Targets in Multiple Myeloma Using Single-cell Technologies

Multiple Myeloma (MM) is a highly heterogeneous disease characterized by uncontrolled clonal expansion of plasma cells. Single-cell techniques are advantageous in providing a more granular understanding of inter- and intratumoral genomics and surrounding microenvironments. The high relapse rate and intrinsic complexity of MM make the application of single-cell technologies particularly beneficial. Understanding the concordance of the measurements across single cell techniques in MM is of great interest. In this dissertation, we first integrated three single-cell technologies, namely scRNA-seq, CyTOF, and CITE-seq, to characterize MM immune microenvironment and assess their concordances of measurement. Overall, cell type abundances were relatively consistent, while variations were observed in T cells, macrophages, and monocytes. In addition to immune profiling, we sought to discover tumor specific markers based on single-cell transcriptomic profiling. With better understanding of single cell technologies, we then leveraged a number of scRNA-seq datasets and developed a robust scRNA-seq driven tumor-marker discovery pipeline. In total, we identified 20 MM marker genes encoding cell-surface proteins that are not yet under clinical study. The findings were cross-validated using different methods, including bulk RNA sequencing, flow cytometry, and proteomic mass spectrometry, on both MM cell lines and patient bone marrows. We also used both transcriptomic and immuno-imaging techniques to examine target dynamics and heterogeneity to identify potential combinatorial target partners. Lastly, we further characterized tumor heterogeneity, malignant B cell to plasma cell transitions, lineage compositional changes, and signature genes associated with MM progression by utilizing single-cell RNA sequencing of 361 samples from 263 MM patients in the Multiple Myeloma Research Foundation CoMMpass study. Interestingly, we identified B cell subpopulations as precancerous given their higher mutation burden. Additionally, we observed compositional alterations of immune subsets from baseline to relapse stages and identified differentially expressed genes associated with MM progression. Overall, this dissertation provides a comprehensive interrogation of tumor and the immune microenvironment in MM using single-cell technologies and proteomics, which deepens our understanding of MM disease onset and clinical outcomes and potentially provides novel targets for immunotherapies

Times of Uncertainty: The Psychological and Behavioral Impact of Employment Uncertainty on Furloughed Workers and the Moderating Effect of Work Orientation

Although furloughs have been used by organizations for some time, their use increased sharply during the COVID-19 pandemic. They differ from layoffs in the uncertainty they involve around the employment relationship. However, the phenomenon has received little attention from research on involuntary job loss, and the impact of the employment uncertainty it involves is largely unknown. Furthermore, the moderating factors that differentiate the impacts across employee populations are also unclear. In this dissertation I report a mixed-method field study examining the impact of employment uncertainty on furloughed workers and the moderating role by their work orientation. To guide the development of hypotheses, I conduct a qualitative analysis of semi-structured interviews with 28 furloughed employees. I then test my predictions with furloughed workers from various industries. Results suggest that employment uncertainty increases furloughed workers’ negative emotions while decreasing their occupational commitment. The behavioral impacts of uncertainty include hedging and “live like working,” mediated by occupational commitment. Furthermore, one’s work orientation moderates the adverse impacts of uncertainty such that the effects are alleviated for someone with a stronger sense of calling orientation but worsened for someone with a stronger sense of job orientation. The theoretical and practical implications of the findings are discussed