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Functional dissection of RNA polymerase active sites by deep mutational scanning
No full textTranscription in eukaryotes is carried out by three RNA polymerases (Pol), Pol I, II, and III, which are structurally conserved though they have evolved to have their own regulation and produce different classes of transcripts. At the heart of these RNA polymerases is an ultra- conserved active site domain, the trigger loop (TL), coordinating transcription speed and fidelity by critical conformational changes impacting all three steps of nucleotide addition cycle (NAC) in transcription elongation, substrate selection, catalysis, and translocation. Previous genetic and biochemical studies have shown that substitutions of TL residues disturb its balance and then alter its function. Additionally, studies from our lab have observed different types of residue-residue interactions in Pol II TL, implying the TL’s function is facilitated by residue interaction networks within and around it. Furthermore, identical mutations in a residue conserved between yeast Pol I and Pol II TLs yielded opposite biochemical phenotypes, implying even functions of conserved residues are shaped by individually evolved residue interactions in enzymatic contexts (epistasis). However, the specific mechanisms by which the TL is regulated and how it communicates with the rest of the enzyme remain unclear. Through analysis of over 15,000 alleles representing single mutants, a subset of double mutants, and evolutionarily observed TL haplotypes by deep mutational scanning, I identified intricate pairwise and higher-order epistatic interaction networks controlling TL function. Substituting residues creates allele-specific networks and propagates epistatic effects across the Pol II active site. Additionally, the interaction landscape further distinguishes alleles with similar growth phenotypes, suggesting increased resolution over the
previously reported single mutant phenotypic landscape. Furthermore, we distinguished intricated layers of higher-order epistatic interaction networks within TL haplotypes and TL residues with distinct classes of epistatic patterns in affecting these higher-order interactions. Finally, co- evolutionary analyses reveal groups of co-evolving residues across Pol II converge onto the active site, where evolutionary constraints interface with pervasive epistasis. Our studies provide a powerful system to understand the plasticity of RNA polymerase mechanism and evolution and provide the first example of pervasive epistatic landscape in a highly conserved and constrained domain within an essential enzyme
Title Page Analysis of The Capability Model. Annual Goals Tracking, and Mind on Medicaid Initiatives at Highmark
No full textThis master’s essay analyzes the administrative residency of a Master of Health Administration graduate to examine three projects within Highmark's Medicaid Business Unit (MBU). These projects—The Capability Model, Annual Goals Tracking, and Mind on Medicaid—showcase the MBU's concerted efforts to boost productivity, encourage creativity, and provide Medicaid members with better services. The Capability Model initiative addressed the lack of a coherent roadmap for strategic planning and execution by focusing on creating an organized framework to match the MBU's operations with best-in-class standards. Establishing an open and methodical process for tracking and reporting MBU's annual objectives would help with strategic alignment and well-informed decision-making was the goal of the Annual Goals Tracking project. Through the creation of a dynamic platform, Mind on Medicaid aimed to increase employee awareness, engagement, and knowledge sharing about Medicaid news and innovations within Highmark. These programs not only helped achieve the short-term objectives of strategic expansion and operational excellence, but they also set the groundwork for Highmark's long-term initiatives to offer members exceptional value and promote a culture of ongoing learning
A Compact Machine-Learning Based Diagnostic Utility for Seizure Detection and Localization
No full textSeizures are episodes of abnormally excessive or synchronous electrical activity of localized populations of neurons in the brain. Epilepsy is a condition in which these seizures are repetitive. Some half a million people do not respond to drug therapy, and surgical intervention is necessary. Multi-electrode EEG recording is an important diagnostic tool for pre-surgical planning in these cases. While EEGs have relatively good temporal resolution, they have poor spatial resolution. Therefore, the onset and localization of seizure activity can be difficult to determine by direct observation of the EEG record. If those EEG channels that show the earliest onset of seizure-like activity can be determined, then those channels, corresponding to locations on the cerebral cortex, can indicate sites for the surgical correction of epileptogenic foci. To assist the clinician in determining which channels correspond to the onset of seizure activity, machine-learning tool have shown promise. However, computer-based diagnostic systems that are portable and accurate are not readily available for use by clinicians, especially in underserved areas. Also, the numerous computer-based EEG analysis utilities that have been devised to detect seizures remain limited in one or more respects: 1. a lack of sufficient spatial resolution of the EEG signal to indicate activity at a specific electrode, 2. an inability to resolve both temporal and spatial information for the same EEG signal, 3. the lack of ability to store previous analysis sets, so the system can refine its learning accuracy using new data, and 4. the ability to be quickly and accurately run on a portable computer system for use in underserved, rural, or remote
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geographical regions. Previously, I demonstrated that a relatively simple recurrent neural network was capable of seizure detection and localization from an EEG record. To improve on this system and address the four limitations listed above, I have developed a compact machine-learning utility based on my original system but with significant innovations. This system has shown its effectiveness in determining the onset and cortical localization of seizure activity from high-resolution EEG records
Dynamic Neural Fields Processing Using Temporal Dynamic Vision Sensing and Adaptive Threshold for Motion Tracking
No full textDynamic Neural Fields (DNF) are models that mimic brain functions, which are good at processing information over time and making decisions in changing environments. They can create stable activity patterns for tasks like tracking moving objects and making quick decisions. Similarly, Dynamic Vision Sensors (DVS) have been used in past research for their ability to quickly capture moving objects in scenes. This paper is based on DNF that utilizes DVS as its input to track selected objects. The algorithm enhances the grayscale values of the chosen object, effectively setting the grayscale values of other parts of the image to zero, which is represented as the black part. However, interfering objects close to the selected object might also receive a high value and thus appear in the output. The original approach employed a sigmoidal function to introduce non-linearity to the image, aiming to differentiate between the target and interfering objects. This method, though, has its limitations: for larger objects, the non-linear features might result in the elimination of parts of the object itself, compromising the accuracy of the tracking process.
This work proposes the use of an adaptive threshold applied to the linear function, instead of the sigmoidal function, to distinguish objects. By directly implementing a simple algorithm, one can find out the value of the elements that are related to the threshold and the threshold can be calculated with the relevant elements. In the experiments conducted, by comparing the deviations in the object centers, the proposed method achieved an error reduction of approximately 92% compared to the use of a sigmoidal function. This reduction reveals that adaptive threshold can not only eliminate the existing interference objects but also avoid further bias in tracking, making the tracking performance better than using the sigmoidal function. Moreover, the proposed method keeps the performance stable when the tracking object becomes large, implying a wider range of applicability
Exploring Practitioner Data Use to Support Improvement Work in Education
No full textImprovement networks have become a popular approach to educational change. In theory, data is meant to fundamentally anchor these efforts. However, there are gaps in terms of which, when, and why data are used in practice and how they should be created to better meet practitioner needs. Across three studies, this dissertation provides an in-depth exploration of practitioner data creation and use in a focal improvement network.
Study 1: This mixed-methods case study investigated different ways in which data were created and used, as well as when created data was not used and when data was desired but not available. The findings showed while improvement data were predominantly created, evaluation data were more frequently used to navigate the complex socio-political dynamics typical of improvement networks.
Study 2: Building on practitioner needs identified in Study 1, this study develops an approach for creating and using evaluation data to understand the relationship between network processes and outcomes. In particular, it explored analytic techniques for probing the relationship between teacher implementation of proven instructional practices and growth in student performance. Analyses consistently showed benefits for student growth, overall and for historically underserved and underrepresented students, when teachers more consistently implemented the targeted instructional practices.
Study 3: Addressing another need identified in Study 1, this study develops an approach for creating and using evaluation data to understand the overall impact of the improvement network on student outcomes. In particular, it develops and tests a coarsened exact matching approach for evaluating effects of the network on growth of student outcomes relative to a set of algorithmically matched non-network schools. Overall, many schools participating in the network showed growth that outpaced matched schools, with historically disadvantaged students benefiting especially.
This dissertation suggests implications for theory and practice in terms of how data can be created in order to be more effectively used in improvement networks. Importantly, it emphasizes intentional data creation and use that minimizes associated practitioner effort while maximizing data value to practitioners. It also provides cross-validated examples of new approaches to improvement network evaluation that should be replicated in other initiatives
Bridging the Virtual Divide: The Influence of Diverse STEM Role Models on the STEM Identity of Cyber School Students
No full textIn cyber charter schools, middle-school students face many barriers to developing STEM identity. My theory of improvement was to address sense of belonging in a large virtual classroom to develop STEM identity in my students. By utilizing diverse STEM role models that reflected my students’ racial or ethnic identities and an inquiry-based approach to teaching, my intervention nurtured the development of STEM identity in my online students. This intervention addressed both STEM identity and sense of belonging by encouraging students in underrepresented groups to participate and engage with STEM professionals who look like them in synchronous class sessions. This study shows promise for reducing the barriers to developing STEM identity online because the intervention can foster community and a sense of belonging in the virtual classroom while also teaching about STEM careers, diversity, and inclusion
Loving impartially: reconciling partiality and impartiality in Kantian ethics
No full textThis paper argues for a reading of Kantian ethics that establishes equal ethical concern for all humanity and, in doing so, provides one reasons to be partial towards the ends of special relations (friends and family) out of love. Instead of arguing that acting out of love is merely permissible, I argue that Kantian ethics establishes love, alongside respect, as a possible kind of moral relationship that one can have with another. The argument proceeds with an analysis of how Kant creates a generic account of value through his notion of ends in themselves and how this generic account of value establishes equal ethical concern for all humanity. I then consider some possible ways of understanding how Kant thinks we should treat ends in themselves and argue for the position that treating people as ends in themselves is a matter of recognizing them as self-existent ends according to Kant’s own notion of self-existent ends. I go on to argue that Kant’s notion of self-existent ends provides the basis for the distinction between the moral relationships of respect and love. I then argue that a distinction in kind between respect and love can be found in a notion of deep involvement, where deep involvement is understood as the provision of additional reasons to adopt and promote the ends of another person unique to love. Finally, I consider how these reasons help us to distinguish between the cases in which special relations do and do not think the same ends are important; when one should choose the ends of stranger over a special relation and the different kinds of pathological special relationships that prevent one from doing so; as well as what is owed to lonely people
The Role of Physiologic Loading, Micronutrient and Trace Mineral Deficiencies and Senescence on Bone Functional Adaptation
No full textBone functional adaptation refers to bone tissue’s ability to optimize its structure and mass through adaptive processes, ultimately meeting the contradictory needs of stiffness and flexibility with sufficient stiffness lending to resistance to deformation (i.e. strain) and flexibility that allows for storage of energy in elastic (i.e. reversable) deformation during impact loading, muscle contraction and joint movement. Emerging evidence supports the integral role of micronutrients—namely vitamin D and iron—in mediating bone homeostasis through different mechanisms at the composition, tissue-level and morphologic level. While prior imaging modalities have lacked the resolution necessary to discern evidence of an adaptive response, the pQCT and focally, the HR-pQCT have provided researchers the ability to investigate bone microarchitecture in vivo and quantify densitometric, morphological and geometric adaptation in response to exercise and training exposure, such as concurrent resistance training or military training. Conversely, in an ageing population, the full consequence of micronutrient deficiency and cellular senescence on bone quality remains unknown due to the over reliance of osteoporosis research on low-resolution imaging modalities and the disproportional recruitment of women in prior studies. Therefore, the purpose of this work is to examine the synergistic effort of combining varying physiologic loading models (concurrent resistance training, military training) with potential mediating factors of bone functional adaptation including sex-specific responses, non-mechanical factors such as nutritional deficiencies and cellular senescence in order to further elucidate characteristics contributing to bone functional adaptation
Addressing the Rural Primary Care Physician Shortage: A Focused Review of Policy Interventions and Their Implications
No full textThe primary care physician (PCP shortage in the United States presents a critical public health concern with far-reaching implications for healthcare access and general population well-being. This is underscored by a PCP distribution problem as rural communities face the worst of the shortage. The PCP shortage is shown to be an immediate public health crisis by examining its effects on healthcare delivery, access, and outcomes, particularly in rural and underprivileged populations. A search of the Ovid Medline database yielded several studies that can be utilized to target the PCP shortage. Policy interventions extrapolated from the review of available literature include changing medical school selection processes, expanding and furthering recruitment to the National Health Service Corps (NHSC), mandating the incorporation of rural health exposure during medical school, and widening the scope of practice and lessening restrictions for physician assistants (PAs) and Nure Practitioners (NPs). The IOM developed the Six Aims of Improvement framework to measure healthcare quality, but it is used in this paper to address the feasibility and potential for success in addressing the PCP shortage in rural areas. These interventions are analyzed using the Six Aims of Improvement framework, focusing on their potential to provide safe, effective, patient-centered, timely, efficient, and equitable healthcare services by increasing the number of primary care providers. This analysis yielded several strong options, but ultimately, while several of the approaches have shown promise in solving the PCP shortage, for a more immediate impact on patient care, priority should be given to increasing the utilization of already available healthcare resources, such as PAs and NPs
Public Health Genetics Professionals' Knowledge of and Perceived Barriers to Implementing Trauma-Informed Care in Newborn Screening
No full textChildren with genetic conditions and special healthcare needs (SHCN) are at increased risk of experiencing trauma compared to children without SHCN because they often experience additional stressors that make adverse events more likely. These potentially traumatic experiences may start in the newborn screening (NBS) phase, which is often a family’s first introduction into the medical system. NBS professionals are often in an important position to both prevent trauma as well as identify and support individuals who need it. However, there is little information on implementing trauma-informed care (TIC) approaches into NBS clinics. It is important to understand NBS professionals’ knowledge, perceptions, and barriers to implementing TIC in this setting.
This study is part of a larger study by the geneTIC (Genetics Care that is Trauma-Informed) workgroup of the Midwest Genetics Network. An online survey was distributed to genetics providers and included questions from the “Trauma-Informed Care Provider Survey v2.0” to assess knowledge, opinions, self-rated competence, recent use of TIC approaches, and barriers of use. Data from a subset of respondents who were NBS professionals was analyzed for this report in SPSS for descriptive and frequency statistics.
Results indicate that NBS professionals have knowledge about trauma and TIC approaches, favorable opinions towards TIC, and varying levels of competence in providing TIC. They have utilized some specific TIC approaches and recognize that addressing trauma is a part of their professional role. Barriers identified that prevent the implementation of TIC approaches include time constraints, lack of training, and provider stress/distress. Respondents suggested various resources needed for them to be able to implement TIC into their clinics including webinars, education for all staff, and social work support. These findings will inform future resource development for genetics professionals, as well as with protocol design and implementation strategies for NBS clinics.
The public health significance of this project is that children with genetic conditions and their families are at a greater risk of experiencing trauma and adverse childhood experiences (ACEs). Because of this, it is important that genetics and NBS providers implement TIC approaches to prevent incidents of trauma and re-traumatization in the genetics clinic setting