Ultra-Brief CBT for Primary Care Visits: Pilot Training and Implementation

This study evaluated the feasibility and acceptability of an Ultra-Brief Cognitive-Behavioral Therapy (UB-CBT) intervention for depression and anxiety symptoms in routine primary care visits. The UB-CBT is responsive to the limited access to specialized mental health services, particularly evidence-based interventions, for individuals with depressive and anxiety disorders in the U.S. Most Americans with symptoms of depression and anxiety first report their concerns to their primary care provider (PCP) in routine visits, and the UB-CBT was designed to provide tools for managing these symptoms during these interactions. The UB-CBT training workshop was developed and piloted with 38 providers at three adult primary care and four family medicine sites in Vermont. PCPs completed questionnaires before and after the training. Data were analyzed using mixed qualitative and quantitative methods. Regarding training targets, most providers (79.7%) reported that they learned new information about depression and anxiety treatment and even more providers (88.6%) learned new information about how to address these symptoms in visits. From pre- to post-training, mean scores for provider attitudes toward psychotherapy and perceived competence talking to patients about mental health symptoms and therapy increased, but means scores for perceived comfort in talking to patients about mental health concerns decreased slightly. Data illustrated that most providers found the training and intervention highly feasible and acceptable. Providers especially liked the user friendliness and general feasibility of the intervention. Providers offered ideas about developing online versions of the material and raised some concerns about their ability to administer the intervention in a timely manner. The discussion outlines several steps that will address these concerns and improve the UB-CBT training experience and intervention. The UB-CBT intervention and training program have potential to increase patient access to mental health tools in primary care

Exploring Chemical Space for the Discovery of New Functional Materials and Therapeutics

Given the combined rate of advancement in both computational power and target identification for the treatment of high impact disease, computer-aided drug design (CADD) has emerged as a new alternative to traditional small molecule design, along with the advances in novel materials and biologic derived therapies. Paired with renowned contemporary methodologies for structural determination, the modern drug discovery toolkit has greatly expanded with both large industry and the average patient serving to benefit. Despite these advances, limits and biases in both data diversity and methodology execution still restrict the potential of many computationally guided processes. Designing new small molecules and biologics for previously untreatable targets is thus essential for continuing this path of discovery. The first portion of this dissertation explores the synthesis of sequence defined dendrimers, a new class of functional materials. Sequence defined dendrimers benefit from many of the known desirable properties of traditional dendritic systems, combined with a programable motif to explore sequence specificity. Sequence defined dendrimers with up to six peripheral sites have been successfully synthesized, with applications to combinatorial libraries via automated SPPS ongoing. The latter portion of this dissertation concerns the development of ChemHopper, a computational package which leverages novel molecular design for generative lead optimization. ChemHopper utilizes multi-scale R-group enumeration for the creation of an ultra-large hierarchical library of drug-like fragments. This library is procedurally generated to efficiently explore the chemical space of drug-like moieties, thus avoiding the bias included in open-source data derived from limited known hits. Chemhopper utilizes CPU/GPU parallelization to then screen its internal library for the production of new drug-like molecules, at speeds rivaling modern HTVS methods

Enhancing Chip Security With Physical Unclonable Functions And Self-Destruction

Physical Unclonable Functions (PUFs) are the current state of the art solution to hardware security. A silicon-based PUF exploits local manufacturing variations to produce a secure encryption key that is repeatable, intrinsic, random, unique, and low-cost. In many ways, a PUF can be considered a unique digital ‘fingerprint’ for chip identification and authentication. In this dissertation we cover the properties and industry standard metrics for assessing a PUF. Results in this dissertation, are supported by hardware measurement data from multiple silicon test chips implemented in GLOBALFOUNDRIES 12-nm, TSMC 5-nm, and TSMC 3-nm Fin Field-Effect Transistor (FinFET) Complementary Metal Oxide Semiconductor (CMOS) technologies.We will target three main areas of research: PUF topologies, PUF stability, and PUF feature extensions. Regarding PUF topologies, we will provide an overview of the most common PUF topologies that exist in the industry and provide a comparison to our innovative Pre-Amplifier PUF. In general, the most challenging aspect of a PUF design is to achieve a repeatable and stable key across a wide set of test conditions. For PUF stability, we detail and compare multiple techniques that have been proposed and highlight the single test condition stable bit identification technique that we have developed and utilized to achieve as low as a “zero” Bit Error Rate (BER) in silicon testing. Further, we propose accelerated aging techniques that eliminate the need for storing stable bitcell locations, while still achieving a “zero” BER. PUF feature extensions represent one of the highlights of our research. We demonstrate the first ever silicon-proven methods and structures for a self-destructible PUF that can corrupt and physically destroy the underlying data used to generate the PUF encryption key, blocking future authentication attempts. This tamper response is done by exploiting well-known semiconductor reliability failure mechanisms. In our work, we propose a simultaneous electromigration (EM), and time-dependent dielectric breakdown (TDDB) directed to the PUF array data. The result is an irreversible corruption of the secure encryption key to enhance chip security. Outside of using self-destruct as a tamper response, we propose techniques to utilize these concepts to thwart counterfeit integrated circuits that try to emulate or duplicate the original chip functionality. As an End of Life (EOL) recycling step, PUF self-destruct can be used to safely disable chip functions and corrupt sensitive data

Examining Sustainable Diets for Planetary Health: A Mixed Methods Study of Sustainable Diets Knowledge Creation, Reproduction, and Recommendations

Food systems are a vital component of planetary health, or the inextricably linked health of humans and the environment, with the capacity to both threaten and support all dimensions of sustainability. Sustainable diets are recognized as both a driver and outcome of a sustainable food system needed to support the well-being of people and the planet. Although attention to sustainable diets as both a lever for change and result of complex food system dynamics is growing both within academia and beyond, there have been limited efforts to comprehensively review and synthesize the evolution and current state of sustainable diets research. Similarly, few studies have systematically examined how and what kinds of sustainable diets research is created, reproduced, and recommended for future study and food systems change. This comprehensive understanding of sustainable diets knowledge is essential in determining whether and how this research acknowledges and accounts for the full suite of sustainability dimensions and broader food systems dynamics. It is critical in accurately and thoroughly assessing system trade-offs and designing just, effective strategies for a sustainable food system transformation. Without it, research and solutions run the risk of inhibiting and contradicting planetary health goals. This three article mixed methods dissertation aims to address these gaps in knowledge and analysis through a thematic scoping review, bibliometric and altmetric analysis, and content analysis. Each chapter in this dissertation builds layers of detail and depth to our understanding of sustainable diets research and its implications for future study and food systems change. The first chapter presents a thematic scoping review of sustainable diets literature. This chapter uses topic modeling, a natural language processing method, to identify research gaps, trends, and themes over time and across disciplines, and examines how these themes align with components of sustainable diets described by the Food and Agriculture Organization of the United Nations. Chapter 2 studies how the literature considered in the thematic scoping review is created and reproduced. Drawing from the mutual aims of science of science and research impact evaluation, it examines the practice of science through a citation and altmetric analysis and evaluation of whether and how research characteristics and indicators of power are linked with impact metrics. Chapter 3 takes a closer look at the objectives and recommendations of the most highly cited sustainable diets literature through a content analysis. It also reviews how the literature aligns with upstream and downstream food system influences as described by the Food Systems Dashboard’s Food Systems Framework to identify strengths and gaps in the research. The dissertation concludes with a summary of the findings and a critique of the ability of sustainable diets research to adequately address systems trade-offs necessary to designing solutions for a sustainable food system

Comparison Of The Ptsd Factor Structure Among Hispanics And Non-Hispanic Whites Affected By Hurricanes

The Hispanic population in the United States (US), is a growing segment of the US population. This group is vulnerable to developing posttraumatic stress disorder (PTSD) due to minority-related stressors, financial insecurity, and their concentration in coastal regions prone to natural disasters. PTSD is a highly heterogeneous diagnosis with a complex factor structure. The factor structure within Hispanics may vary from Non-White Hispanic (NHW) individuals, the predominant group used in prior factor analytic work. Identifying such differences would inform culturally relevant theories of PTSD. Most prior research has focused on NHW samples or used DSM-IV criteria for Hispanics. The present study examined the PTSD factor structure in Hispanics after a natural disaster using the DSM-5 criteria. Invariance between Hispanics and NHW was also examined. The results of confirmatory factor analyses (CFA) indicated that the seven-factor Hybrid model exhibited superior model fit compared to the alternative models. There was strict invariance between Hispanics and NHW for this model. The findings suggest that a seven-factor hybrid model offers a reliable conceptualization of PTSD, and a more accurate assessment compared to extant models across Hispanics and NWHs

A Closer Look At Digital Histopathological Slide(s) Analysis Software.

Computer-aided detection or diagnosis systems, which are deployed to detect abnormalities in histological samples, can play a key role in detecting a range of anomalies found in histologic samples. In fact, the earliest venture into the use of computerized image analysis and digital image processing was to analyze microscopy images, not in face recognition/detection, as many would claim. This automated image analysis continues to be transformative for many areas, including in areas of research and medicine like pathology and promises to offer highly accurate and efficient qualitative and quantitative analysis algorithms. Due to these potentials, these algorithms and other related automated analysis techniques have attracted the attention of research in the field. These are deployed in a wide range of research topics, including cancer detection, classification, and even monitoring management response. This study aimed to provide a technical assessment of two analysis approaches that are utilized in software platforms: positive pixel count per tissue area analysis and cell-by-cell analysis approach. These two are commonly used in many digital histopathological slide analysis software(s) in research settings, including ImageScope and HALO, that respectively deploy the above algorithms and thus were used as proxies for this study. We found that both the algorithms we worked with could only characterize IHC markers to some extent, HALO more so than ImageScope. The complicated nature of IHC assessment criteria, guided by the biology of the markers was the biggest influence on the challenges in image analysis. These need to be considered during algorithm development to obtain reliable automated analysis systems applicable in real-world research and/or hospital environments

Addressing Resource Gaps for Autistic Adolescents and Adults

Autistic patients of all ages often experience greater difficulty accessing healthcare and worse health outcomes compared to neurotypical peers. Additionally, patients who are older when they are diagnosed as autistic (e.g. later adolescence, adulthood) frequently report increased comorbid medical problems and problems with mental and emotional health. Healthcare providers often feel they have inadequate knowledge and skills to confidently treat autistic patients, and are also often unaware of what resources are available to support patients. This project describes efforts to better equip primary care providers in Hardwick, VT with resources to support autistic patients, and discusses anticipated outcomes of similar interventions.https://scholarworks.uvm.edu/fmclerk/2214/thumbnail.jp

The Role Of Miro1 Mediated Mitochondrial Positioning On Redox Gradients, Subcellular Signaling, And Gene Expression

Subcellular mitochondrial positioning is necessary to support various cellular processes such as cell migration, invasion and signaling involved in cell growth. Mitochondrial trafficking occurs in part via Miro1, an outer mitochondrial membrane protein, which binds to microtubule motor/adaptor complexes. Deletion of Miro1 (Miro1-/-) from mouse embryonic fibroblasts (MEFs) restricts the mitochondria to the perinuclear space, which is rescued upon the stable re-expression of a Myc-tagged Miro1 plasmid (Myc-Miro1). Deletion of Miro1 does not compromise mitochondrial bioenergetics, indicating the mitochondria are not defective. Thus, differences in cellular processes could be linked to mitochondrial positioning rather than mitochondrial defects. Mitochondria are a significant source of reactive oxygen species, specifically hydrogen peroxide (H2O2) a redox signaling molecule. To quantify subcellular H2O2 levels dependent on Miro1 mitochondrial positioning, we used the H2O2-responsive biosensor HyPer7. Miro1-/- had higher levels of H2O2 in their perinuclear area compared to Miro1+/+ and Myc-Miro1 MEFs, and lower levels in the cell periphery. Mitochondrial density correlated with highest levels of subcellular H2O2. The increased peripheral H2O2 was associated with bigger and more abundant focal adhesions in the Miro1+/+ and Myc-Miro1 MEFs. Additionally, the phosphorylation of vinculin and p-130cas was increased in Miro1+/+ compared to Miro1-/- MEFs. Together, we identified loss of Miro1 disrupts subcellular H2O2 gradients and cell migration phenotypes. We next investigated a role for Miro1 in supporting cell proliferation and gene expression. Mitochondria are highly dynamic during the cell cycle and support signaling events governing transitions through the cell cycle. We determined Miro1-/- proliferated slower compared to Miro1+/+ and Myc-Miro1 MEFs. We show that asynchronous Miro1-/- MEFs have double the number of cells in the S/G2 cell cycle phase. We conducted the first ever RNA-sequencing of Miro1-/- MEFs to evaluate possible differential gene expression changes. We identified differentially expressed genes including those in the MAPK pathway. Literature shows that cell cycle progression is supported by dynamic regulation of ERK1/2 phosphorylation. Therefore, we evaluated phosphorylation of the MAPK proteins MEK1/2 and ERK1/2. We found no difference in MEK1/2 phosphorylation. ERK1/2 was hyperphosphorylated in Miro1-/- MEFs, in both the nuclear and cytoplasmic compartments. ERK1/2 phosphorylation was independent of the oxidation and expression of the dual specificity phosphatases (DUSPs). ERK1/2 phosphorylation was constitutive in Miro1-/- MEFs following serum starvation and stimulation independent of DUSP oxidation or expression. Lastly, we uncovered ERK1/2 oxidation to be increased in Miro1-/- MEFs, a post translational modification that supports persistent ERK1/2 phosphorylation. We next evaluated differential gene expression through RNA sequencing of cells following artificial relocalization of mitochondria via optogenetics. Many pathways including the MAPK pathway, focal adhesions, and angiogenesis were revealed to be altered due to mitochondrial positioning. This system allows us to evaluate the role of subcellular mitochondrial positioning independent of Miro1. These data contribute to the growing body of literature that has identified Miro1 and mitochondrial positioning in governing cell processes in normal and disease states

Optimal Spatio-Temporal Monitoring of Reinforced Concrete Bridges under Multiple Hazards

Bridges are one the most critical elements in transportation infrastructure systems, subject to both gradual and sudden deterioration over their lifespan. Depending on their location, they may face a range of hazards, including marine corrosion, seismic activity, scour, waves, tsunamis, vehicle and barge collision, and other natural and man-made disasters. Consequently, during the last few years, multi-hazard analysis of these structures has gained considerable attention from researchers and practitioners. Given the complexity and time demands of analyzing multiple hazards over extended periods, it is crucial to determine when such detailed analysis is warranted.To address this question, this dissertation introduces a probabilistic computational framework designed to model time-dependent damage processes in reinforced concrete bridges and evaluate the expected system level damage throughout their service life. The analysis focuses on three primary hazards, including seismic activity, scour, and corrosion, while assuming seismic hazard as the most influential. The principal uncertainties in the modeling process involve earthquake occurrence and intensity, corrosion initiation and rate, and stream flow intensity. Utilizing Monte Carlo simulation, the framework generates hazard sequences, including earthquakes, corrosion, and scour, and examines their combined effects on bridge structures. A damage index based on the Park-Ang damage model is adopted to quantify structural damage. The damage index evolves with the age of the bridge and the cumulative impact of multiple hazards. The dissertation also evaluates and compares different health monitoring methods and schedules based on the developed damage metrics. The monitoring strategies include measuring vibrational frequency, crack width, and residual displacement of the bridge at different intervals. The dissertation further explores optimal vibration-based monitoring schedules by minimizing discrepancies between actual and predicted responses. Various bridge monitoring strategies encompassing different inspection parameters, techniques, and intervals are analyzed to balance the value of collected data against its impact on reducing risk estimation uncertainties. This methodology also provides a tool for risk-informed post-earthquake monitoring of bridges of aging reinforced concrete bridges. The proposed framework offers engineers and decision-makers valuable insights into the effectiveness of various monitoring plans and methods. Furthermore, it facilitates the management of bridges by enabling the assessment of their current condition and predicting their future state under the combined influence of multiple hazards

GPR 3D Image Reconstruction with Sparse Recovery for Random Spatial Sampling

Ground Penetrating Radar (GPR) is widely used for subsurface exploration in applications such as structural health monitoring, archaeological surveys, and the detection of buried objects. However, traditional 3D GPR imaging requires dense spatial sampling along regular grids, which is time-consuming and often impractical, especially in complex environments with obstacles or accessibility issues. In this paper, we introduce a novel method that leverages sparse recovery techniques to enhance 3D GPR imaging from reduced spatial measurements collected along arbitrary scanning paths. By exploiting the inherent sparsity of subsurface targets, we employ the Dantzig Selector with cross-validation to accurately reconstruct target locations from spatially random-sampled GPR data. The reconstructed data is then processed using the Back-Projection Algorithm (BPA) to generate high-resolution 3D images. We validate our method through simulations, demonstrating that our approach not only improves imaging quality but also significantly reduces data acquisition time and storage requirements. Performance analysis under various noise levels and sampling densities highlights the robustness and practicality of our method for flexible scanning paths in 3D GPR applications. This work contributes to making GPR surveys more efficient and effective, particularly in scenarios where traditional dense sampling is challenging