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Open Access Publications from the University of California

Scholarly Works (6 results)

  • Article
  • Peer Reviewed
UC San Diego Previously Published Works (2021)
Gastroesophageal reflux disease (GERD) is a disorder due to the retrograde flow of refluxate into the esophagus. Although GERD is a common clinical diagnosis, its pathogenesis is quite complex. As a result of its multifactorial development, many patients continue to experience adverse symptoms due to GERD despite prolonged acid suppression with proton pump inhibitor therapy. The pathogenesis of GERD involves an interplay of chemical, mechanical, psychologic, and neurologic mechanisms, which contribute to symptom presentation, diagnosis, and treatment. As such, GERD should be approached as a disorder beyond acid. This review will investigate the major factors that contribute to the development of GERD, including factors related to the refluxate, esophageal defenses, and factors that promote pathologic reflux into the esophagus. In reviewing GERD pathogenesis, this paper will highlight therapeutic advances, with mention of future opportunities of study when approaching GERD.
    Cover page: Pathophysiology and treatment options for gastroesophageal reflux disease: looking beyond acid.
    • Article
    • Peer Reviewed
    UC San Diego Previously Published Works (2022)
    PURPOSE OF REVIEW: Chicago Classification has standardized clinical approach to primary esophageal motility disorders. With new clinical data and advancing treatments, Chicago Classification has undergone multiple revisions to reflect updated findings and enhance diagnostic accuracy. This review will describe the recently published Chicago Classification version 4.0 (CCv4.0), which aimed to enhance diagnostic characterization and limit overdiagnosis of inconclusive esophageal motility diagnoses. RECENT FINDINGS: Key revisions outlined in CCv4.0 include (1) a modified standardized HRM study protocol performed in supine and upright positions, (2) recommended ancillary testing and manometric provocation for inconclusive manometric diagnoses (3) the required presence of obstructive symptoms for conclusive diagnoses of esophagogastric junction outflow obstruction, distal esophageal spasm and hypercontractile esophagus, and (4) requirement of confirmatory testing for esophagogastric junction outflow obstruction. These key modifications aim to improve diagnostic accuracy and consistency of clinically relevant esophageal motility disorders, and subsequently clinical outcomes.
      Cover page: Evaluation of Esophageal Motility and Lessons from Chicago Classification version 4.0.
      • Thesis
      • Peer Reviewed
      UC Davis Electronic Theses and Dissertations (2024)

      As the global population ages rapidly, there's a growing need for tailored digital solutions to ensure that this population receives the healthcare, social connections, and daily assistance it deserves. Menopause is an unspoken chapter of a woman's life, inadequately addressed by researchers. Despite a growing population of women working past the age of menopause, research on support tools available remains inadequate. This gap calls for evaluation and redesigning of the digital support tools available to empower women to navigate through this phase of life with ease. This study investigates the design and impact of digital women's wellness programs, with a particular focus on programs targeting menopausal women. Using a snowball technique, a 26-question survey was distributed across the University of California, Davis staff and students. The survey findings identified lower awareness of menopause-specific wellness programs compared to general wellness programs. Stigma and time constraints emerged as significant barriers, particularly for working women, while digital literacy posed no obstacle. Despite limited engagement with wellness program designers, this research provides valuable insights into user preferences and the current program landscape. The findings highlight the need for increased awareness and accessibility of menopause-specific digital wellness programs. The current program landscape revealed that interactive online content, telehealth consultations, and non-interactive online content were the most popular delivery methods used. While awareness of digital wellness programs is growing, participants expressed a desire for programs that combine interactive online content with in-person interactions with support group members. A comprehensive approach to content was emphasized, including general wellness education, menopause-specific information, symptom management tools, and information on alternative therapies. The preference for collaboration with healthcare professionals, alongside local health departments, nutritionists, and fitness experts, suggests a strong desire for a multifaceted approach that extends beyond mere symptom management and emphasizes improving overall well-being in daily life. User preferences for convenience and accessibility indicate that mobile applications should be a core element of these programs. Mobile apps can facilitate symptom tracking and data collection for program management while also providing an individualized aspect to the program experience. High user satisfaction is paramount for the long-term viability of these programs. To achieve this, ongoing design refreshes informed by the latest research are crucial, ensuring program effectiveness, user engagement, and, ultimately, sustained user satisfaction.

        • Article
        Family Medicine Research Day 2024 (2024)
        Care of the female athlete has come to the forefront of the Sports Medicine Field as of late for many reasons. One of the areas is related to the impact the menstrual cycle has on athletic performance in the biologically female athlete. The Sports Performance team at a Division I University organized a Female Athlete Summit aimed at educating their scholar athletes about the female specific physical and mental aspects of sport. Our goal was to establish a baseline of knowledge in the body of female athletes about the effects of the menstrual cycle has on athletic performance. 46 completed the pre-summit survey, and 37 completed the post-summit. De-identified data was reviewed and demonstrated an average pre-summit knowledge base of 5.065, and a post-summit knowledge base of 8.838 out of a scale of 0 to 10, 0 being having no knowledge, and 10 being having all the knowledge. Another survey demonstrated an average period length of 4.069 days, the most common symptoms experienced during menses to be cramping (31/41) and mood changes (27/41), and a concern of the menstrual cycle effecting energy level (30/41) and strength (20/41) as the top two concerns about the effect the menstrual cycle has on athletic performance. The significance of this study lies in identifying the knowledge gaps in understanding the needs of female athletes. By identifying the gaps this study aims to pave the way for evidence-based interventions that can enhance performance, mitigate potential challenges, and promote optimal health outcomes for the female athlete.
          Cover page: Female Athlete Summit Survey: An Insight to University Scholar Athlete’s Knowledge about the Impact of the Menstrual Cycle on Athletic Performance
          • Article
          • Peer Reviewed
          UC San Francisco Previously Published Works (2022)
          Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph-based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these "knowledge graphs" (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open-access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open-source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object-oriented classification and graph-oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.
            Cover page: Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science
            • Article
            • Peer Reviewed
            UC San Francisco Previously Published Works (2022)
            Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well-being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline-specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph-based "Translator" system capable of integrating existing biomedical data sets and "translating" those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system's architecture, performance, and quality of results. We apply Translator to several real-world use cases developed in collaboration with subject-matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state-of-the-art, biomedical graph-based question-answering systems.
              Cover page: Progress toward a universal biomedical data translator
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