Interdisciplinary – Page 48 – UROP Spring Symposium 2021

Interdisciplinary

Measurement of Coronary Artery Diameter using Image Processing and Geometric Modeling

While doctors use their eyes to understand and interpret coronary artery data provided by Magnetic Resonance Angiography (MRA) or Computed Tomography Angiography (CTA), researchers have been looking for ways to use technology to automatically track coronary arteries. This document looks to combine two methods of interpreting angiograms, Kalman filtering and a geometric vessel model in order to glean a fuller estimate of a coronary artery’s radius. So far, I have created an algorithm in MATLAB to detect radii across different artery connections. The next step is to compare these radii results to formulae referenced in other research papers and apply the two aforementioned methods to improve the accuracy of my radii measurements. A better estimate of a coronary artery’s radius will prove vital to doctors, who, in relying on their eyes to interpret coronary artery data, might struggle to differentiate noise from weak stenosis requiring treatment. Further, these doctors, though they differ from each other on how they treat varying levels of stenosis, would love to have a standardized way of understanding how severe the stenosis is, and having a more reliable radius will provide exactly that.

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Developing fast and unbiased computer vision algorithms

Computer Vision Algorithms are a fast-developing technology, and we have seen from example that they are currently not as accurate and unbiased as we hope they can be. Our project aims to develop a more efficient system and algorithm to reduce bias in computer vision programs. One way bias may be introduced into these algorithms is through issues with light levels in images and videos. Since many computer vision algorithms rely on video cameras, as opposed to infrared or another type of light, the lack of light in videos introduces uncertainty in a program, which can produce bias, where some categories of images are more accurately processed by the algorithm than others. This bias can manifest itself in different scenarios, such as during nighttime or when recording people with darker skin, and these are the biases that we aim to correct. My part in the project involved labelling the videos that are going to be used for analysis for the algorithms, and attempting to help create a standardized method of labelling in order to have a set of videos with which the algorithm can be trained with. Our sample set was purposefully selected to have a variety of videos with different light levels and skin tones. Our ultimate purpose was to label as many videos as possible to use later on in the project, where other groups are working on developing the algorithm and all other overarching parts of the project. The main project was not completed, and likely will not for some years, but we achieved our loose goal of labelling videos.

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Racial Bias in Medical School Admissions

Currently, the diversity of doctors and healthcare workers is not matching the increasing diversity of Americans (Boscardin, 2015). This lack of diversity contributes to health inequities – many patients of color avoid hospital visits because they feel as if they will not be listened to. In fact, it is proven that Latinx people and African American people utilize healthcare less, even when they have adequate access to healthcare (Ashton, 2003). Additionally, White clinicians may have a negative internal bias (e.g., implicit bias) towards patients of color which affects their treatment decisions. Research (e.g. Steiner, 2013) demonstrates that BIPOC physicians are less likely to have internal biases towards patients of color. Other research (e.g., Dennis, 2001) indicates that African American physicians are four times as likely to provide care to patients of color. Therefore, by increasing the diversity of healthcare professionals, patients of color will be more likely to receive the treatments they need, resulting in the reduction of some healthcare inequities. Diversity in the physician workforce can be facilitated by increasing the number of BIPOC students that are admitted to, and retained in, medical school. However, students of color may be discouraged from pursuing a career in medicine due to racial bias. My review focuses on various types of racial biases that BIPOC applicants face in the admissions process. Across the 15 articles I reviewed, I found that racial bias can occur in many critical stages: during reviews of application materials and letters of recommendation, applicant interviews, and the interpretation of MCAT scores. Additionally, I reviewed articles to identify some strategies that medical schools might implement to minimize the effect of racial bias. I discuss the implications of these studies, and future strategies that medical schools should take to combat racial bias.

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The DISH Survey

The original purpose of this research project was to perform a full literature review on the articles published by researchers at the University of Michigan’s Center for Sexuality and Health Disparities (CSHD). This would have produced the annual Community Report, which was created in order to keep the general public up to date on research findings that pertain to the sexual reproductive health of marginalized communities with a special focus on sexual and gender minorities and/or people of color. However, while beginning the process of creating the Community Report, the research project shifted towards wanting to discover how and where the general American public receives their sexual health information. The Dissemination of Information on Sexual Health (DISH) Survey was created with the intent of better understanding the relationship between demographics, health information-seeking behavior, and perceptions of sexual health issues. This 70+ question survey will recruit individuals using Facebook advertisement for approximately two weeks, with 300-600 responses expected to be collected. Participants will be asked to answer questions concerning their gender, sexuality, and state of health. The CSHD will utilize the data collected to better develop methods to inform the public about their research findings, which would create a more health-informed community.

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Effects of Rapamycin on Age-Associated Vasculature Transcription Profiles

Rapamycin (Rapa), an mTOR1 inhibitor, is one of the few therapies shown to prolong lifespan. It also may mitigate the adverse effects of age on the vasculature. To explore the vascular transcription profiles of age-associated pathways in mice treated with Rapa, mice were 1? treated with varying dosing regimens of Rapa beginning at 20 months of age?. The mice were checked twice daily for health status and were euthanized at 22 months of age. The aortas of mice were collected, and RNA was extracted from the aortas. RNA was then tested to ensure the collected samples were of adequate quality for RNA-sequencing analysis. We expect that the mice experiencing prolonged lifespan in response to Rapa treatment will have differences in their transcription profiles compared to young and old mice which had not been treated with Rapa. This information may provide insight related to the effects of Rapa towards prolongation of lifespan and may direct future studies in humans.

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FADD amplification in lung cancer promotes G1 to S cell cycle transition

Glioblastoma multiforme (GBM) is the most malignant primary central nervous system tumor and once diagnosed, the patient outcome does not look good. Currently, there are no curative treatment options for GBM, and the survival rate of patients diagnosed with the disease remains low. RAD51 is highly expressed in response to radiation and chemotherapy which is required for DNA repair from after these genotoxic therapies. Using small molecule drugs that modulate the RAD51 function, we have shown that they enhance chemo- and radio-sensitization in GBM due to inhibition of DNA repair. My UROP project will involve the purification of RAD51 protein so that the binding site and mechanism by which the RAD51 targeted drugs function can be delineated using X-ray crystallography. We hypothesize that the inhibition of RAD51 will sensitize GSCs to radio and chemotherapy which will further improve the survival of GBM patients. Although there are currently no results, this research and experiment is valuable because there are no effective therapies for GBM.

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Short-term Self-regulation of COPD

Chronic Obstructive Pulmonary Disease creates long-term obstacles for patients, which can result in exacerbations and mortality. Previous clinical trials focus on a patient’s physical well-being, utilizing bronchodilators or inhaled therapy as an attempt to alleviate symptoms and prevent future exacerbations. Short-term Self-regulation of COPD is focused on a patient’s self-regulation and provides an alternative hypothesis that a more active lifestyle will result in improved diligence of self-regulation as a short-term outcome. Participants were recruited from the Ann Arbor and Flint area and severity of their disease was measured prior to randomization. As intense physical activity is not practical for these subjects, this study utilizes chair yoga and imagery in the control group and squats, leg lifts, arm curls, oblique twists, and similar activities led by a kinesiology specialist as part of the experimental group; while group placement is randomly generated, both groups participate in activities that have the potential to improve outcomes. Our analysis involves evaluations taken at baseline and an assessment taken approximately 3 months after completion of the 10-week training classes. This data is taken from the Active for Life with COPD data set that includes testing visits, seven-day activity monitoring, the Chronic Respiratory Disease Questionnaire Self-Administered Standardized (CRQ-SAS), Multidimensional Outcome Expectations for Exercise Scale, and the Self-Regulation for Physical Activity Scale responses. Intervention elements during weeks 1-10 consist of lab-based exercises and an educational program with further intervention elements measured at approximately six months into the study; coaching phone calls and a booster session also occur. Data collection is done with blind testing, surveys, and numerous physical measurements for fatigue and mastery of activities like the six-minute walk. This research aims to support the hypothesis that a less-sedentary lifestyle leads to improved self-regulation in COPD patients.

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Emotion Regulation in Daily Life during COVID-19 Pandemic

The aim of this study is to assess individuals’ day-to-day emotional experiences and how they regulate their emotions, especially in context of the COVID-19 pandemic. Through conducting a 9-month longitudinal online study, we hope to identify the characteristics that are most vulnerable to COVID-19 stress and anxiety. Furthermore, we aim to examine individuals’ pattern of emotion regulation strategies to reduce COVID-19 stress and anxiety. All participants are above 18 years old, located in the University of Michigan. Recruitment was sent by a link 2,000 random University of Michigan students through the Office of Registrar. Using UM Qualtrics we first collected self-report measures of coping and emotion regulation strategies. Second, we conducted a follow-up survey using an Ecological Momentary Assessment (EMA) approach among participants who are interested in the follow-up study. During the study, EMA survey data was collected at 6 time points/per day for 5 days in spaced out intervals. The results from part 1 online-survey provide evidence that emotion regulation strategy patterns have an association with several mental health outcomes and COVID-19 related anxieties. Through these findings we acknowledge the importance of taking a person-centered approach to emotion regulation strategies especially using EMA measurement. Recently, we started another wave data collection using online-survey to understand factors that are associated with the attitude towards COVID-19 vaccinations. We hypothesized that there would be correlation between attitudes (positive/negative) towards COVID-19 and several factors across domains (cognitive, emotional, and behavioral).

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A Qualitative Analysis of Rheumatic Disease Patients’ Experiences with COVID-19

Background: Little is known about how COVID-19 interacts with rheumatic diseases. Although people with autoimmune diseases are thought to be more susceptible to complications of COVID-19, countless Americans with such illnesses still face uncertainty with how to protect themselves and how to seek medical attention. Objectives: This project consists of two subprojects with slightly different aims. The objective of the FORWARD subproject is to understand the experiences of rheumatic disease patients who displayed symptoms of COVID-19. The UofM subproject serves to uncover the long term impacts of COVID-19 among rheumatic disease patients. Methods: Qualitative data was collected from two cohorts. We conducted interviews with rheumatic disease patients from the FORWARD registry who reported testing positive for COVID-19 or antibodies, or received treatment for COVID-19. We reviewed electronic medical records of rheumatic disease patients at Michigan Medicine who tested positive for COVID-19 or antibodies, or were presumed positive and displayed symptoms for one month or more. Qualitative analysis, particularly through open coding, will serve to identify patterns or themes within patients’ experiences. Preliminary Results: One theme that continuously appears is the uncertainty in seeking help. Many patients were misdiagnosed””despite displaying symptoms””and thus received inadequate treatment. These experiences often had an emotional impact, prompting fear in terms of spreading the virus and suffering complications due to their autoimmune disease. We have analyzed data from 12 FORWARD participants, and will continue with the 45 UofM patients, looking for significant themes to shed light on the experiences of rheumatic diseases patients throughout the pandemic.

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Experiences of uncertainty among patients with rheumatic illnesses during Covid-19

Despite the fact that Covid-19 is known to be more severe in patients with other comorbidities, the experiences of people with rheumatic illnesses during the pandemic are seldom discussed. In reality, their experiences are important to understanding both the virus’ physical and emotional effects on at-risk populations. Specific questions were in regards to the main sources of anxiety and uncertainty felt by rheumatic patients, and how many felt impacts to mental health. Using Nvivo analysis software, our research team qualitatively coded deidentified patient transcripts and case reports from FORWARD, the National Databank for Rheumatic Diseases. The software allowed us to compare the data presented in order to find common issues between patient experiences. These comparisons revealed that many of the patients, whether diagnosed or not with Covid-19, felt great anxiety and uncertainty during the pandemic. Further analysis showed that these feelings came from deaths of friends or family members, worsened symptoms in conjunction with their illness, or general lack of knowledge of the effects the virus could have. Although each patient as an individual had their own experiences, the qualitative coding allowed us to find that uncertainty was a major issue that still affects the mental well-being of these patients, their family members, and their friends. This project will allow health care providers and other stakeholders to understand the rheumatic patient experience with viruses from an emotional level, as well as a physiological one.

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