Changing Gears – Page 7 – UROP Spring Symposium 2021

Changing Gears

Evaluating computational methods for predicting protein stability changes upon mutations

Protein-protein interactions (PPIs) are central in biological processes. Most proteins are marginally stable to perform their functions such as binding. Amino acid mutations taking place on proteins may change the protein stability and the affinity of a binding process, which further affects their biological functions. It is reported that amino acid mutations at protein-protein interfaces are frequently implicated in many diseases, including cancer. Therefore, it is of great significance to quantitatively predict the change of protein stability and binding affinity upon mutations, denoted as ddG_stability and ddG_binding. Many tools have been developed for ddG prediction, but there is lacking in a comprehensive comparison of their predictive powers. This study aimed to evaluate the predictive accuracy of a variety of widely used tools for ddG_stability and ddG_binding estimation on a large scale benchmark, placing a guidance on choosing the most accurate tool for ddG prediction.

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Active for Life: The effect of a low-intensity functional circuit training program on endurance among COPD patients

Patients with Chronic Obstructive Pulmonary Disease (COPD) often lead inactive lifestyles due to breathing difficulties, and sedentary behavior may worsen both symptoms and mortality. The moderate-to-vigorous-intensity exercises emphasized by most fitness programs are not feasible for patients with COPD, but increasing time of light-intensity exercise may be an effective alternative. In this study, a randomized-controlled trial is used to determine whether a light-intensity fitness program called Active for Life (designed by Principal Investigator [PI] Janet Larson) is effective in improving aerobic endurance among COPD patients in the long term (after 52 weeks). Qualified participants are randomly assigned to one of two treatment groups: the Active for Life intervention and the control group. Both groups are guided through physical and behavioral activities with the goal of educating participants about health, but the Active for Life group is focused on functional circuit training (FCT), while the control group involves chair-based movement. All participants undergo ten weeks of lab-based activities according to treatment group, followed by one year of follow-up appointments and self-paced at-home videos. Aerobic endurance is measured by distance walked during the six-minute walk test at baseline, ten weeks, three months, six months, and one year into the program. We hypothesize that engaging participants in the Active for Life program will increase distance walked during the six-minute walk test.

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The Effects of Out-of-Pocket Payments on Emergency and Trauma Surgery Patients’ Livelihoods

Every year, 3 million US residents suffer from injuries leading to needing medical care. The trauma care system has greatly improved saving lives from the time of injury, but many patients are left with out-of-pocket (OOP) payments whether or not they had insurance coverage. We do not know what the burden of these OOP payments are, including the long term financial, mental, and physical impact. The specific aims of this study are to 1) measure the OOP payments for patients who had an emergency surgical procedure, 2) quantify whether these OOP payments change on average by the type of insurance a patient has (private, Medicaid, Medicare, uninsured), and 3) understand the hardship caused by OOP payments for these emergency surgical procedures on the patient and their family. This study reports the findings from in-depth qualitative interviews of 30 patients =18 years of age sustaining a traumatic injury requiring treatment at the University of Michigan Hospital trauma center. We expect our mixed-methods analysis to elucidate the downstream effects of large OOP payments not otherwise able to be captured in available databases. Our findings will be one of the first to describe the long-term burden of trauma care and estimate the out-of-pocket payments trauma patients face from patient-level data.

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The Relationship between COVID-19 Racial Discrimination and Mental Health among Asian Americans

Racism and discrimination is a persisting dilemma that has affected people of color in the United States on many levels, including employment, housing, and health. Specifically, there is multiple evidence that indicates cultural racism (including stereotyping) connected to an increased prevalence of mental health concerns and poor overall wellness. Since the beginning of the COVID-19 pandemic, there has been an influx of anti-Asian racism and violence towards Asian American populations. In addition to the implicit and explicit bias that Asian populations have been facing prior to the COVID-19 pandemic, this current anti-Asian sentiment has the potential to have a toll on their mental and physical health. This research project explores the relationships between encountered racism during the COVID-19 pandemic and mental state among Asian American populations. The method used in this study is a quantitative survey; data collected were based on online survey questions that include demographics, experiences related to racism and/or discrimination after the start of the COVID-19 outbreak, mental state, and actions taken as results of racism experiences. The results and conclusion of the survey are yet to be reviewed and determined. I expect to identify an association between negative COVID-19 racism encounters/heightened fear for one’s safety and worsened mental health. With these results, we can address the need for prevention and intervention strategies to eliminate acts of racism/discrimination and to provide safe and comfortable environments for Asian Americans.

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Consentful Messaging

In the offline world, people’s communication with others revolves around networks. People tend to communicate more with people they have a strong tie with, which is easy to accomplish in fluid and nuanced ways. However, current social media systems lack such mechanisms for controlling interaction and communication based on network strength, which often leads to massive online harassment and abuse. A major example is Twitter, a social platform well-known for its openness. In this work, we present a system called NetRule, a Chrome extension that augments Twitter and gives users the ability to author network rules to control incoming messages and notifications. Through NetRule, users can easily combine and apply network-based rules on Twitter accounts that initiate interactions, such as whether the number of mutuals is high enough, whether the account has been blocked by one’s following, etc. Users also have the freedom to decide what happens to the accounts flagged by the rules, such as muting, blocking, or visibly coloring the accounts on the interface as a warning. Our evaluation of the system, a field deployment study on Twitter, showed that XXX.

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COVID-19 bioinformatics research

Bioinformatics has been a powerful method to study COVID-19 and our project look at ontology-based application in rational drug design. In our previous study (https://www.nature.com/articles/s41597-021-00799-w), the Coronavirus Infectious Disease Ontology (CIDO) was used as an ontological platform to represent anti-coronaviral drugs, drug targets, host-coronavirus interaction (HCI), and their relations. A “HCI checkpoint cocktail” strategy was further proposed to interrupt the important checkpoints in the dynamic HCI network and ontologies support this design process. However, the users such as drug researchers might not have the required ontology knowledge to use the information represented by the CIDO. Therefore, our project aims to design and build a user-friendly tool/website to allow basic queries and facilitate rational drug design using “checkpoint cocktail” strategy. We have developed a MySQL relational database that systematically represent the drugs, bioentities, interactions, pathways, and their relations. A set of real life data were added to the database. MySQL queries were performed to demonstrate our capabiliities to query different contents from the database to support the query of anti-coronaviral drug information. A web interface is being developed in order to further support online query and analysis of anti-coronaviral drugs, leading to rational anticoronaviral drug cocktail design.

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Sentiment Analysis of International Trade Agreements

The aim was to examine the changes in sentiment that occurred within trade agreements over time using rule-based sentiment analysis. In this case, the sentiment of a text was measured by the degree to which it expresses or implies an opinion. The focus was on a collection of English hundred trade agreements written within the last few decades. Before analysis, a dictionary of trade terms was created using seminal texts. Terms were categorized based on if they expressed a cooperative, punitive, or bureaucratic sentiment. The analysis entailed assigning sentiment scores to trade agreements based on the number of categorized terms within. There is no clear expected result, but there will likely be some observable change in overall sentiment over time, whether it is more or less sentiment.

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Data is asset – Evaluating the market value of databases

The topic of research concerns where SEC-licensed broker-dealers send their securities trades to be executed by financial services companies and if the payment for this order flow (PFOF) depends on the broker internalization’s market power and/or the broker-dealer’s trading volume. This research seeks to answer why certain broker-dealers send their trades to certain financial companies to execute their orders and if this reveals anything about trade practices. The SEC 606 reports that track this information are newly revised as of 2020 so this is fairly untouched public information that has had little-to-no analysis currently preformed on it. The main methodology used for data collection was simply searching through the broker-dealers websites for their 606 report which details where they send their trades to be executed and how much it costs to route orders to each firm. I tracked every broker-dealers information on an Excel spreadsheet and we will use this information to draw conclusions. We hope to find meaningful connections between broker-dealers order routing practices and the amount of market power they hold. We think there will be some connection between the amounts paid to certain companies and the amount of influence these firms have over the financial system. We don’t have any conclusions yet but we hope to start the data analysis soon. We hope to find patterns in our research that point to some conclusion on why certain companies behave the way they do with financial institutions and the implications that may have. This project hopes to shed some light on financial practices between institutions and to better explain how our financial system is structured as a whole and how much market power influences financial transactions. The results we find may help public policy makers, economists, politicians, etc., who all may use data such as this to have a basis for the functioning of our financial system.

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Data is asset – Evaluating the market value of databases

The project aims to evaluate how the market value reflects the value of the firms’ data accumulation. Traditionally, the market value can be estimated using the discounted cash flow (DCF) method. This approach is flawed because the prediction of future cash flow is always inaccurate. This project uses firms’ data accumulations as inputs. Regression models are fitted to quantify the results.

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