Health Sciences – Page 10 – UROP Spring Symposium 2021

Health Sciences

Altered Kynurenine Pathway in Aortic Patients is Linked to CKD Atherosclerosis

Skyelar Herriman Pronouns: she/her/hers Research Mentor(s): Anna Mathew, Assistant Professor Research Mentor School/College/Department: Internal Medicine/ Nephrology, Michigan Medicine Presentation Date: Thursday, April 22, 2021 Session: Session 5 (3pm-3:50pm) Breakout Room: Room 11 Presenter: 5 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Skyelar Herriman, Julian Meza, Biaoxin Chai, […]

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Restoring regulatory T cells in cigarette smoke-induced emphysema

Our research seeks to develop novel therapies to prevent chronic obstructive pulmonary disease progression (COPD), and associated mortality, through the demonstration that regulatory T cells, otherwise known as Tregs, reduce lung injury in a murine cigarette smoke exposure model. We hypothesize that by restoring regulatory T cells in subjects with COPD, natural killer cell (NK) cytotoxicity (percentage of cell death that occurs over the baseline) will be inhibited, therefore reducing the impact of natural killer cells on lung damage. Presently, our studies show that natural killer cell cytotoxicity positively correlates with epithelial cell apoptosis, indicating their relationship with tissue pathology. Additionally, we have shown that regulatory T cells are diminished in COPD, and that murine Tregs suppress NK cytotoxicity in vitro and in vivo following adoptive transfer. To further our murine exposure model, we utilize a Jaeger-Baumgartner Smoking Machine to expose the subjects to cigarette smoke for one hour per day for five days of the week to emulate the NK cytotoxicity observed in COPD subjects. These exposed mice will then be transferred nTreg, eTreg, mTreg, and Tconv or vehicle (negative controls) to later be euthanized and evaluated for Treg suppression of NKs, Treg phenotype stability, Treg migration and measurements of lung injury/inflammation, Treg suppression of T cell cytokine production, and Treg transcriptional signatures.Through sequencing, data processing and cell-type identification, power calculation and statistical analysis, and bioinformatic analysis for scRNA-sequences, we anticipate suppression of NK cytotoxicity with the transfer of mTregs, although we do expect for this suppression to decrease following sustained CS exposure. We also expect positive correlation between the stability of the Treg phenotype and the ability to inhibit natural killer cells.

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Restoring regulatory T cells in cigarette smoke-induced emphysema

Our research seeks to develop novel therapies to prevent chronic obstructive pulmonary disease progression (COPD), and associated mortality, through the demonstration that regulatory T cells, otherwise known as Tregs, reduce lung injury in a murine cigarette smoke exposure model. We hypothesize that by restoring regulatory T cells in subjects with COPD, natural killer cell (NK) cytotoxicity (percentage of cell death that occurs over the baseline) will be inhibited, therefore reducing the impact of natural killer cells on lung damage. Presently, our studies show that natural killer cell cytotoxicity positively correlates with epithelial cell apoptosis, indicating their relationship with tissue pathology. Additionally, we have shown that regulatory T cells are diminished in COPD, and that murine Tregs suppress NK cytotoxicity in vitro and in vivo following adoptive transfer. To further our murine exposure model, we utilize a Jaeger-Baumgartner Smoking Machine to expose the subjects to cigarette smoke for one hour per day for five days of the week to emulate the NK cytotoxicity observed in COPD subjects. These exposed mice will then be transferred nTreg, eTreg, mTreg, and Tconv or vehicle (negative controls) to later be euthanized and evaluated for Treg suppression of NKs, Treg phenotype stability, Treg migration and measurements of lung injury/inflammation, Treg suppression of T cell cytokine production, and Treg transcriptional signatures.Through sequencing, data processing and cell-type identification, power calculation and statistical analysis, and bioinformatic analysis for scRNA-sequences, we anticipate suppression of NK cytotoxicity with the transfer of mTregs, although we do expect for this suppression to decrease following sustained CS exposure. We also expect positive correlation between the stability of the Treg phenotype and the ability to inhibit natural killer cells.

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Hispanic Youth Nutritional Messaging Preferences in an mHealth Intervention

Background: There is a disparity in the prevalence of obesity for Black/African American and Hispanic/Latinx adolescents living in the United States compared to non-Hispanic White youth. One factor that influences this disparity is a lack of culturally relevant nutrition education for the Hispanic population. Previous studies have identified the need for more effective cultural tailoring and improved translations in order to overcome linguistic barriers and enhance the understanding of nutritional topics. Advances in technology, and obtaining messaging content preferences from Hispanic youth may provide a means of rectifying these cultural barriers and increase the efficacy of health behavior interventions.

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Scoping review on the impact of type 2 diabetes self management programs in Asian-Americans

Type 2 diabetes (T2D) is among the top reasons for deaths in Asian-Americans (AA). While this group consists of people from over 20 different countries, existing research often does not reflect the diversity and differences among AA, including many existing diabetes self-management programs (DSMP). No previous studies have compared existing DSMPs targeting AA. This scoping review includes adult AA participants and T2 DSMPs. DSMPs were defined as managing an individual’s condition, including self-care, symptom management, family management, medical-management, emotional management, or resource utilization. Keywords used to search for relevant articles included type 2 diabetes, Asian Americans (and its different subpopulations), and self-management. We searched for relevant articles with no data range in six databases, yielding 2581 results. DistillerSR was used to screen and extract data. After screening for titles and abstracts, 311 articles were included in the full-text screening. After screening the full-text articles, 31 articles were included in the final analysis. Articles were excluded if they were non-primary research studies, did not focus on T2D or AA adults, and did not include DSMPs. Data on different interventions and outcomes were extracted and analyzed using a charting form. We hypothesized that there is a need for more research focusing on minority subgroups. We also hypothesized that there is a need for more specialization of DSMPs to overcome many barriers AA face in healthcare, so that specific cultural and ethnic needs are addressed. Improved understanding of existing research may improve and guide future research in developing T2D self-management interventions for AA.

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Bioinformatics study on genetic diseases

Proteins are responsible for much of the functions and regulation of living organisms and their body systems. Understanding protein function has much to do with protein structure, thus, knowing what form proteins take is very useful. There are millions of different types of proteins, many of which are essential for human survival. Current ways to determine protein structure require knowledge of the genetic DNA sequence, which can later be translated into an amino acid sequence, thus revealing the shape through chemical properties. However, this study aims to create a program that can accurately predict protein structure without knowledge of the amino acid sequence. Instead, cryo-EM density maps are utilized to map the protein structure. The density maps are created utilizing convolutional neural networks (CNN), which are used to predict key atoms. These deep learning techniques are applied to create the program that can accurately predict a protein structure. This research is valuable because other scientists who require knowledge of protein structure could use it, especially if they do not have access to a specific genetic sequence they need. Next steps include perfecting the program such that the predictions reach the threshold for accuracy.

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Understanding how liver metastases regulate cancer trajectory

Moniah Almaweri Pronouns: She, Her, Hers Research Mentor(s): Michael Green, Assistant Professor Research Mentor School/College/Department: Radiation Oncology, Michigan Medicine Presentation Date: Thursday, April 22, 2021 Session: Session 5 (3pm-3:50pm) Breakout Room: Room 10 Presenter: 4 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Moniah Almaweri, Priyal Bajaj, Long

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Defining the Impact of Liver Metastases on Disease Trajectory

Priyal Bajaj Pronouns: She/Her/Hers Research Mentor(s): Michael Green, Assistant Professor Research Mentor School/College/Department: Radiation Oncology, Michigan Medicine Presentation Date: Thursday, April 22, 2021 Session: Session 5 (3pm-3:50pm) Breakout Room: Room 10 Presenter: 5 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Priyal Bajaj, Moniah Almaweri, Long Jiang, Amanda

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Modeling Molecular Pathogenesis of Idiopathic Pulmonary Fibrosis associated Lung Cancer (IPF-LC) in mice

Lung diseases are prolific killers in the United States each year. Of the major respiratory illnesses and cancers, lung cancer (LC) and idiopathic pulmonary fibrosis (IPF) are especially notable. In the US alone, there is estimated to be 250,000 new cases of lung cancer diagnosed annually, and around 130,000 patients die from the disease as well (Cancer.org). Meanwhile, IPF affects close to 200,000 people in the United States with a 3-5 year survival rate of 50% (National Heart, Lung, and Blood Institute). For each of the two diseases, treatment options are very different, making it especially difficult to provide sufficient care. In addition, around 22% of IPF patients will go on further to develop non-small cell lung carcinoma (NSCLC), or lung cancer (The Lancet). While it is not completely clear as to why this happens, it is likely due to increased inflammation in the lungs, providing an optimal ground for tumor growth.

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Bioinformatics study on genetic diseases

Missense single nucleotide polymorphisms (SNPs) are single point mutations that alter the amino acid produced. By changing the amino acid, protein stability, pathogenicity, or chemical properties of the protein can change. These mutations can also cause various diseases, specifically diabetes, intellectual disability, and speech-language disorder. However, not all mutations are pathogenic. This study’s objective is to research the properties of these mutations by looking at the change in free energy, amino acid change, and pathogenicity and to determine whether or not it’s harmful to humans. The study specifically focused on the forkhead transcription factors, a set of DNA-binding proteins involved in regulating gene expression. Data was gathered from the Uniprot database, and PyMOL was used to determine protein to DNA contact. EvoEF was used to calculate the change in free energy, and SIFT and Polyphen-2 were used to predict pathogenicity. The results showed common trends among most pathogenic mutations such as high ??G values, no DNA contact, and a high damaging score. Therefore, the data collected is useful for making predictions about mutations.

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