Biomedical Informatics Commons^™

Controlling Multiple Covid-19 Epidemic Waves: An Insight From A Multi-Scale Model Linking The Behaviour Change Dynamics To The Disease Transmission Dynamics, Biao Tang, Weike Zhou, Xia Wang, Hulin Wu, Yanni Xiao

Faculty, Staff and Student Publications

COVID-19 epidemics exhibited multiple waves regionally and globally since 2020. It is important to understand the insight and underlying mechanisms of the multiple waves of COVID-19 epidemics in order to design more efficient non-pharmaceutical interventions (NPIs) and vaccination strategies to prevent future waves. We propose a multi-scale model by linking the behaviour change dynamics to the disease transmission dynamics to investigate the effect of behaviour dynamics on COVID-19 epidemics using game theory. The proposed multi-scale models are calibrated and key parameters related to disease transmission dynamics and behavioural dynamics with/without vaccination are estimated based on COVID-19 epidemic data (daily reported …

Non-Linear Machine Learning Models Incorporating Snps And Prs Improve Polygenic Prediction In Diverse Human Populations, Michael Elgart, Genevieve Lyons, Santiago Romero-Brufau, Nuzulul Kurniansyah, Jennifer A Brody, Xiuqing Guo, Henry J Lin, Laura Raffield, Yan Gao, Han Chen, Paul De Vries, Donald M Lloyd-Jones, Leslie A Lange, Gina M Peloso, Myriam Fornage, Jerome I Rotter, Stephen S Rich, Alanna C Morrison, Bruce M Psaty, Daniel Levy, Susan Redline, Nhlbi’S Trans-Omics In Precision Medicine (Topmed) Consortium, Tamar Sofer

Faculty, Staff and Student Publications

Polygenic risk scores (PRS) are commonly used to quantify the inherited susceptibility for a trait, yet they fail to account for non-linear and interaction effects between single nucleotide polymorphisms (SNPs). We address this via a machine learning approach, validated in nine complex phenotypes in a multi-ancestry population. We use an ensemble method of SNP selection followed by gradient boosted trees (XGBoost) to allow for non-linearities and interaction effects. We compare our results to the standard, linear PRS model developed using PRSice, LDpred2, and lassosum2. Combining a PRS as a feature in an XGBoost model results in a relative increase in …

Building Consensus For A Shared Definition Of Adverse Events: A Case Study In The Profession Of Dentistry, Amy Franklin, Elsbeth Kalenderian, Nutan Hebballi, Veronique Delattre, Jini Etoule, Joel White, Ram Vaderhobli, Denice Stewart, Karla Kent, Alfa Yansane, Muhammad Walji

Faculty, Staff and Student Publications

BACKGROUND: To achieve high-quality health care, adverse events (AEs) must be proactively recognized and mitigated. However, there is often ambiguity in applying guidelines and definitions. We describe the iterative calibration process needed to achieve a shared definition of AEs in dentistry. Our alignment process includes both independent and consensus building approaches.

OBJECTIVE: We explore the process of defining dental AEs and the steps necessary to achieve alignment across different care providers.

METHODS: Teams from 4 dental institutions across the United States iteratively reviewed patient records after identification of charts using an automated trigger tool. Calibration across teams was supported through …

Development Of A Quality Improvement Dental Chart Review Training Program, Elsbeth Kalenderian, Nutan B Hebballi, Amy Franklin, Alfa Yansane, Ana M Ibarra Noriega, Joel White, Muhammad F Walji

Faculty, Staff and Student Publications

INTRODUCTION: Chart review is central to understanding adverse events (AEs) in medicine. In this article, we describe the process and results of educating chart reviewers assigned to evaluate dental AEs.

METHODS: We developed a Web-based training program, "Dental Patient Safety Training," which uses both independent and consensus-based curricula, for identifying AEs recorded in electronic health records in the dental setting. Training included (1) didactic education, (2) skills training using videos and guided walkthroughs, (3) quizzes with feedback, and (4) hands-on learning exercises. In addition, novice reviewers were coached weekly during consensus review discussions. TeamExpert was composed of 2 experienced reviewers, …

Assessing The Practicality Of Using A Single Knowledge-Based Planning Model For Multiple Linac Vendors, Raphael J Douglas, Adenike Olanrewaju, Lifei Zhang, Beth M Beadle, Laurence E Court

Faculty, Staff and Student Publications

Purpose: Knowledge-based planning (KBP) has been shown to be an effective tool in quality control for intensity-modulated radiation therapy treatment planning and generating high-quality plans. Previous studies have evaluated its ability to create consistent plans across institutions and between planners within the same institution as well as its use as teaching tool for inexperienced planners. This study evaluates whether planning quality is consistent when using a KBP model to plan across different treatment machines.

Materials and methods: This study used a RapidPlan model (Varian Medical Systems) provided by the vendor, to which we added additional planning objectives, maximum dose limits, …

Drug-Target Network Study Reveals The Core Target-Protein Interactions Of Various Covid-19 Treatments, Yulin Dai, Hui Yu, Qiheng Yan, Bingrui Li, Andi Liu, Wendao Liu, Xiaoqian Jiang, Yejin Kim, Yan Guo, Zhongming Zhao

Faculty, Staff and Student Publications

The coronavirus disease 2019 (COVID-19) pandemic has caused a dramatic loss of human life and devastated the worldwide economy. Numerous efforts have been made to mitigate COVID-19 symptoms and reduce the death rate. We conducted literature mining of more than 250 thousand published works and curated the 174 most widely used COVID-19 medications. Overlaid with the human protein-protein interaction (PPI) network, we used Steiner tree analysis to extract a core subnetwork that grew from the pharmacological targets of ten credible drugs ascertained by the CTD database. The resultant core subnetwork consisted of 34 interconnected genes, which were associated with 36 …

Translating Electronic Health Record-Based Patient Safety Algorithms From Research To Clinical Practice At Multiple Sites, Andrew J Zimolzak, Hardeep Singh, Daniel R Murphy, Li Wei, Sahar A Memon, Divvy K Upadhyay, Saritha Korukonda, Lisa Zubkoff, Dean F Sittig

Faculty, Staff and Students Publications

INTRODUCTION: Researchers are increasingly developing algorithms that impact patient care, but algorithms must also be implemented in practice to improve quality and safety.

OBJECTIVE: We worked with clinical operations personnel at two US health systems to implement algorithms to proactively identify patients without timely follow-up of abnormal test results that warrant diagnostic evaluation for colorectal or lung cancer. We summarise the steps involved and lessons learned.

METHODS: Twelve sites were involved across two health systems. Implementation involved extensive software documentation, frequent communication with sites and local validation of results. Additionally, we used automated edits of existing code to adapt it …

Vaccine Hesitancy And Betrayal Aversion, Abdelaziz Alsharawy, Esha Dwibedi, Jason Aimone, Sheryl Ball

Faculty, Staff and Student Publications

The determinants of vaccine hesitancy remain complex and context specific. Betrayal aversion occurs when an individual is hesitant to risk being betrayed in an environment involving trust. In this pre-registered vignette experiment, we show that betrayal aversion is not captured by current vaccine hesitancy measures despite representing a significant source of unwillingness to be vaccinated. Our survey instrument was administered to 888 United States residents via Amazon Mechanical Turk in March 2021. We find that over a third of participants have betrayal averse preferences, resulting in an 8-26% decline in vaccine acceptance, depending on the betrayal source. Interestingly, attributing betrayal …

Adding Customized Electron Energy Beams To Truebeam Linear Accelerators, Song Gao, Manickam Muruganandham, Weiliang Du, Jared Ohrt, Rajat J Kudchadker, Peter A Balter

Faculty, Staff and Student Publications

Purpose: To better meet clinical needs and facilitate optimal treatment planning, we added two new electron energy beams (7 and 11 MeV) to two Varian TrueBeam linacs.

Methods: We worked with the vendor to create two additional customized electron energies without hardware modifications. For each beam, we set the bending magnet current and then optimized other beam-specific parameters to achieve depths of 50% ionization (I50 ) of 2.9 cm for 7 MeV and 4.2 cm for the 11 MeV beam with the 15 × 15 cm2 cone at 100 cm source-to-surface distance (SSD) by using an ionization chamber profiler (ICP) …

Promoting Cancer Health Equity: A Qualitative Study Of Mentee And Mentor Perspectives Of A Training Program For Underrepresented Scholars In Cancer Health Disparities, Anastasia Rogova, Isabel Martinez Leal, Maggie Britton, Shine Chang, Kamisha H Escoto, Kayce D Solari Williams, Crystal Roberson, Lorna H Mcneill, Lorraine R Reitzel

Faculty, Staff and Student Publications

Racial and ethnic minorities, and women, experience stark disparities in cancer risk behaviors and mortality rates, yet often remain underrepresented in scientific research positions. We conducted an exploratory, qualitative study to examine the value of mentored research experience as part of an NCI-funded research training program designed to increase the representation of minority and women scientists in cancer disparities research. Using individual interviews, we explored 16 mentees' and 7 mentors' program experiences and perspectives to identify the most effective strategies to build strong mentoring relationships that could ultimately contribute to increased representation in health disparities research. Two expert analysts employed …

Unpacking Misinfodemic During A Global Health Crisis: A Qualitative Inquiry Of Psychosocial Characteristics In Social Media Interactions, Sofia M Olivares, Sahiti Myneni

Faculty, Staff and Student Publications

The pervasiveness of health information in social media has led to a modern misinformation crisis, also known as a misinfodemic. Misinfodemics have upended public health activities as clearly evident during the COVID-19 pandemic. The objective of this study is to characterize social media content and information sources using theory-driven health behavior and psychology constructs to better understand the motifs of misinformation and their role in the dissemination of health (mis)information in Twitter posts. We analyzed 1,400 randomly selected tweets related to COVID-19 to ascertain four important variables, what is the tweet about (content), how is it structured (linguistic features), who …

Latent Linguistic Motifs In Social Media Postings Resisting Covid-19 Misinformation, Tavleen Singh, Sofia Olivares, Sahiti Myneni

Faculty, Staff and Student Publications

Social media has become a predominant source of information for many health care consumers. However, false and misleading information is a pervasive problem in this context. Specifically, health-related misinformation has become a significant public health challenge, impeding the effectiveness of public health awareness campaigns and resulting in suboptimal responsiveness to the communication of legitimate risk-related information. Little is known about the mechanisms driving the seeding and spreading of such information. In this paper, we specifically examine COVID-19 tweets which attempt to correct misinformation. We employ a mixed-methods approach comprising qualitative coding, deep learning classification, and computerized text analysis to understand …

Predictive Performance Of Different Ntcp Techniques For Radiation-Induced Esophagitis In Nsclc Patients Receiving Proton Radiotherapy, Mei Chen, Zeming Wang, Shengpeng Jiang, Jian Sun, Li Wang, Narayan Sahoo, G Brandon Gunn, Steven J Frank, Cheng Xu, Jiayi Chen, Quynh-Nhu Nguyen, Joe Y Chang, Zhongxing Liao, X Ronald Zhu, Xiaodong Zhang

Faculty, Staff and Student Publications

This study aimed to compare the predictive performance of different modeling methods in developing normal tissue complication probability (NTCP) models for predicting radiation-induced esophagitis (RE) in non-small cell lung cancer (NSCLC) patients receiving proton radiotherapy. The dataset was composed of 328 NSCLC patients receiving passive-scattering proton therapy and 41.6% of the patients experienced ≥ grade 2 RE. Five modeling methods were used to build NTCP models: standard Lyman-Kutcher-Burman (sLKB), generalized LKB (gLKB), multivariable logistic regression using two variable selection procedures-stepwise forward selection (Stepwise-MLR), and least absolute shrinkage and selection operator (LASSO-MLR), and support vector machines (SVM). Predictive performance was internally …

A Multi-Task Gaussian Process Self-Attention Neural Network For Real-Time Prediction Of The Need For Mechanical Ventilators In Covid-19 Patients, Kai Zhang, Siddharth Karanth, Bela Patel, Robert Murphy, Xiaoqian Jiang

Faculty, Staff and Student Publications

OBJECTIVE: The Coronavirus Disease 2019 (COVID-19) pandemic has overwhelmed the capacity of healthcare resources and posed a challenge for worldwide hospitals. The ability to distinguish potentially deteriorating patients from the rest helps facilitate reasonable allocation of medical resources, such as ventilators, hospital beds, and human resources. The real-time accurate prediction of a patient's risk scores could also help physicians to provide earlier respiratory support for the patient and reduce the risk of mortality.

METHODS: We propose a robust real-time prediction model for the in-hospital COVID-19 patients' probability of requiring mechanical ventilation (MV). The end-to-end neural network model incorporates the Multi-task …

A Roadmap To Clinical Trials For Flash, Paige A Taylor, Jean M Moran, David A Jaffray, Jeffrey C Buchsbaum

Faculty, Staff and Student Publications

While FLASH radiation therapy is inspiring enthusiasm to transform the field, it is neither new nor well understood with respect to the radiobiological mechanisms. As FLASH clinical trials are designed, it will be important to ensure we can deliver dose consistently and safely to every patient. Much like hyperthermia and proton therapy, FLASH is a promising new technology that will be complex to implement in the clinic and similarly will require customized credentialing for multi-institutional clinical trials. There is no doubt that FLASH seems promising, but many technologies that we take for granted in conventional radiation oncology, such as rigorous …

Knowledge-Based Planning For The Radiation Therapy Treatment Plan Quality Assurance For Patients With Head And Neck Cancer, Wenhua Cao, Mary Gronberg, Adenike Olanrewaju, Thomas Whitaker, Karen Hoffman, Carlos Cardenas, Adam Garden, Heath Skinner, Beth Beadle, Laurence Court

Faculty, Staff and Student Publications

This study aimed to investigate the feasibility of using a knowledge-based planning technique to detect poor quality VMAT plans for patients with head and neck cancer. We created two dose-volume histogram (DVH) prediction models using a commercial knowledge-based planning system (RapidPlan, Varian Medical Systems, Palo Alto, CA) from plans generated by manual planning (MP) and automated planning (AP) approaches. DVHs were predicted for evaluation cohort 1 (EC1) of 25 patients and compared with achieved DVHs of MP and AP plans to evaluate prediction accuracy. Additionally, we predicted DVHs for evaluation cohort 2 (EC2) of 25 patients for which we intentionally …

Platelets Increase The Expression Of Pd-L1 In Ovarian Cancer, Min Soon Cho, Hani Lee, Ricardo Gonzalez-Delgado, Dan Li, Tomoyuki Sasano, Wendolyn Carlos-Alcalde, Qing Ma, Jinsong Liu, Anil K Sood, Vahid Afshar-Kharghan

Faculty, Staff and Student Publications

The interactions between platelets and cancer cells activate platelets and enhance tumor growth. Platelets increase proliferation and epithelial-mesenchymal transition in cancer cells, inhibit anoikis, enhance the extravasation of cancer cells, and protect circulating tumor cells against natural killer cells. Here, we have identified another mechanism by which platelets dampen the immune attack on cancer cells. We found that platelets can blunt the antitumor immune response by increasing the expression of inhibitory immune checkpoint (PD-L1) on ovarian cancer cells in vitro and in vivo. Platelets increased PD-L1 in cancer cells via contact-dependent (through NF-κB signaling) and contact-independent (through TFGβR1/Smad signaling) pathways. …

An Observational Retrospective Study Of Adverse Events And Behavioral Outcomes During Pediatric Dental Sedation, Kawtar Zouaidi, Gregory Olson, Helen H Lee, Elsbeth Kalenderian, Muhammad F Walji

Faculty, Staff and Student Publications

Purpose: The purpose of this study was to examine a university-based dental electronic health records (EHR) database to identify sedation-related adverse events (AEs) and assess patients' behavioral outcomes during routine pediatric dental sedations (PDSs) in a dental school clinic.

Methods: A database was screened for patients younger than 18 years old who had received dental sedation in 2019. The qualifying EHRs were then accessed and sedations were reviewed for AEs, which were categorized using a 12-point classification system and the Tracking and Reporting Outcomes of Procedural Sedation Tool. Patient behaviors were assessed using provider progress notes and categorized as presence/ …

Factors Associated With Covid-19 Death In The United States: Cohort Study, Uan-I Chen, Hua Xu, Trudy Millard Krause, Raymond Greenberg, Xiao Dong, Xiaoqian Jiang

Faculty, Staff and Student Publications

BACKGROUND: Since the initial COVID-19 cases were identified in the United States in February 2020, the United States has experienced a high incidence of the disease. Understanding the risk factors for severe outcomes identifies the most vulnerable populations and helps in decision-making.

OBJECTIVE: This study aims to assess the factors associated with COVID-19-related deaths from a large, national, individual-level data set.

METHODS: A cohort study was conducted using data from the Optum de-identified COVID-19 electronic health record (EHR) data set; 1,271,033 adult participants were observed from February 1, 2020, to August 31, 2020, until their deaths due to COVID-19, deaths …

An Efficient Magnetic Resonance Image Data Quality Screening Dashboard, Evan D H Gates, Adrian Celaya, Dima Suki, Dawid Schellingerhout, David Fuentes

Faculty, Staff and Student Publications

Purpose: Complex data processing and curation for artificial intelligence applications rely on high-quality data sets for training and analysis. Manually reviewing images and their associated annotations is a very laborious task and existing quality control tools for data review are generally limited to raw images only. The purpose of this work was to develop an imaging informatics dashboard for the easy and fast review of processed magnetic resonance (MR) imaging data sets; we demonstrated its ability in a large-scale data review.

Methods: We developed a custom R Shiny dashboard that displays key static snapshots of each imaging study and its …

Pgc1Α/Β Expression Predicts Therapeutic Response To Oxidative Phosphorylation Inhibition In Ovarian Cancer, Carmen Ghilardi, Catarina Moreira-Barbosa, Laura Brunelli, Paola Ostano, Nicolò Panini, Monica Lupi, Alessia Anastasia, Fabio Fiordaliso, Monica Salio, Laura Formenti, Massimo Russo, Edoardo Arrigoni, Ferdinando Chiaradonna, Giovanna Chiorino, Giulio Draetta, Joseph R Marszalek, Christopher P Vellano, Roberta Pastorelli, Mariarosa Bani, Alessandra Decio, Raffaella Giavazzi

Faculty, Staff and Student Publications

Ovarian cancer is the deadliest gynecologic cancer, and novel therapeutic options are crucial to improve overall survival. Here we provide evidence that impairment of oxidative phosphorylation (OXPHOS) can help control ovarian cancer progression, and this benefit correlates with expression of the two mitochondrial master regulators PGC1α and PGC1β. In orthotopic patient-derived ovarian cancer xenografts (OC-PDX), concomitant high expression of PGC1α and PGC1β (PGC1α/β) fostered a unique transcriptional signature, leading to increased mitochondrial abundance, enhanced tricarboxylic acid cycling, and elevated cellular respiration that ultimately conferred vulnerability to OXPHOS inhibition. Treatment with the respiratory chain complex I inhibitor IACS-010759 caused mitochondrial swelling …

Effect Of Perfluorocarbon Composition On Activation Of Phase-Changing Ultrasound Contrast Agents, Trevor M Mitcham, Dmitry Nevozhay, Yunyun Chen, Linh D Nguyen, Gianmarco F Pinton, Stephen Y Lai, Konstantin V Sokolov, Richard R Bouchard

Faculty, Staff and Student Publications

BACKGROUND: While microbubble contrast agents (MCAs) are commonly used in ultrasound (US), they are inherently limited to vascular targets due to their size. Alternatively, phase-changing nanodroplet contrast agents (PNCAs) can be delivered as nanoscale agents (i.e., small enough to extravasate), but when exposed to a US field of sufficient mechanical index (MI), they convert to MCAs, which can be visualized with high contrast using nonlinear US.

PURPOSE: To investigate the effect of perfluorocarbon (PFC) core composition and presence of cholesterol in particle coatings on stability and image contrast generated from acoustic activation of PNCAs using high-frequency US suitable for clinical …

Sars-Cov-2 Rna Abundance In Wastewater As A Function Of Distinct Urban Sewershed Size., Rochelle H. Holm, Anish Mukherjee, Jayesh P. Rai, Ray A. Yeager, Daymond Talley, Shesh N. Rai, Aruni Bhatnagar, Ted Smith

Faculty and Staff Scholarship

During the COVID-19 pandemic, wastewater-based epidemiology has emerged as a promising approach for monitoring SARS-CoV-2 prevalence on a community-level. Despite much being known about the utility of making these measurements in large wastewater treatment plants, little is known about the correlation with finer geographic resolution, such as those obtained through sewershed sub-area catchments. This study aims to identify community wastewater surveillance characteristics between sewershed areas that affect the strength of the association of SARS-CoV-2 RNA detection in a metropolitan area. For this, wastewater from 17 sewershed areas were sampled in Louisville/Jefferson County, Kentucky (USA), from August 2020 to April 2021 …

Use Of The Deep Learning Approach To Measure Alveolar Bone Level, Chun-Teh Lee, Tanjida Kabir, Jiman Nelson, Sally Sheng, Hsiu-Wan Meng, Thomas E Van Dyke, Muhammad F Walji, Xiaoqian Jiang, Shayan Shams

Faculty, Staff and Student Publications

AIM: The goal was to use a deep convolutional neural network to measure the radiographic alveolar bone level to aid periodontal diagnosis.

MATERIALS AND METHODS: A deep learning (DL) model was developed by integrating three segmentation networks (bone area, tooth, cemento-enamel junction) and image analysis to measure the radiographic bone level and assign radiographic bone loss (RBL) stages. The percentage of RBL was calculated to determine the stage of RBL for each tooth. A provisional periodontal diagnosis was assigned using the 2018 periodontitis classification. RBL percentage, staging, and presumptive diagnosis were compared with the measurements and diagnoses made by the …

Brain Stereotactic Radiosurgery Using Mr-Guided Online Adaptive Planning For Daily Setup Variation: An End-To-End Test, Eun Young Han, He Wang, Tina Marie Briere, Debra Nana Yeboa, Themistoklis Boursianis, Georgios Kalaitzakis, Evangelos Pappas, Pamela Castillo, Jinzhong Yang

Faculty, Staff and Student Publications

Online magnetic resonance (MR)-guided radiotherapy is expected to benefit brain stereotactic radiosurgery (SRS) due to superior soft tissue contrast and capability of daily adaptive planning. The purpose of this study was to investigate daily adaptive plan quality with setup variations and to perform an end-to-end test for brain SRS with multiple metastases treated with a 1.5-Tesla MR-Linac (MRL). The RTsafe PseudoPatient Prime brain phantom was used with a delineation insert that includes two predefined structures mimicking gadolinium contrast-enhanced brain lesions. Daily adaptive plans were generated using six preset and six random setup variations. Two adaptive plans per daily MR image …

Of Vascular Defense, Hemostasis, Cancer, And Platelet Biology: An Evolutionary Perspective, David G Menter, Vahid Afshar-Kharghan, John Paul Shen, Stephanie L Martch, Anirban Maitra, Scott Kopetz, Kenneth V Honn, Anil K Sood

Faculty, Staff and Student Publications

We have established considerable expertise in studying the role of platelets in cancer biology. From this expertise, we were keen to recognize the numerous venous-, arterial-, microvascular-, and macrovascular thrombotic events and immunologic disorders are caused by severe, acute-respiratory-syndrome coronavirus 2 (SARS-CoV-2) infections. With this offering, we explore the evolutionary connections that place platelets at the center of hemostasis, immunity, and adaptive phylogeny. Coevolutionary changes have also occurred in vertebrate viruses and their vertebrate hosts that reflect their respective evolutionary interactions. As mammals adapted from aquatic to terrestrial life and the heavy blood loss associated with placentalization-based live birth, platelets …

Machine Learning For Predicting Risk Of Early Dropout In A Recovery Program For Opioid Use Disorder, Assaf Gottlieb, Andrea Yatsco, Christine Bakos-Block, James R Langabeer, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

BACKGROUND: An increase in opioid use has led to an opioid crisis during the last decade, leading to declarations of a public health emergency. In response to this call, the Houston Emergency Opioid Engagement System (HEROES) was established and created an emergency access pathway into long-term recovery for individuals with an opioid use disorder. A major contributor to the success of the program is retention of the enrolled individuals in the program.

METHODS: We have identified an increase in dropout from the program after 90 and 120 days. Based on more than 700 program participants, we developed a machine learning …

Magi1 Inhibits Interferon Signaling To Promote Influenza A Infection, Yin Wang, Jun-Ichi Abe, Khanh M Chau, Yongxing Wang, Hang Thi Vu, Loka Reddy Velatooru, Fahad Gulraiz, Masaki Imanishi, Venkata S K Samanthapudi, Minh T H Nguyen, Kyung Ae Ko, Ling-Ling Lee, Tamlyn N Thomas, Elizabeth A Olmsted-Davis, Sivareddy Kotla, Keigi Fujiwara, John P Cooke, Di Zhao, Scott E Evans, Nhat-Tu Le

Faculty, Staff and Student Publications

We have shown that membrane-associated guanylate kinase with inverted domain structure-1 (MAGI1), a scaffold protein with six PSD95/DiscLarge/ZO-1 (PDZ) domains, is involved in the regulation of endothelial cell (EC) activation and atherogenesis in mice. In addition to causing acute respiratory disease, influenza A virus (IAV) infection plays an important role in atherogenesis and triggers acute coronary syndromes and fatal myocardial infarction. Therefore, the aim of this study is to investigate the function and regulation of MAGI1 in IAV-induced EC activation. Whereas, EC infection by IAV increases MAGI1 expression, MAGI1 depletion suppresses IAV infection, suggesting that the induction of MAGI1 may …

High-Resolution Metabolomics Of Exposure To Tobacco Smoke During Pregnancy And Adverse Birth Outcomes In The Atlanta African American Maternal-Child Cohort, Youran Tan, Dana Boyd Barr, P Barry Ryan, Veronika Fedirko, Jeremy A Sarnat, Audrey J Gaskins, Che-Jung Chang, Ziyin Tang, Carmen J Marsit, Elizabeth J Corwin, Dean P Jones, Anne L Dunlop, Donghai Liang

Faculty, Staff and Student Publications

Exposure to tobacco smoke during pregnancy has been associated with a series of adverse reproductive outcomes; however, the underlying molecular mechanisms are not well-established. We conducted an untargeted metabolome-wide association study to identify the metabolic perturbations and molecular mechanisms underlying the association between cotinine, a widely used biomarker of tobacco exposure, and adverse birth outcomes. We collected early and late pregnancy urine samples for cotinine measurement and serum samples for high-resolution metabolomics (HRM) profiling from 105 pregnant women from the Atlanta African American Maternal-Child cohort (2014-2016). Maternal metabolome perturbations mediating prenatal tobacco smoke exposure and adverse birth outcomes were assessed …

Update On Mri In Evaluation And Treatment Of Endometrial Cancer, Ekta Maheshwari, Stephanie Nougaret, Erica B Stein, Gaiane M Rauch, Ken-Pin Hwang, R Jason Stafford, Ann H Klopp, Pamela T Soliman, Katherine E Maturen, Andrea G Rockall, Susanna I Lee, Elizabeth A Sadowski, Aradhana M Venkatesan

Faculty, Staff and Student Publications

Endometrial cancer is the second most common gynecologic cancer worldwide and the most common gynecologic cancer in the United States, with an increasing incidence in high-income countries. Although the International Federation of Gynecology and Obstetrics (FIGO) staging system for endometrial cancer is a surgical staging system, contemporary published evidence-based data and expert opinions recommend MRI for treatment planning as it provides critical diagnostic information on tumor size and depth, extent of myometrial and cervical invasion, extrauterine extent, and lymph node status, all of which are essential in choosing the most appropriate therapy. Multiparametric MRI using a combination of T2-weighted sequences, …