Data Science Commons^™

A Novel Integrated Approach To Predicting Cancer Immunotherapy Efficacy, Ruihan Luo, Jacqueline Chyr, Jianguo Wen, Yanfei Wang, Weiling Zhao, Xiaobo Zhou

Faculty, Staff and Student Publications

Immunotherapies have revolutionized cancer treatment modalities; however, predicting clinical response accurately and reliably remains challenging. Neoantigen load is considered as a fundamental genetic determinant of therapeutic response. However, only a few predicted neoantigens are highly immunogenic, with little focus on intratumor heterogeneity (ITH) in the neoantigen landscape and its link with different features in the tumor microenvironment. To address this issue, we comprehensively characterized neoantigens arising from nonsynonymous mutations and gene fusions in lung cancer and melanoma. We developed a composite NEO2IS to characterize interplays between cancer and CD8+ T-cell populations. NEO2IS improved prediction accuracy of patient responses to immune-checkpoint …

Inferring Personalized Treatment Effect Of Antihypertensives On Alzheimer's Disease Using Deep Learning, Pulakesh Upadhyaya, Yaobin Ling, Luyao Chen, Yejin Kim, Xiaoqian Jiang

Faculty, Staff and Student Publications

Alzheimer's disease (AD) is one of the leading causes of death in the United States, especially among the elderly. Recent studies have shown how hypertension is related to cognitive decline in elderly patients, which in turn leads to increased mortality as well as morbidity. There have been various studies that have looked at the effect of antihypertensive drugs in reducing cognitive decline, and their results have proved inconclusive. However, most of these studies assume the treatment effect is similar for all patients, thus considering only the average treatment effects of antihypertensive drugs. In this paper, we assume that the effect …

Predicting The Risk Of Alzheimer's Disease And Related Dementia In Patients With Mild Cognitive Impairment Using A Semi-Competing Risk Approach, Zhaoyi Chen, Yuchen Yang, Dazheng Zhang, Jingchuan Guo, Yi Guo, Xia Hu, Yong Chen, Jiang Bian

Faculty, Staff and Student Publications

Alzheimer's disease (AD) and AD-related dementias (AD/ADRD) are a group of progressive neurodegenerative diseases. The progression of AD can be conceptualized as a continuum in which patients progress from normal cognition to preclinical AD (i.e., no symptoms but biological changes in the brain) to mild cognitive impairment (MCI) due to AD (i.e., mild symptoms but not interfere with daily activities), followed by increasing severity of dementia due to AD. Early detection and prediction models for the transition of MCI to AD/ADRD are needed, and efforts have been made to build predictions of MCI conversion to AD/ADRD. However, most existing studies …

Comparative Analyses Define Differences Between Bhd-Associated Renal Tumour And Sporadic Chromophobe Renal Cell Carcinoma, Ryosuke Jikuya, Todd A Johnson, Kazuhiro Maejima, Jisong An, Young-Seok Ju, Hwajin Lee, Kyungsik Ha, Woojeung Song, Youngwook Kim, Yuki Okawa, Shota Sasagawa, Yuki Kanazashi, Masashi Fujita, Seiya Imoto, Taku Mitome, Shinji Ohtake, Go Noguchi, Sachi Kawaura, Yasuhiro Iribe, Kota Aomori, Tomoyuki Tatenuma, Mitsuru Komeya, Hiroki Ito, Yusuke Ito, Kentaro Muraoka, Mitsuko Furuya, Ikuma Kato, Satoshi Fujii, Haruka Hamanoue, Tomohiko Tamura, Masaya Baba, Toshio Suda, Tatsuhiko Kodama, Kazuhide Makiyama, Masahiro Yao, Brian M Shuch, Christopher J Ricketts, Laura S Schmidt, W Marston Linehan, Hidewaki Nakagawa, Hisashi Hasumi

Faculty, Staff and Student Publications

BACKGROUND: Birt-Hogg-Dubé (BHD) syndrome, caused by germline alteration of folliculin (FLCN) gene, develops hybrid oncocytic/chromophobe tumour (HOCT) and chromophobe renal cell carcinoma (ChRCC), whereas sporadic ChRCC does not harbor FLCN alteration. To date, molecular characteristics of these similar histological types of tumours have been incompletely elucidated.

METHODS: To elucidate renal tumourigenesis of BHD-associated renal tumours and sporadic renal tumours, we conducted whole genome sequencing (WGS) and RNA-sequencing (RNA-seq) of sixteen BHD-associated renal tumours from nine unrelated BHD patients, twenty-one sporadic ChRCCs and seven sporadic oncocytomas. We then compared somatic mutation profiles with FLCN variants and RNA expression profiles between BHD-associated …

The Integrative Studies On The Functional A-To-I Rna Editing Events In Human Cancers, Sijia Wu, Zhiwei Fan, Pora Kim, Liyu Huang, Xiaobo Zhou

Faculty, Staff and Student Publications

Adenosine-to-inosine (A-to-I) RNA editing, constituting nearly 90% of all RNA editing events in humans, has been reported to contribute to the tumorigenesis in diverse cancers. However, the comprehensive map for functional A-to-I RNA editing events in cancers is still insufficient. To fill this gap, we systematically and intensively analyzed multiple tumorigenic mechanisms of A-to-I RNA editing events in samples across 33 cancer types from The Cancer Genome Atlas. For individual candidate among ∼ 1,500,000 quantified RNA editing events, we performed diverse types of downstream functional annotations. Finally, we identified 24,236 potentially functional A-to-I RNA editing events, including the cases …

Statistical And Biological Analyses Of Acoustic Signals In Estrildid Finches, Moises Rivera

Dissertations, Theses, and Capstone Projects

Acoustic communication is a process that involves auditory perception and signal processing. Discrimination and recognition further require cognitive processes and supporting mechanisms in order to successfully identify and appropriately respond to signal senders. Although acoustic communication is common across birds, classical research has largely disregarded the perceptual abilities of perinatal altricial taxa. Chapter 1 reviews the literature of perinatal acoustic stimulation in birds, highlighting the disproportionate focus on precocial birds (e.g., chickens, ducks, quails). The long-held belief that altricial birds were incapable of acoustic perception in ovo was only recently overturned, as researchers began to find behavioral and physiological evidence …

Deep Hybrid Modeling Of Neuronal Dynamics Using Generative Adversarial Networks, Soheil Saghafi

Dissertations

Mechanistic modeling and machine learning methods are powerful techniques for approximating biological systems and making accurate predictions from data. However, when used in isolation these approaches suffer from distinct shortcomings: model and parameter uncertainty limit mechanistic modeling, whereas machine learning methods disregard the underlying biophysical mechanisms. This dissertation constructs Deep Hybrid Models that address these shortcomings by combining deep learning with mechanistic modeling. In particular, this dissertation uses Generative Adversarial Networks (GANs) to provide an inverse mapping of data to mechanistic models and identifies the distributions of mechanistic model parameters coherent to the data.

Chapter 1 provides background information on …

Target Cell-Specific Synaptic Dynamics Of Excitatory To Inhibitory Neuron Connections In Supragranular Layers Of Human Neocortex, Mean-Hwan Kim, Cristina Radaelli, Elliot R Thomsen, Deja Monet, Thomas Chartrand, Nikolas L Jorstad, Joseph T Mahoney, Michael J Taormina, Brian Long, Katherine Baker, Trygve E Bakken, Luke Campagnola, Tamara Casper, Michael Clark, Nick Dee, Florence D'Orazi, Clare Gamlin, Brian E Kalmbach, Sara Kebede, Brian R Lee, Lindsay Ng, Jessica Trinh, Charles Cobbs, Ryder P Gwinn, C Dirk Keene, Andrew L Ko, Jeffrey G Ojemann, Daniel L Silbergeld, Staci A Sorensen, Jim Berg, Kimberly A Smith, Philip R Nicovich, Tim Jarsky, Hongkui Zeng, Jonathan T Ting, Boaz P Levi, Ed Lein

Faculty, Staff and Student Publications

Rodent studies have demonstrated that synaptic dynamics from excitatory to inhibitory neuron types are often dependent on the target cell type. However, these target cell-specific properties have not been well investigated in human cortex, where there are major technical challenges in reliably obtaining healthy tissue, conducting multiple patch-clamp recordings on inhibitory cell types, and identifying those cell types. Here, we take advantage of newly developed methods for human neurosurgical tissue analysis with multiple patch-clamp recordings, post-hoc fluorescent in situ hybridization (FISH), machine learning-based cell type classification and prospective GABAergic AAV-based labeling to investigate synaptic properties between pyramidal neurons and PVALB- …

Nanoscratch-Induced Formation Of Metallic Micro/Nanostructures With Resin Masks, Mingyong Xin, Qihui Feng, Changbao Xu, Licong Cui, Jie Zhu, Yinkai Gan, Bingjun Yu

Faculty, Staff and Student Publications

Metallic micro/nanostructures present a wide range of applications due to the small size and superior performances. In order to obtain high-performance devices, it is of great importance to develop new methods for preparing metallic micro/nanostructures with high quality, low cost, and precise position. It is found that metallic micro/nanostructures can be obtained by scratch-induced directional deposition of metals on silicon surface, where the mask plays a key role in the process. This study is focused on the preparation of keto-aldehyde resin masks and their effects on the formation of scratch-induced gold (Au) micro/nanostructures. It is also found that the keto-aldehyde …

Genome-Wide Association Study Of Lung Adenocarcinoma In East Asia And Comparison With A European Population, Jianxin Shi, Kouya Shiraishi, Jiyeon Choi, Keitaro Matsuo, Tzu-Yu Chen, Juncheng Dai, Rayjean J Hung, Kexin Chen, Xiao-Ou Shu, Young Tae Kim, Maria Teresa Landi, Dongxin Lin, Wei Zheng, Zhihua Yin, Baosen Zhou, Bao Song, Jiucun Wang, Wei Jie Seow, Lei Song, I-Shou Chang, Wei Hu, Li-Hsin Chien, Qiuyin Cai, Yun-Chul Hong, Hee Nam Kim, Yi-Long Wu, Maria Pik Wong, Brian Douglas Richardson, Karen M Funderburk, Shilan Li, Tongwu Zhang, Charles Breeze, Zhaoming Wang, Batel Blechter, Bryan A Bassig, Jin Hee Kim, Demetrius Albanes, Jason Y Y Wong, Min-Ho Shin, Lap Ping Chung, Yang Yang, She-Juan An, Hong Zheng, Yasushi Yatabe, Xu-Chao Zhang, Young-Chul Kim, Neil E Caporaso, Jiang Chang, James Chung Man Ho, Michiaki Kubo, Yataro Daigo, Minsun Song, Yukihide Momozawa, Yoichiro Kamatani, Masashi Kobayashi, Kenichi Okubo, Takayuki Honda, Dean H Hosgood, Hideo Kunitoh, Harsh Patel, Shun-Ichi Watanabe, Yohei Miyagi, Haruhiko Nakayama, Shingo Matsumoto, Hidehito Horinouchi, Masahiro Tsuboi, Ryuji Hamamoto, Koichi Goto, Yuichiro Ohe, Atsushi Takahashi, Akiteru Goto, Yoshihiro Minamiya, Megumi Hara, Yuichiro Nishida, Kenji Takeuchi, Kenji Wakai, Koichi Matsuda, Yoshinori Murakami, Kimihiro Shimizu, Hiroyuki Suzuki, Motonobu Saito, Yoichi Ohtaki, Kazumi Tanaka, Tangchun Wu, Fusheng Wei, Hongji Dai, Mitchell J Machiela, Jian Su, Yeul Hong Kim, In-Jae Oh, Victor Ho Fun Lee, Gee-Chen Chang, Ying-Huang Tsai, Kuan-Yu Chen, Ming-Shyan Huang, Wu-Chou Su, Yuh-Min Chen, Adeline Seow, Jae Yong Park, Sun-Seog Kweon, Kun-Chieh Chen, Yu-Tang Gao, Biyun Qian, Chen Wu, Daru Lu, Jianjun Liu, Ann G Schwartz, Richard Houlston, Margaret R Spitz, Ivan P Gorlov, Xifeng Wu, Ping Yang, Stephen Lam, Adonina Tardon, Chu Chen, Stig E Bojesen, Mattias Johansson, Angela Risch, Heike Bickeböller, Bu-Tian Ji, H-Erich Wichmann, David C Christiani, Gadi Rennert, Susanne Arnold, Paul Brennan, James Mckay, John K Field, Sanjay S Shete, Loic Le Marchand, Geoffrey Liu, Angeline Andrew, Lambertus A Kiemeney, Shan Zienolddiny-Narui, Kjell Grankvist, Mikael Johansson, Angela Cox, Fiona Taylor, Jian-Min Yuan, Philip Lazarus, Matthew B Schabath, Melinda C Aldrich, Hyo-Sung Jeon, Shih Sheng Jiang, Jae Sook Sung, Chung-Hsing Chen, Chin-Fu Hsiao, Yoo Jin Jung, Huan Guo, Zhibin Hu, Laurie Burdett, Meredith Yeager, Amy Hutchinson, Belynda Hicks, Jia Liu, Bin Zhu, Sonja I Berndt, Wei Wu, Junwen Wang, Yuqing Li, Jin Eun Choi, Kyong Hwa Park, Sook Whan Sung, Li Liu, Chang Hyun Kang, Wen-Chang Wang, Jun Xu, Peng Guan, Wen Tan, Chong-Jen Yu, Gong Yang, Alan Dart Loon Sihoe, Ying Chen, Yi Young Choi, Jun Suk Kim, Ho-Il Yoon, In Kyu Park, Ping Xu, Qincheng He, Chih-Liang Wang, Hsiao-Han Hung, Roel C H Vermeulen, Iona Cheng, Junjie Wu, Wei-Yen Lim, Fang-Yu Tsai, John K C Chan, Jihua Li, Hongyan Chen, Hsien-Chih Lin, Li Jin, Jie Liu, Norie Sawada, Taiki Yamaji, Kathleen Wyatt, Shengchao A Li, Hongxia Ma, Meng Zhu, Zhehai Wang, Sensen Cheng, Xuelian Li, Yangwu Ren, Ann Chao, Motoki Iwasaki, Junjie Zhu, Gening Jiang, Ke Fei, Guoping Wu, Chih-Yi Chen, Chien-Jen Chen, Pan-Chyr Yang, Jinming Yu, Victoria L Stevens, Joseph F Fraumeni, Nilanjan Chatterjee, Olga Y Gorlova, Chao Agnes Hsiung, Christopher I Amos, Hongbing Shen, Stephen J Chanock, Nathaniel Rothman, Takashi Kohno, Qing Lan

Faculty, Staff and Student Publications

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European …

Quehry: A Question Answering System To Query Electronic Health Records, Sarvesh Soni, Surabhi Datta, Kirk Roberts

Faculty, Staff and Student Publications

OBJECTIVE: We propose a system, quEHRy, to retrieve precise, interpretable answers to natural language questions from structured data in electronic health records (EHRs).

MATERIALS AND METHODS: We develop/synthesize the main components of quEHRy: concept normalization (MetaMap), time frame classification (new), semantic parsing (existing), visualization with question understanding (new), and query module for FHIR mapping/processing (new). We evaluate quEHRy on 2 clinical question answering (QA) datasets. We evaluate each component separately as well as holistically to gain deeper insights. We also conduct a thorough error analysis for a crucial subcomponent, medical concept normalization.

RESULTS: Using gold concepts, the precision of quEHRy …

Shared Decision Making In Acute Pain Management In Patients With Opioid Use Disorder: A Scoping Review, Peter D Vu, Aila Malik, A Sarah Cohen, Vishal Bansal, Morgan R Cowan, Gregory M Blazek, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

The treatment of acute pain over the years has changed with increasing alternative therapies and increased scrutiny of opioid prescriptions. Shared Decision Making (SDM) has become a vital tool in increasing patient engagement and satisfaction in treatment decisions. SDM has been successfully implemented in the management of pain in a variety of settings; however, information regarding the use of SDM for treating acute pain in patients with a history of opioid use disorder (OUD) remains scarce. Following the Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension for Scoping Reviews (PRISMA-ScR), we conducted a review to understand how SDM is …

Analytical Approach For Monitoring The Behavior Of Patients With Pancreatic Adenocarcinoma At Different Stages As A Function Of Time, Aditya Chakaborty Dr, Chris P. Tsokos Dr

Biology and Medicine Through Mathematics Conference

No abstract provided.

Automated Delineation Of Visual Area Boundaries And Eccentricities By A Cnn Using Functional, Anatomical, And Diffusion-Weighted Mri Data, Noah C. Benson, Bogeng Song, Toshikazu Miyata, Hiromasa Takemura, Jonathan Winawer

MODVIS Workshop

Delineating visual field maps and iso-eccentricities from fMRI data is an important but time-consuming task for many neuroimaging studies on the human visual cortex because the traditional methods of doing so using retinotopic mapping experiments require substantial expertise as well as scanner, computer, and human time. Automated methods based on gray-matter anatomy or a combination of anatomy and functional mapping can reduce these requirements but are less accurate than experts. Convolutional Neural Networks (CNNs) are powerful tools for automated medical image segmentation. We hypothesize that CNNs can define visual area boundaries with high accuracy. We trained U-Net CNNs with ResNet18 …

Toward A Manifold Encoding Neural Responses, Luciano Dyballa, Andra M. Rudzite, Mahmood S. Hoseini, Mishek Thapa, Michael P. Stryker, Greg D. Field, Steven W. Zucker

MODVIS Workshop

Understanding circuit properties from physiological data presents two challenges: (i) recordings do not reveal connectivity, and (ii) stimuli only exercise circuits to a limited extent. We address these challenges for the mouse visual system with a novel neural manifold obtained using unsupervised algorithms. Each point in our manifold is a neuron; nearby neurons respond similarly in time to similar parts of a stimulus ensemble. This ensemble includes drifting gratings and flows, i.e., patterns resembling what a mouse would “see” running through fields.

Regarding (i), our manifold differs from the standard practice in computational neuroscience: embedding trials in neural coordinates. Topology …

Locomotion And Life History In A Leaping Primate: Mechanics And Energetics Of Movement Throughout The Propithecus Lifespan, Nicholas Heslep

Masters Theses, 2020-current

Arboreal primates are typically altricial, exhibit long juvenile periods, and use dynamic locomotor behaviors that can be challenging and risky. Sifaka (Propithecus verreauxi) have particularly slow life histories for their size, with long juvenile periods, protracted reproductive careers, and long life spans. Slow somatic growth poses potential mechanical challenges for juvenile sifaka who use thigh-powered vertical clinging and leaping to follow group members during travel. I examined mechanical and energetic costs of movement in developing sifaka. I instrumented 8 wild sifaka (3 yearlings, 3 subadults, 2 adults) in 4 social groups with inertial sensors measuring tri-axial acceleration for …

Mesoporous Silica Nanoparticles As A Gene Delivery Platform For Cancer Therapy, Nisar Ul Khaliq, Juyeon Lee, Joohyeon Kim, Yejin Kim, Sohyeon Yu, Jisu Kim, Sangwoo Kim, Daekyung Sung, Hyungjun Kim

Faculty, Staff and Student Publications

Cancer remains a major global health challenge. Traditional chemotherapy often results in side effects and drug resistance, necessitating the development of alternative treatment strategies such as gene therapy. Mesoporous silica nanoparticles (MSNs) offer many advantages as a gene delivery carrier, including high loading capacity, controlled drug release, and easy surface functionalization. MSNs are biodegradable and biocompatible, making them promising candidates for drug delivery applications. Recent studies demonstrating the use of MSNs for the delivery of therapeutic nucleic acids to cancer cells have been reviewed, along with their potential as a tool for cancer therapy. The major challenges and future interventions …

A Vlp-Based Vaccine Displaying Hbha And Mtp Antigens Of Mycobacterium Tuberculosis Induces Potentially Protective Immune Responses In M Tuberculosis H37ra Infected Mice, Juan Wang, Tao Xie, Inayat Ullah, Youjun Mi, Xiaoping Li, Yang Gong, Pu He, Yuqi Liu, Fei Li, Jixi Li, Zengjun Lu, Bingdong Zhu

Faculty, Staff and Student Publications

Heparin-binding hemagglutinin (HBHA) and M. tuberculosis pili (MTP) are important antigens on the surface of Mycobacterium tuberculosis. To display these antigens effectively, the fusion protein HBHA-MTP with a molecular weight of 20 kD (L20) was inserted into the receptor-binding hemagglutinin (HA) fragment of influenza virus and was expressed along with matrix protein M1 in Sf9 insect cells to generate influenza virus-like particles (LV20 in short). The results showed that the insertion of L20 into the envelope of the influenza virus did not affect the self-assembly and morphology of LV20 VLPs. The expression of L20 was successfully verified by transmission …

Hawk Mountain Raptor Migration Phenology’S Relation To Weather, Eric Burgos

Computer Science and Information Technology Faculty

We have been studying year-round raptor migration phenology across the United States and North America for multiple decades now. Hawk Mountain Sanctuary’s Autumn migration hawk count began in 1934 and is the longest running raptor migration count in the world. A decline in total raptor counts passing through Hawk Mountain’s North Lookout is well documented and much research has already been done in what could be the main causes for this decrease in counts year-over-year. We know that cold front passages have long been associated with autumnal migration in northeastern North America. Using updated analysis techniques, we examined 60 years’ …

A Programmatic Geographic Information Systems Analysis Of Plant Hardiness Zones, Andrew Bowen

Electronic Theses and Dissertations

The Plant Hardiness Zone Map consists of thirteen geographical zones that describe whether a plant can survive based on average annual minimal temperatures. As climate change progresses, minimum temperatures in all regions are expected to change. This work programmatically evaluates predicted future climate projection data and converts it to United States Department of Agriculture-defined hardiness zones. Through the next 80 years, hardiness zones are projected to move poleward; in effect, colder zones will lose area and warmer zones will gain area globally. Some implications include changes in crop growing degree days, which could alter crop productivity, migration and settlement of …

Deephtlv: A Deep Learning Framework For Detecting Human T-Lymphotrophic Virus 1 Integration Sites, Johnathan Jia, Johnathan Jia

Dissertations and Theses (Open Access)

In the 1980s, researchers found the first human oncogenic retrovirus called human T-lymphotrophic virus type 1 (HTLV-1). Since then, HTLV-1 has been identified as the causative agent behind several diseases such as adult T-cell leukemia/lymphoma (ATL) and a HTLV-1 associated myelopathy or tropical spastic paraparesis (HAM/TSP). As part of its normal replication cycle, the genome is converted into DNA and integrated into the genome. With several hundreds to thousands of unique viral integration sites (VISs) distributed with indeterminate preference throughout the genome, detection of HTLV-1 VISs is a challenging task. Experimental studies typically use molecular biology …

Toward A Neural Semantic Parsing System For Ehr Question Answering, Sarvesh Soni, Kirk Roberts

Faculty, Staff and Student Publications

Clinical semantic parsing (SP) is an important step toward identifying the exact information need (as a machine-understandable logical form) from a natural language query aimed at retrieving information from electronic health records (EHRs). Current approaches to clinical SP are largely based on traditional machine learning and require hand-building a lexicon. The recent advancements in neural SP show a promise for building a robust and flexible semantic parser without much human effort. Thus, in this paper, we aim to systematically assess the performance of two such neural SP models for EHR question answering (QA). We found that the performance of these …

The Bellarmine Bee Bed: Organizing A Native Plant Garden Using Feedback From The Local Community, Kate Moran

Undergraduate Theses

Animal pollinators are the cornerstone of healthy ecosystems. Their survival is essential for the persistence of entire food chains: from the flowers they cross-pollinate directly, to the animals who depend on those plants for nutrition. The establishment of pollinator gardens—particularly ones that consist of native plants—is an effective way to enhance their biodiversity, abundance, and well-being.

The main goal of this thesis is to construct a pollinator garden that maximizes the benefits for animal pollinators using feedback from local gardeners. A survey was used to gather information about the popularity and preferences of 40 flowering plants, and after analyzing the …

Learning In A Virtual Environment To Improve Type 2 Diabetes Outcomes: Randomized Controlled Trial, Constance M Johnson, Gail D'Eramo Melkus, Louise Reagan, Wei Pan, Sathya Amarasekara, Katherine Pereira, Nancy Hassell, Sarah Nowlin, Allison Vorderstrasse

Faculty, Staff and Student Publications

Background: Given the importance of self-management in type 2 diabetes mellitus (T2DM), a major aspect of health is providing diabetes self-management education and support. Known barriers include access, availability, and the lack of follow through on referral to education programs. Virtual education and support have increased in use over the last few years.

Objective: The purpose of the Diabetes Learning in a Virtual Environment (LIVE) study was to compare the effects of the LIVE intervention (educational 3D world) to a diabetes self-management education and support control website on diet and physical activity behaviors and behavioral and metabolic outcomes in adults …

A Multi-Site Randomized Trial Of A Clinical Decision Support Intervention To Improve Problem List Completeness, Adam Wright, Richard Schreiber, David W Bates, Skye Aaron, Angela Ai, Raja Arul Cholan, Akshay Desai, Miguel Divo, David A Dorr, Thu-Trang Hickman, Salman Hussain, Shari Just, Brian Koh, Stuart Lipsitz, Dustin Mcevoy, Trent Rosenbloom, Elise Russo, David Yut-Chee Ting, Asli Weitkamp, Dean F Sittig

Faculty, Staff and Student Publications

OBJECTIVE: To improve problem list documentation and care quality.

MATERIALS AND METHODS: We developed algorithms to infer clinical problems a patient has that are not recorded on the coded problem list using structured data in the electronic health record (EHR) for 12 clinically significant heart, lung, and blood diseases. We also developed a clinical decision support (CDS) intervention which suggests adding missing problems to the problem list. We evaluated the intervention at 4 diverse healthcare systems using 3 different EHRs in a randomized trial using 3 predetermined outcome measures: alert acceptance, problem addition, and National Committee for Quality Assurance Healthcare …

The Potential Regulation Of A-To-I Rna Editing On Genes In Parkinson's Disease, Sijia Wu, Qiuping Xue, Xinyu Qin, Xiaoming Wu, Pora Kim, Jacqueline Chyr, Xiaobo Zhou, Liyu Huang

Faculty, Staff and Student Publications

Parkinson's disease (PD) is characterized by dopaminergic neurodegeneration and an abnormal accumulation of α-synuclein aggregates. A number of genetic factors have been shown to increase the risk of PD. Exploring the underlying molecular mechanisms that mediate PD's transcriptomic diversity can help us understand neurodegenerative pathogenesis. In this study, we identified 9897 A-to-I RNA editing events associated with 6286 genes across 372 PD patients. Of them, 72 RNA editing events altered miRNA binding sites and this may directly affect miRNA regulations of their host genes. However, RNA editing effects on the miRNA regulation of genes are more complex. They can (1) …

Physio-Psycho-Social Interaction Mechanism In Dyadic Health Of Young And Middle-Aged Stroke Survivors And Their Spousal Caregivers: A Longitudinal Observational Study Protocol, Dandan Xiang, Zhen-Xiang Zhang, Song Ge, Wen Na Wang, Bei-Lei Lin, Su-Yan Chen, Er-Feng Guo, Peng-Bo Zhang, Zhi-Wei Liu, Hui Li, Yong-Xia Mei

Faculty, Staff and Student Publications

Introduction: In recent years, stroke has become more common among young people. Stroke not only has a profound impact on patients' health but also incurs stress and health threats to their caregivers, especially spousal caregivers. Moreover, the health of stroke survivors and their caregivers is interdependent. To our knowledge, no study has explored dyadic health of young and middle-aged stroke survivors and their spousal caregivers from physiological, psychological and social perspectives. Therefore, this proposed study aims to explore the mechanism of how physiological, psychological and social factors affect dyadic health of young and middle-aged stroke survivors and their spousal caregivers. …

Quantitative Proteomic Screening Uncovers Candidate Diagnostic And Monitoring Serum Biomarkers Of Ankylosing Spondylitis, Mark Hwang, Shervin Assassi, Jim Zheng, Jessica Castillo, Reyna Chavez, Kamala Vanarsa, Chandra Mohan, John Reveille

Faculty, Staff and Student Publications

BACKGROUND: We sought to discover serum biomarkers of ankylosing spondylitis (AS) for diagnosis and monitoring disease activity.

METHODS: We studied biologic-treatment-naïve AS and healthy control (HC) patients' sera. Eighty samples matched by age, gender, and race (1:1:1 ratio) for AS patients with active disease, inactive disease, and HC were analyzed with SOMAscan™, an aptamer-based discovery platform. T-tests tests were performed for high/low-disease activity AS patients versus HCs (diagnosis) and high versus low disease activity (Monitoring) in a 2:1 and 1:1 ratio, respectively, to identify differentially expressed proteins (DEPs). We used the Cytoscape Molecular Complex Detection (MCODE) plugin to find clusters …

Distribution Of Serum Uric Acid Concentration And Its Association With Lipid Profiles: A Single-Center Retrospective Study In Children Aged 3 To 12 Years With Adenoid And Tonsillar Hypertrophy, Jiating Yu, Xin Liu, Honglei Ji, Yawei Zhang, Hanqiang Zhan, Ziyin Zhang, Jianguo Wen, Zhimin Wang

Faculty, Staff and Student Publications

BACKGROUND: Presently, there is no consensus regarding the optimal serum uric acid (SUA) concentration for pediatric patients. Adenoid and tonsillar hypertrophy is considered to be closely associated with pediatric metabolic syndrome and cardiovascular risk and is a common condition in children admitted to the hospital. Therefore, we aimed to evaluate the relationship between SUA and dyslipidemia and propose a reference range for SUA concentration that is associated with a healthy lipid profile in hospitalized children with adenoid and tonsillar hypertrophy.

METHODS: Preoperative data from 4922 children admitted for elective adenoidectomy and/or tonsillectomy surgery due to adenoid and tonsillar hypertrophy were …

Analysis Of Hawk Mountain Wind Speed To Raptor Count Trends From 1976 Through 2021, Dale E. Parson

Computer Science and Information Technology Faculty

This analysis of summer 2023 is a sequel to the summer 2022 Analysis of Hawk Mountain Sanctuary Observation Data from 1976 through 2021, also available as a web page through end of 2024 here. A presentation of that and subsequent analysis presented at Kutztown University in November 2022 and to Hawk Mountain researchers in January 2023 is available as PDF slides here and also on the web through 2024 here. This work was funded by a Kutztown University Research Grant for spring 2022 through summer 2023. Analytical use of these data proceeded through a subset of projects in three courses …