Digital Commons Network^™

Machine Learning-Based Aggression Detection In Children With Adhd Using Sensor-Based Physical Activity Monitoring, Catherine Park, Mohammad Dehghan Rouzi, Md Moin Uddin Atique, M G Finco, Ram Kinker Mishra, Griselda Barba-Villalobos, Emily Crossman, Chima Amushie, Jacqueline Nguyen, Chadi Calarge, Bijan Najafi

Center on Aging Staff Publications

Aggression in children is highly prevalent and can have devastating consequences, yet there is currently no objective method to track its frequency in daily life. This study aims to investigate the use of wearable-sensor-derived physical activity data and machine learning to objectively identify physical-aggressive incidents in children. Participants (n = 39) aged 7 to 16 years, with and without ADHD, wore a waist-worn activity monitor (ActiGraph, GT3X+) for up to one week, three times over 12 months, while demographic, anthropometric, and clinical data were collected. Machine learning techniques, specifically random forest, were used to analyze patterns that identify physical-aggressive incident …

Breaking Down Grit: Persistency And Flexibility In The Career Plans Of Military Medical Students., Ryan R Landoll, Krista Highland, Kameha Bell, Anthony R. Artino, Col Lisa K Moores, Michael Soh, Sebastian Uijtdehaage, Steven J Durning, Neil E Grunberg, Ting Dong

Health Sciences Education Research

INTRODUCTION: The field of medicine is experiencing a crisis as high levels of physician and trainee burnout threaten the pipeline of future physicians. Grit, or passion and perseverance for long-term goals, has been studied in high-performing and elite military units and found to be predictive of successful completion of training in adverse conditions. The Uniformed Services University of the Health Sciences (USU) graduates military medical leaders who make up a significant portion of the Military Health System physician workforce. Taken together, an improved understanding of the relationships between burnout, well-being, grit, and retention among USU graduates is critical to the …

Sarcopenia And Cardiovascular Diseases, Abdulla A Damluji, Maha Alfaraidhy, Noora Alhajri, Namit N Rohant, Manish Kumar, Christina Al Malouf, Samira Bahrainy, Min Ji Kwak, Wayne B Batchelor, Daniel E Forman, Michael W Rich, James Kirkpatrick, Ashok Krishnaswami, Karen P Alexander, Gary Gerstenblith, Peggy Cawthon, Christopher R Defilippi, Parag Goyal

Faculty, Staff and Student Publications

Sarcopenia is the loss of muscle strength, mass, and function, which is often exacerbated by chronic comorbidities including cardiovascular diseases, chronic kidney disease, and cancer. Sarcopenia is associated with faster progression of cardiovascular diseases and higher risk of mortality, falls, and reduced quality of life, particularly among older adults. Although the pathophysiologic mechanisms are complex, the broad underlying cause of sarcopenia includes an imbalance between anabolic and catabolic muscle homeostasis with or without neuronal degeneration. The intrinsic molecular mechanisms of aging, chronic illness, malnutrition, and immobility are associated with the development of sarcopenia. Screening and testing for sarcopenia may be …

Patterns Of Oncogene Coexpression At Single-Cell Resolution Influence Survival In Lymphoma, Michal Marek Hoppe, Patrick Jaynes, Fan Shuangyi, Yanfen Peng, Shruti Sridhar, Phuong Mai Hoang, Clementine Xin Liu, Sanjay De Mel, Limei Poon, Esther Hian Li Chan, Joanne Lee, Choon Kiat Ong, Tiffany Tang, Soon Thye Lim, Chandramouli Nagarajan, Nicholas F Grigoropoulos, Soo-Yong Tan, Susan Swee-Shan Hue, Sheng-Tsung Chang, Shih-Sung Chuang, Shaoying Li, Joseph D Khoury, Hyungwon Choi, Carl Harris, Alessia Bottos, Laura J Gay, Hendrik F P Runge, Ilias Moutsopoulos, Irina Mohorianu, Daniel J Hodson, Pedro Farinha, Anja Mottok, David W Scott, Jason J Pitt, Jinmiao Chen, Gayatri Kumar, Kasthuri Kannan, Wee Joo Chng, Yen Lin Chee, Siok-Bian Ng, Claudio Tripodo, Anand D Jeyasekharan

Faculty, Staff and Student Publications

Cancers often overexpress multiple clinically relevant oncogenes, but it is not known if combinations of oncogenes in cellular subpopulations within a cancer influence clinical outcomes. Using quantitative multispectral imaging of the prognostically relevant oncogenes MYC, BCL2, and BCL6 in diffuse large B-cell lymphoma (DLBCL), we show that the percentage of cells with a unique combination MYC+BCL2+BCL6- (M+2+6-) consistently predicts survival across four independent cohorts (n = 449), an effect not observed with other combinations including M+2+6+. We show that the M+2+6- percentage can be mathematically derived from quantitative measurements of the individual oncogenes and correlates with survival in IHC (n …

Comparison Of Reconstructed Prompt Gamma Emissions Using Maximum Likelihood Estimation And Origin Ensemble Algorithms For A Compton Camera System Tailored To Proton Range Monitoring, Ingrid Valencia Lozano, George Dedes, Steve Peterson, Dennis Mackin, Andreas Zoglauer, Sam Beddar, Stephen Avery, Jerimy Polf, Katia Parodi

Faculty, Staff and Student Publications

Compton-based prompt gamma (PG) imaging is being investigated by several groups as a potential solution for in vivo range monitoring in proton therapy. The performance of this technique depends on the detector system as well as the ability of the reconstruction method to obtain good spatial resolution to establish a quantitative correlation between the PG emission and the proton beam range in the patient. To evaluate the feasibility of PG imaging for range monitoring, we quantitatively evaluated the emission distributions reconstructed by a Maximum Likelihood Expectation Maximization (MLEM) and a Stochastic Origin Ensemble (SOE) algorithm. To this end, we exploit …

Combining Physics-Based Models With Deep Learning Image Synthesis And Uncertainty In Intraoperative Cone-Beam Ct Of The Brain, Xiaoxuan Zhang, Alejandro Sisniega, Wojciech B Zbijewski, Junghoon Lee, Craig K Jones, Pengwei Wu, Runze Han, Ali Uneri, Prasad Vagdargi, Patrick A Helm, Mark Luciano, William S Anderson, Jeffrey H Siewerdsen

Faculty, Staff and Student Publications

BACKGROUND: Image-guided neurosurgery requires high localization and registration accuracy to enable effective treatment and avoid complications. However, accurate neuronavigation based on preoperative magnetic resonance (MR) or computed tomography (CT) images is challenged by brain deformation occurring during the surgical intervention.

PURPOSE: To facilitate intraoperative visualization of brain tissues and deformable registration with preoperative images, a 3D deep learning (DL) reconstruction framework (termed DL-Recon) was proposed for improved intraoperative cone-beam CT (CBCT) image quality.

METHODS: The DL-Recon framework combines physics-based models with deep learning CT synthesis and leverages uncertainty information to promote robustness to unseen features. A 3D generative adversarial network …

Disclosing Quantitative Rt-Pcr Raw Data During Manuscript Submission: A Call For Action, Andreas Untergasser, Jan Hellemans, Michael W Pfaffl, Jan M Ruijter, Maurice J B Van Den Hoff, Mihnea P Dragomir, Douglas Adamoski, Sandra Martha Gomes Dias, Rui Manuel Reis, Manuela Ferracin, Emmanuel Dias-Neto, Ian Marsh, Mikael Kubista, Muller Fabbri, Ajay Goel, Ondřej Slabý, Erik Knutsen, Baoqing Chen, Massimo Negrini, Koshi Mimori, Martin Pichler, Maria Papatriantafyllou, Simone Anfossi, Thomas D Schmittgen, Jim Huggett, Stephen Bustin, Jo Vandesompele, George A Calin, Heroic (The Initiative Group On Qrt Disclosure) Consortium

Faculty, Staff and Student Publications

Accuracy and transparency of scientific data are becoming more and more relevant with the increasing concern regarding the evaluation of data reproducibility in many research areas. This concern is also true for quantifying coding and noncoding RNAs, with the remarkable increase in publications reporting RNA profiling and sequencing studies. To address the problem, we propose the following recommendations: (a) accurate documentation of experimental procedures in Materials and methods (and not only in the supplementary information, as many journals have a strict mandate for making Materials and methods as visible as possible in the main text); (b) submission of RT‐qPCR raw …

Monte Carlo-Derived 99m Tc Uptake Quantification With Commercial Planar Mbi: Absolute Tumor Activity, Benjamin P Lopez, Srinivas Cheenu Kappadath

Faculty, Staff and Student Publications

BACKGROUND: Molecular breast imaging (MBI) of 99mTc-sestamibi is an emerging adjunct qualitative tool in the detection and diagnosis of breast cancer.

PURPOSE: This work outlines the development and performance evaluation of a methodology to absolutely quantify tumor 99mTc activity uptake using a commercially available dual-headed MBI system by implementing corrections for background, scatter, attenuation, and detector characteristics.

METHODS: A validated Monte Carlo application of a commercial MBI system was used to simulate over 7000 unique acquisitions of spherical and ellipsoidal tumors in breast tissue. Tumor absolute activity was calculated following background, scatter, and attenuation corrections of tumor region of interest …

Gwas And Meta-Analysis Identifies 49 Genetic Variants Underlying Critical Covid-19, Erola Pairo-Castineira, Konrad Rawlik, Andrew D Bretherick, Ting Qi, Yang Wu, Isar Nassiri, Glenn A Mcconkey, Marie Zechner, Lucija Klaric, Fiona Griffiths, Wilna Oosthuyzen, Athanasios Kousathanas, Anne Richmond, Jonathan Millar, Clark D Russell, Tomas Malinauskas, Ryan Thwaites, Kirstie Morrice, Sean Keating, David Maslove, Alistair Nichol, Malcolm G Semple, Julian Knight, Manu Shankar-Hari, Charlotte Summers, Charles Hinds, Peter Horby, Lowell Ling, Danny Mcauley, Hugh Montgomery, Peter J M Openshaw, Colin Begg, Timothy Walsh, Albert Tenesa, Carlos Flores, José A Riancho, Augusto Rojas-Martinez, Pablo Lapunzina, Genomicc Investigators, Scourge Consortium, Isaricc Investigators, 23andme Covid-19 Team, Jian Yang, Chris P Ponting, James F Wilson, Veronique Vitart, Malak Abedalthagafi, Andre D Luchessi, Esteban J Parra, Raquel Cruz, Angel Carracedo, Angie Fawkes, Lee Murphy, Kathy Rowan, Alexandre C Pereira, Andy Law, Benjamin Fairfax, Sara Clohisey Hendry, J Kenneth Baillie

Faculty, Staff and Student Publications

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a …

Mastro I: Meta-Analysis And Systematic Review Of Thrombectomy Stent Retriever Outcomes: Comparing Functional, Safety And Recanalization Outcomes Between Embotrap, Solitaire And Trevo In Acute Ischemic Stroke, Osama O Zaidat, Shelly Ikeme, Sunil A Sheth, Shinichi Yoshimura, Xin-Guang Yang, Waleed Brinjikji, David F Kallmes, Patrick Brouwer, John Pederson, Ranita Tarchand, Annie Steffenson, Kevin M Kallmes, Jillienne Touchette, Tommy Andersson

Faculty, Staff and Student Publications

Aims:

Stent-retriever (SR) thrombectomy has demonstrated superior outcomes in patients with acute ischemic stroke compared with medical management alone, but differences among SRs remain unexplored. We conducted a Systematic Review/Meta-Analysis to compare outcomes between three SRs: EmboTrap^®, Solitaire™, and Trevo^®.

Methods:

We conducted a PRISMA-compliant Systematic Review among English-language studies published after 2014 in PubMed/MEDLINE that reported SRs in ≥25 patients. Functional and safety outcomes included 90-day modified Rankin scale (mRS 0-2), mortality, symptomatic intracranial hemorrhage (sICH), and embolization to new territory (ENT). Recanalization outcomes included modified thrombolysis in cerebral infarction (mTICI) and first-pass recanalization (FPR). …

Clinical Consensus Guideline On The Management Of Phaeochromocytoma And Paraganglioma In Patients Harbouring Germline Sdhd Pathogenic Variants, David Taïeb, George B Wanna, Maleeha Ahmad, Charlotte Lussey-Lepoutre, Nancy D Perrier, Svenja Nölting, Laurence Amar, Henri J L M Timmers, Zachary G Schwam, Anthony L Estrera, Michael Lim, Erqi Liu Pollom, Lucas Vitzthum, Isabelle Bourdeau, Ruth T Casey, Frédéric Castinetti, Roderick Clifton-Bligh, Eleonora P M Corssmit, Ronald R De Krijger, Jaydira Del Rivero, Graeme Eisenhofer, Hans K Ghayee, Anne-Paule Gimenez-Roqueplo, Ashley Grossman, Alessio Imperiale, Jeroen C Jansen, Abhishek Jha, Michiel N Kerstens, Henricus P M Kunst, James K Liu, Eamonn R Maher, Daniele Marchioni, Leilani B Mercado-Asis, Ozgur Mete, Mitsuhide Naruse, Naris Nilubol, Neeta Pandit-Taskar, Frédéric Sebag, Akiyo Tanabe, Jiri Widimsky, Leah Meuter, Jacques W M Lenders, Karel Pacak

Faculty, Staff and Student Publications

Patients with germline SDHD pathogenic variants (encoding succinate dehydrogenase subunit D; ie, paraganglioma 1 syndrome) are predominantly affected by head and neck paragangliomas, which, in almost 20% of patients, might coexist with paragangliomas arising from other locations (eg, adrenal medulla, para-aortic, cardiac or thoracic, and pelvic). Given the higher risk of tumour multifocality and bilaterality for phaeochromocytomas and paragangliomas (PPGLs) because of SDHD pathogenic variants than for their sporadic and other genotypic counterparts, the management of patients with SDHD PPGLs is clinically complex in terms of imaging, treatment, and management options. Furthermore, locally aggressive disease can be discovered at a …

A Model For Gastrointestinal Tract Motility In A 4d Imaging Phantom Of Human Anatomy, Ergys Subashi, Paul Segars, Harini Veeraraghavan, Joseph Deasy, Neelam Tyagi

Faculty, Staff and Student Publications

BACKGROUND: Gastrointestinal (GI) tract motility is one of the main sources for intra/inter-fraction variability and uncertainty in radiation therapy for abdominal targets. Models for GI motility can improve the assessment of delivered dose and contribute to the development, testing, and validation of deformable image registration (DIR) and dose-accumulation algorithms.

PURPOSE: To implement GI tract motion in the 4D extended cardiac-torso (XCAT) digital phantom of human anatomy.

MATERIALS AND METHODS: Motility modes that exhibit large amplitude changes in the diameter of the GI tract and may persist over timescales comparable to online adaptive planning and radiotherapy delivery were identified based on …

Risk Factors For Head And Neck Cancer In More And Less Developed Countries: Analysis From The Inhance Consortium, Neerav Goyal, Max Hennessy, Erik Lehman, Wenxue Lin, Antonio Agudo, Wolfgang Ahrens, Stefania Boccia, Paul Brennan, Hermann Brenner, Gabriella Cadoni, Cristina Canova, Chu Chen, David Conway, Maria Paula Curado, Luigino Dal Maso, Alexander W Daudt, Valeria Edefonti, Eleonora Fabianova, Leticia Fernandez, Silvia Franceschi, Werner Garavello, Maura Gillison, Richard B Hayes, Claire Healy, Rolando Herrero, Ivana Holcatova, Jossy L Kanda, Karl Kelsey, Bo T Hansen, Rosalina Koifman, Pagona Lagiou, Carlo La Vecchia, Fabio Levi, Guojun Li, Jolanta Lissowska, Rossana Mendoza López, Danièle Luce, Gary Macfarlane, Dana Mates, Keitaro Matsuo, Michael Mcclean, Ana Menezes, Gwenn Menvielle, Hal Morgenstern, Kirsten Moysich, Eva Negri, Andrew F Olshan, Tamas Pandics, Jerry Polesel, Mark Purdue, Loredana Radoi, Heribert Ramroth, Lorenzo Richiardi, Stimson Schantz, Stephen M Schwartz, Diego Serraino, Oxana Shangina, Elaine Smith, Erich M Sturgis, Beata Świątkowska, Peter Thomson, Thomas L Vaughan, Marta Vilensky, Deborah M Winn, Victor Wunsch-Filho, Guo-Pei Yu, Jose P Zevallos, Zuo-Feng Zhang, Tongzhang Zheng, Ariana Znaor, Paolo Boffetta, Mia Hashibe, Yuan-Chin A Lee, Joshua E Muscat

Faculty, Staff and Students Publications

Objective: We analyzed the pooled case-control data from the International Head and Neck Cancer Epidemiology (INHANCE) consortium to compare cigarette smoking and alcohol consumption risk factors for head and neck cancer between less developed and more developed countries.

Subjects and methods: The location of each study was categorized as either a less developed or more developed country. We compared the risk of overall head and neck cancer and cancer of specific anatomic subsites associated with cigarette smoking and alcohol consumption. Additionally, age and sex distribution between categories was compared.

Results: The odds ratios for head and neck cancer sites associated …

Conditional Concordance-Assisted Learning Under Matched Case-Control Design For Combining Biomarkers For Population Screening, Wen Li, Ruosha Li, Qingxiang Yan, Ziding Feng, Jing Ning

Faculty, Staff and Student Publications

Incorporating promising biomarkers into cancer screening practices for early-detection is increasingly appealing because of the unsatisfactory performance of current cancer screening strategies. The matched case-control design is commonly adopted in biomarker development studies to evaluate the discriminative power of biomarker candidates, with an intention to eliminate confounding effects. Data from matched case-control studies have been routinely analyzed by the conditional logistic regression, although the assumed logit link between biomarker combinations and disease risk may not always hold. We propose a conditional concordance-assisted learning method, which is distribution-free, for identifying an optimal combination of biomarkers to discriminate cases and controls. We …

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 …

Mapping The Functional Interactions At The Tumor-Immune Checkpoint Interface, Behnaz Bozorgui, Elisabeth K Kong, Augustin Luna, Anil Korkut

Faculty, Staff and Student Publications

The interactions between tumor intrinsic processes and immune checkpoints can mediate immune evasion by cancer cells and responses to immunotherapy. It is, however, challenging to identify functional interactions due to the prohibitively complex molecular landscape of the tumor-immune interfaces. We address this challenge with a statistical analysis framework, immuno-oncology gene interaction maps (ImogiMap). ImogiMap quantifies and statistically validates tumor-immune checkpoint interactions based on their co-associations with immune-associated phenotypes. The outcome is a catalog of tumor-immune checkpoint interaction maps for diverse immune-associated phenotypes. Applications of ImogiMap recapitulate the interaction of SERPINB9 and immune checkpoints with interferon gamma (IFNγ) expression. Our analyses …

Modelling Radiation Cancer Treatment With A Death-Rate Term In Ordinary And Fractional Differential Equations, Nicole Wilson, Corina S Drapaca, Heiko Enderling, Jimmy J Caudell, Kathleen P Wilkie

Faculty, Staff and Student Publications

Fractional calculus has recently been applied to the mathematical modelling of tumour growth, but its use introduces complexities that may not be warranted. Mathematical modelling with differential equations is a standard approach to study and predict treatment outcomes for population-level and patient-specific responses. Here, we use patient data of radiation-treated tumours to discuss the benefits and limitations of introducing fractional derivatives into three standard models of tumour growth. The fractional derivative introduces a history-dependence into the growth function, which requires a continuous death-rate term for radiation treatment. This newly proposed radiation-induced death-rate term improves computational efficiency in both ordinary and …

Armo: Automated And Reliable Multi-Objective Model For Lymph Node Metastasis Prediction In Head And Neck Cancer, Zhiguo Zhou, Liyuan Chen, Michael Dohopolski, David Sher, Jing Wang

Faculty, Staff and Student Publications

Objective:

Accurate diagnosis of lymph node metastasis (LNM) is critical in treatment management for patients with head & neck cancer. Positron emission tomography (PET) and computed tomography (CT) are routinely used for identifying LNM status. However, for small or less fluorodeoxyglucose (FDG) avid nodes, there are always uncertainties in LNM diagnosis. We are aiming to develop a reliable prediction model is for identifying LNM.

Approach:

In this study, a new automated and reliable multi-objective learning model (ARMO) is proposed. In ARMO, a multi-objective model is introduced to obtain balanced sensitivity and specificity. Meanwhile, confidence is calibrated by introducing individual reliability, …

Machine Learning Models For The Identification Of Prognostic And Predictive Cancer Biomarkers: A Systematic Review, Qasem Al-Tashi, Maliazurina B Saad, Amgad Muneer, Rizwan Qureshi, Seyedali Mirjalili, Ajay Sheshadri, Xiuning Le, Natalie I Vokes, Jianjun Zhang, Jia Wu

Faculty, Staff and Student Publications

The identification of biomarkers plays a crucial role in personalized medicine, both in the clinical and research settings. However, the contrast between predictive and prognostic biomarkers can be challenging due to the overlap between the two. A prognostic biomarker predicts the future outcome of cancer, regardless of treatment, and a predictive biomarker predicts the effectiveness of a therapeutic intervention. Misclassifying a prognostic biomarker as predictive (or vice versa) can have serious financial and personal consequences for patients. To address this issue, various statistical and machine learning approaches have been developed. The aim of this study is to present an in-depth …

Physician Stress In The Era Of Covid-19 Vaccine Disparity: A Multi-Institutional Survey, Sarah Zahl, Debasis Mondal, David Tolentino, Jennifer A Fischer, Sherry Jimenez

Rowan-Virtua School of Osteopathic Medicine Departmental Research

CONTEXT: Healthcare workers are at a high risk of infection during infectious disease outbreaks, such as the COVID-19 pandemic. Despite the availability of several vaccines against COVID-19, the absence of vaccination in patients and colleagues remains a continuous source of stress in healthcare workers. We conducted a survey of physician preceptors, both MDs and DOs, to explore the impact of differences in the patients' and colleagues' vaccination status on their well-being, stress, and burnout.

OBJECTIVES: The objective of this study is to determine whether exposure to unvaccinated patients and/or colleagues increases stress and burnout in physician preceptors by utilizing a …

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 …

Modeling Collective Cell Behavior In Cancer: Perspectives From An Interdisciplinary Conversation, Frederick R Adler, Alexander R A Anderson, Abhinav Bhushan, Paul Bogdan, Jose Javier Bravo-Cordero, Amy Brock, Yun Chen, Edna Cukierman, Kathleen E Delgiorno, Gerald V Denis, Meghan C Ferrall-Fairbanks, Zev Jordan Gartner, Ronald N Germain, Deborah M Gordon, Ginger Hunter, Mohit Kumar Jolly, Loukia Georgiou Karacosta, Karthikeyan Mythreye, Parag Katira, Rajan P Kulkarni, Matthew L Kutys, Arthur D Lander, Ashley M Laughney, Herbert Levine, Emil Lou, Pedro R Lowenstein, Kristyn S Masters, Dana Pe'er, Shelly R Peyton, Manu O Platt, Jeremy E Purvis, Gerald Quon, Jennifer K Richer, Nicole C Riddle, Analiz Rodriguez, Joshua C Snyder, Gregory Lee Szeto, Claire J Tomlin, Itai Yanai, Ioannis K Zervantonakis, Hannah Dueck

Faculty, Staff and Student Publications

Collective cell behavior contributes to all stages of cancer progression. Understanding how collective behavior emerges through cell-cell interactions and decision-making will advance our understanding of cancer biology and provide new therapeutic approaches. Here, we summarize an interdisciplinary discussion on multicellular behavior in cancer, draw lessons from other scientific disciplines, and identify future directions.

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) …

Feature Selection For Support Vector Regression Using A Genetic Algorithm, Shannon B Mckearnan, David M Vock, G Elisabeta Marai, Guadalupe Canahuate, Clifton D Fuller, Julian Wolfson

Faculty, Staff and Student Publications

Support vector regression (SVR) is particularly beneficial when the outcome and predictors are nonlinearly related. However, when many covariates are available, the method's flexibility can lead to overfitting and an overall loss in predictive accuracy. To overcome this drawback, we develop a feature selection method for SVR based on a genetic algorithm that iteratively searches across potential subsets of covariates to find those that yield the best performance according to a user-defined fitness function. We evaluate the performance of our feature selection method for SVR, comparing it to alternate methods including LASSO and random forest, in a simulation study. We …

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 …

Evaluation Of Focal Adhesion Mediated Subcellular Curvature Sensing In Response To Engineered Extracellular Matrix, Daniel T Bowers, Mary Elizabeth Mcculloch, Justin L Brown

Faculty, Staff and Student Publications

Fibril curvature is bioinstructive to attached cells. Similar to natural healthy tissues, an engineered extracellular matrix can be designed to stimulate cells to adopt desired phenotypes. To take full advantage of the curvature control in biomaterial fabrication methodologies, an understanding of the response to fibril subcellular curvature is required. In this work, we examined morphology, signaling, and function of human cells attached to electrospun nanofibers. We controlled curvature across an order of magnitude using nondegradable poly(methyl methacrylate) (PMMA) attached to a stiff substrate with flat PMMA as a control. Focal adhesion length and the distance of maximum intensity from the …

Discerning Conversational Context In Online Health Communities For Personalized Digital Behavior Change Solutions Using Pragmatics To Reveal Intent In Social Media (Prism) Framework, Tavleen Singh, Kirk Roberts, Trevor Cohen, Nathan Cobb, Amy Franklin, Sahiti Myneni

Faculty, Staff and Student Publications

BACKGROUND: Online health communities (OHCs) have emerged as prominent platforms for behavior modification, and the digitization of online peer interactions has afforded researchers with unique opportunities to model multilevel mechanisms that drive behavior change. Existing studies, however, have been limited by a lack of methods that allow the capture of conversational context and socio-behavioral dynamics at scale, as manifested in these digital platforms.

OBJECTIVE: We develop, evaluate, and apply a novel methodological framework, Pragmatics to Reveal Intent in Social Media (PRISM), to facilitate granular characterization of peer interactions by combining multidimensional facets of human communication.

METHODS: We developed and applied …

An Untrained Deep Learning Method For Reconstructing Dynamic Mr Images From Accelerated Model-Based Data, Kalina P Slavkova, Julie C Dicarlo, Viraj Wadhwa, Sidharth Kumar, Chengyue Wu, John Virostko, Thomas E Yankeelov, Jonathan I Tamir

Faculty, Staff and Student Publications

PURPOSE: To implement physics-based regularization as a stopping condition in tuning an untrained deep neural network for reconstructing MR images from accelerated data.

METHODS: The ConvDecoder (CD) neural network was trained with a physics-based regularization term incorporating the spoiled gradient echo equation that describes variable-flip angle data. Fully-sampled variable-flip angle k-space data were retrospectively accelerated by factors of R = {8, 12, 18, 36} and reconstructed with CD, CD with the proposed regularization (CD + r), locally low-rank (LR) reconstruction, and compressed sensing with L1-wavelet regularization (L1). Final images from CD + r training were evaluated at the "argmin" of …