Other Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

Impact Of Body Mass Index And Body Fat Percentage On Subjective Weight Status, Kelly Staples, Adarsh Gupta

Rowan-Virtua Research Day

• In the United States, the prevalence of obesity in adults is 42.4% of the population
• Body mass index (BMI) is the most frequently used tool to screen and assess for obesity
• BMI fails to account for body composition and body fat percentage (BFP)
• The objective of our study is to assess for understanding of BMI, BFP, and how these two measures are related to self-perception of body mass.
• Findings showed positive correlations between BMI, gender, and perception of body figure

Aerobic Exercise As A Pioneer Treatment For Post-Concussion Patients, Neha Bhandari

D.U.Quark

Concussions are highly prevalent injuries in both youth and adult sports and can severely impact daily functions by impairing mental and physical health. Existing treatments, such as resting, have been found to be ineffective in promoting a faster recovery. They often lead to a decline in mental health, which can exacerbate ongoing symptoms. However, aerobic exercise is an emerging field that has the potential to make concussion recovery more effective. This literature review will explore the effectiveness of aerobic exercise on faster recovery rates, return to play, and its impact at the cellular level for concussion patients. In addition, it …

Estimating The Analytical Performance Of Raman Spectroscopy For Quantification Of Active Ingredients In Human Stratum Corneum, Hichem Kichou, Emilie Munnier, Yuri Dancik, Kamilia Kemel, Hugh Byrne, Ali Tfayli, Dominique Bertrand, Martin Soucé, Igor Chourpa, Franck Bonnier

Articles

Confocal Raman microscopy (CRM) has become a versatile technique that can be applied routinely to monitor skin penetration of active molecules. In the present study, CRM coupled to multivariate analysis (namely PLSR—partial least squares regression) is used for the quantitative measurement of an active ingredient (AI) applied to isolated (ex vivo) human stratum corneum (SC), using systematically varied doses of resorcinol, as model compound, and the performance is quantified according to key figures of merit defined by regulatory bodies (ICH, FDA, and EMA). A methodology is thus demonstrated to establish the limit of detection (LOD), precision, accuracy, sensitivity (SEN), and …

Differential Associations Of Conduct Disorder, Callous‑Unemotional Traits And Irritability With Outcome Expectations And Values Regarding The Consequences Of Aggression, J. Elowsky, S. Bajaj, J. Bashford‑Largo, R. Zhang, A. Mathur, A. Schwartz, M. Dobbertin, K. S. Blair, E. Leibenluft, D. Pardini, R. J.R. Blair

Center for Brain, Biology, and Behavior: Faculty Publications

Background: Previous work has examined the association of aggression levels and callous-unemotional traits with outcome expectations and values regarding the consequences of aggression. Less work has examined the outcome expectations and values regarding the consequences of aggression of adolescents with Conduct Disorder (CD). Also, no studies have examined links between irritability (a second socio-affective trait associated with CD) and these social cognitive processes despite the core function of anger in retaliatory aggression and establishing dominance.

Method: The current study, investigating these issues, involved 193 adolescents (typically developing [TD; N = 106], 87 cases with CD [N = 87]). Participants completed …

Electrocardiogram-Based Machine Learning Emulator Model For Predicting Novel Echocardiography-Derived Phenogroups For Cardiac Risk-Stratification: A Prospective Multicenter Cohort Study, Heenaben B. Patel, Naveena Yanamala, Brijesh Patel, Sameer Raina, Peter D. Farjo, Srinidhi Sunkara, Márton Tokodi, Nobuyuki Kagiyama, Grace Casaclang-Verzosa, Partho P. Sengupta

Journal of Patient-Centered Research and Reviews

Purpose: Electrocardiography (ECG)-derived machine learning models can predict echocardiography (echo)-derived indices of systolic or diastolic function. However, systolic and diastolic dysfunction frequently coexists, which necessitates an integrated assessment for optimal risk-stratification. We explored an ECG-derived model that emulates an echo-derived model that combines multiple parameters for identifying patient phenogroups at risk for major adverse cardiac events (MACE).

Methods: In this substudy of a prospective, multicenter study, patients from 3 institutions (n = 727) formed an internal cohort, and the fourth institution was reserved as an external test set (n = 518). A previously validated patient similarity analysis model was used …

Liquid Biopsies For Type 2 Diabetes Mellitus: Biomarkers For Disease Risk And Diagnosis, Stephanie Chidester

Dissertations

Background: Type 2 diabetes mellitus (T2DM) has reached epidemic proportions in the United States. There is a critical need for earlier and more effective screening and diagnostic tools. Innovative liquid biopsy technologies may play a key role in meeting this need. Liquid biopsies are a non-invasive, adjunctive tool for determining diagnosis, prognosis, and therapeutic response. This dissertation focuses on two potential applications of liquid biopsy technologies to T2DM: (1) epigenome-wide association studies to identify epigenetic markers of risk for T2DM, and (2) extracellular vesicle (EV)-based biomarker studies to identify and detect markers associated with T2DM development and progression. Dissertation studies: …

Effects Of Environmental Conditions, Core Temperature, And Hydration Status On Women’S Soccer Performance, Abigail G. Poague

Student Scholar Showcase

This study aimed to discover the effects of hydration status, core temperature, sleep data, perceived exertion, and environmental conditions affected the GPS-tracked performance of women's division III soccer players. The results of this study support the association between internal load, hydration status, and environmental conditions with external load.

Comparative Kinematic Gait Analysis In Adults With Multiple Disabilities, Lauren Rumbalski

Undergraduate Honors Thesis Projects

The purpose of this research is to identify abnormal gait parameters or patterns amongst young adults with multiple disabilities enrolled in a work transition program sponsored by a public-school system. Gait disorders are commonly seen in individuals with neurologic disorders, with significant research in children with autism. Gait disorders have been linked with fall and injury risk, with significant research in elderly populations. Gait analysis technology can be used to identify gait characteristics in populations that are abnormal or contribute to gait disorders. In an observational design, students from the transitional program promoted by Westerville City Schools, housed on Otterbein …

Succinic Semialdehyde Dehydrogenase Deficiency (Ssadhd): Qualitative Needs Assessment For Patients With A Rare Neurological Disorder, Cassandra Bovee, Kayla Woodring

Annual Research Symposium

No abstract provided.

A High Precision Machine Learning-Enabled System For Predicting Idiopathic Ventricular Arrhythmia Origins, Jianwei Zheng, Guohua Fu, Daniele Struppa, Islam Abudayyeh, Tahmeed Contractor, Kyle Anderson, Huimin Chu, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Background: Radiofrequency catheter ablation (CA) is an efficient antiarrhythmic treatment with a class I indication for idiopathic ventricular arrhythmia (IVA), only when drugs are ineffective or have unacceptable side effects. The accurate prediction of the origins of IVA can significantly increase the operation success rate, reduce operation duration and decrease the risk of complications. The present work proposes an artificial intelligence-enabled ECG analysis algorithm to estimate possible origins of idiopathic ventricular arrhythmia at a clinical-grade level accuracy.

Method: A total of 18,612 ECG recordings extracted from 545 patients who underwent successful CA to treat IVA were proportionally sampled into training, …

Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead

Engineering Faculty Articles and Research

Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavioral—that are collected as part of scientific studies or a part of treatment can provide a deeper, more nuanced insight into both diagnosis and treatment of ASD. This paper reviews 43 papers using unsupervised machine learning in ASD, including k-means clustering, hierarchical clustering, model-based clustering, and self-organizing maps. The aim of this review is to provide a survey of the current uses of …

A Physical Therapy Mobility Checkup For Older Adults: Feasibility And Participant Preferences From A Discrete Choice Experiment, Dalerie Lieberz, Hannah Borgeson, Steven Dobson, Lindsey Ewings, Karen Johnson, Kori Klaysmat, Abby Schultz, Rachel Tasson, Alexandra L. Borstad

Journal of Patient-Centered Research and Reviews

Purpose: Physical performance measures, like walking speed, identify and predict preclinical mobility disability but are rarely used in routine medical care. A preventive model of care called Mobility Checkup is being designed to reduce mobility disability in older adults. This study had two purposes: 1) determine feasibility and outcomes of the Mobility Checkup, and 2) identify preferences of older adults regarding this model of care using a discrete choice experiment.

Methods: Adults over 55 years of age were recruited from the community. In the study’s first phase, participants completed a Mobility Checkup, with feasibility evaluated using 6 criteria. In the …

Progression Through Return-To-Sport And Return-To-Academics Guidelines For Concussion Management And Recovery In Collegiate Student Athletes: Findings From The Ivy League–Big Ten Epidemiology Of Concussion Study, Douglas J. Wiebe, Abigail C. Bretzin, Bernadette A. D'Alonzo, Ivy League–Big Ten Epidemiology Of Concussion Study Investigators, Arthur C. Maerlender

Center for Brain, Biology, and Behavior: Faculty Publications

Objective To examine the progression of collegiate student athletes through five stages of a return-to- activity protocol following sport-related concussion (SRC).

Methods In a multisite prospective cohort study, we identified the frequency of initial 24–48 hours physical and cognitive rest, and the sequence of (1) symptom resolution and return to (2) exertion activity, (3) limited sport, (4) full sport and (5) full academics. In resulting profiles we estimated the likelihood of return to full sport ≤14 days or prolonged >28 days and tested for variability based on timing of the stages.

Results Among 1715 athletes with SRC (31.6% females), 67.9% …

Head Impact Exposure In Youth And Collegiate American Football, Grace B. Choi, Eric P. Smith, Stefan M. Duma, Steven Rowson, Eamon Campolettano, Mireille E. Kelley, Derek A. Jones, Joel D. Stitzel, Jillian E. Urban, Amaris Genemaras, Jonathan G. Beckwith, Richard M. Greenwald, Arthur C. Maerlender, Joseph J. Crisco

Center for Brain, Biology, and Behavior: Faculty Publications

The relationship between head impact and subsequent brain injury for American football players is not well defined, especially for youth. The objective of this study is to quantify and assess Head Impact Exposure (HIE) metrics among youth and collegiate football players. This multiseason study enrolled 639 unique athletes (354 collegiate; 285 youth, ages 9–14), recording 476,209 head impacts (367,337 collegiate; 108,872 youth) over 971 sessions (480 collegiate; 491 youth). Youth players experienced 43 and 65% fewer impacts per competition and practice, respectively, and lower impact magnitudes compared to collegiate players (95th percentile peak linear acceleration (PLA, g) competition: 45.6 vs …

Constructing Neural Network Models From Brain Data Reveals Representational Transformations Linked To Adaptive Behavior, Takuya Ito, Guangyu Robert Yang, Patryk Laurent, Douglas H. Schultz, Michael W. Cole

Center for Brain, Biology, and Behavior: Faculty Publications

The human ability to adaptively implement a wide variety of tasks is thought to emerge from the dynamic transformation of cognitive information. We hypothesized that these transformations are implemented via conjunctive activations in “conjunction hubs”—brain regions that selectively integrate sensory, cognitive, and motor activations. We used recent advances in using functional connectivity to map the flow of activity between brain regions to construct a task-performing neural network model from fMRI data during a cognitive control task. We verified the importance of conjunction hubs in cognitive computations by simulating neural activity flow over this empirically-estimated functional connectivity model. These empiricallyspecified simulations …

Affective Flexibility As A Developmental Building Block Of Cognitive Reappraisal: An Fmri Study, Jordan E. Pierce, Eisha Haque, Maital Neta

Center for Brain, Biology, and Behavior: Faculty Publications

Cognitive reappraisal is a form of emotion regulation that involves reinterpreting the meaning of a stimulus, often to downregulate one’s negative affect. Reappraisal typically recruits distributed regions of prefrontal and parietal cortex to generate new appraisals and downregulate the emotional response in the amygdala. In the current study, we compared reappraisal ability in an fMRI task with affective flexibility in a sample of children and adolescents (ages 6–17, N = 76). Affective flexibility was defined as variability in valence interpretations of ambiguous (surprised) facial expressions from a second behavioral task. Results demonstrated that age and affective flexibility predicted reappraisal ability, …

Robust Testing Of Paired Outcomes Incorporating Covariate Effects In Clustered Data With Informative Cluster Size, Sandipan Dutta

Mathematics & Statistics Faculty Publications

Paired outcomes are common in correlated clustered data where the main aim is to compare the distributions of the outcomes in a pair. In such clustered paired data, informative cluster sizes can occur when the number of pairs in a cluster (i.e., a cluster size) is correlated to the paired outcomes or the paired differences. There have been some attempts to develop robust rank-based tests for comparing paired outcomes in such complex clustered data. Most of these existing rank tests developed for paired outcomes in clustered data compare the marginal distributions in a pair and ignore any covariate effect on …

Altitude Illness, Kali Hepner

Capstone Showcase

With an increasing number of individuals traveling to high altitudes, it is important to address the risk these individuals face of developing altitude related illnesses. An example of high altitude related illness might be the elevation transition of travelers flying into Denver, Colorado (1,673 m) with the intention to then drive up to Rocky Mountain National Park’s Alpine Visitor Center (3,595 m) in the same day. This poses increased risk of unacclimatized visitors experiencing altitude illness in remote areas of the national park. This poster summarizes the diagnosis, prevention, and treatment of altitude illnesses so that clinicians and travelers may …

A Novel Computational Network Methodology For Discovery Of Biomarkers And Therapeutic Targets, Qing Ye

Graduate Theses, Dissertations, and Problem Reports (ETD)

Lung cancer has the second highest cancer incidence rate and the top cancer-related mortality worldwide. An estimate from the American Cancer Society shows that, in 2022, there will be about 236,740 lung cancer cases (117,910 men and 118,830 women) in the US. To date, there are no prognostic/predictive biomarkers to select chemotherapy, immunotherapy, and radiotherapy in individual non-small cell lung cancer (NSCLC) patients. There is an unmet clinical need to identify patients with early-stage NSCLC who are likely to develop recurrence and to predict their therapeutic responses. This dissertation developed a novel computational methodology for modeling molecular gene association networks …

Modeling Of Patient-Specific Periaortic Mechanics And Pulmonary Artery Hemodynamics Based On Phase-Contrast Magnetic Resonance Imaging Sequences., Johane H. Bracamonte

Theses and Dissertations

Inverse modeling in cardiovascular medicine is a collection of methodologies that can provide non-invasive patient-specific estimations of clinical risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs.

Herein, three different phase contrast magnetic resonance imaging (MRI) modalities were implemented as input data, displacement encoding with stimulated echoes (DENSE MRI) applied, and time-resolved velocity encoding phase-contrast MRI, in 1D and 3D, applied to pulmonary artery (PA) hemodynamics.

A model to account for the effect of periaortic interactions due to static and dynamic structures …