Digital Commons Network^™

A Longitudinal Analysis Of Morphological Shape Variation Of Spleen In Patients With Fontan Surgery, Varatharajan Nainamalai, Håvard Bjørke Jenssen, Mostafa Rezaeitaleshmahalleh, Djinaud Prophete, Jordan Gosnell, Sarah Khan, Marcus Haw, Jingfeng Jiang, Joseph Vettukattil

Michigan Tech Publications

Background: Splenic size serves as a surrogate biomarker for predicting portal vein hyper-tension and liver abnormalities in subjects with Fontan Associated Liver Disease (FALD). We analyze the long-term shape variation of the spleen in FALD subjects using morphological shape features of radiomic features. Methods: We used 154 (84 from computed tomography and 70 from magnetic resonance) image volumes obtained from 36 individuals who underwent stage 3 Fontan procedure and 145 computed tomography images from controls to assess splenomegaly. To understand the splenomegaly, thirteen shape features of the spleen over three 10-year intervals, and variations between controls and FALD subjects were …

A Comprehensive Deep Learning System With Mgrf Modeling For Predicting Breast Cancer Response To Neoadjuvant Chemotherapy, Ahmed Sharafeldeen, Fatma Taher, Norah Saleh Alghamdi, Eman Alnaghy, Reham Alghandour, Khadiga M. Ali, Sameh Shamaa, Abdelrahman Gamal, Mohammed Ghazal, Sohail Contractor, Ayman El-Baz

All Works

Accurate prediction of breast cancer (BC) response to neoadjuvant chemotherapy (NAC) is critical for tailoring treatment strategies and improving patient outcomes. This study introduces a novel deep learning-based framework that integrates multi-parametric magnetic resonance imaging (MRI) (i.e., T1, T2, STIR, and DWI), along with clinical and molecular subtype markers, to classify tumor response into pathological complete response (pCR), partial response (PR), and stable disease (SD). First, tumor regions are delineated across MRI modalities and then modeled using a translation-invariant Markov-Gibbs random field (MGRF) with analytical parameter estimation to capture modality-specific spatial appearance patterns correlated with NAC response. Subsequently, diffusion-weighted MRI …

Unlocking Efficiency In Real-World Collaborative Studies: A Multi-Site International Study With One-Shot Lossless Glmm Algorithm, Jiayi Tong, Chongliang Luo, Et Al.

2020-Current year OA Pubs

The widespread adoption of real-world data has given rise to numerous healthcare-distributed research networks, but multi-site analyses still face administrative burdens and data privacy challenges. In response, we developed a Collaborative One-shot Lossless Algorithm for Generalized Linear Mixed Models (COLA-GLMM), the first-ever algorithm that achieves both lossless and one-shot properties. COLA-GLMM ensures accuracy against the gold standard of pooled data while requiring only summary statistics and completes within a single communication round, eliminating the usual back-and-forth overhead. We further introduced an enhanced version that employs homomorphic encryption to reduce the risks of summary statistics misuse at the coordinating center. The …

A Cancer Education Needs Assessment: Informing Middle-Aged Female Patients About The Relationships Between Obesity And Women’S Health Concerns In The Reproductive System, Breast, And Endometrial Health, Batul Mirza

MUSC Theses and Dissertations

Obesity significantly impacts women’s health, particularly among middle-aged women, by increasing the risk of hormone-sensitive cancers such as breast, endometrial, and reproductive system cancers. This study examines the educational needs of this demographic group regarding obesity-related cancer risks and explores effective intervention strategies. Obesity-induced mechanisms – hormonal imbalances, chronic inflammation, and insulin resistance – drive cancer susceptibility, emphasizing the need for targeted health education. The study employs a qualitative design, which includes interviews with subject matter experts (SMEs) and surveys of middle-aged women. The goal is to assess awareness, perceived barriers, and preferred learning methods. Findings suggest that with many …

Image-Based Inference Of Tumor Cell Trajectories Enables Large-Scale Cancer Progression Analysis, Yang Liu, Ling Cai, Ruichen Rong, Shidan Wang, Liwei Jia, Peiran Quan, Qin Zhou, Guanghua Xiao, Yang Xie

Faculty, Staff and Student Publications

Current approaches to estimating cell trajectories, tumor progression dynamics, and cell population diversity of tumor microenvironment often depend on single-cell RNA sequencing, which is costly and resource intensive. To address this limitation, we developed an artificial intelligence (AI) model that leverages cell morphology features and histological spatial organization to classify tumor cell differentiation status, infer cell dynamic trajectories, and quantify tumor progression from hematoxylin and eosin (H&E)-stained whole-slide images. In three independent lung adenocarcinoma cohorts, our AI-based model accurately predicted cell differential status and provided quantifiable measures of tumor progression that were prognostic of patient survival. Spatial transcriptomic integrative analyses …

What Drives Weight Status Among Female University Students? A Machine Learning Analysis Of Sociodemographic, Dietary, And Lifestyle Determinants, Radwan Qasrawi, Abir Ajab, Leila Cheikh Ismail, Ayesha Al Dhaheri, Sharifa Alblooshi, Razan Abu Ghoush, Stephanny Vicuna Polo, Malak Amro, Suliman Thwib, Ghada Issa, Haleama Al Sabbah

All Works

Background: Obesity and underweight are increasingly common among young adult women, often resulting from complex interactions between diet, lifestyle, and socioeconomic factors. This study addresses that gap by applying machine learning to a wide range of behavioral, dietary, and demographic data. The main research question asks: What are the key factors influencing weight status among female university students, and how accurately can machine learning models identify them? We hypothesize that different factors are significantly associated with underweight, overweight, and obesity, and that machine learning can reliably detect these patterns. The aim is to identify the strongest predictors and support more …

Secondary Malignancies In Patients With Meningioma: A Surveillance, Epidemiology, And End Results Data Analysis, Maxwell W. Pickles, Thomas Z. Rohan, Shreya Vinjamuri, Nikolaos Mouchtouris, Roger Murayi, David P. Bray, James J. Evans

Department of Neurosurgery Faculty Papers

BACKGROUND: The risk of secondary primary malignancies (SPMs) in meningioma patients is not well understood. In this unidirectional analysis, we evaluated the risk of SPMs occurring following a primary diagnosis of meningioma.

METHODS: The Surveillance, Epidemiology, and End Results (SEER-17) database (2000-2020) was used to identify 124,769 meningioma patients from a total of 9,208,295 cancer cases. Standardized incidence ratios (SIRs) were calculated using SEER's statistical analysis package to evaluate SPM risk. Basic demographic and treatment information was collected as well.

RESULTS: Of the 124,769 patients, 11,411 (9.2%) received diagnoses of an SPM, which correlates to a higher risk than the …

Predicting Sleep And Sleep Stage In Children Using Actigraphy And Heartrate Via A Long Short-Term Memory Deep Learning Algorithm: A Performance Evaluation, Robert Weaver Med, Phd, James White, Olivia Finnegan, Hongpeng Yang, Zifei Zhong, Keagan Kiely, Catherine Jones, Yan Tong, Srihari Nelakuditi, Rahul Ghosal, David E. Brown, Russell R. Pate Ph.D., Gregory J. Welk, Massimiliano De Zambotti, Yuan Wang, Sarah Burkart, Elizabeth L. Adams Phd, Bridget Armstrong, Michael Beets Med, Mph, Phd

Faculty Publications

Children's ambulatory sleep is commonly measured via actigraphy. However, traditional actigraphy measured sleep (e.g., Sadeh algorithm) struggles to predict wake (i.e., specificity, values typically < 70) and cannot predict sleep stages. Long short-term memory (LSTM) is a machine learning algorithm that may address these deficiencies. This study evaluated the agreement of LSTM sleep estimates from actigraphy and heartrate (HR) data with polysomnography (PSG). Children (N = 238, 5–12 years,52.8% male, 50% Black 31.9% White) participated in an overnight laboratory polysomnography. Participants were referred be-cause of suspected sleep disruptions. Children wore an ActiGraph GT9X accelerometer and two of three consumer wearables(i.e., Apple Watch Series 7, Fitbit Sense, Garmin Vivoactive 4) on their non-dominant wrist during the polysomnogram. LSTM estimated sleep versus wake and sleep stage (wake, not-REM, REM) using raw actigraphy and HR data for each 30-s epoch. Logistic regression and random forest were also estimated as a benchmark for performance with which to compare the LSTM results. A 10-fold cross-validation technique was employed, and confusion matrices were constructed. Sensitivity and specificity were calculated to assess the agreement between research-grade and consumer wearables with the criterion polysomnography. For sleep versus wake classification, LSTM outperformed logistic regression and random forest with accuracy ranging from 94.1to 95.1, sensitivity ranging from 94.9 to 95.9 across different devices, and specificity ranging from 84.5 to 89.6. The addition of HR improved the prediction of sleep stages but not binary sleep versus wake. LSTM is promising for predicting sleep and sleep staging from actigraphy data, and HR may improve sleep stage prediction.

Dose Characterization Of Galactic Cosmic Rays In The Human Brain: A Phits-Based Study With A Segmented Anatomical Phantom, Shanice N. Manning

LSU Master's Theses

Astronauts aboard the International Space Station (ISS) are chronically exposed to a complex space radiation environment composed of galactic cosmic rays (GCR), solar particles, and Earth's trapped radiation. These high-energy particles interact with spacecraft shielding, producing secondary particles that can penetrate inside and deposit energy in sensitive tissues. Although animal studies have been useful in assessing space radiation risks, anatomical and physiological differences limit their applicability to human anatomy especially neuroanatomy. To address this gap, we developed a computational framework to model radiation dose distribution within the human brain using Monte Carlo simulations in Particle and Heavy Ion Transport code …

Following Painting's Quiet Call To Adventure, Kelly Allen

The Open Journal of Occupational Therapy

Yael Goverover, OTR/L, Ph.D., professor and post-professional program director of occupational therapy at New York University at Steinhardt (NYU), provided the cover art for the summer issue of the Open Journal of Occupational Therapy. This oil painting on canvas, titled, Still Life, 2024, features an arrangement of everyday objects with vibrant tones of gold, yellow, orange, and green found in the vase, and a coffeepot, fruits, and botanicals set against a backdrop of scarlet and striped patterned fabrics. She created this piece while on sabbatical in Israel as she studied under the tutelage of a seasoned oil …

Use Of Podcasts As Emerging Technology In Occupational Therapy Education, Abbigail Kubiak, Karen Jacobs, Varsha S. Kulkarni, Maruška Vizek

The Open Journal of Occupational Therapy

Podcasts are an emerging modality with a developing evidence base to reinforce their use in educational settings; in particular, to support knowledge retention and introduce topics. This research demonstrates the potential of podcasting in an educational context. Podcasts were used to educate occupational therapy (OT) students about emerging and innovative OT career opportunities. A series of 13 standardized 20- to 30-min podcasts featuring occupational therapists in emerging and innovative practice areas (E/IPA) globally were developed. In each podcast, the occupational therapist described implicit and explicit aspects of their career experiences. The podcasts were piloted in an entry-level OT doctoral course …

Analyzing Environmental Health: Air Pollution And Human Health Using Geospatial Data Science, Yanhong Huang

Geography ETDs

Air pollution from industrial emissions and wildfire smoke poses growing threats to public health. This dissertation employs geospatial data science to examine these challenges through three interrelated studies. The first study investigates the relationship between maternal residential exposure to industrial pollutants and low birth weight, identifying five chemicals as significant risk factors. The second study assesses the impact of industrial air pollution on lung and bronchus cancer survival, finding that exposure to 1,1,1-trichloroethane and cobalt is associated with reduced survival. The third study explores disparities in wildfire smoke PM_2.5 exposure and its association with asthma exacerbations. Results show disparities …

The Hazard Ratio Is Equivalent To An Odds Under The Assumption Of Proportional Hazards, David M. Thompson

Journal of Patient-Centered Research and Reviews

Clinicians routinely interpret statistical findings from medical research to inform patients of treatment benefits. Studies that use the hazard ratio present special challenges. Clinicians should not equate hazard ratios with risk ratios, ie, relative risks. However, clinicians can provide patients with a straightforward interpretation of the hazard ratio as an odds, as long as the ratio was calculated in a study in which the assumption of proportional hazards is justified. In such a case, the hazard ratio is equivalent to the odds that a person, who is randomly chosen from the group represented in the ratio’s numerator, experiences an event …

Spike Timing-Dependent Plasticity And Random Inputs Shape Interspike Interval Regularity Of Model Stn Neurons, Thoa Thieu, Roderick Melnik

School of Mathematical & Statistical Sciences Faculty Publications

Background/Objectives: Neuronal oscillations play a key role in the symptoms of Parkinson’s disease (PD). This study investigates the effects of random synaptic inputs, their correlations, and the interaction with synaptic dynamics and spike timing-dependent plasticity (STDP) on the membrane potential and firing patterns of subthalamic nucleus (STN) neurons, both in healthy and PD-affected states. Methods: We used a modified Hodgkin–Huxley model with a Langevin stochastic framework to study how synaptic conductance, random input fluctuations, and STDP affect STN neuron firing and membrane potential, including sensitivity to refractory period and synaptic depression variability. Results: Our results show that random inputs significantly …

Cilia In The Brain Display Region-Dependent Oscillations Of Length And Orientation, Roudabeh Vakil Monfared, Sherif Abdelkarim, Pieter Derdeyn, Kiki Chen, Hanting Wu, Kenneth Leong, Tiffany Chang, Justine Lee, Sara Versales, Surya M. Nauli, Kevin Beier, Pierre Baldi, Amal Alachkar

Pharmacy Faculty Articles and Research

In this study, we conducted high-throughput spatiotemporal analysis of primary cilia length and orientation across 22 mouse brain regions. We developed automated image analysis algorithms, which enabled us to examine over 10 million individual cilia, generating the largest spatiotemporal atlas of cilia. We found that cilia length and orientation display substantial variations across different brain regions and exhibit fluctuations over a 24-h period, with region-specific peaks during light-dark phases. Our analysis revealed unique orientation patterns of cilia, suggesting that cilia orientation within the brain is not random but follows specific patterns. Using BioCycle, we identified rhythmic fluctuations in cilia length …

Comparison Of Leveling A Deep Curve Of Spee With Extractions Versus Non-Extraction: A Biomechanical Perspective, Mitchell James Muller

Master's Theses (2009 -)

Introduction: This study evaluated and compared orthodontic forces from different archwire designs and materials used to correct a deep curve of Spee. Methods: A three-dimensional orthodontic force tester (OFT) was used to measure forces and moments exerted by archwires on brackets from central incisors to first molars. Two setups were tested: one with a full dentition from central incisor to first molar, and another simulating bicuspid extractions with the first premolar removed. Dentoform models representing a deep curve of Spee were created using cone-beam computed tomography (CBCT) data. The setup employed 0.022 × 0.028-inch zero-prescription brackets secured with elastomeric ligatures. …

Investigation Of Subcellular Damage And Long-Term Non-Cancerous Cardiovascular Effects Following Whole-Body Photon Irradiation, Nousha Afshari

LSU Doctoral Dissertations

Current radiobiological models focus primarily on nuclear DNA damage and fail to fully explain radiation-induced noncancerous health effects. This dissertation investigates whether non-nuclear subcellular structures contribute to radiation-induced biological damage through experimental biomarker analysis and computational microdosimetry. The central hypothesis posits that whole-body photon irradiation results in subcellular non-nuclear damage, specifically increased circulating mitochondrial DNA concentrations, that correlates with radiation dose and long-term noncancerous effects such as cardiovascular disease.

Specific Aim 1 measured mitochondrial and nuclear DNA concentrations in banked blood samples from 72 Chinese rhesus macaques that previously received whole-body photon irradiation ($0-10$ Gy) from Cobalt-60 or LINAC sources. …

Networked Behaviors Associated With A Large-Scale Secure Messaging Network: Cross-Sectional Secondary Data Analysis, Laura Rosa Baratta, Linlin Xia, Daphne Lew, Elise Eiden, Y Jasmine Wu, Noshir Contractor, Bruce L Lambert, Sunny S Lou, Thomas Kannampallil

2020-Current year OA Pubs

BACKGROUND: Communication among health care professionals is essential for effective clinical care. Asynchronous text-based clinician communication-secure messaging-is rapidly becoming the preferred mode of communication. The use of secure messaging platforms across health care institutions creates large-scale communication networks that can be used to characterize how interaction structures affect the behaviors and outcomes of network members. However, the understanding of the structure and interactions within these networks is relatively limited.

OBJECTIVE: This study investigates the characteristics of a large-scale secure messaging network and its association with health care professional messaging behaviors.

METHODS: Data on electronic health record-integrated secure messaging use from …

Fireworks And Wood Combustion Impacts On Air Quality, Iris Keller

DePaul Discoveries

Fire is used as a land management tool to improve ecosystem health and to reduce wildfire risk by lowering tree and litter density. However, prescribed fire as a management practice has faced difficulties with public perception, because of increased awareness of air pollution. Understanding the way that prescribed burns impact air quality and how beneficial they are for ecosystems can help the public to recognize their necessity. This study measured particulate matter (PM) emissions from prescribed burns but also considered other PM sources: fireworks and bonfires. The measurements were conducted in Minnesota, Wisconsin, and the Chicagoland area in the summer …

Factors Motivating Clothing Choice: Environmental Impact Of T-Shirts, Lauren Hunt

DePaul Discoveries

Second only to oil, the fashion industry is one of the most pollutive industries globally. Due to the rise of fast fashion, this environmental issue is continually growing. The level of production has dramatically increased while quality of apparel has decreased, causing shorter garment lifespans. This research utilizes life cycle assessment to identify the environmental impacts of various textiles used in the production of t-shirts, including cotton, polyester, viscose, and elastane. The research scope focuses from material extraction through garment disposal. The life cycle assessment research is paired with a community survey to determine consumer behavioral patterns surrounding clothing consumption …

Environmental Justice And Soil Lead Contamination: Spatial Analysis Across Seven Community Areas, Arsene Lionel Apabaga

DePaul Discoveries

Pb is a pervasive metal with toxicity linked to numerous human health issues. Urban soil is a well-documented environmental sink for Pb, persisting as a legacy pollutant decades after the phaseout of leaded gasoline. This study measured, mapped, and analyzed the spatial distribution of total soil Pb concentrations across seven Chicago Community Areas (CCAs). The objectives were to: (1) assess the relationship between mean soil Pb concentration and mean Community Environmental Justice Index (CEJI) score per CCA, (2) determine the relationship between soil Pb levels and the percentage of industrial land use, and (3) quantify and compare the percentage of …

“Put Me In Coach!”: The Impact Of College Sport Team’S Mentorship In Chronically Ill And Disabled Children And Adolescents Adherence To Medical Regimen, Jameela Askira

DePaul Discoveries

The purpose of this study was to see if participation in TeamIMPACT, a program which matches ill children with college sports teams, aided chronically ill children and adolescents in adhering to their treatment regimen. This research is a part of a larger study where 25 child participants were interviewed via Zoom to answer questions regarding their time in the program, peer and family relationships, coping and resilience and other factors. The current study solely analyzed answers to questions regarding adherence to medical treatments. There were three measures: Child vs Parent Response, Treatment Regimen Components and Care Responsibility. Through a descriptive …

Using Synchrotron Wide-Angle X-Ray Scattering To Study Collagen Degradation In Second Metacarpal Bones, Zeel Sheth, Misha Romanov, Ruby Schwieger

DePaul Discoveries

The study examines female human second metacarpal (mc2) bones from early medieval cemetery at Greding, Germany, using high-energy Wide-Angle X-ray Scattering (WAXS) at beamline 1-ID of the Advanced Photon Source (APS) at Argonne National Laboratory. Rietveld refinement showed that carbonated apatite lattice parameters did not correlate with estimated age-at-death. For six of the mc2, widths of 00.2 and 00.4 diffraction peaks were substantially narrower than those of a modern (non-diagenetically altered) mc2 and of the other four ancient mc2. The peak width results are interpreted as indicating that four of the ten ancient mc2 retain substantial collagen and six of …

Modified 2-Quinolinones For Photocatalysis: The Fluorescence Quantum Yield (Φf) Of Novel 2-Quinolinone Derivatives, Reggina Moreno Trevino, Graham Griffin

DePaul Discoveries

The photophysical properties of novel 2-quinolinone derivatives were examined to evaluate their potential as photocatalysts using fluorescence and UV-Vis absorbance spectroscopy. The fluorescence quantum yields were determined via the relative comparative method, using target absorbance values at a specific wavelength to prepare solutions and comparing these measurements to the reference molecule carbostyril-124. Molar absorptivity values were also calculated to assess the light absorption properties for each compound. Among the derivatives, PAV-3 presented with the highest molar absorptivity and fluorescence quantum yield values (ε= 15297.3 M-1 cm-1, ΦF= 17.1%), while PAV-5 showed the lowest (ε= 4796.2 M-1 cm-1, ΦF= 2.3%). The …

Race/Ethnicity, Living Arrangements, And Access To Healthcare Among Older Adults With Alzheimer’S Disease In The United States: Multiple Systematic Reviews In Relation To Health Outcomes, Chela Reiss, Grace Vethacke

DePaul Discoveries

Alzheimer’s disease (AD) is a neurodegenerative condition primarily affecting older adults. It is a growing public health crisis that affects memory, thinking, and behavior. The number of adults aged 65 and older is projected to reach 98.2 million by 2060, leading to a continued rise in the prevalence of AD. Understanding the socioeconomic factors that influence health outcomes in patients with Alzheimer's Disease and Related Dementias (ADRD) is essential in addressing the disparities within patient care and quality of life. This systematic review examined three socioeconomic factors - race/ethnicity, living arrangements, and access to healthcare - and their related health …

Depaul Discoveries Volume 14 Cover Art, Reggina Moreno Trevino

DePaul Discoveries

No abstract provided.

Effects Of 25-Hydroxyvitamin D₃ Supplementation As A Partial Replacement For Vitamin D₃ On Laying Performance, Egg Quality, And Bone Traits In Late-Stage Laying Hens, Morakot Nuntapaitoon, Nan Choisunirachon, Somporn Techangvamsuwan, Jiramate Jittidecha

The Thai Journal of Veterinary Medicine

The objective of this study was to assess the impact of dietary 25-hydroxy vitamin D₃ (25OHD₃) supplementation during the late laying hens on egg quality, hen performance and bone computerized tomography (CT) scanning parameters. In total, 24,862 Hy-Line Brownmax hens of 61 weeks old were randomly divided into two groups: the control group (n = 12,368) received a diet containing vitamin D₃ at 3,000 IU/kg, and the treatment group (n = 12,494) received a diet containing vitamin D3 at 1,500 IU/kg and 25OHD₃ at 1,500 IU/kg. The dietary intervention from 61 weeks of age to …

Overcoming Barriers To Literacy For Individuals Who Need Or Use Aac: Lived Experiences, Key Research Findings, And Future Directions, Janice Light, Christine Holyfield, David Mcnaughton, Dana Nieder, Jamie Preece

Communication Disorders and Occupational Therapy Faculty Publications and Presentations

Literacy supports participation in education, employment, healthcare, and community living, and enhances communication for individuals who need or use augmentative and alternative communication (AAC). Research has demonstrated that individuals with developmental disabilities who need or use AAC can successfully acquire a wide range of literacy skills when provided with effective tools and evidence-based, adapted instruction delivered by trained professionals. Unfortunately, individuals who need or use AAC typically face significant barriers to literacy learning: (1) They may be excluded from literacy instruction or only have access to instruction that requires spoken responses severely limiting their participation; (2) Their service providers may …

Modeling, Analysis, And Prediction Of Covid-19 Dynamics With Interacting Subpopulations And Implicit Behavior Using Physics-Informed Neural Networks, Naima Aubry-Romero, Alonso Ogueda-Oliva, Padmanabhan Seshaiyer

Spora: A Journal of Biomathematics

In this paper, we consider an extended SEIR compartmental model that incorporates young and old interacting subpopulations, allowing for cross-group transmission dynamics. Implicit behavioral changes are included to determine the influence of social behavior on coronavirus transmission dynamics. The basic reproduction number, the average number of secondary cases of infection produced by a single primary case, is derived for both the explicit and implicit model using the next-generation matrix method. We solve the associated differential equation systems and estimate useful parameters in the explicit model using physics-informed neural networks (PINNs). Our results point to how the PINNs approach offers an …

Predictive Indicators For Graduation Upon Acceptance Into A Naacls-Approved Medical Laboratory Science Program, Warren Hovis

LSU Doctoral Dissertations

The primary purpose of this study was to determine the influence of selected academic and personal demographic characteristics on student success at a NAACLS-accredited medical laboratory science program in the southern portion of the United States.

Both academic and demographic categories were selected on students who entered the medical laboratory science program from 2014 to 2019 (pre-COVID). The sanitized, archived data set was provided by the MLS department and the registrar and student affairs office at the participating school. The extant data set contained academic and demographic variables, collected over a five-year period, of initially over 170 accepted MLS students. …