Medicine and Health Sciences Commons^™

Modeling Synergistic Effects Of Integrin And Tgf-Beta Signaling In Epithelial Mesenchymal Transition, Prerak Thakkar

Biology and Medicine Through Mathematics Conference

No abstract provided.

Oral Administration Of Ph-Responsive Polymeric Nanoparticles Based On Zein And Their Therapeutic Potential On Cancer., Bruno Alejandro Valades-Aguilar, José Raúl Rangel-López, Jennifer Citlally Leos-Rivera, Moisés Armides Franco-Molina, María Cristina Rodríguez-Padilla, Diana Ginette Zárate-Triviño

Research Symposium

Background: Zein is a water-insoluble protein extracted from the endosperm of corn seeds, this polymer is an attractive matrix to encapsulate hydrophilic compounds because of its high proportion of hydrophobic amino acids, making it a potential smart delivery material for several treatments in the biopharmaceutical industry. nanoparticles have been used as drug delivery systems for the improvement of oral bioavailability; however, the strategies of nanoparticle obtention need the addition of stabilizers. in this study, a modified method to obtain zein nanoparticles was developed.

Methods: Zein nanoparticles (ZNps) were made by a thermal treatment and precipitated into ovalbumin at a ratio …

La1-Xsrxcoo3 Perovskite Nanomaterial: Synthesis, Characterization, And Its Biomedical Application, Adhira Tippur, Anyet Shohag, Luke Franco, Ahmed Touhami, Swati Mohan, Mohammed Uddin

Research Symposium

Early cancer detection is paramount for effective treatment and potential cures. This research explores the application of perovskite materials, specifically Sr2+-doped Lanthanum Cobaltite (La1-xSrxCoO3) nanomaterials, in cancer detection, with a focus on rats as an experimental model. The ferroelectric nature of these materials, synthesized through a combination of sol-gel and molten-salt processes, was examined at varying Sr2+ doping levels (1-20 wt%). Rigorous characterization, employing X-ray diffraction and scanning electron microscopy, confirmed the uniform morphology of nano cubes, laying the foundation for subsequent investigations. The magnetic properties of the perovskite nanoparticles were probed, suggesting their potential as a diagnostic tool for …

Emotion Recognition As A Novel Indicator For Assessing Brain Health: A Machine Learning Approach, Nayarah Shabir, Parveen Lehana

Research Symposium

Background: Emotion is being referred to as a person’s mental state, since it relates to their ideas, feelings, and actions. There is a lot of evidence that health affects the emotion. Therefore, the nature of emotions ought to reveal the health of a person. The emotions are represented by facial expressions controlled by muscular motor actions. Brain health may affect the working of the muscles leading to the emotional changes extracted from the facial images.

Methods: A dataset of facial images annotated with matching emotion labels is the first step in using convolutional neural networks (CNNs) for facial …

Modified Zero-Gravity Chair In The Management Of Pain And Anxiety With Emphasis On Pre And Post Anesthesia For Surgical Procedures, Alexander Tisdale, Kinsley Batson, Zachary Jamous, Isabella Termini, Kyle Mooday, Matt Cohn, Jackson Justice

Annual Research Symposium

The purpose of this research is the integration of a zero-gravity chair with planar vibration as a non-pharmaceutical approach to preoperative anxiety and postoperative pain management. The treatment plan involves preoperative familiarization with the chair's vibrational patterns and postoperative use for pain relief. Integration of this approach holds promise in reshaping postoperative care paradigms, advocating for personalized, holistic interventions to enhance patient well-being and mitigate opioid-related risks.

Multimode Point Spectroscopy For Food Authentication, Sayed Asaduzzaman, Nicholas Mackinnon, Hossein Kashani Zadeh

SDSU Data Science Symposium

Enhancing food quality measurement is a necessity to guarantee food safety and adherence to health regulations. Current methods involve lab testing which are time-consuming, costly, destructive and require skilled workers. Spectroscopy has the potential to overcome these challenges. This study employs a multi-mode point spectroscopy method to distinguish food products according to their spectral characteristics,. The system records fluorescence, excited at 365 and 405 nm, visible-near infrared (Vis-NIR) and short-wave infrared (SWIR) spectra. The three main subjects of the study are olive oil, milk, and honey. Samples were kept in a transparent cell culture pot, and Gray and White Spectralon …

Engineering Of Functionalized Carbon Nano-Onions Embedded Bsa Nanocomposite Fibers For Stimuli-Responsive Drug Release, Ramiro Manuel Velasco Delgadillo, Narsimha Mamidi

Research Symposium

Background: Advanced drug delivery systems (DDSs) have received enormous attention in biomedical applications due to their pharmacodynamic and pharmacokinetic drug properties. For the present study, poly 4-hydroxyphenyl methacrylate (PHPMA)/CNOs (f-CNOs) inserted bovine serum albumin (BSA) nanofibers were prepared for stimuli-responsive release of Doxorubicin (DOX). Temperature and pH would be altered to study the release of DOX in acidic microenvironments.

Methods: PHPMA were coupled with COOH-CNOs via ester coupling via the sonochemical method to produce PHPMA-CNOs (f-CNOs). Then, f-CNOs/DOX embedded BSA nanofibers were prepared at room temperature using Forcespinning. UV spectra of DOX-loaded nanofibers were studied to investigate the …

A 3d Printed Microneedle System For Transdermal Drug Delivery Of Anticancer Drugs, Md Jasim Uddin, Tanvir Ahmed, Dennis Douroumis

Research Symposium

Background: Transdermal delivery of drugs is an attractive alternative to the conventional route of administration as oral delivery. The hypodermic injections are painful and less patient compliance. Microneedles (MNs) are micron-sized, minimally invasive needles to deliver a wide range of molecules (e.g., small, DNA, vaccines etc.) to the upper portion of the dermis in a sustained and controlled manner, without causing any pain. The introduction of 3D printing technologies in the fabrication of MN will promote one-step manufacturing tools and scale-up for the delivery devices of anticancer drugs.

Methods: The 3D printed MN (3DMN) arrays were fabricated using Stereolithography (SLA), …

Noninvasively Monitoring Of Cerebral Blood Flow In Piglet Models Of Graded Hemorrhage And Hypoxic Ischemic Brain Injury Using Diffuse Correlation Spectroscopy And Near-Infrared Spectroscopy, Randolph Sinahon, Danielle Shoshany, Shadi Malaeb, Mert Deniz Polat, Meltem Izzetoglu, Kurtulus Izzetoglu

St. Chris Research Day

No abstract provided.

Cerebral Blood Flow Measured By Diffuse Correlation Spectroscopy For Monitoring Depth Of Anesthesia In Piglets, Mert Deniz Polat, Kurtulus Izzetoglu, Randolph Sinahon, Meltem Izzetoglu, Shadi Malaeb

St. Chris Research Day

No abstract provided.

Modeling Epithelial-Mesenchymal Transition In A 3d Multicellular Model Of Tgf-Β1 Signaling, Kristin Kim, Chris Lemmon

Biology and Medicine Through Mathematics Conference

No abstract provided.

Enhancement Of Deep Learning Protein Structure Prediction, Ruoming Shen

Modeling, Simulation and Visualization Student Capstone Conference

Protein modeling is a rapidly expanding field with valuable applications in the pharmaceutical industry. Accurate protein structure prediction facilitates drug design, as extensive knowledge about the atomic structure of a given protein enables scientists to target that protein in the human body. However, protein structure identification in certain types of protein images remains challenging, with medium resolution cryogenic electron microscopy (cryo-EM) protein density maps particularly difficult to analyze. Recent advancements in computational methods, namely deep learning, have improved protein modeling. To maximize its accuracy, a deep learning model requires copious amounts of up-to-date training data.

This project explores DeepSSETracer, a …

The Effects Of Demographics And Risk Factors On The Morphological Characteristics Of Human Femoropopliteal Arteries, Sayed Ahmadreza Razian, Majid Jadidi, Alexey Kamenskiy

UNO Student Research and Creative Activity Fair

Background: Disease of the lower extremity arteries (Peripheral Arterial Disease, PAD) is associated with high morbidity and mortality. During disease development, the arteries adapt by changing their diameter, wall thickness, and residual deformations, but the effects of demographics and risk factors on this process are not clear.

Methods: Superficial femoral arteries from 736 subjects (505 male, 231 female, 12 to 99 years old, average age 51±17.8 years) and the associated demographic and risk factor variables were used to construct machine learning (ML) regression models that predicted morphological characteristics (diameter, wall thickness, and longitudinal opening angle resulting from the …

Session 12: Active Learning To Minimize The Possible Risk From Future Epidemics, Kc Santosh

SDSU Data Science Symposium

In medical imaging informatics, for any future epidemics (e.g., Covid-19), deep learning (DL) models are of no use as they require a large dataset as they take months and even years to collect enough data (with annotations). In such a context, active learning (or human/expert-in-the-loop) is the must, where a machine can learn from the first day with minimum possible labeled data. In unsupervised learning, we propose to build pre-trained DL models that iteratively learn independently over time, where human/expert intervenes only when it makes mistakes and for only a limited data. In our work, deep features are used to …

2d Respiratory Sound Analysis To Detect Lung Abnormalities, Rafia Sharmin Alice, Kc Santosh

SDSU Data Science Symposium

Abstract. In this paper, we analyze deep visual features from 2D data representation(s) of the respiratory sound to detect evidence of lung abnormalities. The primary motivation behind this is that visual cues are more important in decision-making than raw data (lung sound). Early detection and prompt treatments are essential for any future possible respiratory disorders, and respiratory sound is proven to be one of the biomarkers. In contrast to state-of-the-art approaches, we aim at understanding/analyzing visual features using our Convolutional Neural Networks (CNN) tailored Deep Learning Models, where we consider all possible 2D data such as Spectrogram, Mel-frequency Cepstral Coefficients …

Open-Source And 3-D Printed Autoinjector, Anjutha Selvaraj

Undergraduate Student Research Internships Conference

Autoinjectors have become popular modern injectable medical devices used as drug delivery systems. Due to its ease, capability and reliability compared to other conventional injectable medical devices, the market and manufacturing demand for autoinjector devices are increasing at a staggering rate. Although autoinjectors can offset healthcare treatment costs through self-administered medication, they are expensive for consumers. This paper describes the design and manufacture of a spring-driven and 3-D printed autoinjector using open-source hardware. By making it an open-source resource for everyone, the barrier of advanced research in design and production can be lifted, thus making it easily manufacturable and cost-effective. …

Producing And Measuring Oscillatory Shear In A Novel Microfluidic Chip, Sanaz Lordfard, Daniel Lorusso, Tamie L. Poepping, Hristo N Nikolov, Kayla Soon, Stephen Sims, Jeffrey Dixon, David Holdsworth

Undergraduate Student Research Internships Conference

Purpose: To demonstrate the effectiveness of a novel microfluidic device mimicking oscillatory blood flow, allowing cell biologists to examine how endothelial cells respond to a range of oscillatory shear stress levels.

Methods: The microfluidic chip consists of a circular-shaped reservoir, leading to a rectangular channel that is examined under a microscope. The plunger is connected to a speaker system and oscilloscope, allowing the plunger to apply a range of frequencies (5-60Hz) and voltages (5-10 V, leading to a variety in oscillation amplitudes) to the reservoir region. 1.1 um fluorescent particles diluted in distilled water were used for tracking. Processing was …

Combination Of Statistical Shape Modeling And Statistical Parametric Mapping To Quantify Cartilage Contact Mechanics In Hip Dysplasia, Penny R. Atkins Phd, Shireen Y. Elhabian Phd, Jeffrey A. Weiss Phd, Ross T. Whitaker Phd, Christopher L. Peters Md, Andrew E. Anderson Phd

PanaSoMM

Finite element models can predict subject-specific chondrolabral stresses and help to elucidate the effect of under-coverage and incongruency of the hip joint in patients with dysplasia. However, complex stress patterns are difficult to generalize and evaluate statistically. With an established correspondence across shapes from statistical shape modeling (SSM), statistical parametric mapping (SPM) allows for evaluation of local variability while preserving model subject-specificity. Herein, we evaluated the combined application of SSM and SPM to compare cartilage contact stress between control subjects and patients with dysplasia.

Previously published hip joint contact stresses were mapped onto chondrolabral surface meshes and incorporated into an …

Application Of Statistical Shape Modeling To Predict Clinical Metric Of Femoral Head Coverage In Patients With Developmental Dysplasia, Penny R. Atkins Phd, Praful Agrawal Phd, Joseph D. Mozingo Phd, Keisuke Uemura Md, Phd, Kunihiko Tokunaga Md, Christopher L. Peters Md, Shireen Y. Elhabian Phd, Ross T. Whitaker Phd, Andrew E. Anderson Phd

PanaSoMM

Developmental dysplasia of the hip (DDH) is described as under-coverage of the femoral head by the acetabulum, resulting in mechanical instability. Though DDH is often diagnosed using plain film radiographs, these images cannot adequately capture 3D joint coverage. Herein, we applied a 3D statistical shape model (SSM) to the femur and hemi-pelvis of patients with DDH to objectively measure shape variation and evaluated whether SSM outputs could predict measurements of joint coverage.

The femur and hemi-pelvis were semi-automatically segmented from CT images (83 hips from 47 females with DDH). Surfaces of each hip were reconstructed from segmentations, aligned, and input …

Study Of Cardiovascular Dynamics During Graded Head-Up Tilt Test In The Young With Syncope Tendency, Martin A. Miranda Sr

Biology and Medicine Through Mathematics Conference

No abstract provided.

Evaluating The Use Of Nintendo Labo As A Rehabilitation Tool, Jacob Colwell, Logan Suiter, Amanda Wells

ONU Student Research Colloquium

Serious gaming is the practice of using video games, either commercial or specifically designed, for physical rehabilitation. Serious games have emerged in the last decade as a way to increase patient involvement in rehabilitation, increase the likelihood of patients continuing treatment after progress stalls, and generally increase mental health during treatment. However, the current literature has not kept pace with the evolution of technology and therefore the use of next-generation consoles for serious gaming is underdeveloped.

The Nintendo Switch could provide new avenues for serious gaming because of the advanced sensing ability of its controllers (Joy-Cons) and the engaging ways …

Medical Manikin Augmented Reality Simulation (M2ars), Pauline Delacruz, Jacob Gibson, Daniel Howard, Jaclyn Peacock, Kendall Robbins

Modeling, Simulation and Visualization Student Capstone Conference

The Medical Manikin Augmented Reality Simulation (M2ARS) is an augmented reality simulation application built for the Microsoft HoloLens 2 that uses the principles of anatomy transfer to overlay human anatomical structures onto a medical manikin digitally. These structures currently consist of the skeletal, muscular, and circulatory systems. In addition, a model of the lungs and an animated heart are also available within the simulation. M2ARS allows the user to view these structures in a manner that is both visually and spatially accurate to the human body. This application contains two modes; an augmented reality mode, which uses a manikin, and …

Multi-Modality Breast Mri Segmentation Using Nn-Unet For Preoperative Planning Of Robotic Surgery Navigation, Motaz Alqaoud, John Plemmons Md, Eric Feliberti Md, Facs, Krishnanand Kaipa, Siqin Dong, Gabor Fichtinger, Yimming Xiao, Michel Audette

Modeling, Simulation and Visualization Student Capstone Conference

Segmentation of the chest region and breast tissues is essential for surgery planning and navigation. This paper proposes the foundation for preoperative segmentation based on two cascaded architectures of deep neural networks (DNN) based on the state-of-the-art nnU-Net. Additionally, this study introduces a polyvinyl alcohol cryogel (PVA-C) breast phantom based on the segmentation of the DNN automated approach, enabling the experiments of navigation system for robotic breast surgery. Multi-modality breast MRI datasets of T2W and STIR images were acquired from 10 patients. Segmentation evaluation utilized the Dice Similarity Coefficient (DSC), segmentation accuracy, sensitivity, and specificity. First, a single class labeling …

Optimization Of The Musculoskeletal Simulation In Estimation Of Metabolic Cost, Arash Mohammadzadeh Gonabadi, Philippe Malcolm

UNO Student Research and Creative Activity Fair

Energy from food is supplied to the human body in the form of chemical energy in the muscles. This metabolic energy expenditure is one of the main determinants of the way we walk, and indirect calorimetry measurements are an essential tool for understanding how increases in metabolic cost restrict the mobility of clinical populations. Respiratory oxygen consumption measurements allow recording of the average metabolic cost of walking. However, the time required for these measurements prevents assessing metabolic rate in patients who cannot walk long enough. Musculoskeletal modeling techniques allow to estimate average muscle energy expenditure during locomotion in conjunction with …

How Can Actuation Timing And Magnitude Of A Bilateral Semi-Rigid Hip Exoskeleton Optimize Metabolic Cost, Arash Mohammadzadeh Gonabadi, Prokopios Antonellis, Sara Myers, Iraklis Pipinos, Philippe Malcolm

UNO Student Research and Creative Activity Fair

Semi-rigid exoskeletons could combine some advantages of rigid and soft approaches. The purpose of this study was to investigate the effects of timing and magnitude of assistance from a semi-rigid hip exoskeleton. For ten participants, we tested ten conditions that were combinations of 5 different end-timings, ranging from 21% to 49%, and 2 different moment magnitudes ranging from 0.06 to 0.12 Nm.kg^-1. The participants walked in two reference conditions: a condition without actuation and a condition without the exoskeleton. A semi-rigid hip exoskeleton could alter metabolic rate. However, to produce a net assistive effect, it is necessary to …

Design And Development Of Software With A Graphical User Interface To Display And Convert Multiple Microscopic Histology Images, Sayed Ahmadreza Razian, Majid Jadidi, Alexey Kamenskiy

UNO Student Research and Creative Activity Fair

Histological images are widely used to assess the microscopic anatomy of biological tissues. Recent advancements in image analysis allow the identification of structural features on histological sections that can help advance medical device development, brain and cancer research, drug discovery, vascular mechanobiology, and many other fields. Histological slide scanners create images in SVS and TIFF formats that were designed to archive image blocks and high-resolution textual information. Because these formats were primarily intended for storage, they are often not compatible with conventional image analysis software and require conversion before they can be used in research. We have developed a user-friendly …

Breaks In Longitudinal Elastic Fibers Of Human Femoropopliteal Arteries, Elham Zamani

UNO Student Research and Creative Activity Fair

Breaks in Longitudinal Elastic Fibers of Human Femoropopliteal Arteries

Elham Zamani1, Majid Jadidi1

1 Department of Biomechanics, University of Nebraska Omaha, Omaha, NE

Introduction: Elastin is a major protein in the body with half-life >50 years. It is thought that elastic fibers are formed before the postnatal period. In the femoropopliteal artery (FPA), the main artery in the leg, longitudinal elastic fibers are present in External Elastic Lamina (EEL). Our team has studied more than 1000 cadaveric human FPA and has noticed that there are big breaks in their longitudinal elastic fibers in some subjects. Our goal in this work …

A Note From The Co-Editors, Jada C. Johnson

Ideas: Exhibit Catalog for the Honors College Visiting Scholars Series

An introduction to the fifth issue of the third volume of Ideas Magazine, concerning the thoughts, experience, and work of Dr. Marcelo J.S. de Lemos.

Development Of A Low-Cost Algometer, Thomas D. Naish, Ana Luisa Trejos, Dave M. Walton

Undergraduate Student Research Internships Conference

Many people suffer from chronic pain, the reasons for which are not always well understood. Algometers are instruments that can help clinicians understand the nature of pain by determining the force at which pain becomes noticeable or unbearable. Algometers can also be used to determine the effects that external influences can have on pain tolerance in healthy people.

The goal of this project was to develop an algometer that can measure the normal range of pain thresholds and tolerances of most patients, which ranges up to 35 lbs. Also, the result needed to be accurate to about 1% and made …

Automatic Data Collection System And Video Laryngoscope Database, Gabrielle Hoyer

Utah Space Grant Consortium

The aggregate intubation data collected by a network of video laryngoscopes can be processed to understand the quality of an individual’s or a group of individual’s practice(s). Currently, all data surrounding intubations is self-reported and not understood on an aggregate basis. We are developing a technology which can enable monitoring and benchmarking of intubations across a wide variety of practices.