Biomedical Engineering and Bioengineering Commons^™

Improving And Integrating Quantitative Single Cell Spatial Biology For Theranostic Medicine, Peng Lu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Disease states are the result of a complex interplay of many different cell types interacting in close proximity in the context of often heterogeneous tissues. Alpha particles are drawing intense research and clinical interest because of their potent cytotoxic effects and their short path lengths. Analyzing the dose distribution and tissue micro-environment for alpha therapy plays a key role in predicting the efficacy of this targeted radiotherapy. However, to date there have been no direct on-tissue analytical methods for alpha dose distributions and the corresponding tissue microenvironments.

Therefore, we have developed a pipeline to overcome this limitation by utilizing quantitative …

Deep Learning And Generative Ai Approaches For Automated Diagnosis And Personalized Treatment: Bridging Machine Learning, Medicine, And Biomechanics In Predicting Tissue Mechanics And Biomaterial Properties., Yasin Shokrollahi

Theses and Dissertations

Machine learning, particularly deep neural networks, has demonstrated significant potential in predicting high-dimensional tasks across various domains. This work encompasses a detailed review of Generative AI in healthcare and three studies integrating machine learning with finite element analysis for predicting biomechanical behaviors and properties. Initially, we provide a comprehensive overview of Generative AI applications in healthcare, focusing on Transformers and Denoising Diffusion models and suggesting potential research avenues to address existing challenges.

Subsequently, we addressed soccer-related ocular injuries by combining finite element analysis and machine learning to predict retinal mechanics following a soccer ball hit rapidly. The prediction errors are …

An Improved Saliency Map With Trustworthiness For Localizing Abnormalities In Medical Imaging, Nolan C. Skelly

Theses and Dissertations

Saliency maps are a widely used methodology to make deep learning models more interpretable. They provide post-hoc explanations through identification of the most pertinent areas of an input medical image. These techniques have been assessed based on 1) localization utility, 2) sensitivity to model weight randomization, 3) repeatability, and 4) reproducibility. Ten saliency map techniques will be tested, Grad, Smooth Grad, Integrated Gradients, Smooth Integrated Gradients, XRAI, Grad-CAM, Guided Backpropagation, Guided GradCAM, GradCAM++, and ScoreCAM. The neural networks used to predict and read medical information require a reliable solution to provide medical practitioners intelligible results. Using the information of two, …

Effects Of Indole Derivative Idc16 On Cell Proliferation, Transfection, And Alternative Splicing In Production Of Lentiviral Vectors By Transient Co-Transfection, Nataly Mier

All Graduate Theses and Dissertations, Fall 2023 to Present

Viruses can efficiently introduce genetic material into a variety of cells through cell infection. Therefore, viral vectors, defined as virus-based gene delivery systems, effectively transfer functional gene constructs to target cells. Among different viral vectors, lentiviral vectors are of interest due to the advantages offered to research and therapeutic applications. Low productivity of lentiviral vectors in mammalian producer cells and high production cost, however, remain barriers to the vectors’ routinary use, particularly in clinical settings.

Since most lentiviral vectors are derived from human immunodeficiency virus type I, their genome has been engineered to increase safety. Nevertheless, modifications of the lentiviral …

1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine (Mptp)-Treated Adult Zebrafish As A Model For Parkinson’S Disease, Emmeline Bagwell

All Theses

The use of adult zebrafish, Danio rerio, as a model for human neurodegenerative diseases has proven valuable in pharmaceutical development and genetic disease research due to their high genetic homology to humans, cost-effective husbandry, and quick life cycle breeding times. Despite their promise, most zebrafish research has focused on embryonic stage organisms, primarily due to the ease of direct handling protocols and rapid progression through developmental stages. Recognizing the limitations of early-stage organisms in modeling adult diseases, recent efforts have shifted the applicability of zebrafish models, particularly for Parkinson's Disease, due to the nature of the disease impacting patients 55 …

Medical Simulation-Based Sensor Methods For Ultrasound-Guided Dialysis Cannulation Skill Assessment, Devansh Shukla

All Theses

End-stage kidney disease (EKSD) is the final, permanent stage of chronic kidney disease (CKD), where the body's kidneys cannot filter blood sufficiently. Hemodialysis treats ESKD by filtering wastes and water from your blood externally via a dialyzer. Patients on hemodialysis require a vascular access, typically an arteriovenous fistula (AVF) or arteriovenous graft (AVG) for dialysis, which is used three times a week for about four hours a session. These life-saving therapies can be quite tedious, especially for elderly patients and patients with co-morbidities. As such, successful cannulation is extremely important to ensure the longevity of the patient's vascular access and …

Investigating The Effects Of Collagen Alignment And Tricalcium Phosphate Incorporation On Osteoblast Cell Response, Kathryn Elizabeth Bock

Theses and Dissertations

Every year, over 20 million people globally are affected by bone tissue loss due to disease or trauma. Bone tissue engineering (BTE) is touted as a promising approach to promote bone tissue repair and regeneration. In this realm, development of collagen-based scaffolds incorporated with a bioceramic is often attempted to generate tissue scaffolds that resemble the organic and inorganic composition of native bone. In addition, a variety of different collagen processing techniques have been employed to produce anisotropically aligned scaffolds that can provide the essential biochemical and structural cues to guide cell response. While there have been numerous studies on …

Development Of A Physics-Informed Neural Network For Prediction Of Blood Flow, Marcello Vittorio Mattei Di Eugenio

Theses and Dissertations

Abstract—Objective: We propose a new neural network architecture that accepts point clouds and outputs 3D velocity profiles for aneurysm geometries. Methods: We generated a synthetic aneurysm 3D flow dataset using CFD and used it to train our model architecture and compare it with other popular architectures like U-net and PointNet. We incorporate tools for improving model performance such as incorporating a distance function, a physics-informed loss to enforce the law of mass conservation, and the Huber loss to learn patterns across heterogeneous velocity components of multiple dimensions. Results: The tools implemented together with our architecture achieved the best performance on …

Exploring The Potential Of Tesla Valve For Filtering And Sorting Microscale Active Swimmers: A Computational Study, Ariel Rogers, Zhiyao He, Yong Wang

Physics Faculty Publications and Presentations

It is well-known that a Tesla valve allows fluids to flow unidirectionally without moving parts; however, how Tesla valves interact with active matters and the potential applications of Tesla valves in biology remain largely unexplored. Here, we present a computational study on the potential use of Tesla valves for filtering and sorting microscale active swimmers such as bacteria. We investigated the behavior of microscale swimmers passing through the Tesla valve at different linear and angular velocities using numerical simulations and quantified the diodicity of the Tesla valve for active swimmers. Our results demonstrate that the Tesla valve can effectively filter …

Characterizing Intervertebral Disc Strain Under Dynamic Loading Conditions Using Ultrasound Texture Analysis, Radhika Kulkarni

Discovery Undergraduate Interdisciplinary Research Internship

Herniated discs in the spine are a significant patient burden, with potential links to lower back and leg discomfort and a considerable impact on daily life. These discs, located between spinal vertebrae, are comprised of the annulus fibrosus (AF) and the nucleus pulposus (NP). Herniations happen when the NP protrudes through a full-thickness annular tear, possibly compressing spinal nerves. The mechanical factors underlying herniated discs are poorly understood, necessitating research into these mechanisms and accessible diagnostic techniques. Our study employs high-resolution ultrasound and texture correlation to quantify strain patterns in intervertebral discs during dynamic loading.

A motion segment from the …

Controlled Radiation Capsule For Precision And Rapid Cancer Treatment, Hoseon Lee, Zsolt Kollar, Bailey R. White, Junia Nguyen, David Roque, Sowjanya Palagani

Symposium of Student Scholars

This research aims to transform cancer treatment through the optimization of brachytherapy, with a focus on reducing treatment duration, setup complexities, and financial burdens, all while emphasizing patient safety. Patients living at a distance from radiation clinics, particularly those undergoing extended Low Dose Radiation brachytherapy, often struggle with the formidable financial challenges associated with securing nearby accommodations. In response to these issues, the research introduces a radiation capsule designed to condense the conventional six-month treatment period to approximately just one week, thereby significantly reducing the duration of required accommodations. This capsule is especially relevant considering the construction cost of $40 …

Deep Multi-Stage System For Liver And Lesions Segmentation Using Ct Images, Nermeen Elmenabawy, Mervat El-Seddek, Hossam El-Din Moustafa, Ahmed Elnakib

Mansoura Engineering Journal

Accurate tumor segmentation plays a pivotal role in cancer diagnosis and treatment planning. This study introduces an automated system for segmenting liver and tumors in CT images through a multi-stage process. Initial preprocessing improves image quality, followed by feature extraction using pretrained VGG16-Segnet and FCNAlexnet models. Outputs from both models are combined using a parallel fusion operation. Finally, pixel-wise classification designates pixels as liver, tumor, or background. Evaluation on the MICCAI'2017 LiTS database yielded a Dice coefficient of 95.3% for liver and 78.1% for tumors using 5-fold cross-validation. Comparative studies highlight the superior accuracy of our approach in liver and …

Occlusive Membranes For Guided Regeneration Of Inflamed Tissue Defects., Woojin Choi, Utkarsh Mangal, Jin-Young Park, Ji-Yeong Kim, Taesuk Jun, Ju Won Jung, Moonhyun Choi, Sungwon Jung, Milae Lee, Ji-Yeong Na, Du Yeol Ryu, Jin Man Kim, Jae-Sung Kwon, Won-Gun Koh, Sangmin Lee, Patrick T J Hwang, Kee-Joon Lee, Ui-Won Jung, Jae-Kook Cha, Sung-Hwan Choi, Jinkee Hong

Henry M. Rowan College of Engineering Departmental Research

Guided bone regeneration aided by the application of occlusive membranes is a promising therapy for diverse inflammatory periodontal diseases. Symbiosis, homeostasis between the host microbiome and cells, occurs in the oral environment under normal, but not pathologic, conditions. Here, we develop a symbiotically integrating occlusive membrane by mimicking the tooth enamel growth or multiple nucleation biomineralization processes. We perform human saliva and in vivo canine experiments to confirm that the symbiotically integrating occlusive membrane induces a symbiotic healing environment. Moreover, we show that the membrane exhibits tractability and enzymatic stability, maintaining the healing space during the entire guided bone regeneration …

The Effects Of Engineering Summer Camps On Middle And High School Students’ Engineering Interest And Identity Formation: A Multi-Methods Study, Timothy Robinson, Adam Kirn, Jenny Amos, Indira Chatterjee

Journal of Pre-College Engineering Education Research (J-PEER)

This multi-methods study explores changes in engineering interest and identity of middle and high school students (n = 79) attending introductory-level engineering summer camps at a large western land grant university. Middle school is a critical time when student interest, identity, and subsequently career choice begin to emerge and hence it is important that at this age students are given accurate information about engineering majors in college and future career opportunities in engineering. Data were collected over a period of two years in six summer camps. Three separate populations of middle and high school students participated in the summer …

Real-Time Arrhythmia Detection Using Convolutional Neural Networks, Thong Vu, Tyler Petty, Kemal Yakut, Muhammad Usman, Wei Xue, Francis M. Haas, Robert A. Hirsh, Xinghui Zhao

Henry M. Rowan College of Engineering Departmental Research

Cardiovascular diseases, such as heart attack and congestive heart failure, are the leading cause of death both in the United States and worldwide. The current medical practice for diagnosing cardiovascular diseases is not suitable for long-term, out-of-hospital use. A key to long-term monitoring is the ability to detect abnormal cardiac rhythms, i.e., arrhythmia, in real-time. Most existing studies only focus on the accuracy of arrhythmia classification, instead of runtime performance of the workflow. In this paper, we present our work on supporting real-time arrhythmic detection using convolutional neural networks, which take images of electrocardiogram (ECG) segments as input, and classify …

Evolutionary Conservation And Times Of Action Of Heterochronic Genes, Maria Ivanova

Theses and Dissertations

The heterochronic pathway of C. elegans is the most well-characterized system to date for controlling the sequence and timing of developmental events. However, we still have critical unanswered questions to address. First, little is known about the evolution of the heterochronic pathway, and of developmental timing in general. To determine if the roles of major heterochronic genes are conserved, I made mutants in orthologs of these genes in C. briggsae, using CRISPR/Cas9. My studies revealed a significant drift in the roles of some of the genes, although all of them are still involved in the developmental timing regulation, and several …

Differential Impact Of Blood Pressure Control Targets On Epicardial Coronary Flow After Transcatheter Aortic Valve Replacement, Brennan Vogl, Alejandra Chavez-Ponce, Adam Wentworth, Eric Erie, Pradeep Yadav, Vinod H. Thourani, Lakshmi Prasad Dasi, Brian Lindman, Mohamad Alkhouli, Hoda Hatoum

Michigan Tech Publications

Background: The cause for the association between increased cardiovascular mortality rates and lower blood pressure (BP) after aortic valve replacement (AVR) is unclear. This study aims to assess how the epicardial coronary flow (ECF) after AVR varies as BP levels are changed in the presence of a right coronary lesion. Methods: The hemodynamics of a 3D printed aortic root model with a SAPIEN 3 26 deployed were evaluated in an in vitro left heart simulator under a range of varying systolic blood pressure (SBP) and diastolic blood pressure (DBP). ECF and the flow ratio index were calculated. Flow index value …

Transport Barriers Influence The Activation Of Anti-Tumor Immunity: A Systems Biology Analysis, Mohammad R. Nikmaneshi, James W. Baish, Hengbo Zhou, Lance L. Munn

Faculty Journal Articles

Effective anti-cancer immune responses require activation of one or more naïve T cells. If the correct naïve T cell encounters its cognate antigen presented by an antigen presenting cell, then the T cell can activate and proliferate. Here, mathematical modeling is used to explore the possibility that immune activation in lymph nodes is a rate-limiting step in anti-cancer immunity and can affect response rates to immune checkpoint therapy. The model provides a mechanistic framework for optimizing cancer immunotherapy and developing testable solutions to unleash anti-tumor immune responses for more patients with cancer. The results show that antigen production rate and …

Integrative Transcriptomics And Proteomics Profiling Of Arabidopsis Thaliana Elucidates Novel Mechanisms Underlying Spaceflight Adaptation, Gbolaga O. Olanrewaju, Natasha J. Haveman, Michael J. Naldrett, Anna-Lisa Paul, Robert J. Ferl, Sarah E. Wyatt

Nebraska Center for Biotechnology: Faculty and Staff Publications

Spaceflight presents a unique environment with complex stressors, including microgravity and radiation, that can influence plant physiology at molecular levels. Combining transcriptomics and proteomics approaches, this research gives insights into the coordination of transcriptome and proteome in Arabidopsis’ molecular and physiological responses to Spaceflight environmental stress. Arabidopsis seedlings were germinated and grown in microgravity (μg) aboard the International Space Station (ISS) in NASA Biological Research in Canisters – Light Emitting Diode (BRIC LED) hardware, with the ground control established on Earth. At 10 days old, seedlings were frozen in RNA-later and returned to Earth. RNA-seq transcriptomics and TMTlabeled LC-MS/MS proteomic …

Computational Modeling Using A Novel Continuum Approach Coupled With Pathway-Informed Neural Networks To Optimize Dynein-Mediated Centrosome Positioning In Polarized Cells, Arkaprovo Ghosal, Padmanabhan Seshaiyar Dr., Adriana Dawes Dr., General Genomics Inc.

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.