Biomedical Engineering and Bioengineering Commons^™

Robotic Resistance Treadmill Training Improves Locomotor Function In Children With Cerebral Palsy: A Randomized Controlled Pilot Study, Ming Wu, Janis Kim, Deborah J. Gaebler-Spira, Brian D. Schmit, Pooja Arora

Biomedical Engineering Faculty Research and Publications

Objective

To determine whether applying controlled resistance forces to the legs during the swing phase of gait may improve the efficacy of treadmill training as compared with applying controlled assistance forces in children with cerebral palsy (CP).

Design

Randomized controlled study.

Setting

Research unit of a rehabilitation hospital.

Participants

Children with spastic CP (N=23; mean age, 10.6y; range, 6–14y; Gross Motor Function Classification System levels, I–IV).

Interventions

Participants were randomly assigned to receive controlled assistance (n=11) or resistance (n=12) loads applied to the legs at the ankle. Participants underwent robotic treadmill training 3 times a week for 6 weeks (18 …

Incorporation Of Catalytic Modalities For Forming Of A Catalytic Cascade, Albert T. Perry Iii

Nanoscience and Microsystems ETDs

This dissertation investigates the novel incorporation of inorganic and enzymatic catalysts. There is little literature on inorganic catalysts operating at biologically relevant pHs and as such a significant amount of this dissertation focuses on determination of catalyst activity. Mn amino-anitpyrene (MnAAPyr), Pt, Pt alloys, Mn-N-C and Pd catalysts on 3D graphene supports(3D-GNS), were explored for activity towards glycerol intermediates: oxalic acid, mesoxalic acid, glyoxalic acid, and formic acid. MnAAPyr was designed to mimic the reaction center of oxalate decarboxylase and oxalate oxidaze, the natural catalyst towards oxalic acid. It showed high activity towards oxalic acid, with onset potentials of 0.714±0.002V …

Pattern Discovery In Brain Imaging Genetics Via Scca Modeling With A Generic Non-Convex Penalty, Lei Du, Kefei Liu, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen, Michael W. Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, Charles D. Smith, Gregory Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad

Neurology Faculty Publications

Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose ℓ₁-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the ℓ₁-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce …

Integrative Computational Modeling For Developing Means To Manipulate Biological Cells And For Solving Complex Engineering Problems, Yu Zhao, Guigen Zhang

Commonwealth Computational Summit

A brief discussion on reductive vs integrative investigation

A case study: how integrative computational modeling helps advance the understanding and application of dielectrophoresis (DEP) in various situations

Other applications in advancing the design and development of nanopore, medical devices, novel materials, actuation devices, and coupled spectroscopic techniques, etc.

Integrative Computational Modeling For Developing Means To Manipulate Biological Cells And For Solving Complex Engineering Problems, Yu Zhao, Guigen Zhang

Commonwealth Computational Summit

Computational modeling has become more widely used to guide the design of microfluidic devices for manipulating cells using Dielectrophoresis (DEP), and devise novel means for advancing the study of cellular science and engineering. Conventionally, cells are treated as volumeless points in the system, which allows study of the movement of groups of particles under the effect of field. However, this approach often neglects the distortion effect of particle on external field, as well as interactions among particles. Moreover, it ignores the complex inner structures of cell, which are the causes of distinctive cell behavior. To more accurately model the behavior …

Parallelization Of A Three-Dimensional Full Multigrid Algorithm To Simulate Tumor Growth, Dylan Goodin, Chin F. Ng, Hermann B. Frieboes

Commonwealth Computational Summit

We present the performance gains of an openMP implementation of a fully adaptive nonlinear full multigrid (FMG) algorithm to simulate three-dimensional multispecies desmoplastic tumor growth on computer systems of varying processing capabilities. The FMG algorithm is applied to solve a recently published thermodynamic mixture model that uses a diffuse interface approach with fourth-order reaction-advection-diffusion PDEs (Cahn-Hilliard-type equations) that are coupled, nonlinear, and numerically stiff. The model includes multiple cell species and extracellular matrix (ECM), with adhesive and elastic energy contributions in chemical potential terms, as well as including blood and lymphatic vessels represented as continuous vasculatures. Advection-reaction-diffusion PDEs are employed …

Hierarchical Fusion Based Deep Learning Framework For Lung Nodule Classification, Kazim Sekeroglu

LSU Doctoral Dissertations

Lung cancer is the leading cancer type that causes the mortality in both men and women. Computer aided detection (CAD) and diagnosis systems can play a very important role for helping the physicians in cancer treatments. This dissertation proposes a CAD framework that utilizes a hierarchical fusion based deep learning model for detection of nodules from the stacks of 2D images. In the proposed hierarchical approach, a decision is made at each level individually employing the decisions from the previous level. Further, individual decisions are computed for several perspectives of a volume of interest (VOI). This study explores three different …

Dual-Drug Containing Core-Shell Nanoparticles For Lung Cancer Therapy, Jyothi Unnikrishna Menon, Aneetta Kuriakose, Roshni Iyer, Elizabeth Hernandez, Leah Gandee, Shanrong Zhang, Masaya Takahashi, Zhang Zhang, Debabrata Saha, Kytai Truong Nguyen

Bioengineering Faculty Publications - Archive

Late-stage diagnosis of lung cancer occurs ~95% of the time due to late manifestation of its symptoms, necessitating rigorous treatment following diagnosis. Existing treatment methods are limited by lack of specificity, systemic toxicity, temporary remission, and radio-resistance in lung cancer cells. In this research, we have developed a folate receptor-targeting multifunctional dual drug-loaded nanoparticle (MDNP) containing a poly(N-isopropylacrylamide)-carboxymethyl chitosan shell and poly lactic-coglycolic acid (PLGA) core for enhancing localized chemo-radiotherapy to effectively treat lung cancers. The formulation provided controlled releases of the encapsulated therapeutic compounds, NU7441 - a potent radiosensitizer, and gemcitabine - an FDA approved chemotherapeutic drug for lung …

Co-Existence Of Microbial Ecology In A Chemostat Using A Robust Feedback, Hector Puebla, Mariana Rodriguez-Jara, Margarita M. Gonzalez-Brambila, Eliseo Hernandez-Martinez, Alejandra Velasco-Perez, Ennio Piceno-Diaz

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Open Source Artificial Intelligence In A Biological/Ecological Context, Trevor Grant

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Food Web Control And Synchronization Using A Robust Feedback, Hector Puebla, Mariana Rodriguez-Jara, Cesar S. Lopez-Monsalvo, Eliseo Hernandez-Martinez, Alejandra Velasco-Perez

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Microfluidic Biopsy Trapping Device For The Real-Time Monitoring Of The Tumor Microenvironment, Angela Holton

USF Tampa Graduate Theses and Dissertations

The tumor microenvironment is composed of cellular and stromal components such as tumor cells, mesenchymal cells, immune cells, cancer associated fibroblasts and the supporting extracellular matrix. The tumor microenvironment provides crucial support for growth and progression of tumor cells and affects tumor response to therapeutic interventions. To better understand tumor biology and to develop effective cancer therapeutic agents it is important to develop preclinical platforms that can faithfully recapitulate the tumor microenvironment and the complex interaction between the tumor and its surrounding stromal elements. Drug studies performed in vitro with conventional two-dimensional cancer cell line models do not optimally represent …

Designing Biomaterials Using Mussel Adhesive Chemistry, Bruce P. Lee

TechTalks

Marine mussels secrete adhesive proteins that enable them to anchor to surfaces under water. We are exploiting chemistry utilized by mussels to design bioadhesives for tissue repair and wound healing, smart biomaterials for on-demand antipathogenic applications, and smart adhesives that can be turned on and off with externally applied stimuli.

Decreased Triple Network Connectivity In Patients With Recent Onset Post-Traumatic Stress Disorder After A Single Prolonged Trauma Exposure, Yang Liu, Liang Li, Baojuan Li, Na Feng, Lihong Li, Xi Zhang, Hongbing Lu, Hong Yin

Publications and Research

The triple network model provides a common framework for understanding affective and neurocognitive dysfunctions across multiple disorders, including central executive network (CEN), default mode network (DMN), and salience network (SN). Considering the effect of traumatic experience on post-traumatic stress disorder (PTSD), this study aims to explore the alteration of triple network connectivity in a specific PTSD induced by a single prolonged trauma exposure. With an arterial spin labeling sequence, three networks were first identified using independent component analysis among 10 PTSD patients and 10 healthy survivors, who experienced the same coal mining flood disaster. Then, the triple network connectivity was …

Multiscale Modeling Of Cardiovascular Flows, Alison Marsden, Ethan Kung

Publications

Simulations of blood flow in the cardiovascular system offer investigative and predictive capabilities to augment current clinical tools. Using image-based modeling, the Navier-Stokes equations can be solved to obtain detailed 3-dimensional hemodynamics in patient-specific anatomical models. Relevant parameters such as wall shear stress and particle residence times can then be calculated from the 3D results and correlated with clinical data for treatment planning and device evaluation. Reduced-order models such as open or closed loop 0D lumped-parameter models can simulate the dynamic behavior of the circulatory system using an analogy to electrical circuits. When coupled to 3D simulations as boundary conditions, …

Utilizing Functional Near-Infrared Spectroscopy For Prediction Of Cognitive Workload In Noisy Work Environments, Ryan Gabbard, Mary E. Fendley, Irfaan A. Dar, Rik Warren, Nasser H. Kashou

Biomedical, Industrial & Human Factors Engineering Faculty Publications

Occupational noise frequently occurs in the work environment in military intelligence, surveillance, and reconnaissance operations. This impacts cognitive performance by acting as a stressor, potentially interfering with the analysts’ decision-making process. We investigated the effects of different noise stimuli on analysts’ performance and workload in anomaly detection by simulating a noisy work environment. We utilized functional near-infrared spectroscopy (fNIRS) to quantify oxy-hemoglobin (HbO) and deoxy-hemoglobin concentration changes in the prefrontal cortex (PFC), as well as behavioral measures, which include eye tracking, reaction time, and accuracy rate. We hypothesized that noisy environments would have a negative effect on the participant in …

The Prospects Of Zinc As A Structural Material For Biodegradable Implants—A Review Paper, Galit Katarivas Levy, Jeremy Goldman, Eli Aghion

Michigan Tech Publications, Part 1

In the last decade, iron and magnesium, both pure and alloyed, have been extensively studied as potential biodegradable metals for medical applications. However, broad experience with these material systems has uncovered critical limitations in terms of their suitability for clinical applications. Recently, zinc and zinc-based alloys have been proposed as new additions to the list of degradable metals and as promising alternatives to magnesium and iron. The main byproduct of zinc metal corrosion, Zn²⁺, is highly regulated within physiological systems and plays a critical role in numerous fundamental cellular processes. Zn²⁺ released from an implant may suppress …

Tuning Properties Of Poly(Ethylene Glycol)-Block-Poly(Simvastatin) Copolymers Synthesized Via Triazabicyclodecene, Theodora A. Asafo-Adjei, Thomas D. Dziubla, David A. Puleo

Biomedical Engineering Faculty Publications

Simvastatin was polymerized into copolymers to better control drug loading and release for therapeutic delivery. When using the conventional stannous octoate catalyst in ring-opening polymerization (ROP), reaction temperatures ≥ 200 °C were required, which promoted uncontrollable and undesirable side reactions. Triazabicyclodecene (TBD), a highly reactive guanidine base organocatalyst, was used as an alternative to polymerize simvastatin. Polymerization was achieved at 150 °C using 5 kDa methyl-terminated poly(ethylene glycol) (mPEG) as the initiator. ROP reactions with 2 kDa or 550 Da mPEG initiators were also successful using TBD at 150 °C instead of stannous octoate, which required a higher reaction temperature. …

Computational Modeling For Abnormal Brain Tissue Segmentation, Brain Tumor Tracking, And Grading, Syed Mohammad Shamin Reza

Electrical & Computer Engineering Theses & Dissertations

This dissertation proposes novel texture feature-based computational models for quantitative analysis of abnormal tissues in two neurological disorders: brain tumor and stroke. Brain tumors are the cells with uncontrolled growth in the brain tissues and one of the major causes of death due to cancer. On the other hand, brain strokes occur due to the sudden interruption of the blood supply which damages the normal brain tissues and frequently causes death or persistent disability. Clinical management of these brain tumors and stroke lesions critically depends on robust quantitative analysis using different imaging modalities including Magnetic Resonance (MR) and Digital Pathology …

Development And Validation Of A Hybrid Virtual/Physical Nuss Procedure Surgical Trainer, Mohammad F. Obeid

Computational Modeling & Simulation Engineering Theses & Dissertations

With continuous advancements and adoption of minimally invasive surgery, proficiency with nontrivial surgical skills involved is becoming a greater concern. Consequently, the use of surgical simulation has been increasingly embraced by many for training and skill transfer purposes. Some systems utilize haptic feedback within a high-fidelity anatomically-correct virtual environment whereas others use manikins, synthetic components, or box trainers to mimic primary components of a corresponding procedure.

Surgical simulation development for some minimally invasive procedures is still, however, suboptimal or otherwise embryonic. This is true for the Nuss procedure, which is a minimally invasive surgery for correcting pectus excavatum (PE) – …