Matching Items (8)
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- All Subjects: Biomaterials
- Creators: Vernon, Brent
- Status: Published
Description
Myocardial infarction (MI) remains the leading cause of mortality and morbidity in the U.S., accounting for nearly 140,000 deaths per year. Heart transplantation and implantation of mechanical assist devices are the options of last resort for intractable heart failure, but these are limited by lack of organ donors and potential surgical complications. In this regard, there is an urgent need for developing new effective therapeutic strategies to induce regeneration and restore the loss contractility of infarcted myocardium. Over the past decades, regenerative medicine has emerged as a promising strategy to develop scaffold-free cell therapies and scaffold-based cardiac patches as potential approaches for MI treatment. Despite the progress, there are still critical shortcomings associated with these approaches regarding low cell retention, lack of global cardiomyocytes (CMs) synchronicity, as well as poor maturation and engraftment of the transplanted cells within the native myocardium. The overarching objective of this dissertation was to develop two classes of nanoengineered cardiac patches and scaffold-free microtissues with superior electrical, structural, and biological characteristics to address the limitations of previously developed tissue models. An integrated strategy, based on micro- and nanoscale technologies, was utilized to fabricate the proposed tissue models using functionalized gold nanomaterials (GNMs). Furthermore, comprehensive mechanistic studies were carried out to assess the influence of conductive GNMs on the electrophysiology and maturity of the engineered cardiac tissues. Specifically, the role of mechanical stiffness and nano-scale topographies of the scaffold, due to the incorporation of GNMs, on cardiac cells phenotype, contractility, and excitability were dissected from the scaffold’s electrical conductivity. In addition, the influence of GNMs on conduction velocity of CMs was investigated in both coupled and uncoupled gap junctions using microelectrode array technology. Overall, the key contributions of this work were to generate new classes of electrically conductive cardiac patches and scaffold-free microtissues and to mechanistically investigate the influence of conductive GNMs on maturation and electrophysiology of the engineered tissues.
ContributorsNavaei, Ali (Author) / Nikkhah, Mehdi (Thesis advisor) / Brafman, David (Committee member) / Migrino, Raymond Q. (Committee member) / Stabenfeldt, Sarah (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2018
Description
Rapid intraoperative diagnosis of brain tumors is of great importance for planning treatment and guiding the surgeon about the extent of resection. Currently, the standard for the preliminary intraoperative tissue analysis is frozen section biopsy that has major limitations such as tissue freezing and cutting artifacts, sampling errors, lack of immediate interaction between the pathologist and the surgeon, and time consuming.
Handheld, portable confocal laser endomicroscopy (CLE) is being explored in neurosurgery for its ability to image histopathological features of tissue at cellular resolution in real time during brain tumor surgery. Over the course of examination of the surgical tumor resection, hundreds to thousands of images may be collected. The high number of images requires significant time and storage load for subsequent reviewing, which motivated several research groups to employ deep convolutional neural networks (DCNNs) to improve its utility during surgery. DCNNs have proven to be useful in natural and medical image analysis tasks such as classification, object detection, and image segmentation.
This thesis proposes using DCNNs for analyzing CLE images of brain tumors. Particularly, it explores the practicality of DCNNs in three main tasks. First, off-the shelf DCNNs were used to classify images into diagnostic and non-diagnostic. Further experiments showed that both ensemble modeling and transfer learning improved the classifier’s accuracy in evaluating the diagnostic quality of new images at test stage. Second, a weakly-supervised learning pipeline was developed for localizing key features of diagnostic CLE images from gliomas. Third, image style transfer was used to improve the diagnostic quality of CLE images from glioma tumors by transforming the histology patterns in CLE images of fluorescein sodium-stained tissue into the ones in conventional hematoxylin and eosin-stained tissue slides.
These studies suggest that DCNNs are opted for analysis of CLE images. They may assist surgeons in sorting out the non-diagnostic images, highlighting the key regions and enhancing their appearance through pattern transformation in real time. With recent advances in deep learning such as generative adversarial networks and semi-supervised learning, new research directions need to be followed to discover more promises of DCNNs in CLE image analysis.
Handheld, portable confocal laser endomicroscopy (CLE) is being explored in neurosurgery for its ability to image histopathological features of tissue at cellular resolution in real time during brain tumor surgery. Over the course of examination of the surgical tumor resection, hundreds to thousands of images may be collected. The high number of images requires significant time and storage load for subsequent reviewing, which motivated several research groups to employ deep convolutional neural networks (DCNNs) to improve its utility during surgery. DCNNs have proven to be useful in natural and medical image analysis tasks such as classification, object detection, and image segmentation.
This thesis proposes using DCNNs for analyzing CLE images of brain tumors. Particularly, it explores the practicality of DCNNs in three main tasks. First, off-the shelf DCNNs were used to classify images into diagnostic and non-diagnostic. Further experiments showed that both ensemble modeling and transfer learning improved the classifier’s accuracy in evaluating the diagnostic quality of new images at test stage. Second, a weakly-supervised learning pipeline was developed for localizing key features of diagnostic CLE images from gliomas. Third, image style transfer was used to improve the diagnostic quality of CLE images from glioma tumors by transforming the histology patterns in CLE images of fluorescein sodium-stained tissue into the ones in conventional hematoxylin and eosin-stained tissue slides.
These studies suggest that DCNNs are opted for analysis of CLE images. They may assist surgeons in sorting out the non-diagnostic images, highlighting the key regions and enhancing their appearance through pattern transformation in real time. With recent advances in deep learning such as generative adversarial networks and semi-supervised learning, new research directions need to be followed to discover more promises of DCNNs in CLE image analysis.
ContributorsIzady Yazdanabadi, Mohammadhassan (Author) / Preul, Mark (Thesis advisor) / Yang, Yezhou (Thesis advisor) / Nakaji, Peter (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2019
Description
With an increased demand for more enzyme-sensitive, bioresorbable and more biodegradable polymers, various studies of copolymers have been developed. Polymers are widely used in various applications of biomedical engineering such as in tissue engineering, drug delivery and wound healing. Depending on the conditions in which polymers are used, they are modified to accommodate a specific need. For instance, polymers used in drug delivery are more efficient if they are biodegradable. This ensures that the delivery system does not remain in the body after releasing the drug. It is therefore crucial that the polymer used in the drug system possess biodegradable properties. Such modification can be done in different ways including the use of peptides to make copolymers that will degrade in the presence of enzymes. In this work, we studied the effect of a polypeptide GAPGLL on the polymer NIPAAm and compare with the previously studied Poly(NIPAAm-co-GAPGLF). Both copolymers Poly(NIPAAm-co-GAPGLL) were first synthesized from Poly(NIPAAm-co-NASI) through nucleophilic substitution by the two peptides. The synthesis of these copolymers was confirmed by 1H NMR spectra and through cloud point measurement, the corresponding LCST was determined. Both copolymers were degraded by collagenase enzyme at 25 ° C and their 1H NMR spectra confirmed this process. Both copolymers were cleaved by collagenase, leading to an increase in solubility which yielded a higher LCST compared to before enzyme degradation. Future studies will focus on evaluating other peptides and also using other techniques such as Differential Scanning Microcalorimetry (DSC) to better observe the LCST behavior. Moreover, enzyme kinetics studies is also crucial to evaluate how fast the enzyme degrades each of the copolymers.
ContributorsUwiringiyimana, Mahoro Marie Chantal (Author) / Vernon, Brent (Thesis director) / Nikkhah, Mehdi (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This report provides information concerning qualities of methylcellulose and how those properties affect further experimentation within the biomedical world. Utilizing the compound’s biocompatibility many issues, ranging from surgical to cosmetic, can be solved. As of recent, studies indicate, methylcellulose has been used as a physically cross-linked gel, which cannot sustain a solid form within the body. Therefore, this report will ultimately explore the means of creating a non-degradable, injectable, chemically cross-linking methylcellulose- based hydrogel. Methylcellulose will be evaluated and altered in experiments conducted within this report and a chemical cross-linker, developed from Jeffamine ED 2003 (O,O′-Bis(2-aminopropyl) polypropylene glycol-block-polyethylene glycol-block-polypropylene glycol), will be created. Experimentation with these elements is outlined here, and will ultimately prompt future revisions and analysis.
ContributorsBundalo, Zoran Luka (Author) / Vernon, Brent (Thesis director) / LaBelle, Jeffrey (Committee member) / Overstreet, Derek (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05
Description
Rupture of intracranial aneurysms causes a subarachnoid hemorrhage, which is often lethal health event. A minimally invasive method of solving this problem may involve a material, which can be administered as a liquid and then becomes a strong solid within minutes preventing flow of blood in the aneurysm. Here we report on the development of temperature responsive copolymers, which are deliverable through a microcatheter at body temperature and then rapidly cure to form a highly elastic hydrogel. To our knowledge, this is the first physical-and chemical-crosslinked hydrogel capable of rapid crosslinking at temperatures above the gel transition temperature. The polymer system, poly(N-isopropylacrylamide-co-cysteamine-co-Jeffamine® M-1000 acrylamide) and poly(ethylene glycol) diacrylate, was evaluated in wide-neck aneurysm flow models to evaluate the stability of the hydrogels. Investigation of this polymer system indicates that the Jeffamine® M-1000 causes the gels to retain water, resulting in gels that are initially weak and viscous, but become stronger and more elastic after chemical crosslinking.
ContributorsLee, Elizabeth Jean (Author) / Vernon, Brent (Thesis director) / Brennecka, Celeste (Committee member) / Overstreet, Derek (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2013-05
Description
The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and time effectiveness. Theoretical data for the time to 60% drug release and the slope and intercept of the log-log plot were collected and subjected to statistical analysis in JMP. Since the scope of this project focuses on microparticle surface degradation drug release with no drug diffusion, the characteristic variables relating to the slope (n = diffusional release exponent) and the intercept (k = kinetic constant) do not directly apply to the distribution model within the scope of the research. However, these variables are useful for analysis when the Mathcad template is applied to other types of drug release models.
ContributorsHan, Priscilla (Author) / Vernon, Brent (Thesis director) / Nickle, Jacob (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Intraoperative diagnosis in neurosurgery has traditionally relied on frozen and formalin-fixed, paraffin-embedded section analysis of biopsied tissue samples. Although this technique is considered to be the “gold standard” for establishing a histopathologic diagnosis, it entails a number of significant limitations such as invasiveness and the time required for processing and interpreting the tissue. Rapid intraoperative diagnosis has become possible with a handheld confocal laser endomicroscopy (CLE) system. Combined with appropriate fluorescent stains or labels, CLE provides an imaging technique for real-time intraoperative visualization of histopathologic features of the suspected tumor and healthy tissues.
This thesis scrutinizes CLE technology for its ability to provide real-time intraoperative in vivo and ex vivo visualization of histopathological features of the normal and tumor brain tissues. First, the optimal settings for CLE imaging are studied in an animal model along with a generational comparison of CLE performance. Second, the ability of CLE to discriminate uninjured normal brain, injured normal brain and tumor tissues is demonstrated. Third, CLE was used to investigate cerebral microvasculature and blood flow in normal and pathological conditions. Fourth, the feasibility of CLE for providing optical biopsies of brain tumors was established during the fluorescence-guided neurosurgical procedures. This study established the optimal workflow and confirmed the high specificity of the CLE optical biopsies. Fifth, the feasibility of CLE was established for endoscopic endonasal approaches and interrogation of pituitary tumor tissue. Finally, improved and prolonged near wide-field fluorescent visualization of brain tumor margins was demonstrated with a scanning fiber endoscopy and 5-aminolevulinic acid.
These studies suggested a novel paradigm for neurosurgery-pathology workflow when the noninvasive intraoperative optical biopsies are used to interrogate the tissue and augment intraoperative decision making. Such optical biopsies could shorten the time for obtaining preliminary information on the histological composition of the tissue of interest and may lead to improved diagnostics and tumor resection. This work establishes a basis for future in vivo optical biopsy use in neurosurgery and planning of patient-related outcome studies. Future studies would lead to refinement and development of new confocal scanning technologies making noninvasive optical biopsy faster, convenient and more accurate.
This thesis scrutinizes CLE technology for its ability to provide real-time intraoperative in vivo and ex vivo visualization of histopathological features of the normal and tumor brain tissues. First, the optimal settings for CLE imaging are studied in an animal model along with a generational comparison of CLE performance. Second, the ability of CLE to discriminate uninjured normal brain, injured normal brain and tumor tissues is demonstrated. Third, CLE was used to investigate cerebral microvasculature and blood flow in normal and pathological conditions. Fourth, the feasibility of CLE for providing optical biopsies of brain tumors was established during the fluorescence-guided neurosurgical procedures. This study established the optimal workflow and confirmed the high specificity of the CLE optical biopsies. Fifth, the feasibility of CLE was established for endoscopic endonasal approaches and interrogation of pituitary tumor tissue. Finally, improved and prolonged near wide-field fluorescent visualization of brain tumor margins was demonstrated with a scanning fiber endoscopy and 5-aminolevulinic acid.
These studies suggested a novel paradigm for neurosurgery-pathology workflow when the noninvasive intraoperative optical biopsies are used to interrogate the tissue and augment intraoperative decision making. Such optical biopsies could shorten the time for obtaining preliminary information on the histological composition of the tissue of interest and may lead to improved diagnostics and tumor resection. This work establishes a basis for future in vivo optical biopsy use in neurosurgery and planning of patient-related outcome studies. Future studies would lead to refinement and development of new confocal scanning technologies making noninvasive optical biopsy faster, convenient and more accurate.
ContributorsBelykh, Evgenii (Author) / Preul, Mark C (Thesis advisor) / Vernon, Brent (Thesis advisor) / Nakaji, Peter (Committee member) / Stabenfeldt, Sarah E (Committee member) / Arizona State University (Publisher)
Created2020
Description
There is an increasing interest in developing thermo-responsive polymers for treating aneurysms. In this thesis project, the potential for poly(NIPAAm-co-JAAm-co-HEMA-Acrylate) (PNJHAc) as a treatment method for brain aneurysms was investigated. Five different batches of polymer were synthesized, purified, lyophilized, and characterized using nuclear magnetic resonance and cloud point techniques over the course of several months. Two were tested in aneurysm models. Of these five batches, there were two that showed promise as liquid embolic agents for endovascular embolization.
ContributorsLoui, Michelle (Author) / Vernon, Brent (Thesis director) / Pal, Amrita (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05