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- All Subjects: Biomedical Engineering
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Description
Demand for biosensor research applications is growing steadily. According to a new report by Frost & Sullivan, the biosensor market is expected to reach $14.42 billion by 2016. Clinical diagnostic applications continue to be the largest market for biosensors, and this demand is likely to continue through 2016 and beyond. Biosensor technology for use in clinical diagnostics, however, requires translational research that moves bench science and theoretical knowledge toward marketable products. Despite the high volume of academic research to date, only a handful of biomedical devices have become viable commercial applications. Academic research must increase its focus on practical uses for biosensors. This dissertation is an example of this increased focus, and discusses work to advance microfluidic-based protein biosensor technologies for practical use in clinical diagnostics. Four areas of work are discussed: The first involved work to develop reusable/reconfigurable biosensors that are useful in applications like biochemical science and analytical chemistry that require detailed sensor calibration. This work resulted in a prototype sensor and an in-situ electrochemical surface regeneration technique that can be used to produce microfluidic-based reusable biosensors. The second area of work looked at non-specific adsorption (NSA) of biomolecules, which is a persistent challenge in conventional microfluidic biosensors. The results of this work produced design methods that reduce the NSA. The third area of work involved a novel microfluidic sensing platform that was designed to detect target biomarkers using competitive protein adsorption. This technique uses physical adsorption of proteins to a surface rather than complex and time-consuming immobilization procedures. This method enabled us to selectively detect a thyroid cancer biomarker, thyroglobulin, in a controlled-proteins cocktail and a cardiovascular biomarker, fibrinogen, in undiluted human serum. The fourth area of work involved expanding the technique to produce a unique protein identification method; Pattern-recognition. A sample mixture of proteins generates a distinctive composite pattern upon interaction with a sensing platform consisting of multiple surfaces whereby each surface consists of a distinct type of protein pre-adsorbed on the surface. The utility of the "pattern-recognition" sensing mechanism was then verified via recognition of a particular biomarker, C-reactive protein, in the cocktail sample mixture.
ContributorsChoi, Seokheun (Author) / Chae, Junseok (Thesis advisor) / Tao, Nongjian (Committee member) / Yu, Hongyu (Committee member) / Forzani, Erica (Committee member) / Arizona State University (Publisher)
Created2011
Description
The world of healthcare can be seen as dynamic, often an area where technology and science meet to consummate a greater good for humanity. This relationship has been working well for the last century as evident by the average life expectancy change. For the greater of the last five decades the average life expectancy at birth increased globally by almost 20 years. In the United States specifically, life expectancy has grown from 50 years in 1900 to 78 years in 2009. That is a 76% increase in just over a century. As great as this increase sounds for humanity it means there are soon to be real issues in the healthcare world. A larger older population will need more healthcare services but have fewer young professionals to provide those services. Technology and science will need to continue to push the boundaries in order to develop and provide the solutions needed to continue providing the aging world population sufficient healthcare. One solution sure to help provide a brighter future for healthcare is mobile health (m-health). M-health can help provide a means for healthcare professionals to treat more patients with less work expenditure and do so with more personalized healthcare advice which will lead to better treatments. This paper discusses one area of m-health devices specifically; human breath analysis devices. The current laboratory methods of breath analysis and why these methods are not adequate for common healthcare practices will be discussed in more detail. Then more specifically, mobile breath analysis devices are discussed. The topic will encompass the challenges that need to be met in developing such devices, possible solutions to these challenges, two real examples of mobile breath analysis devices and finally possible future directions for m-health technologies.
ContributorsLester, Bryan (Author) / Forzani, Erica (Thesis advisor) / Xian, Xiaojun (Committee member) / Trimble, Steve (Committee member) / Arizona State University (Publisher)
Created2012
Description
Chimeric antigen receptor (CAR)-T cell therapy is a type of cancer immunotherapy has shown promising results in engineering the T cells which targets a specific antigen. Despite their success rate, there are certain limitations to the use of CAR-T therapies that includes cytokine release syndrome (CRS), neurologic toxicity, lack of response in approximately 50% of treated patients, monitoring of patients treated with CAR-T therapy. However, rapid point- of- care testing helps in quantifying the circulating CAR T cells and can enhance the safety of patients, minimize the cost of CAR-T cell therapy, and ease the management process. Currently, the standard method to quantify CAR-T cell in patient blood samples are flow cytometry and quantitative polymerase chain reaction (qPCR). But these techniques are expensive and are not easily accessible and suitable for point- of- care testing to assist real- time clinical decisions. To overcome these hurdles, here I propose a solution to these problems by rapid optical imaging (ROI)- based principle to monitor and detect CAR-T cells. In this project, a microfluidic device is developed and integrated with two functions: (1) Centrifuge free, filter- based separation of white blood cells and plasma; (2) Optical imaging- based technique for digital counting of CAR T- cells. Here, I carried out proof- of- concept test on the laser cut prototype microfluidic chips as well as the surface chemistry for specific capture of CAR-T cells. These data show that the microfluidic chip can specifically capture CAR-T positive cells with concentration dependent counts of captured cells. Further development of the technology could lead to a new tool to monitor the CAR-T cells and help the clinicians to effectively measure the efficacy of CAR-T therapy treatment in a faster and safer manner.
ContributorsElanghovan, Praveena (Author) / Wang, Shaopeng (Thesis advisor) / Forzani, Erica (Committee member) / Nikkhah, Mehdi (Committee member) / Arizona State University (Publisher)
Created2023
Description
Non-invasive biosensors enable rapid, real-time measurement and quantification of biological processes, such as metabolic state. Currently, the most accurate metabolic sensors are invasive, and significant cost is required, with few exceptions, to achieve similar accuracy using non-invasive methods. This research, conducted within the Biodesign Institute Center for Bioelectronics and Biosensors, leverages the selective reactivity of a chemical sensing solution to develop a sensor which measures acetone in the breath for ketosis and ketoacidosis diagnostics, which is relevant to body weight management and type I diabetes. The sensor displays a gradient of color changes, and the absorbance change is proportional to the acetone concentration in the part- per-million range, making applicable for detection ketosis and ketoacidosis in human breath samples. The colorimetric sensor response can be fitted to a Langmuir-like model for sensor calibration. The sensors best performance comes with turbulent, continuous exposure to the samples, rather than batch sample exposure. With that configuration, these novel sensors offer significant improvements to clinical and at- home measurement of ketosis and ketoacidosis.
ContributorsDenham, Landon (Author) / Forzani, Erica (Thesis advisor) / Wang, Shaopeng (Committee member) / Kulick, Doina (Committee member) / Arizona State University (Publisher)
Created2023
Description
Extracellular vesicles (EVs) are membranous particles that are abundantly secreted in the circulation system by most cells and can be found in most biological fluids. Among different EV subtypes, exosomes are small particles (30 – 150 nm) that are generated through the double invagination of the lipid bilayer membrane of cell. Therefore, they mirror the cell membrane proteins and contain proteins, RNAs, and DNAs that can represent the phenotypic state of their cell of origin, hence considered promising biomarker candidates. Importantly, in most pathological conditions, such as cancer and infection, diseased cells secrete more EVs and the disease associated exosomes have shown great potential to serve as biomarkers for early diagnosis, disease staging, and treatment monitoring. However, using EVs as diagnostic or prognostic tools in the clinic is hindered by the lack of a rapid, sensitive, purification-free technique for their isolation and characterization. Developing standardized assays that can translate the emerging academic EV biomarker discoveries to clinically relevant procedures is a bottleneck that have slowed down advancements in medical research. Integrating widely known immunoassays with plasmonic sensors has shown the promise to detect minute amounts of antigen present in biological sample, based on changes of ambient optical refractive index, and achieve ultra-sensitivity. Plasmonic sensors take advantage of the enhanced interaction of electromagnetic radiations with electron clouds of plasmonic materials at the dielectric-metal interface in tunable wavelengths.
ContributorsAmrollahi, Pouy (Author) / Wang, Xiao (Thesis advisor) / Forzani, Erica (Committee member) / Hu, Tony Ye (Committee member) / Arizona State University (Publisher)
Created2020