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Description
Charlie Arntzen joined ASU in August 2000 as the Florence Ely Nelson Presidential Endowed Chair and retired in 2016 from the School of Life Sciences and Biodesign Institute. Charlie was the founding Director of the Biodesign Institute.
Important ASU stories include:
1) the creation of the Biodesign Institute,
2) the design and operation of the Biodesign labs,
3) the development of ZMapp to fight Ebola,
4) The New American University - a discussion of the importance of collaboration, and
5) several comments about Presidents Coor and Crow and Provost Glick
ContributorsChurch, Kathy (Interviewer) / Arizona State University Retirees Association (Producer)
Created2019-05-08
Description
The development of biosensing platforms not only has an immediate lifesaving effect but also has a significant socio-economic impact. In this dissertation, three very important biomarkers with immense importance were chosen for further investigation, reducing the technological gap and improving their sensing platform.Firstly, gold nanoparticles (AuNP) aggregation and sedimentation-based assays were developed for the sensitive, specific, and rapid detection of Ebola virus secreted glycoprotein (sGP)and severe acute respiratory syndrome coronavirus 2 (SARS-COV2) receptor-binding domain (RBD) antigens. An extensive study was done to develop a complete assay workflow from critical nanobody generation to optimization of AuNP size for rapid detection. A rapid portable electronic reader costing (<$5, <100 cm3), and digital data output was developed. Together with the developed workflow, this portable electronic reader showed a high sensitivity (limit of detection of ~10 pg/mL, or 0.13 pM for sGP and ~40 pg/mL, or ~1.3 pM for RBD in diluted human serum), a high specificity, a large dynamic range (~7 logs), and accelerated readout within minutes. Secondly, A general framework was established for small molecule detection using plasmonic metal nanoparticles through wide-ranging investigation and optimization of assay parameters with demonstrated detection of Cannabidiol (CBD). An unfiltered assay suitable for personalized dosage monitoring was developed and demonstrated. A portable electronic reader demonstrated optoelectronic detection of CBD with a limit of detection (LOD) of <100 pM in urine and saliva, a large dynamic range (5 logs), and a high specificity that differentiates closely related Tetrahydrocannabinol (THC). Finally, with careful biomolecular design and expansion of the portable reader to a dual-wavelength detector the classification of antibodies based on their affinity to SARS-COV2 RBD and their ability to neutralize the RBD from binding to the human Angiotensin-Converting Enzyme 2 (ACE2) was demonstrated with the capability to detect antibody concentration as low as 1 pM and observed neutralization starting as low as 10 pM with different viral load and variant. This portable, low-cost, and versatile readout system holds great promise for rapid, digital, and portable data collection in the field of biosensing.
ContributorsIkbal, Md Ashif (Author) / Wang, Chao (Thesis advisor) / Goryll, Michael (Committee member) / Zhao, Yuji (Committee member) / Wang, Shaopeng (Committee member) / Arizona State University (Publisher)
Created2022
Description
A mobile phone application was designed as part of an X-Prize challenge at Arizona State University (ASU). The team created an application that displays 4D visualization of time sensitive contagion data, specifically focusing on the Ebola Virus Disease. The application, named “Ebola Resource Decision Evaluator” (ERDE), is a tool to aid in resource allocation for decision-makers during epidemics and outbreaks. The predictive algorithm was based on the SIR Model—susceptible, infected, and recovered (or immune). We adapted this predictive model into our application to forecast weeks forward the Ebola incidence in three cities in the Democratic Republic of Congo (DRC).
The current 2D map used by the Center for Disease Control (CDC) displays only the number of deaths in a city caused by the outbreak. But, the cities differ in ways 2D cannot convey. We implemented the augmented reality (AR) aspect to give more meaning to data and to give decision-makers interactive 4D city-by-city comparisons. The outbreak is ongoing as of September 2019 and ASU has committed to hosting the application for other healthcare workers to use. The application incorporates the most recent data on the disease and updates to visualize how many are predicted to become infected given X units of vaccine. We are able to use the data and compare the effectiveness to other cities. After this collection of data, professionals would determine the most efficient action to take against the spread of the disease.
The current 2D map used by the Center for Disease Control (CDC) displays only the number of deaths in a city caused by the outbreak. But, the cities differ in ways 2D cannot convey. We implemented the augmented reality (AR) aspect to give more meaning to data and to give decision-makers interactive 4D city-by-city comparisons. The outbreak is ongoing as of September 2019 and ASU has committed to hosting the application for other healthcare workers to use. The application incorporates the most recent data on the disease and updates to visualize how many are predicted to become infected given X units of vaccine. We are able to use the data and compare the effectiveness to other cities. After this collection of data, professionals would determine the most efficient action to take against the spread of the disease.
ContributorsHu, Lawrence (Author) / Hall, Rick (Thesis director) / Johnson-Glenberg, Mina (Committee member) / Sanford School of Social and Family Dynamics (Contributor) / Edson College of Nursing and Health Innovation (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05