Developing a Flexible, Affinity-based, Electrochemical Sensing Platform Towards Multiplexed Detection of Apocrine and Eccrine Sweat Based Biomarkers; SLOCK: Sensor for Circadian Clock
| dc.contributor.advisor | Prasad, Shalini | |
| dc.contributor.advisor | Gupta, Gopal | |
| dc.contributor.committeeMember | Rodrigues, Danieli | |
| dc.contributor.committeeMember | Polk, Todd | |
| dc.contributor.committeeMember | Sirsi, Shashank | |
| dc.creator | Upasham, Sayali | |
| dc.date.accessioned | 2024-03-18T19:57:29Z | |
| dc.date.available | 2024-03-18T19:57:29Z | |
| dc.date.created | 2021-12 | |
| dc.date.issued | December 2021 | |
| dc.date.submitted | December 2021 | |
| dc.date.updated | 2024-03-18T19:57:30Z | |
| dc.description.abstract | Chronobiology is defined as the temporal fluctuations occurring in the human physiology due to the circadian cycle. These fluctuations are good indicators of the functioning of the HypothalamicPituitary-Adrenal axis (HPA axis) and can be tracked by using biomarkers: Cortisol and Dehydroepiandrosteron (DHEA). Low volume tracking systems are beneficial for patients exposed to chronic stress, patients suffering from endocrine conditions manifested by circadian disruption and act as a lifestyle monitoring tool. An estimate of 50-70 million Americans suffer from chronic sleep disorders (NHLBI, 2003) which hinders routine functioning and has deleterious health implications including elevated cortisol levels, increased risk of hypertension, diabetes, depression, cardiac conditions, and stroke. Currently available technologies for monitoring the circadian rhythm (e.g., Polysomnography (Ambulatory monitoring of nocturnal sleep) or Actigraphy (Multiday ambulatory assessment)) do not provide an accurate estimation of the extent of circadian disruption, as they are superficial. Biomarker assays are the diagnostic gold standard techniques used for the diagnosis of circadian dysregulation caused by adrenal disorders. These assays usually rely on the use of blood or serum and take about 3-4 hours for the test results which proves to be an ineffective solution, from the point of view of developing a circadian profile for the user. Adrenal steroids like cortisol and DHEA are expressed in sweat in the nanogram range and can be used as biomarkers to facilitate self-monitoring. SLOCK is a sweat based chronobiology tracking system that works on the principles of electrochemically transduced affinity-based systems. The sensor can detect cortisol and DHEA in the physiologically relevant ranges i.e., 8-200 ng/ml and 2-131 ng/ml respectively. The sensor was also tested through human subject-based studies and is able to capture rise and fall in biomarker levels on-body. In addition to this, the use of serpentine interdigitated electrodes provides mechanical stability when exposed to oscillations caused due to a wearable form factor. Based on the cross-reactivity studies, the response for target biomarkers is highly specific to the biomarker of interest. Towards the last part of this work, the SLOCK platform was tuned for detection of a protein biomarker, interleukin-31 (IL-31) for the purpose of creating a chronic disease diagnosis and management platform. The benchmarking for this was carried out by modelling it for detection of atopic dermatitis related flares. The platform is able to sensitively detect IL-31 over the dynamic range of 50-1000 pg/mL. The platform was successfully coupled with portable electronics and was able to record biomarker fluctuations on-body through human subject-based testing. The SLOCK platforms offers highly sensitive, non-invasive monitoring of circadian related or chronic disorders in a point-of-need setting. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | ||
| dc.identifier.uri | https://hdl.handle.net/10735.1/10068 | |
| dc.language.iso | en | |
| dc.subject | Engineering, Biomedical | |
| dc.title | Developing a Flexible, Affinity-based, Electrochemical Sensing Platform Towards Multiplexed Detection of Apocrine and Eccrine Sweat Based Biomarkers; SLOCK: Sensor for Circadian Clock | |
| dc.type | Thesis | |
| dc.type.material | text | |
| local.embargo.lift | 2023-12-01 | |
| local.embargo.terms | 2023-12-01 | |
| thesis.degree.college | School of Engineering and Computer Science | |
| thesis.degree.department | Biomedical Engineering | |
| thesis.degree.grantor | The University of Texas at Dallas | |
| thesis.degree.name | PHD |
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