Download

Download Full Text (899 KB)

Description

Human plasma presents as a complex biological matrix that can serve as a valuable source for biomarkers that can help us study health and wellness.Beginning with the plasma samples, a kit was used to further enhance the specimen. This resulted in having a supernatant which was collected and further investigated in our research. The supernatants were divided up with the control set and a treated set. The treated set had two sets of results. The younger cells were injected with a SDH activator, while the older cells were injected with a SDH inhibitor. Using the data from the PARAFAC to explain the difference between samples and show how much NADPH is present with each result, which helps us see the differences between the controlled and the tested cells. Fluorescence measurements, excitation-emission matrices (EEMs), were collected from various samples. To deconvolute the complex makeup of signals, we then applied Parallel Factor analysis (PARAFAC) to the EEM data. This allowed us to isolate signals of several fluorescent components. Finally, the results and findings are benchmarked against previous studies on supernatants, and some of the calculated components are attributed to chemical species such as Tyrosine and NADH. This dataset was made up of subjects varying in age and our analysis examines differences and trends in the dataset between different types of subjects.

Publication Date

4-30-2026

Keywords

Autofluorescence, plasma, computation

Observing Fluorescent Biomarker Differences in Subjects of Varying Age

Share

COinS