Okhai, T.; Idris, A.; Feleni, U.; Snyman, L. Futuristic Silicon Photonic Biosensor with Nanomaterial Enhancement for PSA Detection. Preprints2024, 2024010560. https://doi.org/10.20944/preprints202401.0560.v1
APA Style
Okhai, T., Idris, A., Feleni, U., & Snyman, L. (2024). Futuristic Silicon Photonic Biosensor with Nanomaterial Enhancement for PSA Detection. Preprints. https://doi.org/10.20944/preprints202401.0560.v1
Chicago/Turabian Style
Okhai, T., Usisipho Feleni and Lukas Snyman. 2024 "Futuristic Silicon Photonic Biosensor with Nanomaterial Enhancement for PSA Detection" Preprints. https://doi.org/10.20944/preprints202401.0560.v1
Abstract
This article describes a novel electrochemical on-chip biosensor that utilizes anti-PSA antibody (Ab) and silver nanoparticles (AgNPs) to enhance the sensing and detection capability of prostate specific antigen (PSA) in the blood. The AgNPs are prepared, characterized, and applied onto a silicon photonic on-chip biosensing receptor platform designed to enhance the accurate detection of PSA. The AgNPs were synthesized by a chemical reduction method using silver nitrate (AgNO3) as the precursor. Transmission electron microscopy (TEM), selected area electron diffraction (SAED), energy dispersion X-ray spectroscopy (EDS), small angle X-ray scattering (SAXS), X-ray diffraction (XRD), and light microscopy were among the methods used in the characterization and analysis of the AgNPs. Each stage of the immunosensor fabrication was characterized using cyclic voltammetry. The proposed immunosensor was applied in the detection of PSA, a prostate cancer biomarker, with a high sensitivity and a limit of detection of 0.17 ng/mL over a linear concentration range of 2.5 to 11.0 ng/mL. The immunosensor displayed good stability and was selective in the presence of interfering species like immunoglobulin (Ig) in human serum, ascorbic acid (AA), and diclofenac (Dic). The detectivity and sensitivity are significantly higher than previous reports on similar or related technologies.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
