Rapid, On-Site SARS-CoV‑2 Variant Detection and Differentiation Using GLAD-Pristine Silver Nanorod Arrays and Machine Learning-Enhanced SERS.

ABSTRACT: The rapid evolution of viruses like SARS-CoV-2 and its emerging variants requires advanced diagnostic techniques for effective pandemic management. This study introduces a machine learning (ML)-based surface-enhanced Raman scattering (SERS) methodology for the precise strains, substrains-based detection, and differentiation of SARS-CoV-2 in clinical nasopharyngeal swab samples. Pristine silver nanorod substrates fabricated using the glancing angle deposition method were used for the sensitive detection of the wildtype, kappa, delta, and omicron variants of SARS-CoV-2. Also, four different substrains of omicron strain (BA.1, BA.2, BA.5, and XBB) were detected and distinguished using the developed platform. A detection limit of around 100 pfu/mL was established for the 4 variants and 4 covar

SUBMITTER: Senapati S 

PROVIDER: S-EPMC12508963 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature