Label-free detection and discrimination of respiratory pathogens based on electrochemical synthesis of biomaterials-mediated plasmonic composites and machine learning analysis.

ABSTRACT: Seasonal outbreaks of respiratory viral infections remain a global concern, with increasing morbidity and mortality rates recorded annually. Timely and false responses contribute to the widespread of respiratory pathogenic diseases owing to similar symptoms at an early stage and subclinical infection. The prevention of emerging novel viruses and variants is also a big challenge. Reliable point-of-care diagnostic assays for early infection diagnosis play a critical role in the response to threats of epidemics or pandemics. We developed a facile method for specifically identifying different viruses based on surface-enhanced Raman spectroscopy (SERS) with pathogen-mediated composite materials on Au nanodimple electrodes and machine learning (ML) analyses. Virus particles were trapped in three

SUBMITTER: Ansah IB 

PROVIDER: S-EPMC10165532 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature