Abstract

Globally, hepatitis C virus (HCV) infection is the leading cause for liver related morbidity and mortality. Mortality rate linked with HCV can be effectively lowered by prompt and early diagnosis. In this research work, we aimed to evaluate the potential of attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy to discriminate healthy sera samples from HCV infected freeze-dried sera samples in order to develop a new and quick reagent free diagnostic tool. Clear variation was observed between the ATR-FTIR spectra of 87 HCV infected and 83 healthy freeze-dried sera samples. Major variation was observed in the two spectral regions i.e., 3500–2800 and 1800–900 cm−1. Multivariate classification algorithms including principal component analysis (PCA) and linear discriminant analysis (LDA) were used. PCA scatter plot of first two PCs showed 97% variation between the two sample classes. When the four PCs were projected to the LDA algorithm for developing PCA-LDA diagnostic model it discriminated the HCV and healthy classes with 100% accuracy. This study provides an initial insight on the potential to use ATR-FTIR spectroscopy in conjugation with multivariate data classification tools for effective HCV diagnosis.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.