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FTIR Microspectroscopy Coupled with Two-Class Discrimination Segregates Markers Responsible for Inter- and Intra-Category Variance in Exfoliative Cervical Cytology
- Source :
- Biomarker Insights, Vol 3 (2008)
- Publication Year :
- 2008
- Publisher :
- SAGE Publishing, 2008.
-
Abstract
- Infrared (IR) absorbance of cellular biomolecules generates a vibrational spectrum, which can be exploited as a “biochemical fingerprint” of a particular cell type. Biomolecules absorb in the mid-IR (2–20 μm) and Fourier-transform infrared (FTIR) microspectroscopy applied to discriminate different cell types (exfoliative cervical cytology collected into buffered fixative solution) was evaluated. This consisted of cervical cytology free of atypia (i.e. normal; n = 60), specimens categorised as containing low-grade changes (i.e. CIN1 or LSIL; n = 60) and a further cohort designated as high-grade (CIN2/3 or HSIL; n = 60). IR spectral analysis was coupled with principal component analysis (PCA), with or without subsequent linear discriminant analysis (LDA), to determine if normal versus low-grade versus high-grade exfoliative cytology could be segregated. With increasing severity of atypia, decreases in absorbance intensity were observable throughout the 1,500 cm –1 to 1,100 cm –1 spectral region; this included proteins (1,460 cm –1 ), glycoproteins (1,380 cm –1 ), amide III (1,260 cm –1 ), asymmetric (ν as ) PO 2 – (1,225 cm –1 ) and carbohydrates (1,155 cm –1 ). In contrast, symmetric (ν s ) PO 2 – (1,080 cm –1 ) appeared to have an elevated intensity in high-grade cytology. Inter-category variance was associated with protein and DNA conformational changes whereas glycogen status strongly influenced intra-category. Multivariate data reduction of IR spectra using PCA with LDA maximises inter-category variance whilst reducing the influence of intra-class variation towards an objective approach to class cervical cytology based on a biochemical profile.
- Subjects :
- Medicine (General)
R5-920
Subjects
Details
- Language :
- English
- ISSN :
- 11772719
- Volume :
- 3
- Database :
- Directory of Open Access Journals
- Journal :
- Biomarker Insights
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.8a5a0465e641d4be322e654360e8fd
- Document Type :
- article
- Full Text :
- https://doi.org/10.4137/BMI.S592