Abstract
Schistosoma mansoni infection in mice has been fingerprinted using CE to study the capabilities of this technique as a diagnostic tool for this parasitic disease. Two modes of separation were used in generating the electrophoretic data, with each untreated urine sample the following methods were applied: (i) a fused-silica capillary, operating with an applied potential of 18 kV, in micellar EKC (MEKC) and (ii) a polyacrylamide-coated capillary, operating with an applied potential of -20 kV under zonal CZE conditions. By combining normal and reverse polarities in the data treatment we have extracted more information from the samples, which is a better approach for CE metabolomics. The traditional problems associated with variability in electrophoretic peak migration times for analytes were countered by using a dynamic programming algorithm for the electropherograms alignment. Principal component analyses of these aligned electropherograms and partial least square discriminant analysis (PLS-DA) data are shown to provide a valuable means of rapid and sample classification. This approach may become an important tool for the identification of biomarkers, diagnosis and disease surveillance.
| Original language | English |
|---|---|
| Pages (from-to) | 3201-3206 |
| Number of pages | 6 |
| Journal | Electrophoresis |
| Volume | 29 |
| Issue number | 15 |
| DOIs | |
| Publication status | Published - Aug 2008 |
| Externally published | Yes |
Keywords
- Biomarkers
- Diagnosis
- Metabolomics
- Metabonomics
- Pattern recognition
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