Mathematics – Logic
Scientific paper
Jun 1998
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1998aipc..430...96n&link_type=abstract
The eleventh international conference on fourier transform spectroscopy. AIP Conference Proceedings, Volume 430, pp. 96-109 (19
Mathematics
Logic
Infrared And Raman Spectroscopy
Scientific paper
FT-IR and FT-NIR Raman spectra of intact microbial, plant animal or human cells, tissues, and body fluids are highly specific, fingerprint-like signatures which can be used to discriminate between diverse microbial species and strains, characterize growth-dependent phenomena and cell-drug interactions, and differentiate between various disease states. The spectral information potentially useful for biomedical characterizations may be distributed over the entire infrared region of the electromagnetic spectrum, i.e. over the near-, mid-, and far-infrared. It is therefore a key problem how the characteristic vibrational spectroscopic information can be systematically extracted from the infrared spectra of complex biological samples. In this report these questions are addressed by applying factor and cluster analysis treating the classification problem of microbial infrared spectra as a model task. Particularly interesting applications arise by means of a light microscope coupled to the FT-IR spectrometer. FT-IR spectra of single microcolonies of less than 40 μm in diameter can be obtained from colony replica applying a stamping technique that transfers the different, spatially separated microcolonies from the culture plate to a special IR-sample holder. Using a computer controlled x,y-stage together with mapping and video techniques, the fundamental tasks of microbiological analysis, namely detection, enumeration, and differentiation of micro-organisms can be integrated in one single apparatus. Since high quality, essentially fluorescence free Raman spectra may now be obtained in relatively short time intervals on previously intractable biological specimens, FT-IR and NIR-FT-Raman spectroscopy can be used in tandem to characterize biological samples. This approach seems to open up new horizons for biomedical characterizations of complex biological systems.
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