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The last 15 years have witnessed the development of modern infrared spectroscopy into a useful biodiagnostic tool for the analysis of cells, tissues, and body fluids. Dedicated technologies have evolved for rapidly discriminating between diverse microbial species and strains, testing single cells, and identifying various disease states in humans and animals, to give some examples.
Particularly interesting applications came up by means of light microscopes coupled to infrared spectrometers and the advent of dedicated infrared spectroscopic imaging instrumentation. Infrared microscopes equipped with modern focal plane array detectors allow nowadays routinely the parallel collection of thousands of pixel spectra across microscopic areas of biological samples. This imaging technology can be used for routine automatic histological segmentation and imaging of tissue structures without any requirement of dyes or molecular probes. Recent biomedical studies have proven that FT-IR imaging can be used to objectively differentiate benign from malignant histopathological structures in various tissues. Basically the same experimental set-up is also well suited to integrate the fundamental tasks of microbiological analysis, namely detection, enumeration, and differentiation of micro-organisms in one single apparatus.
Due to its high brilliance, IR-synchrotron light coupled into high-quality FT-IR microscopes has been used for spectral mapping of single cells at a spatial resolution near the diffraction limit of mid-infrared light. Using this technology, the accumulation of the pathogenic prion protein (PrPSc) in neuronal cells, to give an example, could be traced in situ by detecting deposition areas of the misfolded prion protein.
The problem of extracting the characteristic information from the typically very complex, fingerprint-like infrared signatures of biological samples is generally addressed by applying bioinformatic techniques such as factor-, cluster-, linear discriminant analysis, and artificial neural networks together with so-called feature extraction algorithms. Examples will be given on the characterization of micro-organisms, analysis of single eukaryotic cells, imaging of diseased human tissues, and disease recognition from body fluids that highlight the new possibilities of modern biomedical infrared spectroscopy.
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