ABSTRACT
The large mid-infrared absorption coefficient of water frequently hampers the rapid, label-free infrared microscopy of biological objects in their natural aqueous environment. However, the high spectral power density of quantum cascade lasers is shifting this limitation such that mid-infrared absorbance images can be acquired in situ within signal-to-noise ratios of up to 100. Even at sample thicknesses well above 50 µm, signal-to-noise ratios above 10 are readily achieved. The quantum cascade laser-based microspectroscopy of aqueous media is exemplified by imaging an aqueous yeast solution and quantifying glucose consumption, ethanol generation as well as the production of carbon dioxide gas during fermentation.
Subject(s)
Infrared Rays , Lasers, Semiconductor , Microscopy/instrumentation , Microscopy/methods , Water/chemistry , Carbon Dioxide/metabolism , Ethanol/metabolism , Fermentation , Glucose/metabolism , Saccharomyces cerevisiae/metabolism , Signal-To-Noise Ratio , Water/metabolismABSTRACT
Changes in the volume covered by mucin-secreting goblet cell regions within colon thin sections may serve as a means to differentiate between ulcerative colitis and infectious colitis. Here we show that rapid, quantum cascade laser-based mid-infrared microspectroscopy might be able to contribute to the differential diagnosis of colitis ulcerosa, an inflammatory bowel disease. Infrared hyperspectral images of mouse colon thin sections were obtained within 7.5 minutes per section with a pixel size of 3.65 × 3.65 µm(2) and a field of view of 2.8 × 3.1 mm(2). The spectra were processed by training a random decision forest classifier on the basis of k-means clustering on one thin section. The trained algorithm was then applied to 5 further thin sections for a blinded validation and it was able to identify goblet cells in all sections. The rapid identification of goblet cells within these unstained, paraffinized thin sections of colon tissue was enabled by the high content of glycopeptides within the goblet cells as revealed by the pronounced spectral signatures in the 7.6 µm-8.6 µm and the 9.2 µm-9.7 µm wavelength ranges of the electromagnetic spectrum. More so, the simple calculation of the ratio between the absorbance values at 9.29 µm and 8.47 µm provides the potential to further shorten the time for measurement and analysis of a thin section down to well below 1 minute.
