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Observed spectra normally contain spurious features along with those of interest and it is common practice to employ one of several available algorithms to remove the unwanted components. Low frequency spurious components are often referred to as 'baseline', 'background', and/or 'background noise'. Here we examine a cross-section of non-instrumental methods designed to remove background features from spectra; the particular methods considered here represent approaches with different theoretical underpinnings. We compare and evaluate their relative performance based on synthetic data sets designed to exemplify vibrational spectroscopic signals in realistic contexts and thereby assess their suitability for computer automation. Each method is presented in a modular format with a concise review of the underlying theory, along with a comparison and discussion of their strengths, weaknesses, and amenability to automation, in order to facilitate the selection of methods best suited to particular applications.

Blood is a bodily fluid that is vital for a number of life functions in animals. To a first approximation, blood is a mildly alkaline aqueous fluid (plasma) in which a large number of free-floating red cells (erythrocytes), white cells (leucocytes), and platelets are suspended. The primary function of blood is to transport oxygen from the lungs to all the cells of the body and move carbon dioxide in the return direction after it is produced by the cells' metabolism. Blood also carries nutrients to the cells and brings waste products to the liver and kidneys. Measured levels of oxygen, nutrients, waste, and electrolytes in blood are often used for clinical assessment of human health. Raman spectroscopy is a nondestructive analytical technique that uses the inelastic scattering of light to provide information on chemical composition, and hence has a potential role in this clinical assessment process. Raman spectroscopic probing of blood components and of whole blood has been on-going for more than four decades and has proven useful in applications ranging from the understanding of hemoglobin oxygenation, to the discrimination of cancerous cells from healthy lymphocytes, and the forensic investigation of crime scenes. In this paper, we review the literature in the field, collate the published Raman spectroscopy studies of erythrocytes, leucocytes, platelets, plasma, and whole blood, and attempt to draw general conclusions on the state of the field.

Raman microspectroscopy is an attractive approach for chemical imaging of biological specimens, including live cells, without the need for chemi-selective stains. Using a microspectrometer, near-infrared Raman spectra throughout the range 663 cm(-1) to 1220 cm(-1) were obtained from colonies of CA1 human embryonic stem cells (hESCs) and CA1 cells that had been stimulated to differentiate for 3 weeks by 10% fetal bovine serum on gelatin. Distributions and intensities of spectral bands attributed to proteins varied significantly between undifferentiated and differentiated cells. Importantly, compared to proteins and lipids, the band intensities of nucleic acids were dominant in undifferentiated cells with a dominance-reversal in differentiated cells. Thus, we could identify intensity ratios of particular protein-related bands (e.g., 757 cm(-1) tryptophan) to nucleic acid bands (784 cm(-1) DNA/RNA composite) that were effective in discriminating between spectra of undifferentiated and differentiated cells. We observed no discernible negative effects due to the laser exposure in terms of morphology, proliferation, or pluripotency of the stem cells. We conclude that Raman microscopy and complementary data processing procedures provide a rapid, noninvasive approach that can distinguish hESCs from differentiated cells. This is the first report to identify specific Raman markers for the differentiation status of hESCs.