Fourier transform infrared (FTIR) microspectroscopy has been applied to a study of prostate cancer cell lines derived from different metastatic sites and to tissue from benign prostate and Gleason-graded malignant prostate tissue. Paraffin-embedded tissue samples were analysed by FTIR, after mounting onto a BaF(2) plate and subsequent removal of wax using Citroclear followed by acetone. Cell lines were analysed as aliquots of cell suspension held between two BaF(2) plates. It was found that the ratio of peak areas at 1030 and 1080 cm(-1), corresponding to the glycogen and phosphate vibrations respectively, suggests a potential method for the differentiation of benign from malignant cells. The use of this ratio in association with FTIR spectral imaging provides a basis for estimating areas of malignant tissue within defined regions of a specimen. Initial chemometric treatment of FTIR spectra, using the linear discriminant algorithm, demonstrates a promising method for the classification of benign and malignant tissue and the separation of Gleason-graded CaP spectra. Using the principle component analysis, this study has achieved for the first time the separation of FTIR spectra of prostate cancer cell lines derived from different metastatic sites.

Analysis of the static time-of-flight secondary ion mass spectrometry (ToF-SIMS) spectra of adsorbed protein films is reported using principal component analysis (PCA) and a novel artificial neural network (ANN) approach, NeuroSpectraNet, to classify chemically the spectra of the protein films. The ease of application and the efficiency with which each approach classified positive ion spectra from adsorbed films of 13 different proteins is reported and assessed. The ToF-SIMS spectra of adsorbed protein films are especially difficult to analyze owing to the absence of unique peaks in the spectra of different proteins. Although PCA was able to differentiate successfully ToF-SIMS spectra of adsorbed protein films using the ions generated from the fragmentation of the amino acids, differentiation of the spectra using the entire spectrum was unsuccessful. Outliers in several of the protein groups make classification of unknown spectra difficult, despite the use of only amino-acid-specific ions. However, NeuroSpectraNet successfully classified the spectra from 11 of the protein films using the whole positive ion spectra after a vector analysis enhancement had been incorporated into the neural network. Full classification of all 13 proteins was achieved by using the combined positive and negative ion spectra. However, as with PCA, ANN classification was enhanced when the input patterns only contained amino-acid-specific ions. The complex and multivariate nature of static SIMS spectra is a domain well suited to the application of neural networks for pattern recognition and classification.

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The polymer surface compositions of some polyesters of importance in biomaterial science and advanced drug delivery have been examined by x-ray photoelectron spectroscopy (XPS) and static secondary ion mass spectrometry (SSIMS). The XPS results show good quantitative stoichiometric correlation with the known chemical composition of the polyesters. The SIMS spectra show systematic fragmentation patterns in both positive and negative ion modes for the series of structurally related polymers. Evidence for the presence of radical cation formation in SIMS is presented. Comparison between the SIMS spectra of poly-glycolic acid and ply-lactic acid and the pyrolysis mass spectra of these polymers are made, and conclusions drawn on the different mechanisms of fragmentation. The combined application of SSIMS and XPS is shown to give a highly detailed analysis of these polyesters.

A series of colloids based on poly(styrene) were prepared by emulsion copolymerization with various proportions of methacrylic acid. X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) were used to monitor changes in particle surface composition and indicated a substantial enrichment of the methacrylic acid component. Further evidence for the presence of carboxyl groups at the particle surfaces was provided by electrophoretic mobility measurements, which showed a marked increase over the pH range studied.