Classification model based on Raman spectra of selected morphological and biochemical tissue constituents for identification of atherosclerosis in human coronary arteries

This study presents the results of Raman spectroscopy applied to the classification of arterial tissue based on a simplified model using basal morphological and biochemical information extracted from the Raman spectra of arteries. The Raman spectrograph uses an 830-nm diode laser, imaging spectrograph, and a CCD camera. A total of 111 Raman spectra from arterial fragments were used to develop the model, and those spectra were compared to the spectra of collagen, fat cells, smooth muscle cells, calcification, and cholesterol in a linear fit model. Non-atherosclerotic (NA), fatty and fibrous-fatty atherosclerotic plaques (A) and calcified (C) arteries exhibited different spectral signatures related to different morphological structures presented in each tissue type. Discriminant analysis based on Mahalanobis distance was employed to classify the tissue type with respect to the relative intensity of each compound. This model was subsequently tested prospectively in a set of 55 spectra. The simplified diagnostic model showed that cholesterol, collagen, and adipocytes were the tissue constituents that gave the best classification capability and that those changes were correlated to histopathology. The simplified model, using spectra obtained from a few tissue morphological and biochemical constituents, showed feasibility by using a small amount of variables, easily extracted from gross samples.

Transcriptional Response of Peripheral Lymphocytes to Early Fibrosarcoma: A Model System for Cancer Detection Based on Hybridization Signatures

Since circulating leukocytes, mainly B and T cells, continuously maintain vigilant and comprehensive immune surveillance, these cells could be used as reporters for signs of infection or other pathologies, including cancer. Activated lymphocyte clones trigger a sensitive transcriptional response, which could be identified by gene expression profiling. To assess this hypothesis, we conducted microarray analysis of the gene expression profile of lymphocytes isolated from immunocompetent BALB/c mice subcutaneously injected with different numbers of tumorigenic B61 fibrosarcoma cells. Flow cytometry demonstrated that the number of circulating T (CD3(+)CD4(+) or CD3(+)CD8(+)) or B (CD19(+)) cells did not change. However, the lymphocytes isolated from tumor cell-injected animals expressed a unique transcriptional profile that was identifiable before the development of a palpable tumor mass. This finding demonstrates that the transcriptional response appears before alterations in the main lymphocyte subsets and that the gene expression profile of peripheral lymphocytes can serve as a sensitive and accurate method for the early detection of cancer. Exp Biol Med 234:802-812, 2009