Micro-Raman spectroscopic study of thyroid tissues.

Thyroid carcinomas are the most common endocrine malignancy. Inconclusive results for the analysis of malignancies are an issue in the diagnosis of thyroid carcinomas; 20% of thyroid cancer diagnoses are indeterminate or suspicious, resulting in a surgical procedure without immediate need. The use of Raman spectroscopy may help improve the diagnosis of thyroid carcinoma. In this study, 30 thyroid samples, including normal thyroid, goiter and thyroid cancer, were analyzed by confocal Raman spectroscopy. Principal component analysis (PCA), linear discriminant analysis (LDA) with cross validation and binary logistic regression (BLR) analysis were applied to discriminate among tissues. Significant discrimination was observed, with a consistent rate of concordant pairs of 89.2% for normal thyroid versus cancer, 85.7% for goiter versus cancer and 80.6% for normal thyroid versus goiter using just the amide III region. Raman spectroscopy was thus proven to be an important and fast tool for the diagnosis of thyroid tissues. The spectral region of 1200-1400cm-1 discriminated normal versus goiter tissues despite the great similarity of these tissues.

DFT:B3LYP/3-21G theoretical insights on the confocal Raman experimental observations in skin dermis of healthy young, healthy elderly, and diabetic elderly women.

In the confocal Raman spectra of skin dermis, the band area in the spectral region of proline and hydroxyproline varies according to the age and health condition of the volunteers, classified as healthy young women, healthy elderly women, and diabetic elderly women. Another observation refers to the intensity variation and negative Raman shift of the amide I band. To understand these effects, we adopted a model system using the DFT/B3LYP:3-21G procedure, considering the amino acid chain formed by glycine, hydroxyproline, proline, and alanine, which interacts with two and six water molecules. Through these systems, polarizability variations were analyzed to correlate its values with the observed Raman intensities of the three groups of volunteers and to assign the vibrational spectra of the skin dermis. As a way to correlate other experimental trends, we propose a model of chemical reaction of water interchange between the bonding amino acids, in which water molecules are attached with glucose by hydrogen bonds. The theoretical results are in accordance with the observed experimental trends.

Statistical strategies to reveal potential vibrational markers for in vivo analysis by confocal Raman spectroscopy.

The analysis of biological systems by spectroscopic techniques involves the evaluation of hundreds to thousands of variables. Hence, different statistical approaches are used to elucidate regions that discriminate classes of samples and to propose new vibrational markers for explaining various phenomena like disease monitoring, mechanisms of action of drugs, food, and so on. However, the technical statistics are not always widely discussed in applied sciences. In this context, this work presents a detailed discussion including the various steps necessary for proper statistical analysis. It includes univariate parametric and nonparametric tests, as well as multivariate unsupervised and supervised approaches. The main objective of this study is to promote proper understanding of the application of various statistical tools in these spectroscopic methods used for the analysis of biological samples. The discussion of these methods is performed on a set of in vivo confocal Raman spectra of human skin analysis that aims to identify skin aging markers. In the Appendix, a complete routine of data analysis is executed in a free software that can be used by the scientific community involved in these studies.