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Microcalcifications are an early mammographic sign of breast cancer and a target for stereotactic breast needle biopsy. Here, we develop and compare different approaches for developing Raman classification algorithms to diagnose invasive and in situ breast cancer, fibrocystic change and fibroadenoma that can be associated with microcalcifications. In this study, Raman spectra were acquired from tissue cores obtained from fresh breast biopsies and analyzed using a constituent-based breast model. Diagnostic algorithms based on the breast model fit coefficients were devised using logistic regression, C4.5 decision tree classification, k-nearest neighbor (k -NN) and support vector machine (SVM) analysis, and subjected to leave-one-out cross validation. The best performing algorithm was based on SVM analysis (with radial basis function), which yielded a positive predictive value of 100% and negative predictive value of 96% for cancer diagnosis. Importantly, these results demonstrate that Raman spectroscopy provides adequate diagnostic information for lesion discrimination even in the presence of microcalcifications, which to the best of our knowledge has not been previously reported.

Melanosomes are long lived organelles in retinal pigment epithelium cells and are primarily responsible for photoprotection. However, with aging or prolong light radiation, the function of melanosomes diminishes, which may be due to photobleaching of melanin pigments present in melanosomes. In this study, melanosomes were isolated from the retinal pigment epithelium cells and exposed to green light (532 nm), and the chemical changes were monitored using Raman microspectroscopy. Photochemical changes were recorded for different power levels and exposure times. The threshold power and the rate for irreversible photobleaching of melanosomes were calculated by fitting the experimental data with a proposed model.

Lead ions in solution interact strongly with human serum albumin and modify the properties and function of albumin molecules. In the present study, we used optical spectroscopic techniques to explore the binding sites of lead, present in albumin. Structural and chemical analysis of albumin molecules using fluorescence and Raman spectroscopy, predicted the modification of two major amino acids in albumin due to lead binding. No secondary structural changes are observed in the protein molecule, which is further confirmed using circular dichroism absorption measurements. The results indicate that loss of charge from the binding site of albumin by the charged lead ions, give rise to dipole interaction which acts as the major contributor to promote protein agglomeration. Stepwise formation of a protein cluster in the presence of a lead ion.