Near-infrared Raman Microspectroscopy Research Articles

Raman spectroscopy coupled with advanced statistics for differentiating menstrual and peripheral blood

Body fluids are a common and important type of forensic evidence. In particular, the identification of menstrual blood stains is often a key step during the investigation of rape cases. Here, we report on the application of near-infrared Raman microspectroscopy for differentiating menstrual blood from peripheral blood. We observed that the menstrual and peripheral blood samples have similar but distinct Raman spectra. Advanced statistical analysis of the multiple Raman spectra that were automatically (Raman mapping) acquired from the 40 dried blood stains (20 donors for each group) allowed us to build classification model with maximum (100%) sensitivity and specificity. We also demonstrated that despite certain common constituents, menstrual blood can be readily distinguished from vaginal fluid. All of the classification models were verified using cross-validation methods. The proposed method overcomes the problems associated with currently used biochemical methods, which are destructive, time consuming and expensive.

Near-infrared Raman Microspectroscopy Detects High-risk Human Papillomaviruses

BACKGROUND: Detecting human papillomaviruses (HPVs) infection in cervical cells is an exceedingly important part of the clinical management of cervical dysplasia. Current guidelines in women's health outline the need for both the Papanicolaou test as well as high-risk HPV testing. Testing for HPV is expensive, is time-consuming, and requires experienced technicians. METHODS: Two sets of near-infrared Raman microspectroscopy experiments were conducted using a Raman confocal microscope system. First, Raman spectra were acquired from four different cell culture lines, two positive for HPV (HeLa, SiHa), one negative for HPV, but malignant (C33A), and one normal, HPV-negative line (NHEK). The three malignant lines were all derived from cervical cells. Second, Raman spectra were acquired from deidentified patient samples that were previously tested for the presence of high-risk HPV. RESULTS: The spectra from the cell culture lines and the patient samples contained many statistically significant differences. Using sparse multinomial logistic regression to classify the data led to classification accuracies of 89% to 97% for the cell culture samples and 98.5% for the patient samples. CONCLUSIONS: Raman micro-spectroscopy can be used to detect HPV and differentiate among specific HPV strains. This technique may provide health providers with a new method for quickly testing cell samples for the presence of HPV.

Raman Spectroscopic Analysis of Gunshot Residue Offering Great Potential for Caliber Differentiation

Near-infrared (NIR) Raman microspectroscopy combined with advanced statistics was used to differentiate gunshot residue (GSR) particles originating from different caliber ammunition. The firearm discharge process is analogous to a complex chemical reaction. The reagents of this process are represented by the chemical composition of the ammunition, firearm, and cartridge case. The specific firearm parameters determine the conditions of the reaction and thus the subsequent product, GSR. We found that Raman spectra collected from these products are characteristic for different caliber ammunition. GSR particles from 9 mm and 0.38 caliber ammunition, collected under identical discharge conditions, were used to demonstrate the capability of confocal Raman microspectroscopy for the discrimination and identification of GSR particles. The caliber differentiation algorithm is based on support vector machines (SVM) and partial least squares (PLS) discriminant analyses, validated by a leave-one-out cross-validation method. This study demonstrates for the first time that NIR Raman microspectroscopy has the potential for the reagentless differentiation of GSR based upon forensically relevant parameters, such as caliber size. When fully developed, this method should have a significant impact on the efficiency of crime scene investigations.

Raman microspectroscopy for skin cancer detection in vitro

We investigate the potential of near-infrared Raman microspectroscopy to differentiate between normal and malignant skin lesions. Thirty-nine skin tissue samples consisting of normal, basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma from 39 patients were investigated. Raman spectra were recorded at the surface and at 20-microm intervals below the surface for each sample, down to a depth of at least 100 microm. Data reduction algorithms based on the nonlinear maximum representation and discrimination feature (MRDF) and discriminant algorithms using sparse multinomial logistic regression (SMLR) were developed for classification of the Raman spectra relative to histopathology. The tissue Raman spectra were classified into pathological states with a maximal overall sensitivity and specificity for disease of 100%. These results indicate the potential of using Raman microspectroscopy for skin cancer detection and provide a clear rationale for future clinical studies.