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We propose a method for predicting the concentration of a functional ingredient, procyanidin, in apple using Raman spectroscopy in combination with multivariate calibration analysis. A regression model was constructed by partial least-squares (PLS) regression using the collected Raman spectra and the procyanidin concentrations measured by high-performance liquid chromatography (HPLC). Four different preprocessing algorithms—baseline correction, noise removal, averaging, and multiplicative scatter correction—were applied to the acquired Raman spectra. HPLC was used to determine the procyanidin concentrations in the edible part of apple specimens. The PLS regression model predicted the procyanidin concentration in apple with a coefficient of determination of 0.74, a root-mean-square error of calibration of 7.09 µg/g, and a root-mean-square error of prediction of 14.89 µg/g. In addition, the spectra of the carotenoid pigments were observed from the factors extracted from the PLS analysis. Consequently, we found that the procyanidin concentration in apple can be predicted using Raman spectroscopy measurements of carotenoid pigments of apple peel. Compared with conventional destructive measurements, Raman spectroscopy with the aid of multivariate analysis shows strong potential for the rapid and nondestructive quantitative analysis of procyanidin in apples.

A miniaturized Raman endoscope (mRE) system was employed to study the effects of anticancer treatment on colorectal tumors in a live murine model. The endoscope is narrow enough to observe the inside of the mouse colon under anesthesia. It has a channel for a ball lens mounted on a hollow fiber Raman probe (BHRP) to measure any targeted point under the visual control of the endoscope. Colorectal cancer tissue was observed to study the alterations of the tissue in response to anticancer drug treatment. Three anticancer drugs, 5-fluorouracil (5-FU), cisplatin (CDDP), and docetaxel, were employed. Although no alteration was recognized in the endoscopic visual observations at 2 weeks after the drug treatment, the Raman spectra obtained in the live mouse colon indicated that molecular changes of lipids and proteins were observed. This study demonstrates that in situ Raman analysis is highly sensitive for detecting the effects of anticancer drugs.

Egg or embryo quality is typically assessed by viewing the egg morphology and by observing the cleavage rate of the embryo. Assessment of egg or embryo quality based on bio-molecular information might lead to improved outcomes for aquaculture or in vitro fertilization (IVF) treatments. To assess the egg quality, we performed Raman spectroscopy on fish eggs from the Japanese medaka (Oryzias latipes). Good classification results from the yolk were obtained using principal component analysis (PCA) and linear discrimination analysis (LDA). The results show that the supply of oil energy starts immediately after fertilization and embryogenesis is initiated. The presence or absence of fertilization can be evaluated by fatty acid Raman bands with 95.7% accuracy. The Raman results show that the key factors that indicate the viability of fish eggs are amino acid production and carotenoid pigment deposition. The LDA algorithm based on the Raman bands of these substances indicates whether the development is normal or abnormal with 80.3% accuracy. These results show that Raman spectroscopy can be a powerful tool for non-invasive assessment and real time monitoring of fish egg quality and viability.

Virus infection of a human cell was determined only 3 h after invagination. We used viral vector Ad-CMV-control (AdC), which lacks the E1 gene coding for early polypeptide 1 (E1). AdC can replicate in human embryonic kidney 293 (HEK293) cells into which the E1 gene has been transfected. According to partial least-square regression discriminant analysis, it was assumed that two kinds of reaction take place in the cell during viral invasion. The first response of the cell was determined 3 h after the virus invasion, and the second one was determined ∼9 h later. The first one seems to be due to compositional changes in DNA. Analysis of large-scale datasets strongly indicated that the second reaction can be attributed to a reduction in protein concentration or uptake of phenylalanine into the nucleus.

Esophageal cancer is a disease with high mortality. In order to improve the 5 year survival rate after cancer treatment, it is important to develop a method for early detection of the cancer and for therapy support. There is increasing evidence that Raman spectroscopy, in combination with chemometric analysis, is a powerful technique for discriminating pre-cancerous and cancerous biochemical changes. In the present study, we used Raman spectroscopy to examine early-stage (stages 0 and I) esophageal cancer samples ex vivo. Comparison between the Raman spectra of cancerous and normal samples using a t-test showed decreased concentrations of glycogen, collagen, and tryptophan in cancerous tissue. Partial least squares regression (PLSR) analysis and self-organization maps (SOMs) discriminated the datasets of cancerous and normal samples into two groups, but there was a relatively large overlap between them. Linear discriminant analysis (LDA) based on Raman bands found in the t-test was able to predict the tissue types with 81.0% sensitivity and 94.0% specificity.

The esophageal cancer has a tendency to transfer to another part of the body and the surgical operation itself sometimes gives high risk in vital function because many delicate organs exist near the esophagus. So the esophageal cancer is a disease with a high mortality. So, in order to lead a higher survival rate five years after the cancer’s treatment, the investigation of the diagnosis methods or techniques of the cancer in an early stage and support the therapy are required. In this study, we performed the ex vivo experiments to obtain the Raman spectra from normal and early-stage tumor (stage-0) human esophageal sample by using Raman spectroscopy. The Raman spectra are collected by the homemade Raman spectrometer with the wavelength of 785 nm and Raman probe with 600-um-diameter. The principal component analysis (PCA) is performed after collection of spectra to recognize which materials changed in normal part and cancerous pert. After that, the linear discriminant analysis (LDA) is performed to predict the tissue type. The result of PCA indicates that the tumor tissue is associated with a decrease in tryptophan concentration. Furthermore, we can predict the tissue type with 80% accuracy by LDA which model is made by tryptophan bands.

The aim of the present study is to evaluate the capability of a miniaturized Raman endoscope (mRE) system to monitor the advancement of colorectal tumors in live model mice. The endoscope is narrow enough to observe the inside of the mouse colon under anesthesia. The mRE system allows to observe the tissues and to apply a miniaturized Raman probe for the measurement at any targeted point within the colon. Raman spectroscopy allows obtaining information about molecular composition without damaging the tissue (i.e., noninvasively). Continuous monitoring of the same tumor is carried out to study molecular alterations along with its advancement. The Raman spectra measured before and after the anticancer drug (5-FU) treatment indicated spectral changes in the tumor tissue. It suggests that the tumor is not cured but supposedly transformed to another tumor type after the treatment.

Our Raman probe that is called as ball-lens hollow fiber Raman probe (BHRP) had been proved possessing capability to detect the biochemical alteration within biological tissue. Whether BHRP has high capability and sensitivity in diagnosing the biochemical changing of tissue or not, mouse's normal rectal and anorectal prolapse (AP) were decided to be used as a model for this non invasive method. This AP is azoxymethane and DSS-induced mouse’s anorectal prolapse. Main outcome of BHRP will be potential for non-invasive method in tumor diagnosing. BHRP spectra obtained were a high quality and allowed analysis of their differences between normal rectal (control group) and AP. After spectral acquisition and comparison with corresponding images of hematoxylin/eosinstained section observation used to make the histopathologic diagnosing, BHRP detected some differences within the region of moiety of DNA, protein (i.e. collagen) and lipid, then following with the alteration of symmetric P=O stretching vibration compared with the normal rectal tissue. BHRP discriminate normal tissue and AP in the real-time.

Raman spectroscopy is a powerful tool for analyzing live biological samples without staining and labeling. In the present report, developments of instruments and analyzing methods, and their biomedical application studies, especially in live cells and animals are introduced.

The aim of the present study is to evaluate the capability of a miniaturized Raman endoscope (mRE) system to monitor the advancement of colorectal tumors in model mice as a method that is noninvasive to the tumor itself. Nevertheless, the endoscope is narrow enough to observe the inside of the mouse colon in such a way that is semi-noninvasive to the animal. However, the mRE system allowed the visualization and Raman spectral measurement of any targeted point within the colorectal tumor in model mice under anesthesia, without damaging the tissue (i.e., noninvasively). Continuous monitoring of the same tumor allowed the observation of alterations in its molecular composition and size, along with its advancement. The tumor lesion was discriminated from normal tissues of the control mouse with an accuracy of 86.8%. We succeeded in visualizing and performing Raman spectral observations on a shrinking polyp type tumor. The Raman analysis suggested that it was not cured but supposedly transformed to another tumor type.