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Purpose: Colon cancer is a major public health problem due to its high disease rate and death toll worldwide. The use of FTIR microscopy in the field of cancer diagnosis has become attractive over the past 20 years. In the present study, the authors investigated the potential of FTIR microscopy to define spectral changes among normal, polyp, and cancer human colonic biopsied tissues. Methods: A large database of FTIR microscopic spectra was compiled from 230 human colonic biopsies. The database was divided into five subgroups: Normal, canceroustissues, and three stages of benign colonic polyps, namely, mild, moderate, and severe polyps, which are precursors of carcinoma. All biopsied tissue sections were classified concurrently by an expert pathologist. The authors applied the principal components analysis (PCA) model to reduce the dimension of the original data size to 13 principal components. Results: While PCA analysis shows only partial success in distinguishing among cancer, polyp, and the normal tissues, multivariate analysis (e.g., LDA) shows a promising distinction even within the polyp subgroups. Conclusions: Good classification accuracy among normal, polyp, and cancer groups was achieved with a success rate of approximately 85%. These results strongly support the potential of developing FTIR microscopy as a simple, reagent-free tool for early detection of colon cancer and, in particular, for discriminating among the benign premalignant colonic polyps having increasing degrees of dysplasia severity (mild, moderate, and severe).

Light-induced fluorescence (LIF) spectroscopy has demonstrated ability as a novel, noninvasive and sensitive technology for early detection of cancer. The goal of the present study is to examine the potential of this spectroscopic method for early detection and characterization of premalignant changes. As a model we used both cell lines and primary cells, which were transformed to malignant by retrovirus. Fluorescence measurements and morphological observations of the infected cells were performed at various postinfection times. Our results showed gradual attenuation of fluorescence intensities due to cancer progression which corresponds to aromatic amino acids and nicotinamide adenine dinucleotide (NADH) molecules. In order to obtain grading and supervised classifications of the spectral premalignant changes we used approaches of linear discriminant analysis. The classifications based on Mahalanobis distances allowed us to demonstrate that the accuracy of identification of premalignant stages varied between 83.1% and 96.4%. In summary, we conclude that LIF in tandem with proper statistical tools may be a promising technique for early detection of malignant progression.

We investigated the ability of FTIR-microscopy to define spectral changes between drug-sensitive and drug-resistant human melanoma cells. As a model system, a resistant melanoma cell line (GAC) was selected with cisplatin from parental (GA) cells. Using Fourier transform infrared spectroscopy (FTIR) we investigated the ability to differentiate between the resistant variant derived from the sensitive parental cell line, in the absence of cisplatin. We determined and validated spectral parameters (biomarkers) that differentiated between the two cell lines. By applying the principal component analysis (PCA) model, we reduced the original data size to six principal components. We detected a significant and consistent increase in the cell's DNA/RNA ratio as well as an increase in the lipid/protein ratio in the resistant cells. These results strongly support the potential of developing FTIR microspectroscopy as a simple, reagent-free method for the identification of drug-resistant cells. Rapid detection of tumors resistant to a particular drug, should contribute to the ability of the physician to choose an effective treatment protocol.

Fusarium is a large fungi genus of a large variety of species and strains which inhabits soil and vegetation. It is distributed worldwide and affiliated to both warm and cold weather. Fusarium oxysporum species, for instance, cause the Fusarium wilt disease of plants, which appears as a leaf wilting, yellowing and eventually plant death. Early detection and identification of these pathogens are very important and might be critical for their control. Previously, we have managed to differentiate among different fungi genera (Rhizoctonia, Colletotrichum, Verticillium and Fusarium) using FTIR-ATR spectroscopy methods and cluster analysis. In this study, we used Fourier-transform infrared (FTIR) attenuated total reflection (ATR) spectroscopy to discriminate and differentiate between different strains of F. oxysporum. The result obtained was of spectral patterns distinct to each of the various examined strains, which belong to the same species. These differences were not as significant as those found between the different genera species. We applied advanced statistical techniques: principal component analysis (PCA) and linear discriminant analysis (LDA) on the FTIR-ATR spectra in order to examine the feasibility of distinction between these fungi strains. The results are encouraging and indicate that the FTIR-ATR methodology can differentiate between the different examined strains of F. oxysporum with a high success rate. Based on our PCA and LDA calculations performed in the regions [900–1775 cm−1, 2800–2990 cm−1, with 9 PCs], we were able to classify the different strains with high success rates: Foxy1 90%, Foxy2 100%, Foxy3 100%, Foxy4 92.3%, Foxy5 83.3% and Foxy6 100%.

Attenuated total reflection (ATR) spectroscopy is used as an in vitro optical approach for the diagnosis and characterization of cell and tissue pathology. In comparison with the more conventional FTIR microspectroscopy that relies on transmission of IR radiation, ATR spectroscopy uses the evanescent wave technique, which is a step forward toward in vivo research. The aim of the present investigation was to examine the potential of ATR spectroscopy to differentiate between drug-resistant and drug-sensitive melanoma cell lines. We studied two human melanoma parental cell lines, GA and BG, and their cisplatin-resistant counterparts, GAC and BGC, respectively, which were derived by survival selection with this anticancer drug. Cisplatin cytotoxicity was measured on the four cell lines, and their relative resistance to cisplatin was established: BGC > BG > GAC > GA. Different resistance mechanisms were noticed between the two parental groups in accordance with their spectrum. ATR spectra-based cluster analysis of the selective biomarkers, such as phosphate and RNA/DNA, were found useful in differentiating sensitive from resistant cells. Normalized and absolute values of the differences between spectra were employed to compare between the two parental groups. It was possible to predict the relative cisplatin resistance between the cell lines using the discriminant classifying function. The success rates in predicting cisplatin resistance in these cells was 88 and 81% for GA versus GAC and BG versus BGC, respectively. These results support the further development of the ATR technique as a simple, in vitro, reagent-free method to identify drug resistance in cancer cells.

In last decades infrared spectroscopy has demonstrated potential as a novel technology for early cancer diagnosis. Among the various IR spectroscopic techniques special interest has arisen from methods based on evanescent wave absorbance due to the possibility for in situ and in vivo implementation. The goal of the present study is to examine the potential of Attenuated Total Reflectance (ATR) spectroscopy for early detection of premalignant changes. As a model we used both cell lines and primary cells, which were transformed to be malignant by a retrovirus. Spectral measurements were performed at various post infection stages in parallel with morphological observations. Our results showed gradual and consistent spectral alterations in both cell cultures due to carcinogenesis, which were outlined using Principal Component Analysis (PCA). The main spectral differences appeared in three spectral ranges: at 3000-2800 cm(-1) (attributed to stretching vibrational modes of lipids and proteins), at 1470-1300 cm(-1)(attributed to bending overlapping modes of lipids and proteins) and also at the highly overlapping spectral range at 1000-1200 cm(-1) (attributed to bending and starching vibrational modes corresponding to all types of biological macromolecules). In order to obtain robust unsupervised classifications of the malignant progression we applied approaches of Linear Discriminant Analysis (LDA). The classifications based on Mahalanobis distances allowed us to discern that the accuracy of successful identification of premalignant stages varied between 86.5-97.2%. Our results show that ATR spectroscopy in tandem with proper statistical tools may provide a promising technique for early detectable signals of malignant progression.

One of the major public health hazards is colon cancer. There is a great necessity to develop new methods for early detection of cancer. If colon cancer is detected and treated early, cure rate of more than 90% can be achieved. In this study we used FTIR microscopy (MSP), which has shown a good potential in the last 20 years in the fields of medical diagnostic and early detection of abnormal tissues. Large database of FTIR microscopic spectra was acquired from 230 human colonic biopsies. Five different subgroups were included in our database, normal and cancer tissues as well as three stages of benign colonic polyps, namely, mild, moderate and severe polyps which are precursors of carcinoma. In this study we applied advanced mathematical and statistical techniques including principal component analysis (PCA) and linear discriminant analysis (LDA), on human colonic FTIR spectra in order to differentiate among the mentioned subgroups' tissues. Good classification accuracy between normal, polyps and cancer groups was achieved with approximately 85% success rate. Our results showed that there is a great potential of developing FTIR-micro spectroscopy as a simple, reagent-free viable tool for early detection of colon cancer in particular the early stages of premalignancy among the benign colonic polyps.

Colon cancer is a major public health problem due to its high disease rate and death toll worldwide. The use of FTIR microscopy in the field of cancer diagnosis has become attractive over the past 20 years. In the present study, the authors investigated the potential of FTIR microscopy to define spectral changes among normal, polyp, and cancer human colonic biopsied tissues.A large database of FTIR microscopic spectra was compiled from 230 human colonic biopsies. The database was divided into five subgroups: Normal, cancerous tissues, and three stages of benign colonic polyps, namely, mild, moderate, and severe polyps, which are precursors of carcinoma. All biopsied tissue sections were classified concurrently by an expert pathologist. The authors applied the principal components analysis (PCA) model to reduce the dimension of the original data size to 13 principal components.While PCA analysis shows only partial success in distinguishing among cancer, polyp, and the normal tissues, multivariate analysis (e.g., LDA) shows a promising distinction even within the polyp subgroups.Good classification accuracy among normal, polyp, and cancer groups was achieved with a success rate of approximately 85%. These results strongly support the potential of developing FTIR microscopy as a simple, reagent-free tool for early detection of colon cancer and, in particular, for discriminating among the benign premalignant colonic polyps having increasing degrees of dysplasia severity (mild, moderate, and severe).

H and D photofragments produced via vibrationally mediated photodissociation of jet-cooled normal ethene (C2H4), 1,2-trans-d2-ethene (HDCCDH), and 1,1-d2-ethene (CH2CD2), initially excited to the fourth C-H stretch overtone region, were studied for the first time. H and D vibrational action spectra and Doppler profiles were measured. The action spectra include partially resolved features due to rotational cooling, while the monitored room temperature photoacoustic spectra exhibit only a very broad feature in each species. Simulation of the spectral contours allowed determination of the band types and origins, limited precision rotational constants, and linewidths, providing time scales for energy redistribution. The H and D Doppler profiles correspond to low average translational energies and show slight preferential C-H over C-D bond cleavage in the deuterated variants. The propensities toward H photofragments emerge even though the energy flow out of the initially prepared C-H stretch is on a picosecond time scale and the photodissociation occurs following internal conversion, indicating a more effective release of the light H atoms.

Identification of hematopoietic stem cells (HSCs) in different stages of maturation is one of the major issues in stem cell research and bone marrow (BM) transplantation. Each stage of maturation of HSCs is characterized by a series of distinct glycoproteins present on the cell plasma membrane surface, named a cluster of differentiation (CD). Currently, complicated and expensive procedures based on CD expression are needed for identification and isolation of HSCs. This method is under dispute, since the correct markers' composition is not strictly clear, thus there is need for a better method for stem cell characterization. In the present study, Fourier transform infrared (FTIR) spectroscopy is employed as a novel optical method for identification and characterization of HSCs based on their entire biochemical features. FTIR spectral analysis of isolated mice HSCs reveals several spectral markers related to lipids, nucleic acids, and carbohydrates, which distinguish HSCs from BM cells. The unique "open" conformation of HSC DNA as identified by FTIR is exploited for HSCs quantification in the BM. The proposed method of FTIR spectroscopy for HSC identification and quantification can contribute to stem cell research and BM transplantation.

The first overtone region of the C-H stretching vibration of 1,2-trans-d(2)-ethene (HDC=CDH) was monitored via jet-cooled action spectroscopy and room temperature photoacoustic spectroscopy. The spectra include a strong band, which we assigned as the nu(1)+nu(9) C-H stretch vibration, and five additional bands related to transitions to coupled states. The spectral features were modeled in terms of a six-state deperturbation analysis, revealing the energies of the zero-order states and the relatively strong couplings between the initially excited nu(1)+nu(9) state and the doorway states. Considering these energies and the fundamental frequencies of 1,2-trans-d(2)-ethene and presuming that only low-order resonances are involved in the couplings enabled the assignment of the states. The analysis also allowed obtaining insight on energy flow and to find out that the energy oscillations between the C-H stretch state and the doorway states occur on a subpicosecond time scale.