Differentiation of mixed soil-borne fungi in the genus level using infrared spectroscopy and multivariate analysis.

Early detection of soil-borne pathogens, which have a negative effect on almost all agricultural crops, is crucial for effective targeting with the most suitable antifungal agents and thus preventing and/or reducing their severity. They are responsible for severe diseases in various plants, leading in many cases to substantial economic losses. In this study, infrared (IR) spectroscopic method, which is known as sensitive, accurate and rapid, was used to discriminate between different fungi in a mixture was evaluated. Mixed and pure samples of Colletotrichum, Verticillium, Rhizoctonia, and Fusarium genera were measured using IR microscopy. Our spectral results showed that the best differentiation between pure and mixed fungi was obtained in the 675-1800 cm-1 wavenumber region. Principal components analysis (PCA), followed by linear discriminant analysis (LDA) as a linear classifier, was performed on the spectra of the measured classes. Our results showed that it is possible to differentiate between mixed-calculated categories of phytopathogens with high success rates (~100%) when the mixing percentage range is narrow (40-60) in the genus level; when the mixing percentage range is wide (10-90), the success rate exceeded 85%. Also, in the measured mixed categories of phytopathogens it is possible to differentiate between the different categories with ~100% success rate.

Early diagnosis of Alzheimer's disease using infrared spectroscopy of isolated blood samples followed by multivariate analyses.

Alzheimer's disease (AD) is the most common cause of dementia, particularly in the elderly. The disease is characterized by cognitive decline that typically starts with insidious memory loss and progresses relentlessly to produce global impairment of all higher cortical functions. Due to better living conditions and health facilities in developed countries, which result in higher overall life spans, these countries report upward trends of AD among their populations. There are, however, no specific diagnostic tests for AD and clinical diagnosis is especially difficult in the earliest stages of the disease. Early diagnosis of AD is frequently subjective and is determined by physicians (generally neurologists, geriatricians, and psychiatrists) depending on their experience. Diagnosing AD requires both medical history and mental status testing. Having trouble with memory does not mean you have AD. AD has no current cure, but treatments for symptoms are available and research continues. In this study, we investigated the potential of infrared microscopy to differentiate between AD patients and controls, using Fourier transform infrared (FTIR) spectroscopy of isolated blood components. FTIR is known as a quick, safe, and minimally invasive method to investigate biological samples. For this goal, we measured infrared spectra from white blood cells (WBCs) and plasma taken from AD patients and controls, with the consent of the patients or their guardians. Applying multivariate analysis, principal component analysis (PCA) followed by linear discriminant analysis (LDA), it was possible to differentiate among the different types of mild, moderate, and severe AD, and the controls, with 85% accuracy when using the WBC spectra and about 77% when using the plasma spectra. When only the moderate and severe stages were included, an 83% accuracy was obtained using the WBC spectra and about 89% when using the plasma spectra.

Assignment of Colletotrichum coccodes isolates into vegetative compatibility groups using infrared spectroscopy: a step towards practical application.

Colletotrichum coccodes (C. coccodes) is a pathogenic fungus that causes anthracnose on tomatoes and black dot disease in potatoes. It is considered as a seed tuber and soil-borne pathogen that is difficult to control. C. coccodes isolates are classified into Vegetative Compatibility Groups (VCGs). Early classification of isolates into VCGs is of great importance for a better understanding of the epidemiology of the disease and improving its control. Moreover, the differentiation among these isolates and the assignment of newly-discovered isolates enable control of the disease at its early stages. Distinguishing between isolates using microbiological or genetic methods is time-consuming and not readily available. Our results show that it is possible to assign the isolates into their VCGs and to classify them at the isolate level with a high success rate using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).

Characterization of Phytophthora infestans resistance to mefenoxam using FTIR spectroscopy.

Phytophthora infestans (P. infestans) is the causal agent of late blight in potato and tomato. This pathogen devastated the potato crops in Ireland more than a century years ago and is still causing great losses worldwide. Although fungicides controlling P. infestans have been used successfully for almost 100 years, some isolates have developed resistance to most common fungicides. Identification and characterization of these resistant isolates is required for better control of the disease. Current methods that are based on microbiological and molecular techniques are both expensive and time consuming. Fourier Transform Infra-Red spectroscopy (FTIR) is an inexpensive and reagent-free technique that provides accurate results in only a few minutes. In this study the infrared absorption spectra of the sporangia of P. infestans were measured to evaluate the potential of FTIR spectroscopy in tandem with multivariate analysis in order to classify those sporangia into those that were resistant and those that were non-resistant to the phenylamide fungicide mefenoxam. Based on individual measurements, our results show that FTIR spectroscopy enables classification of P. infestans isolates into mefenoxam resistant and mefenoxam non-resistant types with specificity of 81.9% and sensitivity of 75.5%. Using average spectra per leaf, it was possible to improve the classification results to 88% sensitivity and 95% specificity.

Classification of Colletotrichum coccodes isolates into vegetative compatibility groups using infrared attenuated total reflectance spectroscopy and multivariate analysis.

In this study the potential of infrared (IR) spectroscopy for the classification of Colletotrichum coccodes (C. coccodes) isolates into vegetative compatibility groups (VCGs) was evaluated. Isolates which belong to the same VCG may have similar pathological and physiological traits that differ from those that are not assigned to the same VCG. Early classification of isolates into VCGs is of a great importance for a better understanding of the epidemiology of the disease and improves its control. The main goal of the present study was to classify 14 isolates of C. coccodes into VCGs and differentiate between them, based on their IR absorption spectra as obtained by the FTIR-ATR sampling technique. Advanced statistical and mathematical methods, including Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), were applied to the spectra after manipulation. The results show that it is possible to assign the isolates into VCGs with more than 90% success based on the wavenumber low region (1800-800 cm(-1)) and using 15 PCs. However, on the isolate level, the best differentiation results were obtained using PCA (15 PCs) and LDA for the combined regions (2990-2800 cm(-1), 1800-800 cm(-1)), with identification success rates of 87.2%.

Utilizing FTIR-ATR spectroscopy for classification and relative spectral similarity evaluation of different Colletotrichum coccodes isolates.

Colletotrichum coccodes (C. coccodes) is a pathogenic fungus which causes anthracnose on tomatoes and black dot disease in potatoes. It is important to differentiate among these isolates and to detect the origin of newly discovered isolates, in order to treat the disease in its early stages. However, distinguishing between isolates using common biological methods is time-consuming, and not always available. We used Fourier Transform Infra-Red (FTIR)-Attenuated Total Reflectance (ATR) spectroscopy and advanced mathematical and statistical methods to distinguish between different isolates of C. coccodes. To our knowledge, this is the first time that FTIR-ATR spectroscopy was used, combined with multivariate analysis, to classify such a large number of 15 isolates belonging to the same species. We obtained a success rate of approximately 90% which was achieved using the region 800-1775 cm(-1). In addition we succeeded in determining the relative spectral similarity between different fungal isolates by developing a new algorithm. This method could be an important potential diagnostic tool in agricultural research, since it may outline the extent of the biological similarity between fungal isolates. Based on the PCA calculations, we grouped the fifteen isolates included in this study into four different degrees of similarity.

Grading of intrinsic and acquired cisplatin-resistant human melanoma cell lines: an infrared ATR study.

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.

Distinction of Fusarium oxysporum fungal isolates (strains) using FTIR-ATR spectroscopy and advanced statistical methods.

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 reflectance spectroscopy: a promising technique for early detection of premalignancy.

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.

Advanced statistical techniques applied to comprehensive FTIR spectra on human colonic tissues.

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, 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. 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).