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).

Optimization of fiber-optic evanescent wave spectroscopy: a Monte Carlo approach.

The absorbance of the evanescent waves of infrared radiation transmitted through an optical fiber depends on the geometry of the fiber in addition to the wavelength of the electromagnetic radiation. The signal can thus be enhanced by flattening the midsection of the fiber. While the dependence of the absorbance on the thickness of the midsection has already been studied and experimented upon, we demonstrate that similar results are obtained using Monte Carlo methods based simply on geometrical optics, given the dimensions of the fiber and the power distribution of the fired rays. The optimization can be extended to fibers with more complex geometries of the sensor.

Discrimination between drug-resistant and non-resistant human melanoma cell lines by FTIR spectroscopy.

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.

Distinction of malignant melanoma and epidermis using IR micro-spectroscopy and statistical methods.

Infrared spectroscopy is widely perceived as a future technology for cancer detection and grading. Malignant melanoma, an aggressive skin cancer, is accessible to non-invasive IR radiation based surface probes for its identification and grading. The present work examines the differences in the IR spectra of melanoma tissues and the surrounding epidermis in skin biopsies with the objective of identifying diagnostic parameters and suitable computational/statistical methods of analysis. Melanoma could be differentiated from the epidermis in biopsies of 55 patients, using parameters derived from absorbance bands originating from molecular vibrations of nucleic acids and/or their bases. Additionally, absorbances from tyrosine and phosphate that are abnormally elevated in malignant melanoma could be used as markers. Two-dimensional plots of these parameters in tandem with advanced statistical methods successfully demonstrate the potential of IR spectroscopy to distinguish between epidermal and melanoma regions with a high classification success. The work underlines the importance of developing data analysis methods in FTIR based diagnosis using melanoma as a model system.

Potential of 'flat' fibre evanescent wave spectroscopy to discriminate between normal and malignant cells in vitro.

The present study focuses on evaluating the potential of flattened AgClBr fibre-optic evanescent wave spectroscopy (FTIR-FEWS) technique for detection and identification of cancer cells in vitro using cell culture as a model system. The FTIR-FEWS results are compared to those from FTIR-microspectroscopy (FTIR-MSP) method extensively used to identify spectral properties of intact cells. Ten different samples of control and malignant cells were measured in parallel by the above two methods. Our results show a significant similarity between the results obtained by the two methodologies. The absorbance level of Amide I/Amide II, phosphates and carbohydrates were significantly altered in malignant compared to the normal cells using both systems. Thus, common biomarkers such as Amide I/Amide II, phosphate and carbohydrate levels can be derived to discern between normal and cancer cells. However, marked differences are also noted between the two methodologies in the protein bands due to CH3 bending vibration (1480-1350 cm(-1)). The spectral differences may be attributed to the variation in the penetration depth of the two methodologies. The use of flattened fibre rather than the standard cylindrical fibre has several practical advantages and is considered as an important step towards in vivo measurements in real time, such as that of skin nevi and melanoma using special designs of fibre-optic-based sensors.

Use of FTIR spectroscopy to distinguish between capsular types and capsular quantities in Streptococcus pneumoniae.

Fourier transform infrared (FTIR) spectroscopy has shown remarkable ability in distinguishing between bacterial species and identifying bacterial colony structures, when used in tandem with methods such as cluster analysis, principal component analysis, or linear discriminant analysis. The present work was aimed to evaluate the potential of FTIR-microscopy (FTIR-MSP) to distinguish between different serotypes and capsular quantities of Streptococcus pneumoniae. In general, the results obtained have consistently proven that the spectral information at the region 900-1,185 cm(-1) was sufficient to distinguish between various pneumococcal serotypes. Moreover, the method was able to differentiate between S. pneumoniae phase variants on the basis of their relative carbohydrate content. The unsupervised cluster analysis of the samples showed differences, not only in the carbohydrate content, but also in the region 1,350-1,480 cm(-1), which is dominated by absorptions due to lipids and phospholipids. This approach proved to be useful for the distinction between S. pneumoniae serotypes and between phase variants, which were shown to acquire different pathogenic capacity.

Can Fourier transform infrared spectroscopy at higher wavenumbers (mid IR) shed light on biomarkers for carcinogenesis in tissues?

Fourier transform infrared microspectroscopy (FTIR-MSP) has shown promise as a technique for detection of abnormal cell proliferation and premalignant conditions. In the present study, we investigate the absorbance in the sensitive wavenumber region between 2800 and 3000 cm(-1), which has been known to be due to the antisymmetric and symmetric stretching vibrations of CH2 and CH3 groups of proteins and lipids. We report common biomarkers from this region that distinguish between normal and malignant tissues and cell lines. Based on our findings, we propose that the wavenumber region around 2800 to 3000 cm(-1) in the FTIR spectra of cells and tissues could provide valuable scientific evidence at the onset of premalignancy and may be used for ex vivo and in vitro detection of carcinogenesis. To further examine the utility of these markers in cancer diagnosis and management, they are tested successfully in monitoring the changes occurring in leukemia patients during chemotherapy.

Distinction of cervical cancer biopsies by use of infrared microspectroscopy and probabilistic neural networks.

Fourier-transform infrared spectroscopy has shown alterations of spectral characteristics of cells and tissues as a result of carcinogenesis. The research reported here focuses on the diagnosis of cancer in formalin-fixed biopsied tissue for which immunochemistry is not possible and when PAP-smear results are to be confirmed. The data from two groups of patients (a control group and a group of patients diagnosed with cervical cancer) were analyzed. It was found that the glucose/phosphate ratio decreases (by 23-49%) and the RNA/DNA ratio increases (by 38-150%) in carcinogenic compared with normal tissue. Fourier-transform microspectroscopy was used to examine these tissues. This type of study in larger populations may help to set standards or classes with which to use treated biopsied tissue to predict the possibility of cancer. Probabilistic neural networks and statistical tests as parts of these biopsies predict the possibility of cancer with a high degree of accuracy (> 95%).

Protective autoimmunity: interferon-gamma enables microglia to remove glutamate without evoking inflammatory mediators.

Glutamate in excessive amounts is a major contributor to neuronal degeneration, and its removal is attributed mainly to astrocytes. Traumatic injury to the central nervous system (CNS) is often accompanied by disappearance of astrocytes from the lesion site and failure of the remaining cells to withstand the ensuing toxicity. Microglia that repopulate the lesion site are the usual suspects for causing redox imbalance and inflammation and thus further exacerbating the neurotoxicity. However, our group recently demonstrated that early post-injury activation of microglia as antigen-presenting cells correlates with an ability to withstand injurious conditions. Moreover, we found that T cells reactive to CNS-specific self-antigens protected neurons against glutamate toxicity. Here, we show that antigen-specific autoimmune T cells, by tailoring the microglial phenotype, can increase the ability of microglia-enriched cultures to remove glutamate. This T-cell-mediated effect could not be achieved by the potent microglia-activating agent lipopolysaccharide (LPS), but was dose-dependently reproduced by the Th1 cytokine interferon (IFN)-gamma and significantly reduced by neutralizing anti-IFN-gamma antibodies. Under the same conditions, IFN-gamma had no effect on cultured astrocytes. Up-regulation of glutamate uptake induced by IFN-gamma activation was not accompanied by the acute inflammatory response seen in LPS-activated cultures. These findings suggest that T cells or their cytokines can cause microglia to adopt a phenotype that facilitates rather than impairs glutamate clearance, possibly contributing to restoration of homeostasis.

Fourier transform infrared spectroscopy in cancer detection.

The rapid developments in the field of infrared spectroscopy in the past decade have demonstrated a potential for disease diagnosis using noninvasive technologies. Several earlier studies have highlighted the advantage of using infrared spectroscopy both in the near- and mid-infrared regions for diagnostic purposes at clinical levels. The areas of focus have been the distinction of premalignant and malignant cells and tissues from their normal state using specific parameters obtained from Fourier transform infrared spectra, making it a rapid and reagent-free method. While it still requires pilot studies and designed clinical trials to ensure the applicability of such systems for cancer diagnosis, substantial progress has been made in incorporating advances in computational methods into the system to increase the sensitivity of the entire setup, making it an objective and sensitive technique suitable for automation to suit the demands of the medical community. The development of fiber-optics systems for infrared spectroscopy have further opened up new and modern avenues in medical diagnosis at various levels of cells, tissues and organs under laboratory and clinical conditions.

Characteristic absorbance of nucleic acids in the Mid-IR region as possible common biomarkers for diagnosis of malignancy.

FTIR spectroscopy has been extensively used to understand the differences between normal and malignant cells and tissues. In the present study, FTIR microspectroscopy was performed on biopsies to evaluate parameters deduced from changes in nucleic acid absorbance monitored at various characteristic wavenumbers in the Mid-IR region. The data showed that there were differences in the spectra of normal and malignant tissues from several organs such as colon, cervix, skin and blood with respect to absorbance due to nucleic acids. Similar results were observed in the case of cell lines that were transformed to induce carcinogenesis. Of the several ratios examined for consistency in differentiating cancer and normal tissues, the I(996 cm(-1))/I(966 cm(-1)) showed promise as a distinguishing parameter and was comparable to the I(1121 cm(-1))/I(1020 cm(-1)) ratio reported in many earlier studies. The absorbance of nucleic acids is presented with an emphasis on the application of FTIR microspectroscopy for diagnosis of malignancy. Our results indicate that usage of nucleic acid absorbance yield statistically significant parameters, which could differentiate normal and cancerous tissues.