Evaluating biochemical differences in thyroglobulin from normal and goiter tissues by infrared spectral imaging.

Thyroglobulin is a glycoiodoprotein that is produced by thyroid follicular cells; it is stored in follicles in structures known as colloids. The main function of this protein is to stock the hormones triiodothyronine (T3) and thyroxine (T4) until the body requires them. This study aims to demonstrate that infrared spectral imaging with appropriate multivariate analysis can reveal biochemical changes in this glycoprotein. The results achieved herein point out biochemical differences in the colloid samples obtained from normal and goiter patients including glycosylation and changes in the secondary conformational structure. We have presented the first spectral histopathology-based method to detect biochemical differences in thyroid colloids, such as TG iodination, glycosylation, and changes in the secondary structure in normal and goiter patients. The observed changes in the colloids were mainly due to the alterations in amide I and amide II (secondary conformation of proteins) and there is a correlation with different glycosylation between normal and goiter tissues.

Parasites under the Spotlight: Applications of Vibrational Spectroscopy to Malaria Research.

New technologies to diagnose malaria at high sensitivity and specificity are urgently needed in the developing world where the disease continues to pose a huge burden on society. Infrared and Raman spectroscopy-based diagnostic methods have a number of advantages compared with other diagnostic tests currently on the market. These include high sensitivity and specificity for detecting low levels of parasitemia along with ease of use and portability. Here, we review the application of vibrational spectroscopic techniques for monitoring and detecting malaria infection. We discuss the role of vibrational (infrared and Raman) spectroscopy in understanding the processes of parasite biology and its application to the study of interactions with antimalarial drugs. The distinct molecular phenotype that characterizes malaria infection and the high sensitivity enabling detection of low parasite densities provides a genuine opportunity for vibrational spectroscopy to become a front-line tool in the elimination of this deadly disease and provide molecular insights into the chemistry of this unique organism.

Optimizing decision tree structures for spectral histopathology (SHP).

This paper reviews methods to arrive at optimum decision tree or label tree structures to analyze large SHP datasets. Supervised methods of analysis can utilize either sequential or (flat) multi-classifiers depending on the variance in the data, and on the number of spectral classes to be distinguished. For small number of spectral classes, multi-classifiers have been used in the past, but for the analysis of datasets containing large numbers (∼20) of disease or tissue types, mixed decision tree structures were found to be advantageous. In these mixed structures, discrimination into classes and subclasses is achieved via hierarchical decision/label tree structures.

Infrared micro-spectroscopy of human tissue: principles and future promises.

This article summarizes the methods employed, and the progress achieved over the past two decades in applying vibrational (Raman and IR) micro-spectroscopy to problems of medical diagnostics and cellular biology. During this time, several research groups have verified the enormous information contained in vibrational spectra; in fact, information on protein, lipid and metabolic composition of cells and tissues can be deduced by decoding the observed vibrational spectra. This decoding process is aided by the availability of computer workstations and advanced algorithms for data analysis. Furthermore, commercial instrumentation for the fast collection of both Raman and infrared micro-spectral data has enabled the collection of images of cells and tissues based solely on vibrational spectroscopic data. The progress in the field has been manifested by a steady increase in the number and quality of publications submitted by established and new research groups in vibrational spectroscopy in the biological and biomedical arenas.

Cancer screening via infrared spectral cytopathology (SCP): results for the upper respiratory and digestive tracts.

Instrumental advances in infrared micro-spectroscopy have made possible the observation of individual human cells and even subcellular structures. The observed spectra represent a snapshot of the biochemical composition of a cell; this composition varies subtly but reproducibly with cellular effects such as progression through the cell cycle, cell maturation and differentiation, and disease. The aim of this summary is to provide a synopsis of the progress achieved in infrared spectral cytopathology (SCP) - the combination of infrared micro-spectroscopy and multivariate methods of analysis - for the detection of abnormalities in exfoliated human cells of the upper respiratory and digestive tract, namely the oral and nasopharyngeal cavities, and the esophagus.

Classification of malignant and benign tumors of the lung by infrared spectral histopathology (SHP).

We report results of a study utilizing a novel tissue classification method, based on label-free spectral techniques, for the classification of lung cancer histopathological samples on a tissue microarray. The spectral diagnostic method allows reproducible and objective classification of unstained tissue sections. This is accomplished by acquiring infrared data sets containing thousands of spectra, each collected from tissue pixels ∼6 µm on edge; these pixel spectra contain an encoded snapshot of the entire biochemical composition of the pixel area. The hyperspectral data sets are subsequently decoded by methods of multivariate analysis that reveal changes in the biochemical composition between tissue types, and between various stages and states of disease. In this study, a detailed comparison between classical and spectral histopathology is presented, suggesting that spectral histopathology can achieve levels of diagnostic accuracy that is comparable to that of multipanel immunohistochemistry.

A method for the comparison of multi-platform spectral histopathology (SHP) data sets.

Results of a study comparing infrared imaging data sets collected on different instruments or instrument platforms are reported, along with detailed methods developed to permit such comparisons. It was found that different instrument platforms, although employing different detector technologies and pixel sizes, produce highly similar and reproducible spectral results. However, differences in the absolute intensity values of the reflectance data sets were observed that were caused by heterogeneity of the sample substrate in terms of reflectivity and planarity.

Statistical analysis of a lung cancer spectral histopathology (SHP) data set.

We report results on a statistical analysis of an infrared spectral dataset comprising a total of 388 lung biopsies from 374 patients. The method of correlating classical and spectral results and analyzing the resulting data has been referred to as spectral histopathology (SHP) in the past. Here, we show that standard bio-statistical procedures, such as strict separation of training and blinded test sets, result in a balanced accuracy of better than 95% for the distinction of normal, necrotic and cancerous tissues, and better than 90% balanced accuracy for the classification of small cell, squamous cell and adenocarcinomas. Preliminary results indicate that further sub-classification of adenocarcinomas should be feasible with similar accuracy once sufficiently large datasets have been collected.

Infrared micro-spectroscopy for cyto-pathological classification of esophageal cells.

We report results from a study utilizing infrared spectral cytopathology (SCP) to detect abnormalities in exfoliated esophageal cells. SCP has been developed over the past decade as an ancillary tool to classical cytopathology. In SCP, the biochemical composition of individual cells is probed by collecting infrared absorption spectra from each individual, unstained cell, and correlating the observed spectral patterns, and the variations therein, against classical diagnostic methods to obtain an objective, machine-based classification of cells. In the past, SCP has been applied to the analysis and classification of cells exfoliated from the cervix and the oral cavity. In these studies, it was established that SCP can distinguish normal and abnormal cell types. Furthermore, SCP can differentiate between truly normal cells, and cells with normal morphology from the vicinity of abnormalities. Thus, SCP may be a valuable tool for the screening of early stages of dysplasia and pre-cancer.

Roadmap on optical sensors.

Optical sensors and sensing technologies are playing a more and more important role in our modern world. From micro-probes to large devices used in such diverse areas like medical diagnosis, defence, monitoring of industrial and environmental conditions, optics can be used in a variety of ways to achieve compact, low cost, stand-off sensing with extreme sensitivity and selectivity. Actually, the challenges to the design and functioning of an optical sensor for a particular application requires intimate knowledge of the optical, material, and environmental properties that can affect its performance. This roadmap on optical sensors addresses different technologies and application areas. It is constituted by twelve contributions authored by world-leading experts, providing insight into the current state-of-the-art and the challenges their respective fields face. Two articles address the area of optical fibre sensors, encompassing both conventional and specialty optical fibres. Several other articles are dedicated to laser-based sensors, micro- and nano-engineered sensors, whispering-gallery mode and plasmonic sensors. The use of optical sensors in chemical, biological and biomedical areas is discussed in some other papers. Different approaches required to satisfy applications at visible, infrared and THz spectral regions are also discussed.

The characterization of normal thyroid tissue by micro-FTIR spectroscopy.

In this paper, we report the spectral patterns of normal human thyroid tissue and methodology to interpret hyperspectral imaging data and protein conformational changes observed therein. Raw image datasets were imported into software written in-house in the MATLAB environment and processed to yield pseudo-color images of the tissue sections. All spectra were vector normalized, noise-filtered, and corrected for water-vapour contributions and scattering effects before being subjected to Hierarchical Cluster Analysis (HCA) and correlated with histological structures obtained from images of H&E-stained parallel tissue sections. We successfully identified a protein structural heterogeneity that can be correlated with the spatially resolved amount of iodine in the thyroglobulin structure of colloids and follicular cells.

Spectral cytopathology: new aspects of data collection, manipulation and confounding effects.

This paper presents a short review on the improvements in data processing for spectral cytopathology, the diagnostic method developed for large scale diagnostic analysis of spectral data of individual dried and fixed cells. This review is followed by the analysis of the confounding effects introduced by utilizing reflecting "low-emissivity" (low-e) slides as sample substrates in infrared micro-spectroscopy of biological samples such as individual dried cells or tissue sections. The artifact introduced by these substrates, referred to as the "standing electromagnetic wave" artifact, indeed, distorts the spectra noticeably, as postulated recently by several research groups. An analysis of the standing wave effect reveals that careful data pre-processing can reduce the spurious effects to a level where they are not creating a major problem for spectral cytopathology and spectral histopathology.

Monitoring the reversible B to A-like transition of DNA in eukaryotic cells using Fourier transform infrared spectroscopy.

The ability to detect DNA conformation in eukaryotic cells is of paramount importance in understanding how some cells retain functionality in response to environmental stress. It is anticipated that the B to A transition might play a role in resistance to DNA damage such as heat, desiccation and toxic damage. To this end, conformational detail about the molecular structure of DNA has been derived primarily from in vitro experiments on extracted or synthetic DNA. Here, we report that a B- to A-like DNA conformational change can occur in the nuclei of intact cells in response to dehydration. This transition is reversible upon rehydration in air-dried cells. By systematically monitoring the dehydration and rehydration of single and double-stranded DNA, RNA, extracted nuclei and three types of eukaryotic cells including chicken erythrocytes, mammalian lymphocytes and cancerous rodent fibroblasts using Fourier transform infrared (FTIR) spectroscopy, we unequivocally assign the important DNA conformation marker bands within these cells. We also demonstrate that by applying FTIR spectroscopy to hydrated samples, the DNA bands become sharper and more intense. This is anticipated to provide a methodology enabling differentiation of cancerous from non-cancerous cells based on the increased DNA content inherent to dysplastic and neoplastic tissue.

Infrared spectral histopathology (SHP): a novel diagnostic tool for the accurate classification of lung cancer.

We report results of a study utilizing a recently developed tissue diagnostic method, based on label-free spectral techniques, for the classification of lung cancer histopathological samples from a tissue microarray. The spectral diagnostic method allows reproducible and objective diagnosis of unstained tissue sections. This is accomplished by acquiring infrared hyperspectral data sets containing thousands of spectra, each collected from tissue pixels about 6 µm on edge; these pixel spectra contain an encoded snapshot of the entire biochemical composition of the pixel area. The hyperspectral data sets are subsequently decoded by methods of multivariate analysis, which reveal changes in the biochemical composition between tissue types, and between various stages and states of disease. In this study, a detailed comparison between classical and spectral histopathology (SHP) is presented, which suggests SHP can achieve levels of diagnostic accuracy that is comparable to that of multi-panel immunohistochemistry.

Evaluating different fixation protocols for spectral cytopathology, part 1.

Spectral cytopathology (SCP) is a novel approach for disease diagnosis that utilizes infrared spectroscopy to interrogate the biochemical components of cellular samples and multivariate statistical methods, such as principal component analysis, to analyze and diagnose spectra. SCP has taken vast strides in its application for disease diagnosis over the past decade; however, fixation-induced changes and sample handling methods are still not systematically understood. Conversely, fixation and staining methods in conventional cytopathology, typically involving protocols to maintain the morphology of cells, have been documented and widely accepted for nearly a century. For SCP, fixation procedures must preserve the biochemical composition of samples so that spectral changes significant to disease diagnosis are not masked. We report efforts to study the effects of fixation protocols commonly used in traditional cytopathology and SCP, including fixed and unfixed methods applied to exfoliated oral (buccal) mucosa cells. Data suggest that the length of time in fixative and duration of sample storage via desiccation contribute to minor spectral changes where spectra are nearly superimposable. These findings illustrate that changes influenced by fixation are negligible in comparison to changes induced by disease.

Evaluating different fixation protocols for spectral cytopathology, part 2: cultured cells.

Spectral cytopathology (SCP) is a robust and reproducible diagnostic technique that employs infrared spectroscopy and multivariate statistical methods, such as principal component analysis to interrogate unstained cellular samples and discriminate changes on the biochemical level. In the past decade, SCP has taken considerable strides in its application for disease diagnosis. Cultured cell lines have proven to be useful model systems to provide detailed biological information to this field; however, the effects of sample fixation and storage of cultured cells are still not entirely understood in SCP. Conventional cytopathology utilizes fixation and staining methods that have been established and widely accepted for nearly a century and are focused on maintaining the morphology of a cell. Conversely, SCP practices must implement fixation protocols that preserve the sample's biochemical composition and maintain its spectral integrity so not to introduce spectral changes that may mask variance significant to disease. It is not only necessary to evaluate the effects on fixed exfoliated cells but also fixed cultured cells because although they are similar systems, they exhibit distinct differences. We report efforts to study the effects of fixation methodologies commonly used in traditional cytopathology and SCP including both fixed and unfixed routines applied to cultured HeLa cells, an adherent cervical cancer cell line. Data suggest parallel results to findings in Part 1 of this series for exfoliated cells, where the exposure time in fixative and duration of sample storage via desiccation contribute to minor spectral changes only. The results presented here reinforce observations from Part 1 indicating that changes induced by disease are much greater than changes observed as a result of alternate fixation methodologies. Principal component analysis of HeLa cells fixed via the same conditions and protocols as exfoliated cells (Part 1) yield nearly identical results. More importantly, the overall conclusion is that it is necessary that all samples subjected to comparative analysis should be prepared identically because although changes are minute, they are present.

Line shape distortion effects in infrared spectroscopy.

This paper explores different phenomena that cause distortions of infrared absorption spectra by mixing of reflective and absorptive band shape components of infrared spectra, and the resulting distortion of observed band shapes. In the context of this paper, we refer to the line shape of the variations of the refractive index in spectral regions of an absorption maximum (i.e., in regions of "anomalous dispersion") as "dispersive" or "reflective" line shape contributions, in analogy to previous spectroscopic literature. These distortions usually result in asymmetric bands with a negative intensity contribution at the high wavenumber of the band, accompanied by a shift toward lower wavenumber, and confounded band intensities. In extreme cases of band distortions caused by the "resonance Mie" (RMie) mechanism, spectral peaks may be split into doublets of peaks, change from positive to negative peaks, or appear as derivative-shaped features.

Noise adjusted principal component reconstruction to optimize infrared microspectroscopy of individual live cells.

We have optimized an imaging methodology capable of monitoring individual live HeLa cells using non-synchrotron FTIR in an aqueous environment. This methodology, in combination with MATLAB based pre-processing techniques, allows fast and efficient collection of data with high signal-to-noise ratio in comparison with previous methods using point mode data collection, which required manual operation and more collection time. Also, presented are early results that illustrate interpretable spectral differences from live cells treated with chemotherapeutic drugs, demonstrating the potential of this methodology to develop more desirable modes of treatment for patients in their diagnoses and treatments for disease.

Identification of functionally relevant populations in enhanced biological phosphorus removal processes based on intracellular polymers profiles and insights into the metabolic diversity and heterogeneity.

This study proposed and demonstrated the application of a new Raman microscopy-based method for metabolic state-based identification and quantification of functionally relevant populations, namely polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs), in enhanced biological phosphorus removal (EBPR) system via simultaneous detection of multiple intracellular polymers including polyphosphate (polyP), glycogen, and polyhydroxybutyrate (PHB). The unique Raman spectrum of different combinations of intracellular polymers within a cell at a given stage of the EBPR cycle allowed for its identification as PAO, GAO, or neither. The abundance of total PAOs and GAOs determined by Raman method were consistent with those obtained with polyP staining and fluorescence in situ hybridization (FISH). Different combinations and quantities of intracellular polymer inclusions observed in single cells revealed the distribution of different sub-PAOs groups among the total PAO populations, which exhibit phenotypic and metabolic heterogeneity and diversity. These results also provided evidence for the hypothesis that different PAOs may employ different extents of combination of glycolysis and TCA cycle pathways for anaerobic reducing power and energy generation and it is possible that some PAOs may rely on TCA cycle solely without glycolysis. Sum of cellular level quantification of the internal polymers associated with different population groups showed differentiated and distributed trends of glycogen and PHB level between PAOs and GAOs, which could not be elucidated before with conventional bulk measurements of EBPR mixed cultures.