Clinical Spectroscopy最新文献

Multicellular spheroids are the new frontier for studying how the tumour micro-environment interferes with drug uptake and response, since they can reproduce a three-dimensional cellular organisation mimicking the behaviour of in vivo solid tissues. In this study, we exploited Focal Plane Array - Fourier Transform Infrared Imaging spectroscopy to characterize the biochemical features, in terms of distribution and composition of the meaningful macromolecules (lipids, proteins, sugars and nucleic acids), of malignant pleural mesothelioma spheroid sections, and, as further extent, to investigate the penetrating effects of cisplatin within the spheroid mass. The hyperspectral imaging analysis evidenced, in untreated spheroids, the occurrence of a replicative outer region and a hypoxic inner one, as suggested by the band area ratios related to lipid alkyl chains (2925/2960) and glycogen (1020/1650), which showed the highest values in the inner region. Moreover, the HCA spectroscopic images showed, after cisplatin treatment, an increase of the band area ratio related to lipid carbonyl ester moiety (1740/2925), suggesting the occurrence of lipid peroxidation; furthermore, the band area ratio related to nucleic acids (1240/1220) revealed a DNA fragmentation along all regions of spheroids that may be related to apoptotic mechanisms, whereas a reduction of the band area ratios related to glycogen and carbohydrates (1020/1650 and 1054/1650, respectively) appeared consistent with an inhibition of cell division. The few spectral differences between the outer and the inner regions of cisplatin-treated spheroids pointed out the diffuse penetrating effect of the drug.

Fourier-transform infrared spectroscopy (FT-IR) in combination with machine learning and chemometrics is an intensively developed, powerful tool for investigation of tissue biochemical composition with simultaneous microscopic visualization. This nondestructive, information rich and label-free technique has been successfully applied in cancer diagnostics. During the development of a disease or inflammatory processes, not only the chemical composition of tissues changes, but also their spatial organization. FT-IR imaging with linear polarization can provide new and useful information about chemically-specific orientation of macromolecules. Here, we present results of spatial macromolecular orientation in human, pancreatic tissue using four-polarization FT-IR method. Despite the much more complex chemical structure of tissue compared to artificial materials such as fibrillar polymers, the obtained orientations of biomolecules in tissue agreed with theoretical prediction.

Rheumatoid arthritis (RA) possess not only a substantial degree of clinical heterogeneity but is diagnosed on a diverse array of clinical criteria. The lack of a single marker predictive methodology means that the timely diagnosis and treatment of these patients proves challenging. With the advent of targeted therapies, it is becoming increasingly important to accurately diagnose RA at an early stage of disease in order to ensure effective and timely disease management which can minimise long term sequelae such as joint tissue damage. Raman spectroscopy has recently gained increasing clinical recognition as a non-invasive and label-free method for obtaining a complete biochemical fingerprint of the content of biological samples. This study explored the application of Raman spectroscopy coupled with multivariate data analysis, as an adjunct or alternative tool for the differential diagnosis of RA using peripheral blood mononuclear cells (PBMCs) and purified primary immune cell subsets. High performance partial least square discriminant analysis (PLSDA) classification models constructed in this study enabled identification of spectroscopic discrimination of RA patients and healthy controls without influence from confounding factors. Spectral fitting analysis identified potential spectral biomarkers such as Proteinase K and TNF-α that elucidate the spectral classification between healthy controls and RA patients. These results demonstrate the capability of Raman Spectroscopy in RA diagnosis.

In this study, we used stimulated Raman spectroscopy (SRS) microscopy to collect Raman signatures from live Saccharomyces cerevisiae cells in the spectral range 2804−3060 cm⁻¹ and 830−2000 cm⁻¹ with a spectral resolution of 8 cm⁻¹. To effect this, we tuned the pump beam to several distinct wavelengths and thus acquired a series of chemical maps in order to reconstruct SRS spectra based on the intensity of the pixels, an approach also referred as hyperspectral SRS (hsSRS). One of the advantages of hsSRS over spontaneous Raman is that it is not overtly plagued by fluorescence and so fluorescent samples like yeast can be analysed. We show however that Raman signatures acquired by this approach may be subject to spectral artefacts that manifest as drops in intensity of Raman signal due to the movement of lipid droplets (LDs) within the yeast cells. To overcome this issue, yeast cells were chemically fixed with 4% formaldehyde and no artefacts were observed in the Raman signatures acquired from ‘stationary’ samples. Our findings indicate that caution must be applied when analysing SRS signatures obtained through hsSRS from mobile LDs and/or any other moving target within a system, whether biological or not.

Digital analysis of cancer specimens using spectroscopic imaging coupled to machine learning is an emerging area that links spatially localized spectral signatures to tissue structure and disease. In this study, we examine the role of spatial-spectral tradeoffs in infrared spectroscopic imaging configurations for probing tumors and the associated microenvironment profiles at different levels of model complexity. We image breast tissue using standard and high-definition Fourier Transform Infrared (FT-IR) imaging and systematically examine the localization, spectral origins, and utility of data for classification. Results demonstrate that higher spatial detail provides high sensitivity and specificity of tissue segmentation, despite the increased subcellular variability. High definition imaging also allows accurate analysis of complex, multiclass models of breast tissue without compromising accuracy. A comparison of results also highlights the key differences in the data distributions and classification performance across modalities to better guide decision making for acquiring and analyzing IR imaging data for specific histopathological models.

Coordination chemistry enables a variety of vital functions in biological systems; however, characterising the chemical form of metal ions in cells and tissue is notoriously difficult. One technique that is gaining substantial momentum in this research area is X-ray absorption near-edge structure (XANES) spectroscopy. The XANES spectrum can be a rich source of information with respect to the coordination environment of metal ions. Further, XANES spectroscopy is compatible with microscopy mapping protocols as the spectra are recorded across a relatively narrow range of data points (typically 50–100). Although the potential of XANES spectroscopy to study metal ion coordination chemistry has long been known, data collection speed has only relatively recently reached the state in which maps can be collected with a full spectrum per pixel. The realisation of this capability now places XANES spectroscopic mapping among a suite of other spectroscopic imaging techniques, such as Fourier transform infrared (FTIR) spectroscopy and Raman spectroscopy, which are available to characterise biochemical composition, in situ within cells and tissue. Herein, we report a proof-of-concept application of XANES spectroscopic mapping to begin exploration of Fe speciation in brain tissue, which demonstrates the potential of this method for the biomedical sciences, and identifies important areas for consideration with respect to future protocol developments.

Aim of this work is to present the phenotype and biochemical characteristics of primary freshly isolated murine hepatocytes exposed to oleic and palmitic acids, the most abundant fatty acids (FAs) in human diet and serum. Excess of FAs in the diet is one of the factors that contributes to the non-alcoholic fatty liver disease (NAFLD). The hallmark of NAFLD is the overaccumulation of lipids in hepatic tissue and formation of lipid droplets (LDs). With time NAFLD can progress into more advanced stages leading to liver injury. Hepatocytes as the most abundant cells in the liver are strongly involved in the process of LDs formation, therefore are widely used in research on molecular mechanism of NAFLD development and progression. Primary hepatocytes are rarely used in investigations, due to multistep isolation process and loss of functionality under culture conditions. However, they offer substantial advantages, including preserved phenotype and functions. In order to investigate LDs formation and their content, the Raman and FTIR imaging were employed, as they provide spatial and vibrational information on studied cells in label-free manner.

Human saliva is a unique biofluid which can reflect the physiopathological state of an individual. The wide spectrum of molecules present in saliva, compounded by the close association of salivary composition to serum metabolites, can provide valuable information for clinical diagnostic applications through highly sensitive vibrational spectroscopic techniques such as Raman spectroscopy. However, the nature of saliva, in terms of collection and patient-related characteristics, can be considered factors which may strongly affect the Raman spectral profile of salivary samples and disrupt the search for specific salivary biomarkers in the detection of diseases. The main objective of this study was to highlight spectral features associated with the type of collection in an intra- and inter-patient approach. Saliva was collected using both stimulated and non-stimulated approaches from 20 donors, concentrated by centrifugal filtration and further analysed using Raman spectroscopy. The methodology adopted for liquid saliva showed consistency in the qualitative analysis of the groups, confirming the reproducibility of this Raman spectroscopic approach. Using principal component analysis (PCA) and partial least squares – discriminant analysis (PLSDA), non stimulated saliva could be differentiated from stimulated saliva in both intra- and inter-patient analysis, with a classification efficiency of 77 and 87 %, respectively. The bicinchoninic acid (BCA) assay showed a similar trend in terms of total protein concentration, showing a slight increase in stimulated saliva samples. These results are valuable in the process of developing and establishing Raman spectroscopy as a novel diagnostic tool in the future as well as controlling variability, in order to determine specific spectroscopic markers related to a multifactorial disease for diagnostic or follow-up purposes.