Diabetes is a chronic disease that affects millions of people every year worldwide. Patients with diabetes have high levels of glucose in their blood, since their bodies cannot produce or adequately use the insulin produced. Identification of diabetes is usually performed by tests of glucose in the blood by means of colorimetric reactions, which are time consuming and use a considerable amount of reagents. Attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy has been used in clinical research as a potential tool to obtain spectrochemical information of biological materials. The infrared spectra can be used as source of information for classiciation models and biomarker extraction by using specific computational tools. In this paper, a semi-portable Bruker Alpha ATR-FTIR was employed to analyse urine samples of 7 patients (3 normal, 2 diabetics and 2 pre-diabetics) in order to distinguish these three groups based on their spectrochemical information. Cross-validated principal component analysis, coupled with linear discriminant analysis was applied to the spectral dataset, resulting in 94% total accuracy. Sensitivities were observed to be 95%, 96% and 100% for normal, pre-diabetics and diabetics patients, respectively, with specificities of 93%, 91% and 100%. These findings show the potential of ATR-FTIR as a new possible tool for identification of diabetics in clinical environments, whereby the diagnosis can be performed in a rapid, non-invasive and automated way.
It is widely accepted that cervical screening has significantly reduced the incidence of cervical cancer worldwide. The primary screening test for cervical cancer is the Papanicolaou (Pap) test, which has extremely variable specificity and sensitivity. There is an unmet clinical need for methods to aid clinicians in the early detection of cervical precancer. Raman spectroscopy is a label-free objective method that can provide a biochemical fingerprint of a given sample. Compared with studies on infrared spectroscopy, relatively few Raman spectroscopy studies have been carried out to date on cervical cytology. The aim of this study was to define the Raman spectral signatures of cervical exfoliated cells present in liquid-based cytology Pap test specimens and to compare the signature of high-grade dysplastic cells to each of the normal cell types. Raman spectra were recorded from single exfoliated cells and subjected to multivariate statistical analysis. The study demonstrated that Raman spectroscopy can identify biochemical signatures associated with the most common cell types seen in liquid-based cytology samples; superficial, intermediate, and parabasal cells. In addition, biochemical changes associated with high-grade dysplasia could be identified suggesting that Raman spectroscopy could be used to aid current cervical screening tests.
Raman spectroscopy can provide a molecular-level signature of the biochemical composition and structure of cells with excellent spatial resolution and could be useful to monitor changes in composition for early stage and non-invasive cancer diagnosis, both ex-vivo and in vivo. In particular, the fingerprint spectral region (400–1,800 cm-1) has been shown to be very promising for optical biopsy purposes. However, limitations to discrimination of dysplastic and inflammatory processes based on the fingerprint region still persist. In addition, the Raman spectral signal of dysplastic cells is one important source of misdiagnosis of normal versus pathological tissues. The high wavenumber region (2,800–3,600 cm-1) provides more specific information based on N-H, O-H and C-H vibrations and can be used to identify the subtle changes which could be important for discrimination of samples. In this study, we demonstrate the potential of the highwavenumber spectral region by collecting Raman spectra of nucleoli, nucleus and cytoplasm from oral epithelial cancer (SCC-4) and dysplastic (DOK) cell lines and from normal oral epithelial primary cells, in vitro, which were then analyzed by area under the curve as a method to discriminate the spectra. In this region, we will show the discriminatory potential of the CH vibrational modes of nucleic acids, proteins and lipids. This technique demonstrated more efficient discrimination than the fingerprint region when we compared the cell cultures.
Raman spectroscopy coupled with K-means clustering analysis (KMCA) is employed to elucidate the biochemical structure of human skin tissue sections and the effects of tissue processing. Both hand and thigh sections of human cadavers were analyzed in their unprocessed and formalin-fixed, paraffin-processed (FFPP), and subsequently dewaxed forms. In unprocessed sections, KMCA reveals clear differentiation of the stratum corneum (SC), intermediate underlying epithelium, and dermal layers for sections from both anatomical sites. The SC is seen to be relatively rich in lipidic content; the spectrum of the subjacent layers is strongly influenced by the presence of melanin, while that of the dermis is dominated by the characteristics of collagen. For a given anatomical site, little difference in layer structure and biochemistry is observed between samples from different cadavers. However, the hand and thigh sections are consistently differentiated for all cadavers, largely based on lipidic profiles. In dewaxed FFPP samples, while the SC, intermediate, and dermal layers are clearly differentiated by KMCA of Raman maps of tissue sections, the lipidic contributions to the spectra are significantly reduced, with the result that respective skin layers from different anatomical sites become indistinguishable. While efficient at removing the fixing wax, the tissue processing also efficiently removes the structurally similar lipidic components of the skin layers. In studies of dermatological processes in which lipids play an important role, such as wound healing, dewaxed samples are therefore not appropriate. Removal of the lipids does however accentuate the spectral features of the cellular and protein components, which may be more appropriate for retrospective analysis of disease progression and biochemical analysis using tissue banks.
Due to its high lateral resolution, Raman microspectrsocopy is rapidly becoming an accepted technique for
the subcellular imaging of single cells. Although the potential of the technique has frequently been
demonstrated, many improvements have still to be realised to enhance the relevancy of the data collected.
Although often employed, chemical fixation of cells can cause modifications to the molecular composition
and therefore influence the observations made. However, the weak contribution of water to Raman spectra
offers the potential to study live cells cultured in vitro using an immersion lens, giving the possibility to
record highly specific spectra from cells in their original state. Unfortunately, in common 2-D culture
models, the contribution of the substrates to the spectra recorded requires significant data pre-processing
causing difficulties in developing automated methods for the correction of the spectra. Moreover, the 2-D
in vitro cell model is not ideal and dissimilarities between different optical substrates within in vitro cell
cultures results in morphological and functional changes to the cells. The interaction between the cells and
their microenvironment is crucial to their behavior but also their response to different external agents such
as radiation or anticancer drugs. In order to create an experimental model closer to the real conditions
encountered by the cell in vivo, 3-D collagen gels have been evaluated as a substrate for the spectroscopic
study of live cells. It is demonstrated that neither the medium used for cell culture nor the collagen gels
themselves contribute to the spectra collected. Thus the background contributions are reduced to that of the
water. Spectral measurements can be made in full cell culture medium, allowing prolonged measurement
times. Optimizations made in the use of collagen gels for live cells analysis by Raman spectroscopy are
encouraging and studying live cells within a collagenous microenvironment seems perfectly accessible.
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