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Browsing by Subject "pääkomponenttianalyysi"

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  • Kyrö, Minna (2011)
    FTIR spectroscopy (Fourier transform infrared spectroscopy) is a fast method of analysis. The use of interferometers in Fourier devices enables the scanning of the whole infrared frequency region in a couple of seconds. There is no need to elaborate sample preparation when the FTIR spectrometer is equipped with an ATR accessory and the method is therefore easy to use. ATR accessory facilitates the analysis of various sample types. It is possible to measure infrared spectra from samples which are not suitable for traditional sample preparation methods. The data from FTIR spectroscopy is frequently combined with statistical multivariate analysis techniques. In cluster analysis the data from spectra can be grouped based on similarity. In hierarchical cluster analysis the similarity between objects is determined by calculating the distance between them. Principal component analysis reduces the dimensionality of the data and establishes new uncorrelated principal components. These principal components should preserve most of the variation of the original data. The possible applications of FTIR spectroscopy combined with multivariate analysis have been studied a lot. For example in food industry its feasibility in quality control has been evaluated. The method has also been used for the identification of chemical compositions of essential oils and for the detection of chemotypes in oil plants. In this study the use of the method was evaluated in the classification of hog's fennel extracts. FTIR spectra of extracts from different plant parts of hog's fennel were compared with the measured FTIR spectra of standard substances. The typical absorption bands in the FTIR spectra of standard substances were identified. The wave number regions of the intensive absorption bands in the spectra of furanocoumarins were selected for multivariate analyses. Multivariate analyses were also performed in the fingerprint region of IR spectra, including the wave number region 1785-725 cm-1. The aim was to classify extracts according to the habitat and coumarin concentration of the plants. Grouping according to habitat was detected, which could mainly be explained by coumarin concentrations as indicated by analyses of the wave number regions of the selected absorption bands. In these analyses extracts mainly grouped and differed by their total coumarin concentrations. In analyses of the wave number region 1785-725 cm-1 grouping according to habitat was also detected but this could not be explained by coumarin concentrations. These groupings may have been caused by similar concentrations of other compounds in the samples. Analyses using other wave number regions were also performed, but the results from these experiments did not differ from previous results. Multivariate analyses of second-order derivative spectra in the fingerprint region did not reveal any noticeable changes either. In future studies the method could perhaps be further developed by investigating narrower carefully selected wave number regions of second-order derivative spectra.
  • Harju, Elina (2021)
    Extracellular vesicles (EVs) are nano-sized lipid bilayer-delimited particles, released by cells. They take part in intercellular communication by their molecular composition and are part of both physiological and pathophysiological functions. EVs can be extracted from bodily fluids, and they are particularly abundant in blood. The purpose of this thesis was to evaluate the use of Raman spectroscopy in the characterization of EVs. Raman spectroscopy is an analysis method based on the interaction of light and matter, and the inelastic scattering of light, and it is used to get information on the biochemical composition of a substance. Principal component analysis (PCA) was used to investigate if Raman spectroscopy could differentiate two different platelet-derived EV samples, a red blood cell-derived EV-sample and a red blood cell-derived reference material. Evaluation of the characterization also included a stability study of these samples, where it was examined if any temperature dependent changes occurred that could be detected by Raman spectroscopy. Additionally, the applicability of Raman spectroscopy for lipoprotein contamination detection was evaluated by examining if purification of an EV sample decreased the intensity of carotenoid peaks typical for lipoprotein spectra. Raman spectroscopy was able to differentiate all three EV samples and the red blood cell-derived reference material from each other. The most clear differences were found between red blood cell and platelet-derived samples, due to for example the characteristic haemoglobin peaks of red blood cell-derived samples. Differences were also found between the two platelet EV samples, which were thought to implicate difference in protein compositions. The characterization of red blood cell-derived samples proved to be difficult because haemoglobin contained in the samples covered most of the other signal from the samples. Stability studies implicated that during fridge storage the carotenoid peak intensity of platelet-derived EV samples decreases due to the degradation of carotenoids. In the red blood cell-derived samples, no differences assignable to changes in some specific components of the samples were observed. Contamination studies suggested the intensity of the carotenoid peaks may increase due to purification of the sample. This was counter to the assumption and may suggest the carotenoids of the EV samples are not from lipoprotein contamination, but part of the EV composition. In conclusion, Raman spectroscopy proved to be a promising method for characterization and identification of different EV samples.