Browsing by study line "Advanced Spectroscopy in Chemistry"

The most common route to administer drugs is oral drug delivery. However, the effectiveness of a drug or bioavailability depends mainly on the drug solubility and many drugs or drug candidates are poorly water-soluble. This is the case of indomethacin, a nonsteroidal anti-inflammatory drug (NSAID), widely used against arthritis. The drug solubility and hence the bioavailability can be improved by formulation. The formulation can be prepared with an amphiphilic compound, for instance amphiphilic block copolymers like Poly(2-oxazoline)s that have proven to be suitable candidates because they are biocompatible and their solubility and solubilization capacity can be widely modulated. Since after oral administration, the drug will be absorbed in the intestine, the intestinal fluid plays a crucial role in the solubilization, but this is currently poorly understood. Therefore, drug interactions studies are made in solution mimicking fed state intestinal fluid (FeSSIF-V2) composed of lipids (fatty acids FA and lecithin LC) and bile salts (taurocholic acid, TC). Subject of this study was the investigation of the interaction between indomethacin with poly(2-oxazoline) ABA triblock copolymers, (P2), comprising poly(2-methyl-2-oxazoline) as hydrophilic blocks and poly(2-butyl-2-oxazoline) as hydrophobic blocks, and FeSSIF-V2 were carried out using the different NMR techniques such as Diffusion-Ordered NMR spectroscopy (DOSY), nuclear Overhauser effect spectroscopy (NOESY) and 1H-NMR regarding the changes in chemical shift, the changes of the intensities and the integrals Indomethacin alone, polymer P2 alone and P2-Indomethacin formulations were dissolved in FeSSIF-V2. The changes in chemical shift proved that interactions exist between the drug, the formulation and the FeSSIF-V2. It was found (with the changes in chemical shifts, confirmed by DOSY) that the indomethacin interacts with the bile salts (TC). Also the DOSY experiment showed that the polymer P2 interacts with the bile salts (TC) at low concentration and with the lipids at a polymer concentration greater than 0.3 wt%. The same experiment was done using the P2-Indomethacin formulations and at the concentration of 0.3 wt% again the polymer aggregates were going from interacting with the bile salts (TC) to merging with the lipid aggregates, presenting a significant increase of hydrodynamic diameter (from 3.5 nm to 6.2 nm).

In this work, calibration methods, reference compounds and sample introduction system used by various researchers for different ion mobility spectrometer (IMS) techniques have been discussed. Reduced mobility values of positive and negative reference compounds along with the reason for selecting them by different researchers have been described in the literature. Differential mobility spectrometer’s (DMS) performance was evaluated by measuring calibration curves and performing repeatability tests using two test compounds: 2,6-di-tertbutylpyridine (2,6-DtBP) and hexylamine. 2,6-DtBP is often used as a positive reference compound since the mobility of its ions are independent of temperature and humidity of the drift gas. It produces a single mobility peak and due to its high proton affinity, the instrument is sensitive for the analysis of the compound. Hexylamine on the other hand produces proton bound dimer at high concentrations. Both 2,6-DtBP and hexylamine’s peak intensity and peak area showed a linear correlation when plotted against concentration. However, the linearity was only followed up to certain concentration and above this concentration the peak intensity did not follow a linear relationship. Repeatability and calibration plots were studied and compared for both 2,6-DtBP and hexylamine, where both the compounds were diluted with nitrogen gas and nitrogen gas mixed with purified air. The repeatability was good for both the compounds when they were diluted only with nitrogen

Poly(2-oxazoline)/poly(2-oxazine)-based block copolymers have gained significant attention in recent years for their potential use in drug delivery systems. The architecture of amphiphilic poly(2-oxazoline)/poly(2-oxazine) based block copolymers, consisting of hydrophilic outer blocks and a hydrophobic inner block, allows the formation of micelles. The hydrophobic drug is encapsulated within the core, and the hydrophilic shell provides the stability and solubility in aqueous solution. The size and properties of the micelles can be tuned by adjusting the composition of the copolymer, making them a versatile platform for drug delivery. In this work, three different poly(2-oxazoline)/poly(2-oxazine)-based triblock, diblock and gradient copolymers were synthesized via cationic ring-opening polymerization and compared in terms of their drug formulation capability. Triblock copolymers consisting of three polymer blocks, can be tailored to have different hydrophobic and hydrophilic block ratios, allowing for tunable drug release profiles. However, triblock copolymers are more difficult to synthesize, especially if one aims to produce symmetrical ratio of hydrophilic blocks. Diblock copolymers, consisting of two polymer blocks, can also self-assemble into micelles in aqueous solutions and can encapsulate hydrophobic drugs, however, the lower stability of their formulations compared to that of triblock copolymers can limit their drug loading capacity and drug release profiles. In theory, entropy wise, when forming a micelle, the diblock copolymer should be favorable as it doesn’t need to fold, unlike the triblock copolymers, however, the drug formulations by triblock copolymers has shown to be more stable than that of diblock copolymers. Thus, more detailed analysis is needed since the lack of literature on the systematic comparison of these different architectures. Gradient copolymers, consisting of two or more types of monomers that are incorporated into a polymer chain with a gradually changing composition, have more variable properties and are easier to synthesize through one step, than block copolymers. This makes their usage in drug formulation very attractive. However, depending on the reactivity of monomers added, the resulting product can be very different, thus, the kinetics of the copolymerization deserves an attention of the study as well.

The exploration of mineral resources is a major challenge in a world that seeks sustainable energy, renewable energy, advanced engineering, and new commercial technological devices. The rapid decrease in mineral reserves shifted the focus to under-explored and low accessibility areas that led to the use of on-site portable techniques for mineral mapping purposes, such as near infrared hyperspectral image sensors. The large datasets acquired with these instruments needs data pre-processing, a series of mathematical manipulations that can be achieved using machine learning. The aim of this thesis is to improve an existing method for mineralogy mapping, by focusing on the mineral classification phase. More specifically, a spectral similarity index was utilized to support machine learning classifiers. This was introduced because of the inability of the employed classification models to recognize samples that are not part of a given database; the models always classified samples based on one of the known labels of the database. This could be a problem in hyperspectral images as the pure component found in a sample could correspond to a mineral but also to noise or artefacts due to a variety of reasons, such as baseline correction. The spectral similarity index calculates the similarity between a sample spectrum and its assigned database class spectrum; this happens through the use of a threshold that defines whether the sample belongs to a class or not. The metrics utilized in the spectral similarity index were the spectral angler mapper, the correlation coefficient and five different distances. The machine learning classifiers used to evaluate the spectral similarity index were the decision tree, k-nearest neighbor, and support vector machine. Simulated distortions were also introduced in the dataset to test the robustness of the indexes and to choose the best classifier. The spectral similarity index was assessed with a dataset of nine minerals acquired from the Geological Survey of Finland retrieved from a Specim SWIR camera. The validation of the indexes was assessed with two mine samples obtained with a VTT active hyperspectral sensor prototype. The support vector machine was chosen after the comparison between the three classifiers as it showed higher tolerance to distorted data. With the evaluation of the spectral similarity indexes, was found out that the best performances were achieved with SAM and Chebyshev distance, which maintained high stability with smaller and bigger threshold changes. The best threshold value found is the one that, in the dataset analysed, corresponded to the number of spectra available for each class. As for the validation procedure no reference was available; because of this reason, the results of the mine samples obtained with the spectral similarity index were compared with results that can be obtained through visual interpretation, which were in agreement. The method proposed can be useful to future mineral exploration as it is of great importance to correctly classify minerals found during explorations, regardless the database utilized.

Members of the genus Flavivirus are enveloped single strand positive sense RNA viruses, that include many human pathogens. An emerging flavivirus threat in Finland and elsewhere in Europe is tick-borne encephalitis virus (TBEV), which can cause severe, often debilitating and even lethal neurological infections. There are no specific antivirals against TBEV, and only symptomatic treatment is available for affected individuals. The search for specific antivirals backed up by detailed understanding the virus structure, function and interactions with the host is therefore an unmet need. TBEV work requires biosafety level (BSL) containment facilities of level 3 or higher. This poses significant limitations on experimentation approaches for studying TBEV, and especially its highly virulent subtypes and variants. BSL2 models for TBEV can facilitate research, and such a model has been generated by our collaborator Anna Överby (MIMS, Sweden) based on a non-pathogenic Langat virus expressing surface glycoproteins from a highly virulent TBEV isolate. This model virus, rLGTVch, shows greatly reduced virulence in mice and is genetically tractable. In this thesis project, I have performed the initial structural characterization of this virus. I have optimized the production of rLGTVch, now routinely obtaining virus stocks of titers as high as 109 plaque forming units/ml. I have also established a simple and rapid purification protocol for rLGTVch. Using size exclusion chromatography resin, I obtained a highly concentrated, purified rLGTVch preparations. The purified sample was imaged using cryogenic electron microscopy (cryo-EM), and the three-dimensional structure was determined to a resolution of 4.77 Å. The 3D electron density map allowed me to analyse the structural features of the virion and confirm the similarity to a wild type TBEV strain Kuutsalo-14 structure, thus, confirming the usefulness of this model for antigen presentation. This work paves the way for further studies of TBEV using the significantly safer BSL2 model.