Membrane properties of structurally modified ceramides : effects on lipid lateral distribution and sphingomyelin-interactions in artificial bilayer membranes

Ceramides comprise a class of sphingolipids that exist only in small amounts in cellular membranes, but which have been associated with important roles in cellular signaling processes. The influences that ceramides have on the physical properties of bilayer membranes reach from altered thermodynamical behavior to significant impacts on the molecular order and lateral distribution of membrane lipids. Along with the idea that the membrane physical state could influence the physiological state of a cell, the membrane properties of ceramides have gained increasing interest. Therefore, membrane phenomena related to ceramides have become a subject of intense study both in cellular as well as in artificial membranes. Artificial bilayers, the so called model membranes, are substantially simpler in terms of contents and spatio-temporal variation than actual cellular membranes, and can be used to give detailed information about the properties of individual lipid species in different environments. This thesis focuses on investigating how the different parts of the ceramide molecule, i.e., the N-linked acyl chain, the long-chain sphingoid base and the membrane-water interface region, govern the interactions and lateral distribution of these lipids in bilayer membranes. With the emphasis on ceramide/sphingomyelin(SM)-interactions, the relevance of the size of the SMhead group for the interaction was also studied. Ceramides with methylbranched N-linked acyl chains, varying length sphingoid bases, or methylated 2N (amide-nitrogen) and 3O (C3-hydroxyl) at the interface region, as well as SMs with decreased head group size, were synthesized and their bilayer properties studied by calorimetric and fluorescence spectroscopic techniques. In brief, the results showed that the packing of the ceramide acyl chains was more sensitive to methyl-branching in the mid part than in the distal end of the N-linked chain, and that disrupting the interfacial structure at the amide-nitrogen, as opposed to the C3-hydroxyl, had greater effect on the interlipid interactions of ceramides. Interestingly, it appeared that the bilayer properties of ceramides could be more sensitive to small alterations in the length of the long-chain base than what was previously reported for the N-linked acyl chain. Furthermore, the data indicated that the SM-head group does not strongly influence the interactions between SMs and ceramides. The results in this thesis illustrate the pivotal role of some essential parts of the ceramide molecules in determining their bilayer properties. The thesis provides increased understanding of the molecular aspects of ceramides that possibly affect their functions in biological membranes, and could relate to distinct effects on cell physiology.

Forecasting of wind speeds and directions with artificial neural networks

In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.

Artificial Ribonucleases: Oligonucleotides Conjugated with Metal Ion Chelates of Azacrowns

Ribonucleic acid (RNA) has many biological roles in cells: it takes part in coding, decoding, regulating and expressing of the genes as well as has the capacity to work as a catalyst in numerous biological reactions. These qualities make RNA an interesting object of various studies. Development of useful tools with which to investigate RNA is a prerequisite for more advanced research in the field. One of such tools may be the artificial ribonucleases, which are oligonucleotide conjugates that sequence-selectively cleave complementary RNA targets. This thesis is aimed at developing new efficient metal-ion-based artificial ribonucleases. On one hand, to solve the challenges related to solid-supported synthesis of metal-ion-binding conjugates of oligonucleotides, and on the other hand, to quantify their ability to cleave various oligoribonucleotide targets in a pre-designed sequence selective manner. In this study several artificial ribonucleases based on cleaving capability of metal ion chelated azacrown moiety were designed and synthesized successfully. The most efficient ribonucleases were the ones with two azacrowns close to the 3´- end of the oligonucleotide strand. Different transition metal ions were introduced into the azacrown moiety and among them, the Zn2+ ion was found to be better than Cu2+ and Ni2+ ions.

Artificial reflecting structures based on metamaterials

This thesis studies metamaterial-inspired mirrors which provide the most general control over the amplitude and phase of the reflected wavefront. The goal is to explore practical possibilities in designing fully reflective electromagnetic structures with full control over reflection phase. The first part of the thesis describes a planar focusing metamirror with the focal distance less than the operating wavelength. Its practical applicability from the viewpoint of aberrations when the incident angle deviates from the normal one is verified numerically and experimentally. The results indicate that the proposed focusing metamirror can be efficiently employed in many different applications due to its advantages over other conventional mirrors. In the second part of the thesis a new theoretical concept of reflecting metasurface operation is introduced based on Huygens’ principle. This concept in contrast to known approaches takes into account all the requirements of perfect metamirror operation. The theory shows a route to improve the previously proposed metamirrors through tilting the individual inclusions of the structure at a chosen angle from normal. It is numerically tested and the results demonstrate improvements over the previous design.

Modelling the colour difference by artificial neural network

This thesis work studies the modelling of the colour difference using artificial neural network. Multilayer percepton (MLP) network is proposed to model CIEDE2000 colour difference formula. MLP is applied to classify colour points in CIE xy chromaticity diagram. In this context, the evaluation was performed using Munsell colour data and MacAdam colour discrimination ellipses. Moreover, in CIE xy chromaticity diagram just noticeable differences (JND) of MacAdam ellipses centres are computed by CIEDE2000, to compare JND of CIEDE2000 and MacAdam ellipses. CIEDE2000 changes the orientation of blue areas in CIE xy chromaticity diagram toward neutral areas, but on the whole it does not totally agree with the MacAdam ellipses. The proposed MLP for both modelling CIEDE2000 and classifying colour points showed good accuracy and achieved acceptable results.