Experimental approach for studying structural changes in axonal membrane upon nerve excitation

The Hodgkin and Huxley (HH) model of action potential has become a central paradigm of neuroscience. Despite its ability to predict action potentials with remarkable accuracy, it fails to explain several biophysical findings related to the initiation and propagation of the nerve impulse. The isentropic heat release and optical phenomena demonstrated by various experiments suggest that action potential is accompanied by a transient phase change in the axonal membrane. In this study a method was developed for preparing a giant axon from the crayfish abdominal cord for studying the molecular mechanisms of action potential simultaneously by electrophysiological and optical methods. Also an alternative setup using a single-cell culture of an Aplysia sensory neuron is presented. In addition to the description of the method, the preliminary results on the effect of phloretin, a dipole potential lowering compound, on the excitability of a crayfish giant axon are presented.

Molecular mechanisms of hypertension-induced heart failure : Experimental studies with special emphasis on local renin-angiotensin system, cardiac metabolism and levosimendan

Hypertension is a major risk factor for stroke, ischaemic heart disease, and the development of heart failure. Hypertension-induced heart failure is usually preceded by the development of left ventricular hypertrophy (LVH), which represents an adaptive and compensatory response to the increased cardiac workload. Biomechanical stress and neurohumoral activation are the most important triggers of pathologic hypertrophy and the transition of cardiac hypertrophy to heart failure. Non-clinical and clinical studies have also revealed derangements of energy metabolism in hypertensive heart failure. The goal of this study was to investigate in experimental models the molecular mechanisms and signalling pathways involved in hypertension-induced heart failure with special emphasis on local renin-angiotensin-aldosterone system (RAAS), cardiac metabolism, and calcium sensitizers, a novel class of inotropic agents used currently in the treatment of acute decompensated heart failure. Two different animal models of hypertensive heart failure were used in the present study, i.e. hypertensive and salt-sensitive Dahl/Rapp rats on a high salt diet (a salt-sensitive model of hypertensive heart failure) and double transgenic rats (dTGR) harboring human renin and human angiotensinogen genes (a transgenic model of hypertensive heart failure with increased local RAAS activity). The influence of angiotensin II (Ang II) on cardiac substrate utilization and cardiac metabolomic profile was investigated by using gas chromatography coupled to time-of-flight mass spectrometry to detect 247 intermediary metabolites. It was found that Ang II could alter cardiac metabolomics both in normotensive and hypertensive rats in an Ang II receptor type 1 (AT1)-dependent manner. A distinct substrate use from fatty acid oxidation towards glycolysis was found in dTGR. Altered cardiac substrate utilization in dTGR was associated with mitochondrial dysfunction. Cardiac expression of the redox-sensitive metabolic sensor sirtuin1 (SIRT1) was increased in dTGR. Resveratrol supplementation prevented cardiovascular mortality and ameliorated Ang II-induced cardiac remodeling in dTGR via blood pressure-dependent pathways and mechanisms linked to increased mitochondrial biogenesis. Resveratrol dose-dependently increased SIRT1 activity in vitro. Oral levosimendan treatment was also found to improve survival and systolic function in dTGR via blood pressure-independent mechanisms, and ameliorate Ang II-induced coronary and cardiomyocyte damage. Finally, using Dahl/Rapp rats it was demonstrated that oral levosimendan as well as the AT1 receptor antagonist valsartan improved survival and prevented cardiac remodeling. The beneficial effects of levosimendan were associated with improved diastolic function without significantly improved systolic changes. These positive effects were potentiated when the drug combination was administered. In conclusion, the present study points to an important role for local RAAS in the pathophysiology of hypertension-induced heart failure as well as its involvement as a regulator of cardiac substrate utilization and mitochondrial function. Our findings suggest a therapeutic role for natural polyphenol resveratrol and calcium sensitizer, levosimendan, and the novel drug combination of valsartan and levosimendan, in prevention of hypertension-induced heart failure. The present study also provides a better understanding of the pathophysiology of hypertension-induced heart failure, and may help identify potential targets for novel therapeutic interventions.

Distributed algorithms for edge dominating sets

An edge dominating set for a graph G is a set D of edges such that each edge of G is in D or adjacent to at least one edge in D. This work studies deterministic distributed approximation algorithms for finding minimum-size edge dominating sets. The focus is on anonymous port-numbered networks: there are no unique identifiers, but a node of degree d can refer to its neighbours by integers 1, 2, ..., d. The present work shows that in the port-numbering model, edge dominating sets can be approximated as follows: in d-regular graphs, to within 4 − 6/(d + 1) for an odd d and to within 4 − 2/d for an even d; and in graphs with maximum degree Δ, to within 4 − 2/(Δ − 1) for an odd Δ and to within 4 − 2/Δ for an even Δ. These approximation ratios are tight for all values of d and Δ: there are matching lower bounds.

Fast distributed approximation algorithms for vertex cover and set cover in anonymous networks

We present a distributed algorithm that finds a maximal edge packing in O(Δ + log* W) synchronous communication rounds in a weighted graph, independent of the number of nodes in the network; here Δ is the maximum degree of the graph and W is the maximum weight. As a direct application, we have a distributed 2-approximation algorithm for minimum-weight vertex cover, with the same running time. We also show how to find an f-approximation of minimum-weight set cover in O(f2k2 + fk log* W) rounds; here k is the maximum size of a subset in the set cover instance, f is the maximum frequency of an element, and W is the maximum weight of a subset. The algorithms are deterministic, and they can be applied in anonymous networks.

Analysing local algorithms in location-aware quasi-unit-disk graphs

A local algorithm with local horizon r is a distributed algorithm that runs in r synchronous communication rounds; here r is a constant that does not depend on the size of the network. As a consequence, the output of a node in a local algorithm only depends on the input within r hops from the node. We give tight bounds on the local horizon for a class of local algorithms for combinatorial problems on unit-disk graphs (UDGs). Most of our bounds are due to a refined analysis of existing approaches, while others are obtained by suggesting new algorithms. The algorithms we consider are based on network decompositions guided by a rectangular tiling of the plane. The algorithms are applied to matching, independent set, graph colouring, vertex cover, and dominating set. We also study local algorithms on quasi-UDGs, which are a popular generalisation of UDGs, aimed at more realistic modelling of communication between the network nodes. Analysing the local algorithms on quasi-UDGs allows one to assume that the nodes know their coordinates only approximately, up to an additive error. Despite the localisation error, the quality of the solution to problems on quasi-UDGs remains the same as for the case of UDGs with perfect location awareness. We analyse the increase in the local horizon that comes along with moving from UDGs to quasi-UDGs.

Microbiological characterisation of soils : Evaluation of some critical steps in data collection and experimental design

The study of soil microbiota and their activities is central to the understanding of many ecosystem processes such as decomposition and nutrient cycling. The collection of microbiological data from soils generally involves several sequential steps of sampling, pretreatment and laboratory measurements. The reliability of results is dependent on reliable methods in every step. The aim of this thesis was to critically evaluate some central methods and procedures used in soil microbiological studies in order to increase our understanding of the factors that affect the measurement results and to provide guidance and new approaches for the design of experiments. The thesis focuses on four major themes: 1) soil microbiological heterogeneity and sampling, 2) storage of soil samples, 3) DNA extraction from soil, and 4) quantification of specific microbial groups by the most-probable-number (MPN) procedure. Soil heterogeneity and sampling are discussed as a single theme because knowledge on spatial (horizontal and vertical) and temporal variation is crucial when designing sampling procedures. Comparison of adjacent forest, meadow and cropped field plots showed that land use has a strong impact on the degree of horizontal variation of soil enzyme activities and bacterial community structure. However, regardless of the land use, the variation of microbiological characteristics appeared not to have predictable spatial structure at 0.5-10 m. Temporal and soil depth-related patterns were studied in relation to plant growth in cropped soil. The results showed that most enzyme activities and microbial biomass have a clear decreasing trend in the top 40 cm soil profile and a temporal pattern during the growing season. A new procedure for sampling of soil microbiological characteristics based on stratified sampling and pre-characterisation of samples was developed. A practical example demonstrated the potential of the new procedure to reduce the analysis efforts involved in laborious microbiological measurements without loss of precision. The investigation of storage of soil samples revealed that freezing (-20 °C) of small sample aliquots retains the activity of hydrolytic enzymes and the structure of the bacterial community in different soil matrices relatively well whereas air-drying cannot be recommended as a storage method for soil microbiological properties due to large reductions in activity. Freezing below -70 °C was the preferred method of storage for samples with high organic matter content. Comparison of different direct DNA extraction methods showed that the cell lysis treatment has a strong impact on the molecular size of DNA obtained and on the bacterial community structure detected. An improved MPN method for the enumeration of soil naphthalene degraders was introduced as an alternative to more complex MPN protocols or the DNA-based quantification approach. The main advantage of the new method is the simple protocol and the possibility to analyse a large number of samples and replicates simultaneously.

Algorithms for Exact Structure Discovery in Bayesian Networks

Bayesian networks are compact, flexible, and interpretable representations of a joint distribution. When the network structure is unknown but there are observational data at hand, one can try to learn the network structure. This is called structure discovery. This thesis contributes to two areas of structure discovery in Bayesian networks: space--time tradeoffs and learning ancestor relations. The fastest exact algorithms for structure discovery in Bayesian networks are based on dynamic programming and use excessive amounts of space. Motivated by the space usage, several schemes for trading space against time are presented. These schemes are presented in a general setting for a class of computational problems called permutation problems; structure discovery in Bayesian networks is seen as a challenging variant of the permutation problems. The main contribution in the area of the space--time tradeoffs is the partial order approach, in which the standard dynamic programming algorithm is extended to run over partial orders. In particular, a certain family of partial orders called parallel bucket orders is considered. A partial order scheme that provably yields an optimal space--time tradeoff within parallel bucket orders is presented. Also practical issues concerning parallel bucket orders are discussed. Learning ancestor relations, that is, directed paths between nodes, is motivated by the need for robust summaries of the network structures when there are unobserved nodes at work. Ancestor relations are nonmodular features and hence learning them is more difficult than modular features. A dynamic programming algorithm is presented for computing posterior probabilities of ancestor relations exactly. Empirical tests suggest that ancestor relations can be learned from observational data almost as accurately as arcs even in the presence of unobserved nodes.

Water quality estimation by optical remote sensing in boreal lakes

In lake-rich regions, the gathering of information about water quality is challenging because only a small proportion of the lakes can be assessed each year by conventional methods. One of the techniques for improving the spatial and temporal representativeness of lake monitoring is remote sensing from satellites and aircrafts. The experimental material included detailed optical measurements in 11 lakes, air- and spaceborne remote sensing measurements with concurrent field sampling, automatic raft measurements and a national dataset of routine water quality measurements from over 1100 lakes. The analyses of the spatially high-resolution airborne remote sensing data from eutrophic and mesotrophic lakes showed that one or a few discrete water quality observations using conventional monitoring can yield a clear over- or underestimation of the overall water quality in a lake. The use of TM-type satellite instruments in addition to routine monitoring results substantially increases the number of lakes for which water quality information can be obtained. The preliminary results indicated that coloured dissolved organic matter (CDOM) can be estimated with TM-type satellite instruments, which could possibly be utilised as an aid in estimating the role of lakes in global carbon budgets. Based on the results of reflectance modelling and experimental data, MERIS satellite instrument has optimal or near-optimal channels for the estimation of turbidity, chlorophyll a and CDOM in Finnish lakes. MERIS images with a 300 m spatial resolution can provide water quality information in different parts of large and medium-sized lakes, and in filling in the gaps resulting from conventional monitoring. Algorithms that would not require simultaneous field data for algorithm training would increase the amount of remote sensing-based information available for lake monitoring. The MERIS Boreal Lakes processor, trained with the optical data and concentration ranges provided by this study, enabled turbidity estimations with good accuracy without the need for algorithm correction with field measurements, while chlorophyll a and CDOM estimations require further development of the processor. The accuracy of interpreting chlorophyll a via semi empirical algorithms can be improved by classifying lakes prior to interpretation according to their CDOM level and trophic status. Optical modelling indicated that the spectral diffuse attenuation coefficient can be estimated with reasonable accuracy from the measured water quality concentrations. This provides more detailed information on light attenuation from routine monitoring measurements than is available through the Secchi disk transparency. The results of this study improve the interpretation of lake water quality by remote sensing and encourage the use of remote sensing in lake monitoring.