Fast postsynaptic inhibition in the brain is mediated by ionotropic GABA_A receptors (GABA_ARs), which are activated by the release of the neurotransmitter GABA from presynaptic interneurons. The GABA_AR is primarily permeable to chloride ions (Cl-) and therefore the transmembrane gradient for Cl- sets the reversal potential of the receptor (E_GABA-A). When intracellular Cl^- concentrations are relatively low, E_GABA-A is more negative than the membrane potential and GABA_AR responses will have a hyperpolarising and inhibitory effect upon the postsynaptic cell. In contrast, when intracellular Cl^- concentrations are relatively high, E_GABA-A will be more positive and GABA_AR activation will have a depolarising effect. How a neuron controls its intracellular Cl^- concentrations is a fundamental question that has direct relevance to hyperexcitability conditions such as epilepsy. Recently, it has become clear that Cl^- homeostasis is altered in epileptic tissue such that postsynaptic inhibition via the GABA_AR is reduced and, under some conditions, GABA_AR signalling may even be excitatory. In my thesis I explore some of the mechanisms and factors that are responsible for regulating postsynaptic GABA_AR signalling in the context of epileptic seizure activity in the rat hippocampus. In the first series of experiments I combined pharmacological approaches with electrophysiological recordings from pyramidal neurons in the CA3 region of the hippocampus to trigger seizure activity. My results show that intense neuronal activity during a seizure leads to a transient accumulation of intracellular Cl^-, which generates a pronounced depolarising shift in E_GABA-A. Under these conditions, GABAergic synapses become excitatory and contribute to ongoing neuronal activity rather than exerting their normal inhibitory role. I found that the same seizure activity also induces the release of a neuromodulator called adenosine, which serves to limit the deleterious effects of excitatory GABA_AR responses. Adenosine exerts these effects by activating downstream potassium channels, which increase the postsynaptic cell’s membrane conductance and, in doing so, ‘shunt’ incoming GABA_AR responses. In the second series of experiments I examined Cl^- homeostasis and E_GABA-A in the context of neonatal seizures. One of the main mechanisms by which neurons maintain their intracellular Cl^- levels is through the activity of ion transporter proteins that reside in the membrane and move Cl^- either into, or out of, the cell. I discovered that the intracellular trafficking of an important Cl^- transporter protein, NKCC1, correlates with changes in Cl^- homeostasis. Using a combination of biochemical and molecular techniques, I then identified a novel molecular association between NKCC1 and a motor protein, Myosin Va, which has been implicated in the intracellular trafficking of membrane proteins. Using electrophysiological recordings I found that Myosin Va is required for NKCC1’s contribution to Cl^- homeostasis, which may be important for E_GABA-A changes in epilepsy. In the final series of experiments I developed methods to study the temporal dynamics in E_GABA-A during a single seizure. These revealed a Cl^- unloading mechanism that emerges at the end of a seizure and which depends upon hyperpolarisation of the postsynaptic membrane potential. This mechanism aids E_GABA-A recovery after the seizure and moves E_GABA-A to more hyperpolarised values. This mechanism could boost postsynaptic inhibition after a seizure and thereby help to protect against further seizure episodes. In conclusion, this work extends our understanding of postsynaptic GABAergic transmission in the context of epileptic seizure activity and suggests new mechanisms that could be relevant for the development of rational anti-epileptic treatments.

The Diploma thesis is focused on attitudes of helping profession to epilepsy. The aim of theoretical part is to introduce life with epilepsy and to increase public awareness of the illness. As a part of the thesis there is refuting myths and prejudices that are often cause of negative attitudes. Helping professions are a main part of life both of epileptics and their families as well their surroundings and their attitudes affect most of it so it is main sample of the research. Theoretical part is divided into few chapters. In the initial chapter there are defined basic concepts important for good orientation in the topic - stereotypes, prejudices and attitudes. Its theories, functions and changes are further described more in detail. Next chapters describe epilepsy from medical and social aspects such as Etiology of epilepsy, epileptic seizures classification, its diagnostics and treatment are mentioned there. First aid during epileptic seizures and role of social workers are not missing. Further diploma thesis covers problematics such as social stigmatization and myths connected with epilepsy. From wider perspective impact of epilepsy on social and personal life is revealed to readers. Research part of the diploma thesis was created by quantitative method using questionnaire survey. The aim of...

Pharmacodynamic processes and disease progression are increasingly characterized with pharmacometric models. However, modelling options for discrete-type responses remain limited, although these response variables are commonly encountered clinical endpoints. Types of data defined as discrete data are generally ordinal, e.g. symptom severity, count, i.e. event frequency, and time-to-event, i.e. event occurrence. Underlying assumptions accompanying discrete data models need investigation and possibly adaptations in order to expand their use. Moreover, because these models are highly non-linear, estimation with linearization-based maximum likelihood methods may be biased. The aim of this thesis was to explore pharmacometric methods and novel models for discrete data through (i) the investigation of benefits of treating discrete data with different modelling approaches, (ii) evaluations of the performance of several estimation methods for discrete models, and (iii) the development of novel models for the handling of complex discrete data recorded during (pre-)clinical studies. A simulation study indicated that approaches such as a truncated Poisson model and a logit-transformed continuous model were adequate for treating ordinal data ranked on a 0-10 scale. Features that handled serial correlation and underdispersion were developed for the models to subsequently fit real pain scores. The performance of nine estimation methods was studied for dose-response continuous models. Other types of serially correlated count models were studied for the analysis of overdispersed data represented by the number of epilepsy seizures per day. For these types of models, the commonly used Laplace estimation method presented a bias, whereas the adaptive Gaussian quadrature method did not. Count models were also compared to repeated time-to-event models when the exact time of gastroesophageal symptom occurrence was known. Two new model structures handling repeated time-to-categorical events, i.e. events with an ordinal severity aspect, were introduced. Laplace and two expectation-maximisation estimation methods were found to be performing well for frequent repeated time-to-event models. In conclusion, this thesis presents approaches, estimation methods, and diagnostics adapted for treating discrete data. Novel models and diagnostics were developed when lacking and applied to biological observations.