Parametrizovani univerzalni editor programskog teksta

Trigeminalni neuropatski bol je hronično bolno stanje orofacijalne regije koje nastaje kao posledica povrede trigeminalnog živca. Ova vrsta bola loše ili uopšte ne reaguje na terapiju, te njegovo lečenje predstavlja veliki terapijski problem koji utiče kvalitet života pacijenta. U trigeminalnom ganglionu eksprimiran je veliki broj hemijskih medijatora, a GABA je najznačajniji inhibitorni neurotransmiter. Zbog velikog broja podjedinica i njihovih različitih kombinacija, postoji veliki broj efekata koji GABA ostvaruje. U trigeminalnom ganglionu postoje GABAA receptori koji sadrže α6 podjedinicu. Smanjenje ove podjedinice primenom male interferirajuće RNK pojačava bolni odgovor kod eksperimentalnh životinja na modelima miofacijalnog i inflamatornog bola temporomandibularnog zgloba. Trigeminalni ganglion je supstrat za razvoj većeg broja patoloških stanja koje se sreću u stomatologiji, kao što su trigeminalna neuralgija i trigerminalna neuropatija. Hipoteza ove doktorske disertacije je bila da pojačavanje aktivnosti GABAA receptora koji sadrže α6 podjedinicu utiče na smanjenje bolnog odgovora u modelu trigeminalnog neuropatskog bola. Lekovi koji potenciraju aktivnost ove grupe receptora nisu dostupni u kliničkoj praksi. U ovoj doktorskoj disertaciji korišćen je DK-I-56-1, novosintetisani selektivni modulator α6 podjedinice GABAA receptora, koji pripada grupi deuterisanih pirazolohinolinona. Sprovedena je detaljna farmakokinetička analiza ovog jedinjenja na animalnom eksperimentalnom modelu. Dobijeni rezultati pokazuju da je kinetika ovog jedinjenja u plazmi i mozgu relativno spora, sa poluvremenom eliminacije od 6 h odnosno 13 h, pri čemu je postignuta slobodna koncentracija u mozgu u rasponu 10-300 nM. Ovakav farmakokinetički profil je podesan za ispitivanje u protokolima ponavljane primene...poorly controlled by current treatments. It represents major therapeutic concern and reduces patients quality of life. Numerous chemical mediators are present in trigeminal ganglia, and GABA is most common inhbitory neurotransmitter. Due to different subunit combinations, GABA can show diversity of pharmacological effects. GABAA receptors containing α6 subunit are located in trigeminal ganglia, and their reduction by small interfering RNA increases inflammatory temporomandibular and myofascial pain in rats. One of the most common orofacial pain states like trigeminal neuralgia or trigeminal neuropathy begin in trigeminal ganglia. We thus hypothesized that enhancing GABAA receptors containing the α6 subunit activity may help in neuropathic syndromes originating from the trigeminal system. Selective modulators that activate this specific receptor population are not commercially available. In this doctoral dissertation we used recently developed deuterated pyrazoloquinolinone compound, (DK-I-56-1) that selectively activates α6 subunit of GABAA receptors. Here, we performed a detailed pharmacokinetic analysis of DK-I-56-1 on animal experimental model. Both plasma and brain tissue kinetics of DK-I-56-1 were relatively slow, with half-lives of 6 h and 13 h, respectively, enabling the persistence of estimated free brain concentrations in the range 10-300 nM throughout a 24-h period. We confirmed that chronic constriction injury of infraorbital nerve is considered a reliable experimental animal model for trigeminal neuropathic pain. Results were obtained on IoN-CCI protocol in hypersensitive rats dosed intraperitoneally with 10 mg/kg DK-I-56-1 or DK-I-87-1, structurally similar pyrazoloquinolinone compound that can not induce GABA currents on α6 containing receptors..

INVESTIGATION, DEVELOPMENT AND APPLICATION OF KNOWLEDGE BASED DIGITAL SIGNAL PROCESSING METHODS FOR ENHANCING HUMAN EEGsJ

This thesis details the development of new and reliable techniques for enhancing the human Electroencephalogram {EEGI. This development has involved the incorporation of adaptive signal processing (ASP) techniques, within an artificial intelligence (Al) paradigm, more closely matching the implicit signal analysis capabilities of the EEG expert. The need for EEG enhancement, by removal of ocular artefact (OA) , is widely recognised. However, conventional ASP techniques for OA removal fail to differentiate between OAs and some abnormal cerebral waveforms, such as frontal slow waves. OA removal often results in the corruption of these diagnostically important cerebral waveforms. However, the experienced EEG expert is often able to differentiate between OA and abnormal slow waveforms, and between different types of OA. This EEG expert knowledge is integrated with selectable adaptive filters in an intelligent OA removal system (tOARS). The EEG is enhanced by only removing OA when OA is identified, and by applying the OA removal algorithm pre-set for the specific OA type. Extensive EEG data acquisition has provided a database of abnormal EEG recordings from over 50 patients, exhibiting a variety of cerebral abnormalities. Structured knowledge elicitation has provided over 60 production rules for OA identification in the presence of abnormal frontal slow waveforms, and for distinguishing between OA types. The lOARS was implemented on personal computer (PCI based hardware in PROLOG and C software languages. 2-second, 18-channel, EEG signal segments are subjected to digital signal processing, to extract salient features from time, frequency, and contextual domains. OA is identified using a forward/backward hybrid inference engine, with uncertainty management, using the elicited expert rules and extracted signal features. Evaluation of the system has been carried out using both normal and abnormal patient EEGs, and this shows a high agreement (82.7%) in OA identification between the lOARS and an EEG expert. This novel development provides a significant improvement in OA removal, and EEG signal enhancement, and will allow more reliable automated EEG analysis. The investigation detailed in this thesis has led to 4 papers, including one in a special proceedings of the lEE, and been subject to several review articles.Department of Neurophysiology, Derriford Hospital, Plymouth, Devo

Improving program comprehension tools for domain specific languages

Dissertação de Mestrado em InformáticaSince the dawn of times, curiosity and necessity to improve the quality of their life, led humans to find means to understand everything surrounding them, aiming at improving it. Whereas the creating abilities of some was growing, the capacity to comprehend of others follow their steps. Disassembling physical objects to comprehend the connections between the pieces in order to understand how they work together is a common human behavior. With the computers arrival, humans felt the necessity of applying the same techniques (disassemble to comprehend) to their programs. Traditionally, these programs are written resorting to general-purpose programming languages. Hence, techniques and artifacts, used to aid on program comprehension, were built to facilitate the work of software programmers on maintaining and improving programs that were developed by others. Generally, these generic languages deal with concepts at a level that the human brain can hardly understand. So understanding programs written in this languages is an hard task, because the distance between the concepts at the program level and the concepts at the problem level is too big. Thus, as in politics, justice, medicine, etc. groups of words are regularly used facilitating the comprehension between people, also in programming, languages that address a specific domain were created. These programming languages raise the abstraction of the program domain, shortening the gap to the concepts of the problem domain. Tools and techniques for program comprehension commonly address the program domain and they took little advantage of the problem domain. In this master’s thesis, the hypothesis that it is easier to comprehend a program when the underlying problem and program domains are known and a bridge between them is established, is assumed. Then, a program comprehension technique for domain specific languages, is conceived, proposed and discussed. The main objective is to take advantage from the large knowledge about the problem domain inherent to the domain specific language, and to improve traditional program comprehension tools that only dealt, until then, with the program domain. This will create connections between both program and problem domains. The final result will show, visually, what happens internally at the program domain level, synchronized with what happens externally, at problem level.Desde o início dos tempos a curiosidade e a necessidade de melhorar a qualidade de vida impeliram o humano a arranjar meios para compreender o que o rodeia com o objectivo de melhorar. À medida que a habilidade de uns foi aumentando, a capacidade de compreensão de outros seguiu-lhe os passos. Desmontar algo físico de modo a compreender as ligações entre as peças e assim perceber como funcionam num todo, é um acto bastante normal dos humanos. Com o advento dos computadores e os programas para ele codificados, o homem sentiu a necessidade de aplicar as mesmas técnicas (desmontar para compreender) ao código desses programas. Tradicionalmente, a codificação de tais programas é feita usando linguagens genéricas de programação. Desde logo técnicas e artefactos que ajudam na compreensão desses programas (nessas linguagens) foram produzidas para auxiliar o trabalho de engenheiros de software que necessitam de manter ou alterar programas previamente construídos por outros. De um modo geral estas linguagens mais genéricas lidam com conceitos a um nível bastante abaixo daquele que o cérebro humano, facilmente, consegue captar. Previsivelmente, compreender programas neste tipo de linguagens é uma tarefa complexa pois a distância entre os conceitos ao nível do programa e os conceitos ao nível do problema (que o programa aborda) é bastante grande. Deste modo, tal como no dia-a-dia foram surgindo nichos como a política, a justiça, a informática, etc. onde grupos de palavras são usadas com maior regularidade para facilitar a compreensão entre as pessoas, também na programação foram surgindo linguagens que focam em domínios específicos, aumentando a abstracção em relação ao nível do programa, aproximando este do nível dos conceitos subjacentes ao problema. Ferramentas e técnicas de compreensão de programas abordam, geralmente, o domínio do programa, tirando pouco partido do domínio do problema. Na presente tese assume-se a hipótese de que será mais fácil compreender um programa quando os domínios do problema e do programa são conhecidos, e entre eles é estabelecida uma ponte de ligação; e parte-se em busca de uma técnica de compreensão de programas para linguagens de domínio específico, baseada em técnicas já conhecidas para linguagens de carácter geral. O objectivo prende-se com aproveitar o conhecimento sobre o domínio do problema e melhorar as ferramentas de compreensão de programas existentes para as linguagens genéricas, de forma a estabelecer ligações entre domínio do programa e domínio do problema. O resultado será mostrar, visualmente, o que acontece internamente ao nível do programa, sincronizadamente com o que acontece externamente ao nível do problema