Migraine patients often demonstrate cutaneous allodynia, defined as a hypersensitivity of the skin to touch or mechanical stimuli that is considered non-noxious under normal circumstances. The allodynia sometimes begins intracranially and spreads, via unknown mechanisms, to extracranial regions. The goal of the study was to develop and validate a model of cutaneous allodynia triggered by dural inflammation for pain associated with headaches, and to explore neuronal and glial mechanisms underlying generalized allodynia. Inflammatory mediators (IM) were applied to the dura of unanesthetized rats via previously implanted cannulas and sensory thresholds of the face and hindpaws were characterized. IM elicited robust and time-related facial and hindpaw allodynia which peaked after approximately three hours as well as FOS expression in the trigeminal nucleus caudalis (TNC), indicative of central sensitization. These effects were reminiscent of cutaneous allodynia seen in patients with migraine or other primary headache conditions, and were reversed by agents used clinically in the treatment of migraine including sumatriptan, naproxen, CGRP-antagonist, and morphine. Consistent with clinical observations, the allodynia was unaffected by an NK-1 antagonist. Having established facial and hindpaw allodynia as a useful animal surrogate of headache-associated allodynia, we next showed that blocking pain-facilitating processes from the rostral ventromedial medulla (RVM) interfered with its expression. Inactivation of the RVM with local anesthetic, destruction of putative pain-facilitation cells, and blockade of cholecystokinin receptors all prevented or significantly attenuated IM-induced allodynia. Electrophysiological studies confirmed activation of pain-facilitating "ON" cells and transient suppression of "OFF" cells in the RVM following IM. Additionally, microinjection of the RVM with a microglial inhibitor or sumatriptan also inhibited the expression of IM-induced cutaneous allodynia as well as microglial activation. Facial and hindpaw allodynia associated with dural stimulation is a useful surrogate of pain associated with primary headache including migraine and may be exploited mechanistically for the development of novel therapeutic strategies for headache pain. The data also demonstrate a requirement for activation of descending facilitation from the RVM, likely reliant on neuronal-glial interactions, for the expression of cranial and extracranial cutaneous allodynia. Consequently, the findings are consistent with a brainstem generator of allodynia associated with headache disorders.

The adverse interaction between smoking and chronic pain has been known for decades. A variety of chronic pain conditions – ranging from headache to low back pain to fibromyalgia – markedly exacerbate smoking prevalence and intensity in packs per day among multiple patient populations. In patients seeking pain treatment, the prevalence of smoking approaches 50%, compared to less than 20% in the general population. Perhaps not surprisingly, the relationship is bidirectional: not only does persistent pain increase rates and intensity of smoking, but smoking also appears to exacerbate both the intensity and associated impairment of chronic pain. In fact, smoking appears to place individuals at risk for developing a chronic pain condition and may also facilitate the transition from acute to chronic pain. The growing body of literature documenting these associations has led to the proposition of a positive feedback loop: individuals smoke in part to cope with their pain, but smoking actually worsens the pain. Despite the strong evidence for the existence of this adverse interaction, the mechanisms responsible for it remain poorly understood. A number of preclinical and clinical studies have documented that nicotinic acetylcholine receptor (nAChR) agonists, e.g., nicotine, have analgesic efficacy in the acute pain setting, such as that produced experimentally in the research laboratory or experienced by patients postoperatively. In contrast, the role of nAChR activation in modulating chronic pain is less well characterized. The experiments described in this thesis determine whether persistent pain diminishes the antinociceptive (analgesic) efficacy of an α4β2 nAChR agonist in the rostral ventromedial medulla (RVM), a key brainstem pain modulatory nucleus, and subsequently begin to elucidate the mechanisms by which persistent pain elicits this plasticity. The complete Freund’s adjuvant (CFA) model of chronic pain was employed to test the hypothesis that persistent inflammatory injury diminishes the antinociceptive efficacy of the selective and potent α4β2 nAChR agonist epibatidine in key brainstem pain modulatory nuclei. Paw withdrawal latency to a noxious heat stimulus was used to evaluate the anti-hyperalgesic and antinociceptive effects of epibatidine microinjected in the RVM or periaqueductal gray (PAG) of male rats. The effects of epibatidine were assessed both in uninjured animals and in animals at different times after intraplantar CFA injection. Interestingly, pretreatment with an α4β2-selective antagonist demonstrated that the antinociceptive effects of epibatidine in naïve rats were mediated by α4β2 nAChRs in the RVM but not in the PAG. While the antinociceptive effects of epibatidine in the RVM were abolished after two weeks of inflammatory pain, the anti-hyperalgesic effects remained unchanged. Surprisingly, epibatidine no longer appeared to be acting primarily at α4β2 nAChRs as early as four hours after injury. Persistent inflammation did not alter the anti-hyperalgesic or antinociceptive effects of epibatidine in the PAG. Radioligand binding studies were conducted to test the most parsimonious hypothesis that a global reduction in α4β2 nAChR number or binding affinity during persistent injury was in part responsible for the decreased efficacy of epibatidine in the RVM after intraplantar CFA. Saturation binding using [3H]-epibatidine in membrane homogenates prepared from RVM and PAG tissue revealed no differences in receptors between saline- and CFA-treated rats at any time after injury, suggesting that a whole-nucleus reduction in nAChRs could not explain the observed behavioral phenomena. To query functional changes with greater resolution, whole-cell patch clamp electrophysiology was employed to begin assessing the consequences of nAChR activation by nicotine at the level of the neuron. Initial studies performed in the locus coeruleus demonstrated that all neurons responded to nicotine with an inward current that desensitized with continued exposure to the drug. Neurons in the RVM exhibited significantly more heterogeneity in their response to nicotine: desensitizing inward currents were seen in some; sustained outward currents in others; inward currents followed by outward currents in a third population; and still others had no response to nicotine exposure. The sustained outward currents persisted in the presence of the sodium channel blocker tetrodotoxin, were not blocked by an α4β2 nAChR-selective antagonist, and appeared to be mediated by G protein-coupled receptors and potassium channels. Taken together, the present results demonstrate that persistent inflammatory injury produces adaptive changes in nicotinic signaling in the RVM such that the antinociceptive effects of epibatidine activation are abolished in a time-dependent manner. These changes cannot be attributed to a whole-nucleus reduction in α4β2 nAChRs. However, nicotinic signaling in the RVM is complex, and small alterations in the pre- or postsynaptic actions of nicotine may have significant ramifications for the overall nociceptive sensitivity of an animal. The data presented here suggest that plasticity in nicotinic signaling within the bulbospinal pain modulatory pathways may in part explain the adverse interaction between smoking and chronic pain observed in humans.

Sustained administration of morphine in humans and in animals induces a state of abnormal pain (i.e., hyperalgesia) which may be associated with the development of reduced analgesic efficacy (i.e., tolerance). Evidence suggests that opiate treatment may upregulate cholecystokinin (CCK), a pronociceptive peptide, in the brain and spinal cord. Therefore, we hypothesized that CCK may be upregulated by opiate treatment in the rostral ventromedial medulla (RVM) and to subsequently drive descending facilitation mechanisms to elicit hyperalgesia and antinociceptive tolerance in rats.CCK administered into the RVM of naive rats elicited hyperalgesia which was blocked by either RVM CCK2 receptor antagonist L365,260; or by bilateral lesion of dorsolateral funiculus, a major bulbospinal descending pain modulation pathway from the RVM to spinal cord.Sustained subcutaneous morphine induced hyperalgesia and spinal antinociceptive tolerance. Both effects were reversed by RVM CCK2 antagonist, suggesting that the up-regulation of the endogenous RVM CCK system played a critical role in the expression of these phenomena.Lesion of cells in the RVM which selectively express CCK2 receptors with a saporin construct (CCK-SAP) to inhibit ribosome activity, prevented morphine-induced hyperalgesia and spinal antinociceptive tolerance. These findings suggest that the integrity of the RVM CCK system is required for the development of hyperalgesia and antinociceptive tolerance induced by sustained morphine.The CCK system does not seem to play a role in setting the baseline sensory thresholds in normal rats because neither RVM L365,260 nor CCK-SAP treatment altered baseline sensory thresholds in naive rats.CCK appears to be present exclusively in nerve terminals of RVM neurons in naive rats. There was no obvious change in the levels of CCK-LI, CCK2 receptor, or CCK2 receptor mRNA in the RVM after sustained morphine treatment. However, microdialysis studies showed an approximately 5-fold increase in basal CCK levels in the RVM after sustained morphine treatment.Taken together, our results support the hypothesis that increased release of CCK in the RVM is induced by sustained morphine and drives descending facilitation to mediate morphine-induced paradoxical "pain" and spinal antinociceptive tolerance.

Chronic pain is a significant healthcare problem. It is disabling and diminishes quality of life. Opioids, such as morphine, remain a primary pharmacologic management for chronic pain. Opioids act at mu opioid receptors (MOPr) in the rostroventral medial medulla (RVM) to produce their analgesic effect. The RVM is a critical relay in pain inhibitory and facilitatory pathways of pain modulation. Furthermore, chronic inflammatory pain, produced by CFA hindpaw injection, leads to adaptive changes in the RVM that change the balance of these pathways and increase the potency of opioids. MOPr are known to produce their effects via Gi/o proteins. Pretreatment of several pain modulatory regions with pertussis toxin (PTX) effectively attenuates the antinociceptive effects of MOPr agonists, such as DAMGO. In the RVM, PTX effectively reduced DAMGO stimulated GTPãS binding in uninjured rats. However, despite their effective inactivation of Gi/o proteins, PTX did not diminish the antinociceptive effects of DAMGO in the RVM of uninjured rats. In contrast, in rats with a chronic inflammatory injury, PTX completely abolished the antinociceptive effects of DAMGO. These results suggest a transition from Gi/o independent to Gi/o dependent mechanisms following CFA treatment. In addition, the anti-hyperalgesic effects of DAMGO were not inhibited by PTX, suggesting that DAMGO produces anti-hyperalgesia and antinociception by different mechanisms. In the RVM, MOPr are present both postsynaptically and presynaptically. Postsynaptic MOPr are thought to produce antinociception by activating GIRK channels, resulting in hyperpolarization and inhibition of pain facilitatory neurons. Indeed, inhibition of GIRK channels in the RVM, via microinjection of tertiapin-Q, attenuated the antinociceptive effects of DAMGO in uninjured rats, providing the first behavioral evidence that MOPr agonists produce analgesia via this proposed mechanism. Interestingly, however, tertiapin-Q did not block the anti-hyperalgesic effects of DAMGO, nor did it diminish the antinociceptive effects of DAMGO in the contralateral hindpaw of CFA treated rats. Furthermore, these differential effects of tertiapin-Q in the uninjured and injured rats are not the result of transcriptional down regulation of GIRK channels in the RVM. Finally, tertiapin-Q alone in the RVM produced a modest antinociception in uninjured rats, providing the first evidence of constitutive GIRK channel activity in the RVM and demonstrating a role for these in pain modulation. Presynaptic MOPr are thought to produce antinociception by decreasing GABA release onto pain inhibitory neurons. Indeed, microdialysis studies demonstrated that levels of GABA release were decreased in response to DAMGO perfused into the RVM, as well as to high potassium after perfusion of DAMGO. However, they were not decreased in rats after CFA treatment. This suggests that chronic inflammatory injury alters the presynaptic actions of MOPr agonists in the RVM. Interestingly, levels of GLU release where not altered by DAMGO in uninjured or injured rats. Moreover, basal levels of GLU and GABA were also unaltered by CFA treatment. In conclusion, although MOPr mediate their antinociceptive effects in other pain modulatory regions via Gi/o proteins, this is not the case in the RVM during an uninjured state. However, MOPr-induced antinociception transitions from Gi/o independent to Gi/o dependent mechanisms after CFA treatment. Additionally, these results support both the presynaptic and the postsynaptic postulates by which MOPr agonists are thought to produce their analgesic effects. However, although CFA treatment alters the activity of neurons in the RVM and promotes changes that result in an enhanced anti-hyperalgesic and antinociceptive response to DAMGO in the RVM, neither the postsynaptic nor the presynaptic mechanism, in isolation, seem to account for this enhancement.

Decision making in environmental management is faced with uncertainties associated with related environmental variables and processes. Decision makers are inclined to use resources to acquire better information in one or more uncertain variable(s). Typically, with limited resources available, characterizing the feasibility of such investment is desirable yet complicated. In the context of reducing inherent uncertainty, decision makers need to tackle two difficult questions, first, the optimal selection of variable(s) and second, the optimal level of information collection which produces maximum gain in benefits. We develop a new framework to assess the socioeconomic value of potential decisions of collecting additional information for given variable(s) to reduce inherent uncertainty. The suggested framework employs advanced social welfare concepts to facilitate eliciting the social acceptability of decisions to collect better information. The framework produces estimates of changes in utility levels and willingness to pay for target population using the benefit transfer method. The practicality of the framework is established using the following common problems in the field of water resources: 1) the uncertainty in exposure to health risk due to drinking a groundwater source contaminated with a carcinogen, 2) the uncertainty in non point source pollution loadings due to unknown hydrologic processes variability, and 3) the equity level in allocating mitigation responsibilities among polluters. For the three applications, the social acceptability of potential decisions is expressed in monetary terms which represent an extension on typical cost benefit analysis by including the socioeconomic value of a decision. The specific contribution of this research is a theoretical framework for a detailed preliminary analysis to transform and represent the given problem in useable terms for the social welfare analysis. The practical framework is attractive because it avoids the need to employ prohibitively expensive survey-based contingent valuation methods. Instead, the framework utilizes benefit transfer method, which imposes a theoretical behavioral structure on population characteristics such as age and income and to produce empirical estimates for a new problem setting.

No description available.

No description available.

Today the modern power system is more dynamic and its operation is a subject to a number of constraints that are reflected in various management and planning tools used by system operators. In the case of hourly generation planning, Economic Dispatch (ED) allocates the outputs of all committed generating units, which are previously identified by the solution of the Unit Commitment (UC) problem. Thus, the accurate solutions of the ED and UC problems are essential in order to operate the power system in an economic and efficient manner. A number of computation techniques have progressively been proposed to solve these critical issues. One of them is a Particle Swarm Optimisation (PSO), which belongs to the evolutionary computation techniques, and it has attracted a great attention of the research community since it has been found to be extremely effective in solving a wide range of engineering problems. The attractive characteristics of PSO include: ease of implementation, fast convergence compared with the traditional evolutionary computation techniques and stable convergence characteristic. Although the PSO algorithms can converge very quickly towards the optimal solutions for many optimisation problems, it has been observed that in problems with a large number of suboptimal areas (i.e. multi-modal problems), PSO could get trapped in those local minima, including ED and UC problems. Aiming at enhancing the diversity of the traditional PSO algorithms, this thesis proposes a method of combining the PSO algorithms with a real-valued natural mutation (RVM) operator to enhance the global search capability and investigate the performance of the proposed algorithm compared with the standard PSO algorithms and other algorithms. Prior to applying to ED and UC problems, the proposed method is tested with some selected mathematical functions where the results show that it can avoid being trapped in local minima. The proposed methodology is then applied to ED and UC problems, and the obtained results show that it can provide solutions with good accuracy and stable convergence characteristic with simple implementation and satisfactory calculation time. Furthermore, the sensitivity analysis of PSO parameters has been studied so as to investigate the response of the proposed method to the parameter variations, especially in both ED and UC problems. The outcome of this research shows that the proposed method succeeds in dealing with the PSO' s drawbacks and also shows the superiority over the traditional PSO algorithms and other methods in terms of high quality solutions, stable convergence characteristic, and robustness.

No description available.

Forecasting procedures have found applications in a wide variety of areas within finance and have further shown to be one of the most challenging areas of finance. Having an immense variety of economic data, stakeholders aim to understand the current and future state of the market. Since it is hard for a human to make sense out of large amounts of data, different modeling techniques have been applied to extract useful information from financial databases, where machine learning techniques are among the most recent modeling techniques. Binary classifiers such as Support Vector Machines (SVMs) have to some extent been used for this purpose where extensions of the algorithm have been developed with increased prediction performance as the main goal. The objective of this study has been to develop a process for improving the performance when predicting the sign of return of financial time series with soft margin classifiers. An analysis regarding the algorithms is presented in this study followed by a description of the methodology that has been utilized. The developed process containing some of the presented soft margin classifiers, and other aspects of kernel methods such as Multiple Kernel Learning have shown pleasant results over the long term, in which the capability of capturing different market conditions have been shown to improve with the incorporation of different models and kernels, instead of only a single one. However, the results are mostly congruent with earlier studies in this field. Furthermore, two research questions have been answered where the complexity regarding the kernel functions that are used by the SVM have been studied and the robustness of the process as a whole. Complexity refers to achieving more complex feature maps through combining kernels by either adding, multiplying or functionally transforming them. It is not concluded that an increased complexity leads to a consistent improvement, however, the combined kernel function is superior during some of the periods of the time series used in this thesis for the individual models. The robustness has been investigated for different signal-to-noise ratio where it has been observed that windows with previously poor performance are more exposed to noise impact.