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Solid phase extraction is one of the most widely used techniques to trap and release compounds in a solution. A hydrophobic substance will stick efficiently to a hydrophobic surface (the “like dissolves like” principle). With an introduced response (i.e. pH change), a responsive surface can change from hydrophobic to hydrophilic, weakening the hydrophobic substance’s attraction and thus facilitate in an easy removal. A surface has been prepared having a terminal anthranilic acid (AA) moiety on silica gel particles, microscope slides, and TLC plates in three steps. First, a vinyl group was attached to the surface. Then, this vinyl group was reacted to form a surface carboxylic acid group. Finally, the carboxylic acid group was converted to an amide group that linked to the silica surface. FT-IR, and elemental analysis were used to confirm each step of the synthesis. At low pHs the –COOH group on the AA moiety is neutral and intrahydrogen bonding keeps this moiety’s phenyl (hydrophobic) portion exposed to the surface. The effect has been investigated by measuring contact angles at various pH values. At higher pHs the AA’s carboxylic acid group becomes the charged carboxylate, rendering the surface hydrophilic. Substances can be trapped and released using this unique switching approach. 2-naphthol, for example, is hydrophobic and thus was trapped at lower pHs (pH 4) (hydrophobic surface) and released at higher pHs (pH 10) (hydrophilic surface) on this responsive surface

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Studies have shown that long-term opioid agonist (such as morphine) treatment produces antinociceptive tolerance and increased pain sensitivity (hyperalgesia and/or allodynia), limiting the clinical efficacy of morphine. Prolonged opiate administration also upregulates spinal pain neurotransmitter (such as calcitonin gene-related peptide (CGRP)) levels and enhances evoked CGRP release in the dorsal horn of rats. It was suggested that augmented spinal pain neurotransmission may contribute to paradoxical pain sensitization and antinociceptive tolerance. The cellular signal transduction pathways involved in sustained opioid mediated augmentation of spinal pain neurotransmitter are not fully clarified.Sustained morphine treatment was shown to augment the concentrations of inflammatory mediators, such as PGE2 in the spinal cord. Studies have shown that PGE2 stimulates cAMP formation and CGRP release by activation of Gs protein-coupled prostaglandin receptor types in primary sensory neurons. Interestingly, it was found earlier that sustained opioid agonist treatment leads to a Raf-1-dependent sensitization of adenylyl cyclase(s) (AC superactivation), augmenting forskolin-stimulated cAMP formation upon opioid withdrawal (cAMP overshoot). It is well demonstrated that cAMP activates cAMP-dependent protein kinase (PKA), which plays an important role in the modulation of presynaptic neurotransmitter release. Therefore, in this study, we investigate the physiological role of Raf-1 mediated AC superactivation and subsequent PKA activation in A. sustained morphine-mediated augmentation of basal or evoked pain neurotransmitter release in vitro, in cultured primary sensory neurons, and B. in vivo, in sustained morphine mediated paradoxical pain sensitization and antinociceptive tolerance in rats.Our data demonstrates that A. sustained morphine treatment augments both basal and capsaicin-evoked CGRP release from isolated primary sensory neurons in a PKA- and Raf-1- dependent manner. B. sustained morphine treatment- augments of PGE2-evoked CGRP release from these cells. C. selective knockdown of spinal PKA or Raf-1 protein levels by intrathecal PKA- or Raf-1-specific siRNA pretreatment completely attenuates sustained morphine-mediated thermal hyperalgesia, tactile allodynia and greatly reduces antinociceptive tolerance in rats.In conclusion, we suggest that Raf-1-mediated AC superactivation may have a crucial trigger role in sustained morphine-mediated compensatory adaptations in the nervous system. Thus, we expect that pharmacological attenuation of Raf-1-mediated AC superactivation may improve the clinical treatment of chronic and neuropathic pain.

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Forecasting firms' earnings has long been an interest of market participants and academics. Traditional forecasting studies in a multivariate time series setting do not take into account that the timing of market data release for a specific time period of observation is often spread over several days or weeks. This thesis focuses on the separation of announcement timing or data release and the use of econometric real-time methods, which we refer to as an updated vector autoregression (VAR) forecast, to predict data that have yet to be released. In comparison to standard time series forecasting, we show that the updated forecasts will be more accurate the higher the correlation coefficients among the standard VAR innovations are. Forecasting with the sequential release of information has not been studied in the VAR framework, and our approach to U.S. nonfarm payroll employment and the six Canadian banks shows its value. By using the updated VAR forecast, we conclude that there are relative efficiency gains in the one-step-ahead forecast compared to the ordinary VAR forecast, and compared to professional consensus forecasts. Thought experiments emphasize that the release ordering is crucial in determining forecast accuracy. / Thesis (Ph.D, Economics) -- Queen's University, 2010-04-30 12:34:42.629

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This study is undertaken to improve the performance of a Chemotherapy Treatment Unit by increasing the throughput of the clinic and reducing the average patients’ waiting time. In order to achieve this objective, a simulation model of this system is built and several scenarios that target matching the arrival pattern of the patients and resources availability are designed and evaluated. After performing detailed analysis, one scenario proves to provide the best system’s performance. The best scenario determines a rational arrival pattern of the patient matching with the nurses’ availability and can serve 22.5% more patients daily. Although the simulation study shows the way to serve more patients daily, it does not explain how to sequence them properly to minimize the average patients’ waiting time. Therefore, an efficient scheduling algorithm was developed to build a scheduling template that minimizes the total flow time of the system.