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Evans Blue Reduces Neuropathic Pain Behavior by Inhibiting Spinal ATP Release
Yin,,Hong,,Phạ,m,,Shin,,Gwon,,Kwon,,Shin,,Shin,,Lee,,Lee,,Kim, MDPI AG 2019 INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES Vol.20 No.18
<P>Upon peripheral nerve injury, vesicular ATP is released from damaged primary afferent neurons. This extracellular ATP subsequently activates purinergic receptors of the spinal cord, which play a critical role in neuropathic pain. As an inhibitor of the vesicular nucleotide transporter (VNUT), Evans blue (EB) inhibits the vesicular storage and release of ATP in neurons. Thus, we tested whether EB could attenuate neuropathic pain behavior induced by spinal nerve ligation (SNL) in rats by targeting VNUT. An intrathecal injection of EB efficiently attenuated mechanical allodynia for five days in a dose-dependent manner and enhanced locomotive activity in an SNL rat model. Immunohistochemical analysis showed that EB was found in VNUT immunoreactivity on neurons in the dorsal root ganglion and the spinal dorsal horn. The level of ATP in cerebrospinal fluid in rats with SNL-induced neuropathic pain decreased upon administration of EB. Interestingly, EB blocked ATP release from neurons, but not glial cells in vitro. Eventually, the loss of ATP decreased microglial activity in the ipsilateral dorsal horn of the spinal cord, followed by a reduction in reactive oxygen species and proinflammatory mediators, such as interleukin (IL)-1β and IL-6. Finally, a similar analgesic effect of EB was demonstrated in rats with monoiodoacetate-induced osteoarthritis (OA) pain. Taken together, these data demonstrate that EB prevents ATP release in the spinal dorsal horn and reduces the ATP/purinergic receptor-induced activation of spinal microglia followed by a decline in algogenic substances, thereby relieving neuropathic pain in rats with SNL.</P>
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Generic Properties for Semialgebraic Programs
Lee, Gue Myung,Phạ,m, Tien Son Society for Industrial and Applied Mathematics 2017 SIAM journal on optimization Vol.27 No.3
<P>In this paper we study genericity for the class of semialgebraic optimization problems with equality and inequality constraints, in which every problem of the class is obtained by linear perturbations of the objective function, while the 'core' objective function and the constraint functions are kept fixed. Assume that the linear independence constraint qualification is satisfied at every point in the constraint set. It is shown that almost all problems in the class are such that (i) the restriction of the objective function on the constraint set is coercive and regular at in finity; (ii) there is a unique optimal solution, lying on a unique active manifold, at which the strict complementarity and second order sufficiency conditions, the quadratic growth condition, and the Holder type global error bound hold, and (iii) all minimizing sequences converge. Furthermore, the active manifold is constant, and the optimal solution and the optimal value function depend analytically under local perturbations of the objective function. These results are combined with a standard result about the existence of sums of squares certificates to prove that we can build a sequence of semide finite programs whose solutions give rise to a sequence of points converging to the optimal solution of the original problem in finitely many steps. It is worth emphasizing that the results of this study hold globally and we do not require the problem to be convex or the constraint set to be compact.</P>
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Stability and Genericity for Semi-algebraic Compact Programs
Lee, G. M.,Phạ,m, T. n. Springer Science + Business Media 2016 Journal of optimization theory and applications Vol.169 No.2
<P>In this paper, we consider the class of polynomial optimization problems over semi-algebraic compact sets, in which the objective functions are perturbed, while the constraint functions are kept fixed. Under certain assumptions, we establish some stability properties of the global solution map, of the Karush-Kuhn-Tucker set-valued map, and of the optimal value function for all problems in the class. It is shown that, for almost every problem in the class, there is a unique optimal solution for which the global quadratic growth condition and the strong second-order sufficient conditions hold. Furthermore, under local perturbations to the objective function, the optimal solution and the optimal value function (respectively, the Karush-Kuhn-Tucker set-valued map) vary smoothly (respectively, continuously) and the set of active constraint indices is constant. As a nice consequence, for almost every polynomial optimization problem, there is a unique optimal solution, which can be approximated arbitrarily closely by solving a sequence of semi-definite programs.</P>
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