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Keywords = applicability of MEPP

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14 pages, 4167 KiB  
Article
The Anti-Tumor Agent Sodium Selenate Decreases Methylated PP2A, Increases GSK3βY216 Phosphorylation, Including Tau Disease Epitopes and Reduces Neuronal Excitability in SHSY-5Y Neurons
by Wesal Habbab, Imad Aoudé, Freshteh Palangi, Sara Abdulla and Tariq Ahmed
Int. J. Mol. Sci. 2019, 20(4), 844; https://doi.org/10.3390/ijms20040844 - 15 Feb 2019
Cited by 11 | Viewed by 3865
Abstract
Selenium application as sodium selenate was repeatedly shown to have anti-carcinogenic properties by increasing levels of the serine/ threonine protein phosphatase 2A (PP2A) in cancer cells. PP2A has a prominent role in cell development, homeostasis, and in neurons regulates excitability. PP2A, GSK3β and [...] Read more.
Selenium application as sodium selenate was repeatedly shown to have anti-carcinogenic properties by increasing levels of the serine/ threonine protein phosphatase 2A (PP2A) in cancer cells. PP2A has a prominent role in cell development, homeostasis, and in neurons regulates excitability. PP2A, GSK3β and Tau reside together in a complex, which facilitates their interaction and (dys)-function as has been reported for several neurological disorders. In this study we recorded maximum increase in total PP2A at 3 µM sodium selenate in a neuron cell line. In conjunction with these data, whole-cell electrophysiological studies revealed that this concentration had maximum effect on membrane potentials, conductance and currents. Somewhat surprisingly, the catalytically active form, methylated PP2A (mePP2A) was significantly decreased. In close correlation to these data, the phosphorylation state of two substrate proteins, sensitive to PP2A activity, GSK3β and Tau were found to be increased. In summary, our data reveal that sodium selenate enhances PP2A levels, but reduces catalytic activity of PP2A in a dose dependent manner, which fails to reduce Tau and GSK3β phosphorylation under physiological conditions, indicating an alternative route in the rescue of cell pathology in neurological disorders. Full article
(This article belongs to the Section Molecular Neurobiology)
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18 pages, 1893 KiB  
Article
Training Concept, Evolution Time, and the Maximum Entropy Production Principle
by Alexey Bezryadin and Erik Kountz
Entropy 2016, 18(4), 145; https://doi.org/10.3390/e18040145 - 18 Apr 2016
Cited by 5 | Viewed by 5153
Abstract
The maximum entropy production principle (MEPP) is a type of entropy optimization which demands that complex non-equilibrium systems should organize such that the rate of the entropy production is maximized. Our take on this principle is that to prove or disprove the validity [...] Read more.
The maximum entropy production principle (MEPP) is a type of entropy optimization which demands that complex non-equilibrium systems should organize such that the rate of the entropy production is maximized. Our take on this principle is that to prove or disprove the validity of the MEPP and to test the scope of its applicability, it is necessary to conduct experiments in which the entropy produced per unit time is measured with a high precision. Thus we study electric-field-induced self-assembly in suspensions of carbon nanotubes and realize precise measurements of the entropy production rate (EPR). As a strong voltage is applied the suspended nanotubes merge together into a conducting cloud which produces Joule heat and, correspondingly, produces entropy. We introduce two types of EPR, which have qualitatively different significance: global EPR (g-EPR) and the entropy production rate of the dissipative cloud itself (DC-EPR). The following results are obtained: (1) As the system reaches the maximum of the DC-EPR, it becomes stable because the applied voltage acts as a stabilizing thermodynamic potential; (2) We discover metastable states characterized by high, near-maximum values of the DC-EPR. Under certain conditions, such efficient entropy-producing regimes can only be achieved if the system is allowed to initially evolve under mildly non-equilibrium conditions, namely at a reduced voltage; (3) Without such a “training” period the system typically is not able to reach the allowed maximum of the DC-EPR if the bias is high; (4) We observe that the DC-EPR maximum is achieved within a time, Te, the evolution time, which scales as a power-law function of the applied voltage; (5) Finally, we present a clear example in which the g-EPR theoretical maximum can never be achieved. Yet, under a wide range of conditions, the system can self-organize and achieve a dissipative regime in which the DC-EPR equals its theoretical maximum. Full article
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19 pages, 325 KiB  
Review
Entropy and Entropy Production: Old Misconceptions and New Breakthroughs
by Leonid M. Martyushev
Entropy 2013, 15(4), 1152-1170; https://doi.org/10.3390/e15041152 - 26 Mar 2013
Cited by 139 | Viewed by 13043
Abstract
Persistent misconceptions existing for dozens of years and influencing progress in various fields of science are sometimes encountered in the scientific and especially, the popular-science literature. The present brief review deals with two such interrelated misconceptions (misunderstandings). The first misunderstanding: entropy is a [...] Read more.
Persistent misconceptions existing for dozens of years and influencing progress in various fields of science are sometimes encountered in the scientific and especially, the popular-science literature. The present brief review deals with two such interrelated misconceptions (misunderstandings). The first misunderstanding: entropy is a measure of disorder. This is an old and very common opinion. The second misconception is that the entropy production minimizes in the evolution of nonequilibrium systems. However, as it has recently become clear, evolution (progress) in Nature demonstrates the opposite, i.e., maximization of the entropy production. The principal questions connected with this maximization are considered herein. The two misconceptions mentioned above can lead to the apparent contradiction between the conclusions of modern thermodynamics and the basic conceptions of evolution existing in biology. In this regard, the analysis of these issues seems extremely important and timely as it contributes to the deeper understanding of the laws of development of the surrounding World and the place of humans in it. Full article
(This article belongs to the Special Issue Maximum Entropy Production)
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13 pages, 210 KiB  
Article
Modeling Electric Discharges with Entropy Production Rate Principles
by Thomas Christen
Entropy 2009, 11(4), 1042-1054; https://doi.org/10.3390/e11041042 - 8 Dec 2009
Cited by 17 | Viewed by 12850
Abstract
Under which circumstances are variational principles based on entropy production rate useful tools for modeling steady states of electric (gas) discharge systems far from equilibrium? It is first shown how various different approaches, as Steenbeck’s minimum voltage and Prigogine’s minimum entropy production rate [...] Read more.
Under which circumstances are variational principles based on entropy production rate useful tools for modeling steady states of electric (gas) discharge systems far from equilibrium? It is first shown how various different approaches, as Steenbeck’s minimum voltage and Prigogine’s minimum entropy production rate principles are related to the maximum entropy production rate principle (MEPP). Secondly, three typical examples are discussed, which provide a certain insight in the structure of the models that are candidates for MEPP application. It is then thirdly argued that MEPP, although not being an exact physical law, may provide reasonable model parameter estimates, provided the constraints contain the relevant (nonlinear) physical effects and the parameters to be determined are related to disregarded weak constraints that affect mainly global entropy production. Finally, it is additionally conjectured that a further reason for the success of MEPP in certain far from equilibrium systems might be based on a hidden linearity of the underlying kinetic equation(s). Full article
(This article belongs to the Special Issue What Is Maximum Entropy Production and How Should We Apply It?)
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