Different roles of inositol 1,4,5-trisphosphate receptor subtypes in prostaglandin f-2 alpha-induced calcium oscillations and pacemaking activity of nrk fibroblasts

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Oscillatory activity in cells: Multi-stability and hysteresis.

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Depolarization-induced automaticity in rat ventricular cardiomyocytes is based on the gating properties of L-type calcium and slow Kv channels

Depolarization-induced automaticity (DIA) of cardiomyocytes is the property of those cells to generate pacemaker cell-like spontaneous electrical activity when subjected to a depolarizing current. This property provides a candidate mechanism for generation of pathogenic ectopy in cardiac tissue. The purpose of this study was to determine the biophysical mechanism of DIA in terms of the ion conductance properties of the cardiomyocyte membrane. First, we determined, by use of the conventional whole-cell patch-clamp technique, the membrane conductance and DIA properties of ventricular cardiomyocytes isolated from adult rat heart. Second, we reproduced and analysed DIA properties by using an adapted version of the experimentally based mathematical cardiomyocyte model of Pandit et al. (Biophys J 81:3029-3051 2001, Biophys J 84:832-841 2003) and Padmala and Demir (J Cardiovasc Electrophysiol 14:990-995 2003). DIA in 23 rat cardiomyocytes was a damped membrane potential oscillation with a variable number of action potentials and/or waves, depending on the strength of the depolarizing current and the particular cell. The adapted model was used to reconstruct the DIA properties of a particular cardiomyocyte from its whole-cell voltage-clamp currents. The main currents involved in DIA were an L-type calcium current (I (CaL)) and a slowly activating and inactivating Kv current (I (ss)), with linear (I (B)) and inward rectifier (I (K1)) currents acting as background currents and I (Na) and I (t) as modulators. Essential for DIA is a sufficiently large window current of a slowly inactivating I (CaL) combined with a critically sized repolarizing current I (ss). Slow inactivation of I (ss) makes DIA transient. In conclusion, we established a membrane mechanism of DIA primarily based on I (CaL), I (ss) and inward rectifier properties; this may be helpful in understanding cardiac ectopy and its treatment.Cardiolog

Growth-dependent modulation of capacitative calcium entry in normal rat kidney fibroblasts

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Bayesian Decision Modeling in Watershed Management - Cross River Basin, Nigeria

This paper aimed at examining simulation modeling in Bayesian Decision theory and its application in day to day decision making as well as planning in water resources and Environmental engineering. It also gives more insight in the validation of prior probability. The research objectives deals with the multi-objective value of water for its wide range of  purposes such as Power generation, water supply, Navigation, Irrigation, and Flood control, in the Cross River basin using Bayesian Modeling. In line with foregoing objectives, the research aim to achieve the following: (i) to lay bare the usefulness of the Bayesian theory that gives more than point estimation. It measures the magnitude of the difference between alternative actions and provides a variety of estimates for consideration, (ii) to present selected empirical results of a study employing decision-making theory as a framework for considering decision making under uncertainty. (iii) to evaluate the optimal policy or strategy or action that maximizes the expected benefit in the River Basin within the available limited resources and funds over the planning period of a course of action or alternatives. The multi-objectives arising from the development that were optimized include: Economic Efficiency, Regional Economic Distribution, State and Local Economic Redistribution, Youth Employment and Environmental Quality Improvement, which are primarily essential in Cross Rivers State and Nigeria. Methodology applied involving methods, experiments and data were collected for the River Basin Engineering Development, from Parastatals and Ministries. The conceptual framework on Bayesian Decision Model (BDM) as presented captured the iterative updates of prior probability toward achieving an optimum solution of a set problem. The analysis and presentation of results were based on simulation of Bayesian Models Iterations. Chi-square, Contingency and association and Pearson Product Moment Correlation were carried out as Interaction, reliability and Validity tests respectively. The study applied Bayesian Decision Model, where the following parameters were obtained:: (a)Posterior Probabilities of the States of Nature (b) Marginal Probability of the Courses of action, (c) Maximum Expected Monetary Value[EMV*] (d) Expected Profit in a Perfect Information[EPPI], (e) Expected Value of Perfect Information[EVPI], and (f) Expected Value of System Information[EVSI]. In the process of Iteration, and at some point the Prior becomes equal to the Posterior Probability, when this occurs an optimum solution is said to be achieved. However, the correlation of prior and posterior probability is equal to one (1) at the optimum solution. In conclusion, the efficiency of system information is 50%. Table 25 indicates monetary allocation to the multi-objectives which gave a clear indication that the life wire of the watershed/dam lies on it; and therefore should be comparatively considered; because without it, it will be difficult to maintain the watershed. The Basin Authority is expected to pay the researcher the Expected Value of System Information (EVSI) value of = ₦0.1billion for information generated using the Bayesian Decision theory model spreadsheet. The value of Economic efficiency optimized from 1st iteration to 2ndIteration with the EMV values of ₦2.54billion to ₦2.74billion respectively as in [ Table 4 & 15] Keywords: Optimum Solution, Prior-posterior, Probability, River Basin. DOI: 10.7176/CER/11-2-11 Publication date:March 31st 201