A comparative analysis of linear,nonlinear and improved nonlinear thermodynamic models of voltage-dependent ion channel kinetics

The linear, nonlinear and improved nonlinear thermodynamic models of the voltage-dependent ion channels were proposed to deduce the exact functional form of the rate constants. In this context, we present a comparative analysis of the linear, nonlinear and improved nonlinear thermodynamic models of voltage-dependent channel kinetics based on the sodium activation experimental data of Cav3.1 channel. We also provide some insight on the assumptions used to derive the thermodynamic models of the channels and show that the improved nonlinear thermodynamic model provides a simple and physically plausible approach to describe the behavior of the voltage-dependent ion channels.     

Surface-charge-governed ion transport in nanofluidic channels

A study of ion transport in aqueous-filled silica channels as thin as 70 nm reveals a remarkable degree of conduction at low salt concentrations that departs strongly from bulk behavior: In the dilute limit, the electrical conductances of channels saturate at a value that is independent of both the salt concentration and the channel height. Our data are well described by an electrokinetic model parametrized only by the surface-charge density. Using chemical surface modifications, we further demonstrate that at low salt concentrations, ion transport in nanochannels is governed by the surface charge.     

随机中毒对神经元网络时空动力学行为的影响

神经元细胞膜上的离子通道能够被一些有毒的化学物质阻断. 离子通道阻断会降低离子通道的电导率和激活通道数, 影响神经元的放电活动, 进而影响神经网络时空模式的动力学行为. 本文采用具有周期边界的近邻耦合Hodgkin-Huxley神经元网络, 数值研究了钠离子和钾离子通道随机中毒时神经网络时空模式的演化过程. 发现钠离子和钾离子通道随机中毒可以导致螺旋波破裂. 通过分析网络的放电概率, 发现钠离子通道随机中毒降低了神经网络的兴奋性, 且其对中毒的敏感程度与噪声强度有关; 钾离子通道随机中毒增强了神经网络的兴奋性. 与均匀的通道中毒相比, 随机通道中毒的神经网络具有更丰富的动力学行为. 最后, 采用无流边界条件对神经网络进行数值仿真, 得到了类似的结果. 该研究更真实地反映神经系统中毒时整体兴奋性的变化, 从另一个方面揭示离子通道中毒对网络时空行为的影响, 有利于更进一步理解离子通道在网络整体行为中的作用. 关键词： 神经网络 离子通道 随机中毒 时空动力学     

Biexponential distribution of open times of a toy channel model

The biexponential distributions of open times are observed in various types of ion channels. In this paper, by discussing a simple channel model, we show that there are two different schemes to understand the biexponential distribution of open times. One scheme is mathematically strict based on generator matrix theory, while the other one has a clear physical explanation according to an approximation process with numerical simulation of Markovian channel dynamics. Our comparison results suggest that even for biologically complex channels, in addition to carrying out a stochastic simulation,the strict theoretical analysis should be considered to understand the multiple exponential distributions of open times.     

Channel temporal correlation-based optimization method for imperfect underwater acoustic channel state information

The rapid time variations and large channel estimation errors in underwater acoustic (UWA) channels mean that transmitters for adaptive resource allocation quickly become outdated and provide inaccurate channel state information (CSI). This results in poor resource allocation efficiency. To address this issue, this paper proposes an optimization approach for imperfect CSI based on a Gauss–Markov model and the per-subcarrier channel temporal correlation (PSCTC) factor. The proposed scheme is applicable to downlink UWA orthogonal frequency division multiple access systems. The proposed PSCTC factors are measured, and their long-term stability is verified using data recorded in real-world sea tests. Simulation and experimental results show that the optimized CSI effectively mitigates the effects of the temporal variability of UWA channels. It demonstrates that the resource allocation scheme using optimized CSI achieves a higher effective throughput and a lower bit error rate than both imperfect CSI and the CSI predicted by the recursive least-squares (RLS) algorithm.     

Physical properties of voltage gated pores

Experiments on single ionic channels have contributed to a large extent to our current view on the function of cell membrane. In these experiments the main observables are the physical quantities: ionic concentration, membrane electrostatic potential and ionic fluxes, all of them presenting large fluctuations. The classical theory of Goldman–Hodking–Katz assumes that an open channel can be well described by a physical pore where ions follow statistical physics. Nevertheless real molecular channels are active pores with open and close dynamical states. By skipping the molecular complexity of real channels, here we present the internal structure and calibration of two active pore models. These models present a minimum set of degrees of freedom, specifically ion positions and gate states, which follow Langevin equations constructed from a unique potential energy functional and by using standard rules of statistical physics. Numerical simulations of both models are implemented and the results show that they have dynamical properties very close to those observed in experiments of Na and K molecular channels. In particular a significant effect of the external ion concentration on gating dynamics is predicted, which is consistent with previous experimental observations. This approach can be extended to other channel types with more specific phenomenology.     

Speeding up Training of Linear Predictors for Multi-Antenna Frequency-Selective Channels via Meta-Learning

An efficient data-driven prediction strategy for multi-antenna frequency-selective channels must operate based on a small number of pilot symbols. This paper proposes novel channel-prediction algorithms that address this goal by integrating transfer and meta-learning with a reduced-rank parametrization of the channel. The proposed methods optimize linear predictors by utilizing data from previous frames, which are generally characterized by distinct propagation characteristics, in order to enable fast training on the time slots of the current frame. The proposed predictors rely on a novel long short-term decomposition (LSTD) of the linear prediction model that leverages the disaggregation of the channel into long-term space-time signatures and fading amplitudes. We first develop predictors for single-antenna frequency-flat channels based on transfer/meta-learned quadratic regularization. Then, we introduce transfer and meta-learning algorithms for LSTD-based prediction models that build on equilibrium propagation (EP) and alternating least squares (ALS). Numerical results under the 3GPP 5G standard channel model demonstrate the impact of transfer and meta-learning on reducing the number of pilots for channel prediction, as well as the merits of the proposed LSTD parametrization.     

Coupling of Simultaneous Fluorescence and Electrophysiology: Historical Survey, Contributions, and Prospects

The coupling of simultaneous fluorescence and eleclrophysiological measurements paved the way for the development of potentiometric and intracellular free ion-sensitive probes, although the basic and initial aim of these combined studies remains to record fast conformational changes during ion channel activation. Recent high-resolution studies of some channels put back on the agenda challenging methods that combine spectroscopy and electrophysiology. Fluorescence is certainly the most versatile and sensitive spectroscopy in this kind of experiment, and we have recently witnessed significant breakthroughs, at the level of whole cells with intact or mutated channels or with planar lipid bilayers doped with channels or their peptide models. After our initial study of membrane dynamics associated with excitability, following transient pyrene excimer signals during action potentials or voltage-clamp of nerve fibers, we tested the feasability of FRAP (fluorescence recovery after photobleaching) experiments on planar lipid bilayers. This technique was later applied to lateral diffusion measurements of channel forming peptides (alamethicin labeled with fluorescein and the voltage-sensitive segment S4 of the Shaker potassium channel labeled with NBD) under applied voltage. We provide independent evidence for voltage-dependent partitioning and transmembrane insertion and propose renewed experimental avenues to reveal movements and conformational changes associated with ion channel gating and opening.     

Physics of size selectivity

We demonstrate that two mechanisms used by biological ion channels to select particles by size are driven by entropy. With uncharged particles in an infinite cylinder, we show that a channel that attracts particles is small-particle selective and that a channel that repels water from the wall is large-particle selective. Comparing against the extensive density-functional theory calculations of our model, we find that the main physics can be understood with surprisingly simple bulk models that neglect the confining geometry of the channel completely.     

Calculation of the conductance and selectivity of an ion-selective potassium channel (IRK1) from simulation of atomic scale models

We present the equations and methodology for the theoretical prediction of the conductance, permeability and selectivity of a K⁺ channel on the basis of atomic scale models for it. The methodology involves the use of Langevin dynamics and activated trajectories in order to obtain translocation free energies, rate constants and transmission coefficients for an ion going through the channel. The models are for the Inward Rectifier K⁺ channel (IRK1) which is a member of a family of ion-selective K⁺ channels. The IRK1 channel is biologically important because of its role in cardiac pacemaker function. The models we use for the IRK1 channel are developed from a model of the Shaker voltage-gated K⁺ channel. We find that the theoretically predicted conductance is too low by three orders of magnitude. We attribute this underestimate to a specific structural defect in the model used. Perhaps our most significant result is that the computed conductance is tremendously sensitive to the structural details of the so-called ‘P-loop’ that lines the outer half of the permeation pathway of the channel. This sensitivity may be useful in future studies on ion channel proteins for which the structure is not known from X-ray crystallography. In addition, this sensitivity may help determine whether X-ray structures of these proteins correspond to open or closed conformations.     

Investigation on Heat Transfer and Pressure Drop of Copper–Water Nanofluid Flow in Plain and Perforated Channels

This article reports an experimental study on copper–water nanofluid flow inside plain and perforated channels. The effects of flow rate and nanoparticle concentration on the heat transfer and pressure drop are studied. It is found that the perforated channel has a remarkable heat transfer enhancement of 24.6%. Furthermore, by using the copper–water nanofluid instead of the base fluid, the heat transfer coefficient as well as pressure drop are increased for both plain and perforated channels. A noticeable thermal performance factor of 1.34 is obtained for the simultaneous utilization of both the heat transfer enhancement techniques considered in this article.     

Statistical model of current-coupled ion channels in nerve membranes

A statistical model of a driven system is developed. Its microscopic elements are the ion channels through a nerve membrane. Their conductances are stochastically switching under the competing influences of thermal noise and local membrane voltage. A current flow through the membrane induces a coupling between the channels via the electrolytes surrounding the membrane. The long range of the coupling permits a generalized mean field theory for the stationary membrane current as a function of the applied electrode voltage. We derive analytically the macroscopic conductance-voltage-temperature relation for the spatially uniform current state. It shows analogues of first and second order phase transitions. The critical temperature diverges at a finite coupling strength. The theory fits sodium conductance characteristics measured on nerve axon membranes from various species by a variation of only the coupling strength. This supports the hypothesis that this simplest possible model for sodium channels is universal for all species.The work of this author was partially supported by the Deutsche Forschungsgemeinschaft     

Mechanisms for improving mass transfer in food with ultrasound technology: Describing the phenomena in two model cases

The aim of this work was to demonstrate how ultrasound mechanisms (direct and indirect effects) improve the mass transfer phenomena in food processing, and which part of the process they are more effective in. Two model cases were evaluated: the hydration of sorghum grain (with two water activities) and the influx of a pigment into melon cylinders. Different treatments enabled us to evaluate and discriminate both direct (inertial flow and “sponge effect”) and indirect effects (micro channel formation), alternating pre-treatments and treatments using an ultrasonic bath (20 kHz of frequency and 28 W/L of volumetric power) and a traditional water-bath. It was demonstrated that both the effects of ultrasound technology are more effective in food with higher water activity, the micro channels only forming in moist food. Moreover, micro channel formation could also be observed using agar gel cylinders, verifying the random formation of these due to cavitation. The direct effects were shown to be important in mass transfer enhancement not only in moist food, but also in dry food, this being improved by the micro channels formed and the porosity of the food. In conclusion, the improvement in mass transfer due to direct and indirect effects was firstly discriminated and described. It was proven that both phenomena are important for mass transfer in moist foods, while only the direct effects are important for dry foods. Based on these results, better processing using ultrasound technology can be obtained.     

On the Motion of Substance in a Channel of a Network: Extended Model and New Classes of Probability Distributions

We discuss the motion of substance in a channel containing nodes of a network. Each node of the channel can exchange substance with: (i) neighboring nodes of the channel, (ii) network nodes which do not belong to the channel, and (iii) environment of the network. The new point in this study is that we assume possibility for exchange of substance among flows of substance between nodes of the channel and: (i) nodes that belong to the network but do not belong to the channel and (ii) environment of the network. This leads to an extension of the model of motion of substance and the extended model contains previous models as particular cases. We use a discrete-time model of motion of substance and consider a stationary regime of motion of substance in a channel containing a finite number of nodes. As results of the study, we obtain a class of probability distributions connected to the amount of substance in nodes of the channel. We prove that the obtained class of distributions contains all truncated discrete probability distributions of discrete random variable ω which can take values 0,1,⋯,N. Theory for the case of a channel containing infinite number of nodes is presented in Appendix A. The continuous version of the discussed discrete probability distributions is described in Appendix B. The discussed extended model and obtained results can be used for the study of phenomena that can be modeled by flows in networks: motion of resources, traffic flows, motion of migrants, etc.     

Size and Configuration Effect on Ion Transport of Biological Membrane

The theoretical model of the ion channel is described and the conductivity mechanism on the single ion channel of biomembrane has been discussed. By starting with the Boltzmann equation, we obtain the distribution function of ions in the single channel and the expression of electric current in the case of the cylindrical symmetry. Our model takes into account the selectivity for,different ions and supports the binding site model. It has been shown that the interaction between the ion and the protein and water environment in biomembrane is the key factor. The theoretical relation of current-voltage is in agreement with the experimental values.     

Particle-in-Cell Simulation of the Focusing Properties of High Energy Electron Beam in Plasma Ion Channel

The focusing properties of high energy electron beam in ion channel is investigated in the paper. The collisions of electrons with the neutral gas and the ionization resulted are considered to study the formation of ion channels with PIC method. The effects of various parameters on the beam focusing are analyzed.     

Physical properties of relativistic electron beam during long-range propagation in space plasma environment

It is known that ion channel can effectively limit the radial expansion of an artificial electron beam during its longrange propagation in the space plasma environment. Most prior studies discussed the focusing characteristics of the beam in the ion channel, but the establishment process and transient properties of the ion channel itself, which also plays a crucial role during the propagation of the relativistic electron beam in the plasma environment, were commonly neglected. In this study, a series of two-dimensional(2 D) particle-in-cell simulations is performed and an analytical model of ion channel oscillation is constructed according to the single-particle motion. The results showed that when the beam density is higher than the density of plasma environment, ion channel can be established and always continues to oscillate periodically over the entire propagation. Multiple factors, including the beam electron density, initial beam radius, and the plasma density can affect the oscillation properties of ion channel. Axial velocity of the beam oscillates synchronously with the ion channel and this phenomenon will finally develop into a two-stream instability which can seriously affect the effective transport for relativistic electron beam. Choosing appropriate beam parameters based on various plasma environments may contribute to the improvement of the stability of ion channel. Additionally, radial expansion of the beam can be limited by ion channel and a stable long-range propagation in terrestrial atmosphere may be achieved.     

Gaussian Multiuser Wiretap Channels in the Presence of a Jammer-Aided Eavesdropper

This paper considers secure communication in the presence of an eavesdropper and a malicious jammer. The jammer is assumed to be oblivious of the communication signals emitted by the legitimate transmitter(s) but can employ any jamming strategy subject to a given power constraint and shares her jamming signal with the eavesdropper. Four such models are considered: (i) the Gaussian point-to-point wiretap channel; (ii) the Gaussian multiple-access wiretap channel; (iii) the Gaussian broadcast wiretap channel; and (iv) the Gaussian symmetric interference wiretap channel. The use of pre-shared randomness between the legitimate users is not allowed in our models. Inner and outer bounds are derived for these four models. For (i), the secrecy capacity is obtained. For (ii) and (iv) under a degraded setup, the optimal secrecy sum-rate is characterized. Finally, for (iii), ranges of model parameter values for which the inner and outer bounds coincide are identified.     

一种研究二元对称离散信道平均互信息的新方法

在有干扰(噪声)无记忆信道和有记忆信道两种情况下，运用协同学的方法研究如何分配输入概率获取二元对称离散信道最大的平均互信息. 研究结果表明：对于无记忆二元对称离散信道，最大平均互信息与信息论中相同输入概率使平均互信息最大化的结果是一致的；对于干扰(噪声)有记忆二元对称离散信道，考虑输入、输出符号满足不同程度的记忆度和干扰(噪声)因子情况下，得到符号最佳输入概率. 拓展了一种研究信息论的方法. 关键词： 协同学 二元对称离散信道 互信息 转移概率