低盐水体Na^(+)/K^(+)对凡纳滨对虾生长、体成分与肝胰腺、鳃组织结构的影响

缺钾在内陆低盐度盐碱水中经常发生,为探究低盐水体中不同钾缺乏程度对凡纳滨对虾生长、存活、体成分以及鳃和肝胰腺组织结构的影响,实验参照海水离子组成配置盐度为2的低盐度水体,在Na^(+)/K^(+)(mg/mg)比值为27、47、67、87、107 (分别记为A、B、C、D、E组)的条件下,对体重为(1.04±0.23) g的凡纳滨对虾幼虾开展了为期60 d的养殖实验。结果显示,E组对虾的存活率为44.64%±20.95%,显著低于A、B、D三组;E组体重为(4.86±0.66) g,显著低于其他4组;A~D组之间的湿重、增重率、特定生长率差异不显著,但均大于E组且差异显著;在饲料系数上,E组最高并与A、D组差异显著。在体成分上,各组全虾钾含量、灰分含量差异不显著,E组的水分含量高于其他组,并与A、B组差异显著;E组粗蛋白含量最低,且与B组差异显著。E组对虾鳃组织角质层明显受损,红细胞数量减少,空泡增多,肝胰腺B细胞及其内部转运泡体积增大,肝小管结构受损。研究表明,低盐条件下严重缺钾引起了对虾鳃和肝胰腺损伤,降低了对虾的存活率和生长率;水体缺钾在前期即可对对虾的生长产生明显影响,而对存活的影响随养殖时间的增加而增大。实验结果有助于为内陆低盐度盐碱水养殖凡纳滨对虾提供理论依据。

Na^(+)/K^(+)-ATPase:ion pump,signal transducer,or cytoprotective protein,and novel biological functions

Na^(+)/K^(+)-ATPase is a transmembrane protein that has important roles in the maintenance of electrochemical gradients across cell membranes by transporting three Na^(+)out of and two K^(+)into cells.Additionally,Na^(+)/K^(+)-ATPase participates in Ca^(2+)-signaling transduction and neurotransmitter release by coordinating the ion concentration gradient across the cell membrane.Na^(+)/K^(+)-ATPase works synergistically with multiple ion channels in the cell membrane to form a dynamic network of ion homeostatic regulation and affects cellular communication by regulating chemical signals and the ion balance among different types of cells.Therefo re,it is not surprising that Na^(+)/K^(+)-ATPase dysfunction has emerged as a risk factor for a variety of neurological diseases.However,published studies have so far only elucidated the important roles of Na^(+)/K^(+)-ATPase dysfunction in disease development,and we are lacking detailed mechanisms to clarify how Na^(+)/K^(+)-ATPase affects cell function.Our recent studies revealed that membrane loss of Na^(+)/K^(+)-ATPase is a key mechanism in many neurological disorders,particularly stroke and Parkinson's disease.Stabilization of plasma membrane Na^(+)/K^(+)-ATPase with an antibody is a novel strategy to treat these diseases.For this reason,Na^(+)/K^(+)-ATPase acts not only as a simple ion pump but also as a sensor/regulator or cytoprotective protein,participating in signal transduction such as neuronal autophagy and apoptosis,and glial cell migration.Thus,the present review attempts to summarize the novel biological functions of Na^(+)/K^(+)-ATPase and Na^(+)/K^(+)-ATPase-related pathogenesis.The potential for novel strategies to treat Na^(+)/K^(+)-ATPase-related brain diseases will also be discussed.

Piezo1 channel exaggerates ferroptosis of nucleus pulposus cells by mediating mechanical stress-induced iron influx

To date,several molecules have been found to facilitate iron influx,while the types of iron influx channels remain to be elucidated.Here,Piezo1 channel was identified as a key iron transporter in response to mechanical stress.Piezo1-mediated iron overload disturbed iron metabolism and exaggerated ferroptosis in nucleus pulposus cells(NPCs).Importantly,Piezo1-induced iron influx was independent of the transferrin receptor(TFRC),a well-recognized iron gatekeeper.Furthermore,pharmacological inactivation of Piezo1 profoundly reduced iron accumulation,alleviated mitochondrial ROS,and suppressed ferroptotic alterations in stimulation of mechanical stress.Moreover,conditional knockout of Piezo1(Col2a1-CreERT Piezo1^(flox/flox))attenuated the mechanical injury-induced intervertebral disc degeneration(IVDD).Notably,the protective effect of Piezo1 deficiency in IVDD was dampened in Piezo1/Gpx4 conditional double knockout(cDKO)mice(Col2a1-CreERT Piezo1^(flox/flox)/Gpx4^(flox/flox)).These findings suggest that Piezo1 is a potential determinant of iron influx,indicating that the Piezo1-iron-ferroptosis axis might shed light on the treatment of mechanical stress-induced diseases.

Lithium-Ion Charged Polymer Channels Flattening Lithium Metal Anode

The concentration difference in the near-surface region of lithium metal is the main cause of lithium dendrite growth.Resolving this issue will be key to achieving high-performance lithium metal batteries(LMBs).Herein,we construct a lithium nitrate(LiNO_(3))-implanted electroactiveβphase polyvinylidene fluoride-co-hexafluoropropylene(PVDF-HFP)crystalline polymorph layer(PHL).The electronegatively charged polymer chains attain lithium ions on the surface to form lithium-ion charged channels.These channels act as reservoirs to sustainably release Li ions to recompense the ionic flux of electrolytes,decreasing the growth of lithium dendrites.The stretched molecular channels can also accelerate the transport of Li ions.The combined effects enable a high Coulombic efficiency of 97.0%for 250 cycles in lithium(Li)||copper(Cu)cell and a stable symmetric plating/stripping behavior over 2000 h at 3 mA cm^(-2)with ultrahigh Li utilization of 50%.Furthermore,the full cell coupled with PHL-Cu@Li anode and Li Fe PO_(4) cathode exhibits long-term cycle stability with high-capacity retention of 95.9%after 900 cycles.Impressively,the full cell paired with LiNi_(0.87)Co_(0.1)Mn_(0.03)O_(2)maintains a discharge capacity of 170.0 mAh g^(-1)with a capacity retention of 84.3%after 100 cycles even under harsh condition of ultralow N/P ratio of 0.83.This facile strategy will widen the potential application of LiNO_(3)in ester-based electrolyte for practical high-voltage LMBs.

Deep learning for joint channel estimation and feedback in massive MIMO systems

The great potentials of massive Multiple-Input Multiple-Output(MIMO)in Frequency Division Duplex(FDD)mode can be fully exploited when the downlink Channel State Information(CSI)is available at base stations.However,the accurate CsI is difficult to obtain due to the large amount of feedback overhead caused by massive antennas.In this paper,we propose a deep learning based joint channel estimation and feedback framework,which comprehensively realizes the estimation,compression,and reconstruction of downlink channels in FDD massive MIMO systems.Two networks are constructed to perform estimation and feedback explicitly and implicitly.The explicit network adopts a multi-Signal-to-Noise-Ratios(SNRs)technique to obtain a single trained channel estimation subnet that works well with different SNRs and employs a deep residual network to reconstruct the channels,while the implicit network directly compresses pilots and sends them back to reduce network parameters.Quantization module is also designed to generate data-bearing bitstreams.Simulation results show that the two proposed networks exhibit excellent performance of reconstruction and are robust to different environments and quantization errors.

枯草芽孢杆菌YvdSR蛋白转运Na^(+)关键残基的研究

对枯草芽孢杆菌(Bacillus subtilis strain 168)双组分基因YvdSR表达的双组分蛋白YvdSR进行功能鉴定,得出YvdSR具有转运Na^(+)/Li^(+)功能,为探究YvdSR离子转运机制,分别对两种组分作同源序列比对,从每种组分中筛选出完全保守的酸性氨基酸残基并进行氨基酸残基定点突变。结果表明,YvdS和YvdR共有的E13在同源物中完全保守且突变为丙氨酸后均失去Na^(+)(Li^(+))/H^(+)逆向转运活性,说明两种组分的E13均是蛋白质行使功能不可或缺的,YvdS的E13A经回复突变后可恢复高水平Na^(+)(Li^(+))/H^(+)逆向转运活性,YvdR的E13A经回复突变后仍失去Na^(+)(Li^(+))/H^(+)逆向转运活性,表明YvdS和YvdR在Na^(+)(Li^(+))/H^(+)逆向转运中行使不同功能。

Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

Two-Staged Method for Ice Channel Identification Based on Image Segmentation and Corner Point Regression

Identification of the ice channel is the basic technology for developing intelligent ships in ice-covered waters,which is important to ensure the safety and economy of navigation.In the Arctic,merchant ships with low ice class often navigate in channels opened up by icebreakers.Navigation in the ice channel often depends on good maneuverability skills and abundant experience from the captain to a large extent.The ship may get stuck if steered into ice fields off the channel.Under this circumstance,it is very important to study how to identify the boundary lines of ice channels with a reliable method.In this paper,a two-staged ice channel identification method is developed based on image segmentation and corner point regression.The first stage employs the image segmentation method to extract channel regions.In the second stage,an intelligent corner regression network is proposed to extract the channel boundary lines from the channel region.A non-intelligent angle-based filtering and clustering method is proposed and compared with corner point regression network.The training and evaluation of the segmentation method and corner regression network are carried out on the synthetic and real ice channel dataset.The evaluation results show that the accuracy of the method using the corner point regression network in the second stage is achieved as high as 73.33%on the synthetic ice channel dataset and 70.66%on the real ice channel dataset,and the processing speed can reach up to 14.58frames per second.

Na^(+)通道在锰神经细胞毒性中的作用

目的初步探讨Na^(+)通道在锰神经细胞毒性中对γ-氨基丁酸(GABA)的作用。方法SH-SY5Y细胞建立锰暴露模型,并分为空白对照组、0.25 mmol/L MnCl_(2)、0.50 mmol/L MnCl_(2)、1.00 mmol/L MnCl_(2)。河豚毒素(tetrodotoxin,TTX)0.10μmol/L、0.20μmol/L进行干预,MTT法测其细胞存活率、光学显微镜进行形态学观察、蛋白质印迹法检测Na^(+)通道中Nav1.1通道蛋白和GABA的标记酶谷氨酸脱羧酶65(GAD65)蛋白的表达水平。结果MnCl_(2)可抑制细胞增殖,0.25 mmol/L MnCl_(2)、0.50 mmol/L MnCl_(2)、1.00 mmol/L MnCl_(2)均可显著降低细胞存活率,差异均具有统计学意义(P<0.05);TTX可改善锰暴露所致的神经元损伤,提高细胞存活率,差异具有统计学意义(P<0.05);锰暴露可上调神经元GAD65蛋白表达水平,差异具有统计学意义(P<0.05),但锰暴露未改变神经元细胞Nav1.1蛋白的表达水平,差异无统计学意义(P>0.05)。结论锰暴露所致神经元损伤及GABA能损伤可能与其Nav1.1蛋白表达无关。

Cascaded ELM-Based Joint Frame Synchronization and Channel Estimation over Rician Fading Channel with Hardware Imperfections

Due to the interdependency of frame synchronization(FS)and channel estimation(CE),joint FS and CE(JFSCE)schemes are proposed to enhance their functionalities and therefore boost the overall performance of wireless communication systems.Although traditional JFSCE schemes alleviate the influence between FS and CE,they show deficiencies in dealing with hardware imperfection(HI)and deterministic line-of-sight(LOS)path.To tackle this challenge,we proposed a cascaded ELM-based JFSCE to alleviate the influence of HI in the scenario of the Rician fading channel.Specifically,the conventional JFSCE method is first employed to extract the initial features,and thus forms the non-Neural Network(NN)solutions for FS and CE,respectively.Then,the ELMbased networks,named FS-NET and CE-NET,are cascaded to capture the NN solutions of FS and CE.Simulation and analysis results show that,compared with the conventional JFSCE methods,the proposed cascaded ELM-based JFSCE significantly reduces the error probability of FS and the normalized mean square error(NMSE)of CE,even against the impacts of parameter variations.

Transient receptor potential channels as predictive marker and potential indicator of chemoresistance in colon cancer

Transient receptor potential(TRP)channels are strongly associated with colon cancer development and progression.This study leveraged a multivariate Cox regression model on publicly available datasets to construct a TRP channels-associated gene signature,with further validation of signature in real world samples from our hospital treated patient samples.Kaplan-Meier(K-M)survival analysis and receiver operating characteristic(ROC)curves were employed to evaluate this gene signature’s predictive accuracy and robustness in both training and testing cohorts,respectively.Additionally,the study utilized the CIBERSORT algorithm and single-sample gene set enrichment analysis to explore the signature’s immune infiltration landscape and underlying functional implications.The support vector machine algorithm was applied to evaluate the signature’s potential in predicting chemotherapy outcomes.The findings unveiled a novel three TRP channels-related gene signature(MCOLN1,TRPM5,and TRPV4)in colon adenocarcinoma(COAD).The ROC and K-M survival curves in the training dataset(AUC=0.761;p=1.58e-05)and testing dataset(AUC=0.699;p=0.004)showed the signature’s robust predictive capability for the overall survival of COAD patients.Analysis of the immune infiltration landscape associated with the signature revealed higher immune infiltration,especially an increased presence of M2 macrophages,in high-risk group patients compared to their low-risk counterparts.High-risk score patients also exhibited potential responsiveness to immune checkpoint inhibitor therapy,evident through increased CD86 and PD-1 expression profiles.Moreover,the TRPM5 gene within the signature was highly expressed in the chemoresistance group(p=0.00095)and associated with poor prognosis(p=0.036)in COAD patients,highlighting its role as a hub gene of chemoresistance.Ultimately,this signature emerged as an independent prognosis factor for COAD patients(p=6.48e-06)and expression of model gene are validated by public data and real-world patients.Overall,this bioinformatics study provides valuable insights into the prognostic implications and potential chemotherapy resistance mechanisms associated with TRPs-related genes in colon cancer.

新型Na^(+)/H^(+)逆向转运蛋白UPF0118的Na^(+)结合鉴定

UPF0118蛋白是一种新型Na^(+)(Li^(+))/H^(+)逆向转运蛋白,属于AI-2E超家族,目前已被划分至Na^(+)/H^(+)逆向转运蛋白亚家族,但无直接证据表明该蛋白可与Na+产生相互作用。为鉴定UPF0118蛋白是否具有Na^(+)结合功能,利用PCR技术扩增upf0118基因编码序列,通过Eco RⅠ和PstⅠ酶切位点构建至原核表达载体p ETDuet-1,转化至E. coli BL21*(DE3),对诱导后大量表达的蛋白进行Ni^(2+)亲和层析和凝胶过滤层析,利用等温滴定量热技术对纯化蛋白进行滴定。结果表明,在pH 5.5条件下,Na^(+)滴入导致蛋白溶液产生明显放热现象。在pH 5.5条件下该蛋白具有Na^(+)结合功能,证明该蛋白Na+结合功能为其功能单元与分子机制的研究奠定基础。

A Correlation-Based Stochastic Model for Massive MIMO Channel

In this paper,the channel impulse response matrix(CIRM)can be expressed as a sum of couplings between the steering vectors at the base station(BS)and the eigenbases at the mobile station(MS).Nakagami distribution was used to describe the fading of the coupling between the steering vectors and the eigenbases.Extensive measurements were carried out to evaluate the performance of this proposed model.Furthermore,the physical implications of this model were illustrated and the capacities are analyzed.In addition,the azimuthal power spectrum(APS)of several models was analyzed.Finally,the channel hardening effect was simulated and discussed.Results showed that the proposed model provides a better fit to the measured results than the other CBSM,i.e.,Weichselberger model.Moreover,the proposed model can provide better tradeoff between accuracy and complexity in channel synthesis.This CIRM model can be used for massive MIMO design in the future communication system design.

Statistical Channel Modeling for Indoor VLC Communications Based on Channel Measurements

Visible light communication(VLC)has attracted much attention in the research of sixthgeneration(6G)systems.Furthermore,channel modeling is the foundation for designing efficient and robust VLC systems.In this paper,we present extensive VLC channel measurement campaigns in indoor environments,i.e.,an office and a corridor.Based on the measured data,the large-scale fading characteristics and multipath-related characteristics,including omnidirectional optical path loss(OPL),K-factor,power angular spectrum(PAS),angle spread(AS),and clustering characteristics,are analyzed and modeled through a statistical method.Based on the extracted statistics of the above-mentioned channel characteristics,we propose a statistical spatial channel model(SSCM)capable of modeling multipath in the spatial domain.Furthermore,the simulated statistics of the proposed model are compared with the measured statistics.For instance,in the office,the simulated path loss exponent(PLE)and the measured PLE are 1.96and 1.97,respectively.And,the simulated medians of AS and measured medians of AS are 25.94°and 24.84°,respectively.Generally,the fact that the simulated results fit well with measured results has demonstrated the accuracy of our SSCM.

Potassium and calcium channels in different nerve cells act as therapeutic targets in neurological disorders

The central nervous system, information integration center of the body, is mainly composed of neurons and glial cells. The neuron is one of the most basic and important structural and functional units of the central nervous system, with sensory stimulation and excitation conduction functions. Astrocytes and microglia belong to the glial cell family, which is the main source of cytokines and represents the main defense system of the central nervous system. Nerve cells undergo neurotransmission or gliotransmission, which regulates neuronal activity via the ion channels, receptors, or transporters expressed on nerve cell membranes. Ion channels, composed of large transmembrane proteins, play crucial roles in maintaining nerve cell homeostasis. These channels are also important for control of the membrane potential and in the secretion of neurotransmitters. A variety of cellular functions and life activities, including functional regulation of the central nervous system, the generation and conduction of nerve excitation, the occurrence of receptor potential, heart pulsation, smooth muscle peristalsis, skeletal muscle contraction, and hormone secretion, are closely related to ion channels associated with passive transmembrane transport. Two types of ion channels in the central nervous system, potassium channels and calcium channels, are closely related to various neurological disorders, including Alzheimer's disease, Parkinson's disease, and epilepsy. Accordingly, various drugs that can affect these ion channels have been explored deeply to provide new directions for the treatment of these neurological disorders. In this review, we focus on the functions of potassium and calcium ion channels in different nerve cells and their involvement in neurological disorders such as Parkinson's disease, Alzheimer's disease, depression, epilepsy, autism, and rare disorders. We also describe several clinical drugs that target potassium or calcium channels in nerve cells and could be used to treat these disorders. We concluded that there are few clinical drugs that can improve the pathology these diseases by acting on potassium or calcium ions. Although a few novel ion-channelspecific modulators have been discovered, meaningful therapies have largely not yet been realized. The lack of target-specific drugs, their requirement to cross the blood–brain barrier, and their exact underlying mechanisms all need further attention. This review aims to explain the urgent problems that need research progress and provide comprehensive information aiming to arouse the research community's interest in the development of ion channel-targeting drugs and the identification of new therapeutic targets for that can increase the cure rate of nervous system diseases and reduce the occurrence of adverse reactions in other systems.

Artificial Intelligence Based Multi-Scenario mmWave Channel Modeling for Intelligent High-Speed Train Communications

A large amount of mobile data from growing high-speed train(HST)users makes intelligent HST communications enter the era of big data.The corresponding artificial intelligence(AI)based HST channel modeling becomes a trend.This paper provides AI based channel characteristic prediction and scenario classification model for millimeter wave(mmWave)HST communications.Firstly,the ray tracing method verified by measurement data is applied to reconstruct four representative HST scenarios.By setting the positions of transmitter(Tx),receiver(Rx),and other parameters,the multi-scenarios wireless channel big data is acquired.Then,based on the obtained channel database,radial basis function neural network(RBF-NN)and back propagation neural network(BP-NN)are trained for channel characteristic prediction and scenario classification.Finally,the channel characteristic prediction and scenario classification capabilities of the network are evaluated by calculating the root mean square error(RMSE).The results show that RBF-NN can generally achieve better performance than BP-NN,and is more applicable to prediction of HST scenarios.

Cav3.2 channel regulates cerebral ischemia/reperfusion injury:a promising target for intervention

Calcium influx into neurons triggers neuronal death during cerebral ischemia/reperfusion injury.Various calcium channels are involved in cerebral ischemia/reperfusion injury.Cav3.2 channel is a main subtype of T-type calcium channels.T-type calcium channel blockers,such as pimozide and mibefradil,have been shown to prevent cerebral ischemia/reperfusion injury-induced brain injury.However,the role of Cav3.2 channels in cerebral ischemia/reperfusion injury remains unclear.Here,in vitro and in vivo models of cerebral ischemia/reperfusion injury were established using middle cerebral artery occlusion in mice and high glucose hypoxia/reoxygenation exposure in primary hippocampal neurons.The results showed that Cav3.2 expression was significantly upregulated in injured hippocampal tissue and primary hippocampal neurons.We further established a Cav3.2 gene-knockout mouse model of cerebral ischemia/reperfusion injury.Cav3.2 knockout markedly reduced infarct volume and brain water content,and alleviated neurological dysfunction after cerebral ischemia/reperfusion injury.Additionally,Cav3.2 knockout attenuated cerebral ischemia/reperfusion injury-induced oxidative stress,inflammatory response,and neuronal apoptosis.In the hippocampus of Cav3.2-knockout mice,calcineurin overexpression offset the beneficial effect of Cav3.2 knockout after cerebral ischemia/reperfusion injury.These findings suggest that the neuroprotective function of Cav3.2 knockout is mediated by calcineurin/nuclear factor of activated T cells 3 signaling.Findings from this study suggest that Cav3.2 could be a promising target for treatment of cerebral ischemia/reperfusion injury.

A Probing Model of Secret Key Generation Based on Channel Autocorrelation Function

Secret key generation(SKG)is a promising solution to the problem of wireless communications security.As the first step of SKG,channel probing affects it significantly.Although there have been some probing schemes,there is a lack of research on the optimization of the probing process.This study investigates how to optimize correlated parameters to maximize the SKG rate(SKGR)in the time-division duplex(TDD)mode.First,we build a probing model which includes the effects of transmitting power,the probing period,and the dimension of sample vectors.Based on the model,the analytical expression of the SKGR is given.Next,we formulate an optimization problem for maximizing the SKGR and give an algorithm to solve it.We conclude the SKGR monotonically increases as the transmitting power increases.Relevant mathematical proofs are given in this study.From the simulation results,increasing appropriately the probing period and the dimension of the sample vector could increase the SKGR dramatically compared to a yardstick,which indicates the importance of optimizing the parameters related to the channel probing phase.

Heat and Mass Transfer on Non-Newtonian Peristaltic Flow in a Channel in Presence of Magnetic Field: Analytical and Numerical Analysis

A study has been arranged to investigate the flow of non-Newtonian fluid in a vertical asymmetrical channel using peristalsis. The porous medium allows the electrically conductive fluid to flow in the channel, while a uniform magnetic field is applied perpendicular to the flow direction. The analysis takes into account the combined influence of heat and mass transfer, including the effects of Soret and Dufour. The flow’s non-Newtonian behavior is characterized using a Casson rheological model. The fluid flow equations are examined within a wave frame of reference that has a wave velocity. The analytic solution is examined using long wavelengths and a small Reynolds number assumption. The stream function, temperature, concentration and heat transfer coefficient expressions are derived. The bvp4c function from MATLAB has been used to numerically solve the transformed equations. The flow characteristics have been analyzed using graphs to demonstrate the impacts of different parameters.

Entropy variances of pure coherent states in the diffusion channel

Using the operator correspondence of the real and fictious modes in the thermo entangled state representation, wesolve the quantum master equation describing the diffusion channel and obtain the Kraus operator-sum representation ofits analytical solution. we find that the pure coherent states evolve into the new mixed thermal superposed states in thediffusion channel. Also, we investigate the statistical properties of the initial coherent states and their entropy evolutions inthe diffusion channel, and find that the entropy evolutions are only related to the decay time and without the amplitudes ofthe initial coherent states.