细胞骨架生物力学进展

细胞骨架力学作为力学细胞生物学的一个新兴领域, 其研究方法突破传统细胞力学 思想, 不再把活细胞简化为皮质膜包着的弹性、黏性或黏弹性连续介质体, 而是基 于在细胞变形和功能中发挥重要作用的细胞骨架离散网络结构, 在微/纳米尺度建 立一种集细胞形态和功能于一体的离散网络结构. 这种细胞骨架模型作为细胞变形 和生化事件调控的纽带, 能从分子层次上阐述细胞运动、能量转换、信息传递、基 因表达等重大生命活动的潜在机制,同时也能解释生物大分子间相互作用、受体/配体特异性相互作用、 大分子自装配、细胞及分子层次的力学-化学耦合, 为定量研究细胞-亚细胞-生物大 分子等在多种力学刺激下的响应建立了良好的平台, 对于理解生物模式形成、生物 复杂性以及解决重大生物学难题具有深远意义. 本文基于细胞骨架三维离散网络结 构特点及其生物学背景, 从生物力学角度详细阐述近几年国际上流行的细胞骨架模 型理论分析和研究成果的最新进展.     

力敏感受体介导细胞功能调控的力学生物学研究

细胞膜是细胞与外部环境进行物质与能量交换的界面,是调节细胞正常生命活动的重要结构基础.细胞膜上力敏感受体可通过力学作用方式参与并影响细胞的力信号转导等功能.整合素和钙黏素是细胞膜上典型的力敏感受体,可介导细胞与细胞周围基质或邻近细胞发生力学作用,并将力学刺激信号转导为生化信号,进而激活细胞内一系列应答反应,最终影响细胞生长、分化、增殖、凋亡和迁移等功能.力敏感受体介导细胞功能调控研究已成为探索细胞主动响应外界复杂力学微环境的力学生物学机制的关键,为进一步深入认识生理和病理状态下细胞功能变化规律,为揭示疾病的发生、发展机制提供重要的力学生物学理论与实验依据.本文总结了力敏感受体介导细胞功能调控的国内外研究进展;介绍了黏附界面处典型力敏感受体的结构和功能;总结了这些力敏感受体参与的细胞力信号感知与响应的数理模型;概述了细胞通过力敏感受体进行力学信号转导的过程;介绍了黏附介导细胞功能调控的力学生物学过程和机制;简述了体外构建模拟细胞力学微环境中细胞-细胞外基质和细胞-细胞力学相互作用的技术;指出了力敏感受体介导细胞功能调控的力学生物学研究发展趋势和未来方向.     

骨组织生长重建的力学生物学机制研究进展

生物力学已被证实是骨组织生长、重建及成形当中一个十分重要的因素. 骨组织的损 伤修复过程本质上是细胞的生物学过程和应力作用下的生长过程. 这虽然肯定了生物力学在 骨组织生长、重建过程中的重要地位, 但是, 人们对生物力学因素如何诱导骨生长、 重建的力学生物学机制仍不甚了解. 而骨组织工程需要更为科学完善的细胞生物学机制来研究和探 索骨组织的构建过程. 本文概述了国内外生物力学与骨组织生长重建的宏微观理论, 主要讨 论了骨组织结构及功能形成过程中的力学生物学相关问题.     

细胞铺展动力学的研究进展

细胞与细胞外基质之间的相互作用在细胞的迁移、分化、凋亡等生理过程中起着重要的作用,细胞铺展作为细胞与细胞外基质作用的第1步,受到了人们的广泛关注.首先阐述了细胞铺展的关键生物动力学过程,对铺展3个不同阶段的特点进行了总结和归纳,并运用力学的观点阐明了细胞铺展的驱动力及驱动机制,详细讨论了聚合力、黏附力以及细胞张力等3种主要作用力在细胞铺展过程中的作用规律以及相应的物理模型.在此基础上,从细胞的黏性流动及力学平衡两个方面出发,简要综述了已有相关研究结果的不足之处,介绍了当前建立细胞铺展动力学模型的主要思路,并探讨了今后面向细胞生物学需求的相关细胞动力学的研究方向.     

干细胞的生物力学研究

干细胞生物力学作为生物力学的重要分支和前沿学科,近年来在力学-生物学、力学-化学耦合等方面取得了重大进展,已成为生物力学乃至生物医学工程最活跃的领域之一,并对发育生物学、干细胞生物学、组织修复、再生医学等相关领域产生重要影响.干细胞具有独特的力学性质,可感知、传递、转导和响应生理力学微环境的改变,从而调控干细胞的生长、分化等功能,体现出典型的力学-生物学耦合特征.本文将对干细胞的力学性质与细胞力学模型、在体力学环境对干细胞生长和分化的影响、干细胞对外界力学刺激的响应等方面加以综述.     

骨组织细胞的力学调控研究

力学环境是影响骨组织细胞形成、增殖和功能成熟的一个重要因素. 骨细胞是力学感受细胞, 将力学信号传递给效应细胞; 成骨细胞、破骨细胞为力学效应细胞, 使骨形成和骨吸收处于动态平衡以维持骨力学稳定性. 目前对骨组织细胞间力学调控的机理仍不甚清楚. 综述了骨组织细胞力学生物学作用和细胞间力学调控的一些相关问题. 在概述了成骨细胞、骨细胞和破骨细胞的生物学特性基础上,阐述了骨重建力学调控理论,成骨细胞、骨细胞和破骨细胞生物力学效应和细胞间力学调控最新研究进展. 最后对骨组织细胞三维网络间力学调控研究做出展望.     

Biomechanics of stem cells

干细胞生物力学作为生物力学的重要分支和前沿学科,近年来在力学-生物学、力学-化学耦合等方面取得了重大进展,已成为生物力学乃至生物医学工程最活跃的领域之一,并对发生物学、干细胞生物学、组织修复、再生医学等相关领域产生重要影响.干细胞具有独特的力学性质,可感知、传递、转导和响应生理力学微环境的改变,从而调控干细胞的生长、分化等功能,体现出典型的力学-生物学耦合特征.本文将对干细胞的力学性质与细胞力学模型、在体力学环境对干细胞生长和分化的影响、干细胞对外界力学刺激的响应等方面加以综述.     

植物细胞力学模型研究进展

植物细胞在结构上具有特殊性, 即细胞壁和胞内物质在力学性质上差异很大. 因此其力学模 型的研究具有特殊意义. 植物细胞力学模型是植物组织力学行为的研究基础, 是连接宏观与 微观生物力学发展的桥梁, 在农业和食品加工等领域中有重要的潜在应用价值. 本文就目前 国际上在细胞力学模型研究中所采用的模型形式和理论分析与数值模拟等方法做较全面而简 要的介绍, 并对本领域中存在的现实问题加以论述, 希望能够对我国在细胞力学领域的研究 有所帮助.     

生物神经网络系统动力学与功能研究

生物神经系统是由数量极其巨大的神经元相互联结的信息网络系统, 在生物体的感觉、认知和运动控制中发挥关键性的作用. 首先介绍神经元、大脑和一些生物神经网络的生理结构和理论模型, 然后分别介绍其放电活动和网络动态特性的一些重要问题, 包括神经元的复杂放电模式、耦合神经元网络系统的同步活动和时空动力学、 大脑联合皮层神经微回路的网络结构特征, 以及工作记忆和抉择过程的动力学机制等. 最后对今后研究给出一些展望.     

《系统生物学—建模,分析,模拟》书评

生命活动属于最复杂的自然界现象。近代生物学研究已从以实验观察为主的方式逐步发展为与生命体的机理性分析密切结合，并且由生物器官组织的宏观形态和表型向生物细胞和分子的微观行为和演变进行深入探讨。随着生物科学实验技术和方法的飞速进步，人们对生物大分子、基因和蛋白质、生物膜的结构和功能等的研究已经积累了相当丰富的知识。由于生命现象都是生物复杂大系统的综合行为的结果，我们必须把生物系统作为一个整体来研究，从系统论的角度进一步探讨细胞的信息、生长、发育、分化、代谢等动态过程以及生物有机体的功能，而不仅把研究重点放在单个的基因, 蛋白质或者器官上。系统生物学就是这样一门研究生物系统的内部组分结构, 以及在各种内、外部条件下这些组分的相互作用和演化规律的学科，是生命科学的一个前沿领域。目前重点是在分子层次上开展对生命现象（例如遗传基因、蛋白质、重大疾病等）的过程和机制的研究，生物化学反应（包括蛋白质—蛋白质相互作用、DNA—蛋白质相互作用等）和生物网络（包括基因网、蛋白质相互作用网、信号转导网、代谢网等）行为在其中起着重要作用。大量的系统生物学研究对象是动态的和随机的，涉及不同的时空尺度下复杂非线性动力学与控制问题。     

Pattern Formation in Turing Systems on Domains with Exponentially Growing Structures

Turing reaction–diffusion systems have been used to model pattern formation in several areas of developmental biology. Previous biomathematical Turing system models employed static domains which failed to incorporate the growth that inherently occurs as an organism develops. To address this shortcoming, we incorporate an exponentially growing domain into a Turing system, allowing one to more realistically model biological pattern formation. This Turing system can generate patterns on an exponentially growing domain in any of the eleven coordinate systems in which the Helmholtz equation is separable, making the system incredibly flexible and giving one the capability to mathematically model pattern formation on a geometrically diverse group of domains. Linear stability analysis is employed to generate mathematical conditions which ensure such a system can generate patterns. We apply the exponentially growing Turing system to a prolate spheroidal domain and conduct numerical simulations to investigate the system’s pattern-generating behavior. We find that the addition of growth to a Turing system causes a significant change in the pattern-generating behavior of the system. While a static domain Turing system converges to a final pattern, an exponentially growing domain Turing system produces transient patterns that continually evolve and increase in complexity over time.     

Turing patterns of Gierer–Meinhardt model on complex networks

Gierer–Meinhardt (G–M) model is a classical reaction diffusion (RD) model to describe biological and chemical phenomena. Turing patterns of G–M model in continuous space have attracted much attention of researchers. Considering that the RD system defined on discrete network structure is more practical in many aspects than the corresponding system in continuous space, we study Turing patterns of G–M model on complex networks. By numerical simulations, Turing patterns of the G–M model on regular lattice networks and several complex networks are studied, and the influences of system parameters, network types and average degree on pattern formations are discussed. Furthermore, we present an exponential decay of Turing patterns on complex networks, which not only quantitatively depicts the influence of network topology on pattern formations, but also provides the possibility for predict pattern formations.

     

Anisotropic porochemoelectroelastic Mandel's problem solutions for applications in reservoir modeling and laboratory characterization

The porochemoelectroelastic analytical models have been used to describe the response of chemically active and electrically charged saturated porous media such as clay soils, shales, and biological tissues. In this work, the porochemoelectroelastic theory is applied to derive the solution for stress, pore pressure, strain, and displacement of the Mandel's problem for orthotropic charged saturated porous media. Numerical examples are given to demonstrate applications of the present solutions to laboratory characterization and hydraulic fracturing analysis of shale formation. The analysis shows that ignoring either the porochemoelectroelastic effects or the material anisotropy can leads to inaccurate prediction of the pore pressure and effective stress distributions in the shale sample or formations during these processes.     

The race to the nociceptor: mechanical versus temperature effects in thermal pain of dental neurons

The sensing of hot and cold stimuli by dental neurons differs in several fundamental ways. These sensations have been characterized quantitatively through the measured time course of neural discharge signals that result from hot or cold stimuli applied to the teeth of animal models. Although various hypotheses have been proposed to explain the underlying mechanism, the ability to test competing hypotheses against experimental recorded data using biophysical models has been hindered by limitations in our understanding of the specific ion channels involved in nociception of dental neurons. Here we apply recent advances in established biophysical models to test the competing hypotheses. We show that a sharp shooting pain sensa-tion experienced shortly following cold stimulation cannot be attributed to the activation of thermosensitive ion channels, thereby falsifying the so-called neuronal hypothesis,which states that rapidly transduced sensations of coldness are related to thermosensitive ion channels. Our results support a central role of mechanosensitive ion channels and the associated hydrodynamic hypothesis. In addition to the hydrodynamic hypothesis, we also demonstrate that the long time delay of dental neuron responses after hot stimulation could be attributed to the neuronal hypothesis—that a relatively long time is required for the temperature around nociceptors to reach some threshold. The results are useful as a model of how multiphysical phenomena can be combined to provide mechanistic insight into different mechanisms underlying pain sensations.     

螺旋波动力学及其控制

螺旋波是时空斑图结构演化的一个典型研究对象,无论从理论研究意义还是从应用价 值来看都是非常重要的,它可涉及到的领域包括:数学、物理、力学、天文、化学、生物、 医学等学科. 本文较为详细地讨论了螺旋波的动力学行为, 主要包含以下几方面: 螺旋波的 形成、螺旋波的几种常见的形式、螺旋波波头的运动、螺旋波失稳方式等. 由于螺旋波及其 破碎后的行为在许多具体的系统中的有害作用, 本文也介绍了螺旋波的几种控制方案: 反馈 控制方案、外力控制方案、调整参数控制方案等.     

Structural Change in Living Tissues

Tissues change in many ways in the period that they are part of a living organism. Tissues are created in fairly repeatable structural patterns, and the patterns are due to both the genes and the (mechanical) environment, but we do not know exactly what part or percentage of a particular pattern to consider the genes, or the environment, responsible for. We do not know much about the beginning of tissue construction (morphogenesis) and also the methods of tissue construction. When the tissue structure is altered to accommodate a new loading, it is not known how the decision is made for the structural reconstruction. We know that tissues grow or reconstruct themselves without ceasing to continue with their structural function, but we do not understand the processes that permit them to accomplish this. Tissues change their structures to altered mechanical environments, but we are not sure how. Tissues heal themselves and we understand little of the structural mechanics of the process. With the objective of describing the interesting unsolved mechanics problems associated with these biological processes, some aspects of the formation, growth and adaptation of living tissues are reviewed. Beyond the objective is the hope that the work will stimulate new ideas and new observations in developmental biology. This revised version was published online in July 2006 with corrections to the Cover Date.     

A review for dynamics in neuron and neuronal network

The biological Hodgkin–Huxley model and its simplified versions have confirmed its effectiveness for recognizing and understanding the electrical activities in neurons, and bifurcation analysis is often used to detect the mode transition in neuronal activities. Within the collective behaviors of neurons, neuronal network with different topology is designed to study the synchronization behavior and spatial pattern formation. In this review, the authors give careful comments for the presented neuron models and present some open problems in this field, nonlinear analysis could be effective to further discuss these problems and some results could be helpful to give possible guidance in the field of neurodynamics.     

Flow pattern based correlations of two-phase pressure drop in rectangular microchannels

Numerous pressure drop correlations for microchannels have been proposed; most of them can be classified as either a homogeneous flow model (HFM) or a separated flow model (SFM). However, the predictions of these correlations have not been compared directly because they were developed in experiments conducted under a range of conditions, including channel shape, the number of channels, channel material and the working fluid. In this study, single rectangular microchannels with different aspect ratios and hydraulic diameters were fabricated in a photosensitive glass. Adiabatic water-liquid and Nitrogen-gas two-phase flow experiments were conducted using liquid superficial velocities of 0.06–1.0 m/s, gas superficial velocities of 0.06–72 m/s and hydraulic diameters of 141, 143, 304, 322 and 490 μm. A pressure drop in microchannels was directly measured through embedded ports. The flow pattern was visualized using a high-speed camera and a long-distance microscope. A two-phase pressure drop in the microchannel was highly related to the flow pattern. Data were used to assess seven different HFM viscosity models and ten SFM correlations, and new correlations based on flow patterns were proposed for both HFMs and SFMs.     

微尺度相变传热的关键问题

由于航天、信息、生物等高技术的发展,微尺度热物理问题得到了广泛的重视.作为一种 非常高效的能量转换方法,微尺度相变传热的研究远未成熟.本文对微尺度相变传热作了较 为系统的综述,论述了控制微尺度相变传热的准则数,分析了沸腾起始点、流型、压降、传 热系数、不稳定性、临界热流密度六大关键问题.建议从实验和理论两个方面对微尺度相变 传热进行深入的研究,以进一步理解其机理,为微蒸发器的设计、制造及运行提供科学依据 和指导.     

基于模式运算的工程设计方法

研究了复杂的工程设计决策过程,讨论了设计问题的五个性质,提出了两类不同速度的设计过程:以模式识别为基础的快速设计过程和以模式加法、模式联想为基础的慢速设计过程。此外,还讨论了模蝴集合论和人工神经网络在实现模式运算中的应用。