抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

The mechanical properties of soft biological tissues are essential to their physiological function and cannot easily be duplicated by synthetic materials. Unlike simple polymer gels, many biological materials--including blood vessels, mesentery tissue, lung parenchyma, cornea and blood clots--stiffen as they are strained, thereby preventing large deformations that could threaten tissue integrity. The molecular structures and design principles responsible for this nonlinear elasticity are unknown. Here we report a molecular theory that accounts for strain-stiffening in a range of molecularly distinct gels formed from cytoskeletal and extracellular proteins and that reveals universal stress-strain relations at low to intermediate strains. The input to this theory is the force-extension curve for individual semi-flexible filaments and the assumptions that biological networks composed of these filaments are homogeneous, isotropic, and that they strain uniformly. This theory shows that systems of filamentous proteins arranged in an open crosslinked mesh invariably stiffen at low strains without requiring a specific architecture or multiple elements with different intrinsic stiffness.

Nonlinear elasticity in biological gels.

https://www.cell.com/biophysj/pdf/S0006-3495(05)73417-2.pdf

Optical deformability as an inherent cell marker for testing malignant transformation and metastatic competence.

Unlike most synthetic materials, biological materials often stiffen as they are deformed. This nonlinear elastic response, critical for the physiological function of some tissues, has been documented since at least the 19th century, but the molecular structure and the design principles responsible for it are unknown. Current models for this response require geometrically complex ordered structures unique to each material. In this Article we show that a much simpler molecular theory accounts for strain stiffening in a wide range of molecularly distinct biopolymer gels formed from purified cytoskeletal and extracellular proteins. This theory shows that systems of semi-flexible chains such as filamentous proteins arranged in an open crosslinked meshwork invariably stiffen at low strains without the need for a specific architecture or multiple elements with different intrinsic stiffnesses.

http://absimage.aps.org/image/MAR06/MWS_MAR06-2005-000060.pdf

Nonlinear Elasticity in Biological Gels

Pulsed electron-electron double resonance techniques such as the four-pulse double electron-electron resonance experiment measure a dipolar evolution function of the sample. For a sample consisting of spin-carrying nanoobjects, this function is the product of a form factor, corresponding to the internal structure of the nanoobject, and a background factor, corresponding to the distribution of nanoobjects in space. The form factor contains information on the spin-to-spin distance distribution within the nanoobject and on the average number of spins per nanoobject, while the background factor depends on constraints, such as a confinement of the nanoobjects to a two-dimensional layer. Separation of the dipolar evolution function into these two contributions and extraction of the spin-to-spin distance distribution require numerically stable mathematical algorithms that can handle data for different classes of samples, e.g., spin-labelled biomacromolecules and synthetic materials. Furthermore, experimental imperfections such as the limited excitation bandwidth of microwave pulses need to be considered. The software package DeerAnalysis2006 provides access to a comprehensive set of tools for such data analysis within a common user interface. This interface allows for several tests of the reliability and precision of the extracted information. User-supplied models for the spin-to-spin distance distribution within a certain class of nanoobjects can be added to an existing library and be fitted with a universal algorithm.

DeerAnalysis2006 - a comprehensive software package for analyzing pulsed ELDOR data

We study the elasticity of a two-dimensional random network of rigid rods ("Mikado model"). The essential features incorporated into the model are the anisotropic elasticity of the rods and the random geometry of the network. We show that there are three distinct scaling regimes, characterized by two distinct length scales on the elastic backbone. In addition to a critical rigidity percolation region and a homogeneously elastic regime we find a novel intermediate scaling regime, where the elasticity is dominated by bending deformations.

Elasticity of stiff polymer networks.

Living cells are soft bodies of a characteristic form, but endowed with a capacity for a steady turnover of their structures. Both of these material properties, i.e. recovery of the shape after an external stress has been imposed and dynamic structural reorganization, are essential for many cellular phenomena. Examples are mechanical properties of tissue, cell motility, cell growth and division, and active intracellular transport. Numerous experiments in vivo and in vitro have shown that the structural element responsible for the extraordinary mechanical and dynamical properties of eukaryotic cells is the cytoskeleton, a three-dimensional assembly of protein fibers such as actin filaments and microtubules. In addition to those biopolymers various proteins with structural and regulatory functions have a major influence on the mechanical properties. At the relevant length-scales (a few microns at most) the building blocks of these biomaterials are very different from conventional polymeric material. In contrast to flexible polymers the persistence length is of the same order of magnitude as their total contour length or even larger. This implies that the physics of such a system is determined by a subtle interplay between energetic and entropic contributions. We review our present understanding of the physics of biopolymers using concepts from macromolecular and statistical physics complemented by computer simulation. These systems open up a new field of soft condensed matter research, which to date is only poorly understood but has a great potential for interesting new physical phenomena.

/pdf/physics-of-solutions-and-networks-of-semiflexible-30haxf7iki.pdf

Physics of Solutions and Networks of Semiflexible Macromolecules and the Control of Cell Function

Elasticity of Stiff Biopolymer Networks

Living cells are soft bodies of a characteristic form, but endowed with a capacity for a steady turnover of their structures. Both of these material properties, i. e. recovery of the shape after an external stress has been imposed and dynamic structural reorganization, are essential for many cellular phenomena. Examples are active intracellular transport, cell growth ard division, and directed movement of cells. The structural element responsible for the extraordinary mechanical and dynamical properties of eukaryotic cells is a three-dimensional assembly of protein fibers, the cytoskeleton. A major contribution to its mechanical properties is due to actin filaments and proteins that crosslink them. Numerous experiments in vivo [5] and in vitro [14, 13] have shown that the mechanical properties of cells are largely determined by the cytoskeletal network.

/pdf/statistical-mechanics-of-semiflexible-polymers-theory-and-1zfsombzdw.pdf

Statistical Mechanics of Semiflexible Polymers: Theory and Experiment

We calculate the distribution function of the end-to-end distance of a semiflexible polymer with large bending rigidity. This quantity is directly observable in experiments on single semiflexible polymers (e.g., DNA, actin) and relevant to their interpretation. It is also an important starting point for analyzing the behavior of more complex systems such as networks and solutions of semiflexible polymers. To estimate the validity of the obtained analytical expressions, we also determine the distribution function numerically using Monte Carlo simulation and find good quantitative agreement.

Radial Distribution Function of Semiflexible Polymers.

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