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

Energy harvested directly from sunlight offers a desirable approach toward fulfilling, with minimal environmental impact, the need for clean energy. Solar energy is a decentralized and inexhaustible natural resource, with the magnitude of the available solar power striking the earth’s surface at any one instant equal to 130 million 500 MW power plants.1 However, several important goals need to be met to fully utilize solar energy for the global energy demand. First, the means for solar energy conversion, storage, and distribution should be environmentally benign, i.e. protecting ecosystems instead of steadily weakening them. The next important goal is to provide a stable, constant energy flux. Due to the daily and seasonal variability in renewable energy sources such as sunlight, energy harvested from the sun needs to be efficiently converted into chemical fuel that can be stored, transported, and used upon demand. The biggest challenge is whether or not these goals can be met in a costeffective way on the terawatt scale.2

http://pubs.acs.org/doi/pdf/10.1021/cr1002326

Solar Water Splitting Cells

N G van Kampen 1981 Amsterdam: North-Holland xiv + 419 pp price Dfl 180 This is a book which, at a lower price, could be expected to become an essential part of the library of every physical scientist concerned with problems involving fluctuations and stochastic processes, as well as those who just enjoy a beautifully written book. It provides an extensive graduate-level introduction which is clear, cautious, interesting and readable.

https://iopscience.iop.org/article/10.1088/0031-9112/34/4/040/pdf

Stochastic Processes in Physics and Chemistry

日本物理学会誌及びJournal of the Physical Society of Japanの月刊について

Annual review of condensed matter physics

Near equilibrium, small current fluctuations are described by a Gaussian distribution with a linear-response variance regulated by the dissipation. Here, we demonstrate that dissipation still plays a dominant role in structuring large fluctuations arbitrarily far from equilibrium. In particular, we prove a linear-response-like bound on the large deviation function for currents in Markov jump processes. We find that nonequilibrium current fluctuations are always more likely than what is expected from a linear-response analysis. As a small-fluctuations corollary, we derive a recently conjectured uncertainty bound on the variance of current fluctuations.

/pdf/dissipation-bounds-all-steady-state-current-fluctuations-43bcevvwoi.pdf

Dissipation Bounds All Steady-State Current Fluctuations.

In equilibrium thermodynamics, there exists a well-established connection between dynamical fluctuations of a physical system and the dissipation of its energy into an environment. However, few similarly quantitative tools are available for the description of physical systems out of equilibrium. Here, we offer our perspective on the recent development of a new class of inequalities known as thermodynamic uncertainty relations, which have revealed that dissipation constrains current fluctuations in steady states arbitrarily far from equilibrium. We discuss the stochastic thermodynamic origin of these inequalities, and highlight recent efforts to expand their applicability, which have focused on connections between current fluctuations and the fluctuation theorems. A new class of inequalities known as thermodynamic uncertainty relations provides quantitative tools for the description of physical systems out of equilibrium. A perspective is offered on these results and their future developments.

Thermodynamic uncertainty relations constrain non-equilibrium fluctuations

The thermodynamic uncertainty relation offers a universal energetic constraint on the relative magnitude of current fluctuations in nonequilibrium steady states. However, it has only been derived for long observation times. Here, we prove a recently conjectured finite-time thermodynamic uncertainty relation for steady-state current fluctuations. Our proof is based on a quadratic bound to the large deviation rate function for currents in the limit of a large ensemble of many copies.

Proof of the finite-time thermodynamic uncertainty relation for steady-state currents.

Systems coupled to multiple thermodynamic reservoirs can exhibit nonequilibrium dynamics, breaking detailed balance to generate currents. To power these currents, the entropy of the reservoirs increases. The rate of entropy production, or dissipation, is a measure of the statistical irreversibility of the nonequilibrium process. By measuring this irreversibility in several biological systems, recent experiments have detected that particular systems are not in equilibrium. Here we discuss three strategies to replace binary classification (equilibrium versus nonequilibrium) with a quantification of the entropy production rate. To illustrate, we generate time-series data for the evolution of an analytically tractable bead-spring model. Probability currents can be inferred and utilized to indirectly quantify the entropy production rate, but this approach requires prohibitive amounts of data in high-dimensional systems. This curse of dimensionality can be partially mitigated by using the thermodynamic uncertainty relation to bound the entropy production rate using statistical fluctuations in the probability currents.

Quantifying dissipation using fluctuating currents.

Complex physical dynamics can often be modeled as a Markov jump process between mesoscopic configurations. When jumps between mesoscopic states are mediated by thermodynamic reservoirs, the time-irreversibility of the jump process is a measure of the physical dissipation. We rederive a recently introduced inequality relating the dissipation rate to current fluctuations in jump processes. We then adapt these results to diffusion processes via a limiting procedure, reaffirming that diffusions saturate the inequality. Finally, we study the impact of spatial coarse-graining in a two-dimensional model with driven diffusion. By observing fluctuations in coarse-grained currents, it is possible to infer a lower bound on the total dissipation rate, including the dissipation associated with hidden dynamics. The tightness of this bound depends on how well the spatial coarse-graining detects dynamical events that are driven by large thermodynamic forces.

https://iopscience.iop.org/article/10.1088/1751-8121/aa672f/pdf

Todd R. Gingrich

Papers

Dissipation Bounds All Steady-State Current Fluctuations.

Thermodynamic uncertainty relations constrain non-equilibrium fluctuations

Proof of the finite-time thermodynamic uncertainty relation for steady-state currents.

Quantifying dissipation using fluctuating currents.

Inferring dissipation from current fluctuations