Capstan-like mechanism in hyaluronan-phospholipid systems.

Functionality of articular cartilage results from complex interactions between its molecular components. Among many biomolecules, two are of prime importance for lubrication: hyaluronic acid (HA) and phospholipids (PL). The purpose of this study is to discuss a mechanism of interaction between these two components and how their synergies contribute to nanobiolubrication of articular cartilage. Preliminary molecular dynamics simulations have been performed to investigate these interactions by adopting a capstan-like mechanism of action. By applying a constant pulling force to both ends of a HA molecule, wrapped around a PL micelle, we viewed the rotation of the PL micelle. The simulations were performed upon two physicochemical constraints: force- and solvent-dependency. The results show the efficiency of rotation from intermolecular bond creation and annihilation. We found a direct relation between the available surface of the micelle and the magnitude of the force, which varies significantly through the unwinding. The movement of the attached molecules is characterized by a slide-to-roll relation, which is affected by the viscosity of the surrounding medium. As a consequence, two solvents were studied for specific force conditions and the molecular dynamics simulation exhibited double the slide-to-roll coefficient for the viscous solvent as compared to its low-viscosity limit.

Dynamic phenomena and human activity in an artificial society.

We study dynamic phenomena in a large social network of nearly 3x10;{4} individuals who interact in the large virtual world of a massive multiplayer online role playing game. On the basis of a database received from the online game server, we examine the structure of the friendship network and human dynamics. To investigate the relation between networks of acquaintances in virtual and real worlds, we carried out a survey among the players. We show that, even though the virtual network did not develop as a growing graph of an underlying network of social acquaintances in the real world, it influences it. Furthermore we find very interesting scaling laws concerning human dynamics. Our research shows how long people are interested in a single task and how much time they devote to it. Surprisingly, exponent values in both cases are close to -1 . We calculate the activity of individuals, i.e., the relative time daily devoted to interactions with others in the artificial society. Our research shows that the distribution of activity is not uniform and is highly correlated with the degree of the node, and that such human activity has a significant influence on dynamic phenomena, e.g., epidemic spreading and rumor propagation, in complex networks. We find that spreading is accelerated (an epidemic) or decelerated (a rumor) as a result of superspreaders' various behavior.