Antifreeze glycoproteins inhibit leakage from liposomes during thermotropic phase transitions.

Antifreeze glycoproteins (AFGPs), found in the blood of polar fish at concentrations as high as 35 g/liter, are known to prevent ice crystal growth and depress the freezing temperature of the blood. Previously, Rubinsky et al. [Rubinsky, B., Mattioli, M., Arav, A., Barboni, B. & Fletcher, G. L. (1992) Am. J. Physiol. 262, R542-R545] provided evidence that AFGPs block ion fluxes across membranes during cooling, an effect that they ascribed to interactions with ion channels. We investigated the effects of AFGPs on the leakage of a trapped marker from liposomes during chilling. As these liposomes are cooled through the transition temperature, they leak approximately 50% of their contents. Addition of less than 1 mg/ml of AFGP prevents up to 100% of this leakage, both during chilling and warming through the phase transition. This is a general effect that we show here applies to liposomes composed of phospholipids with transition temperatures ranging from 12 degrees C to 41 degrees C. Because these results were obtained with liposomes composed of phospholipids alone, we conclude that the stabilizing effects of AFGPs on intact cells during chilling reported by Rubinsky et al. may be due to a nonspecific effect on the lipid components of native membranes. There are other proteins that prevent leakage, but only under specialized conditions. For instance, antifreeze proteins, bovine serum albumin, and ovomucoid all either have no effect or actually induce leakage. Following precipitation with acetone, all three proteins inhibited leakage, although not to the extent seen with AFGPs. Alternatively, there are proteins such as ovotransferrin that have no effect on leakage, either before or after acetone precipitation.

Self-organized phase transitions in neural networks as a neural mechanism of information processing.

Transitions between dynamically stable activity patterns imposed on an associative neural network are shown to be induced by self-organized infinitesimal changes in synaptic connection strength and to be a kind of phase transition. A key event for the neural process of information processing in a population coding scheme is transition between the activity patterns encoding usual entities. We propose that the infinitesimal and short-term synaptic changes based on the Hebbian learning rule are the driving force for the transition. The phase transition between the following two dynamical stable states is studied in detail, the state where the firing pattern is changed temporally so as to itinerate among several patterns and the state where the firing pattern is fixed to one of several patterns. The phase transition from the pattern itinerant state to a pattern fixed state may be induced by the Hebbian learning process under a weak input relevant to the fixed pattern. The reverse transition may be induced by the Hebbian unlearning process without input. The former transition is considered as recognition of the input stimulus, while the latter is considered as clearing of the used input data to get ready for new input. To ensure that information processing based on the phase transition can be made by the infinitesimal and short-term synaptic changes, it is absolutely necessary that the network always stays near the critical state corresponding to the phase transition point.

Solvent dependence of dynamic transitions in protein solutions

A transition as a function of increasing temperature from harmonic to anharmonic dynamics has been observed in globular proteins by using spectroscopic, scattering, and computer simulation techniques. We present here results of a dynamic neutron scattering analysis of the solvent dependence of the picosecond-time scale dynamic transition behavior of solutions of a simple single-subunit enzyme, xylanase. The protein is examined in powder form, in D2O, and in four two-component perdeuterated single-phase cryosolvents in which it is active and stable. The scattering profiles of the mixed solvent systems in the absence of protein are also determined. The general features of the dynamic transition behavior of the protein solutions follow those of the solvents. The dynamic transition in all of the mixed cryosolvent–protein systems is much more gradual than in pure D2O, consistent with a distribution of energy barriers. The differences between the dynamic behaviors of the various cryosolvent protein solutions themselves are remarkably small. The results are consistent with a picture in which the picosecond-time scale atomic dynamics respond strongly to melting of pure water solvent but are relatively invariant in cryosolvents of differing compositions and melting points.