Cross-bridge Model Research Articles

Load clamp analysis of maximal force potential of mammalian cardiac muscle.

1. Abrupt alterations in load (load clamps) have been imposed on cat papillary muscle during isotonic shortening and relaxation of afterloaded twitch and tetanic contractions, to assess the maximal force potential for a given contractile state. 2. These load clamps were accompanied by an initial fast lengthening reflecting an undamped series compliance. Even when exceeding isometric twitch and tetanic force, these loads could be borne for a considerable time, accompanied by a slower lengthening after the initial extension of the series compliance. At sufficiently high loads the muscle was pulled out very rapidly; a maximal supra-isometric force potential was defined as the load the muscle could bear momentarily and this was measured at times throughout contraction and relaxation. 3. This maximal force potential was determined at different initial muscle lengths. Depending on the instantaneous loading conditions, various length-force relations were obtained from : (a) peak force values of isometric twitches at different starting lengths, (b) the shortest length reached during after loaded isotonic twitches, and (c) the forces obtained in overloaded isotonic twitch contractions. 4. These results are consistent with a crossbridge model in which the delayed lengthening during isotonic overloading is due to back rotation and detachment of attached crossbridges and in which the inital phase of spontaneous isotonic relaxation is governed by the same mechanism.

Computer simulation of movement-generating cross-bridges

A stochastic computational method was developed to study properties of cross-bridge models for muscle contraction, by following the time history of individual cross-bridge model of Andrew Huxley (1957) and a modified two-state model with more realistic behavior during steady stretching are used as examples. The method can readily compute steady-state force during shortening and stretching and force-transients following rapid changes in length. Computations of velocity with a steady load and of velocity transients are more sensitive to the randomness inherent in the stochastic method.

Computer simulation of flagellar movement. IV. Properties of an oscillatory two-state cross-bridge model

A stochastic computational method is used to examine the properties of a simple two-state cross-bridge model, of a type which has been shown previously to self-oscillate without requiring any feedback control of the active process. The force transients obtained with this model show the major features observed with oscillatory insect fibrillar flight muscle. The effects of viscosity and cross-bridge detachment rate on the frequency of oscillation of the model resemble the effects of viscosity and ATP concentration on flagellar oscillation, and the relationship between turnover rate and frequency of oscillation is also consistent with observations on flagella. However, the amplitude of oscillation of the model does not show the degree of frequency-independence which is typical of flagella.

Simulation of Biological Systems: Contraction of Skeletal Muscle

The simulations to be discussed here assume that force is developed at independent tension generators, and they identify those tension generators with the cross bridges seen in electron micrographs. These simulations attempt to de duce how the cross bridges behave under various circum stances, an essential preparatory step for discovering the actual force-producing phenomena. The mechanical proper ties of each individual cross bridge need not mirror those of the whole muscle. The number of cross bridges partici pating in tension development can vary, and some may be impeding contraction while others aid it. Therefore, one cannot easily predict whether cross bridges with any par ticular kind of behavior will produce behavior characteristic of whole muscle. Such predictions are possible with models and simulation. This review describes two specific cross bridge models, representing two general classes of models. It shows how the predictions of simulations led to a specific experiment whose outcome favored only one of these classes.