*Irving R. Epstein and John A. Pojman*

- Published in print:
- 1998
- Published Online:
- November 2020
- ISBN:
- 9780195096705
- eISBN:
- 9780197560815
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780195096705.003.0019
- Subject:
- Chemistry, Physical Chemistry

Including a chapter on biological oscillators was not an easy decision. In one sense, no book on nonlinear chemical dynamics would be complete without such a chapter. Not only are the most ...
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Including a chapter on biological oscillators was not an easy decision. In one sense, no book on nonlinear chemical dynamics would be complete without such a chapter. Not only are the most important and most numerous examples of chemical oscillators to be found in living systems, but the lure of gaining some insight into the workings of biological oscillators and into the remarkable parallels between chemical and biological oscillators attracts many, perhaps most, new initiates to the study of “exotic” chemical systems. On the other hand, it is impossible for us to do even a minimal job of covering the ground that ought to be covered, either in breadth or in depth. To say that the subject demands a whole book is to understate the case badly. There are indeed whole books, many of them excellent, devoted to various aspects of biological oscillators. We mention here only four of our favorites, the volumes by Winfree (1980), Glass and Mackey (1988), Murray (1993) and Goldbeter (1996). Having abandoned the unreachable goal of surveying the field, even superficially, we have opted to present brief looks at a handful of oscillatory phenomena in biology. Even here, our treatment will only scratch the surface. We suspect that, for the expert, this chapter will be the least satisfying in the book. Nonetheless, we have included it because it may also prove to be the most inspiring chapter for the novice. The range of periods of biological oscillators is considerable, as shown in Table 13.1. In this chapter, we focus on three examples of biological oscillation: the activity of neurons; polymerization of microtubulcs; and certain pathological conditions, known as dynamical diseases, that arise from changes in natural biological rhythms. With the possible exception of the first topic, these are not among the best-known nor the most thoroughly studied biological oscillators; they have been chosen because we feel that they can be presented, in a few pages, at a level that will give the reader a sense of the fascinating range of problems offered by biological systems.
Less

Including a chapter on biological oscillators was not an easy decision. In one sense, no book on nonlinear chemical dynamics would be complete without such a chapter. Not only are the most important and most numerous examples of chemical oscillators to be found in living systems, but the lure of gaining some insight into the workings of biological oscillators and into the remarkable parallels between chemical and biological oscillators attracts many, perhaps most, new initiates to the study of “exotic” chemical systems. On the other hand, it is impossible for us to do even a minimal job of covering the ground that ought to be covered, either in breadth or in depth. To say that the subject demands a whole book is to understate the case badly. There are indeed whole books, many of them excellent, devoted to various aspects of biological oscillators. We mention here only four of our favorites, the volumes by Winfree (1980), Glass and Mackey (1988), Murray (1993) and Goldbeter (1996). Having abandoned the unreachable goal of surveying the field, even superficially, we have opted to present brief looks at a handful of oscillatory phenomena in biology. Even here, our treatment will only scratch the surface. We suspect that, for the expert, this chapter will be the least satisfying in the book. Nonetheless, we have included it because it may also prove to be the most inspiring chapter for the novice. The range of periods of biological oscillators is considerable, as shown in Table 13.1. In this chapter, we focus on three examples of biological oscillation: the activity of neurons; polymerization of microtubulcs; and certain pathological conditions, known as dynamical diseases, that arise from changes in natural biological rhythms. With the possible exception of the first topic, these are not among the best-known nor the most thoroughly studied biological oscillators; they have been chosen because we feel that they can be presented, in a few pages, at a level that will give the reader a sense of the fascinating range of problems offered by biological systems.

*Irving R. Epstein and John A. Pojman*

- Published in print:
- 1998
- Published Online:
- November 2020
- ISBN:
- 9780195096705
- eISBN:
- 9780197560815
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780195096705.003.0016
- Subject:
- Chemistry, Physical Chemistry

Mathematically speaking, the most important tools used by the chemical kineticist to study chemical reactions like the ones we have been considering are sets of coupled, first-order, ordinary ...
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Mathematically speaking, the most important tools used by the chemical kineticist to study chemical reactions like the ones we have been considering are sets of coupled, first-order, ordinary differential equations that describe the changes in time of the concentrations of species in the system, that is, the rate laws derived from the Law of Mass Action. In order to obtain equations of this type, one must make a number of key assumptions, some of which are usually explicit, others more hidden. We have treated only isothermal systems, thereby obtaining polynomial rate laws instead of the transcendental expressions that would result if the temperature were taken as a variable, a step that would be necessary if we were to consider thermochemical oscillators (Gray and Scott, 1990), for example, combustion reactions at metal surfaces. What is perhaps less obvious is that our equations constitute an average over quantum mechanical microstates, allowing us to employ a relatively small number of bulk concentrations as our dependent variables, rather than having to keep track of the populations of different states that react at different rates. Our treatment ignores fluctuations, so that we may utilize deterministic equations rather than a stochastic or a master equation formulation (Gardiner, 1990). Whenever we employ ordinary differential equations, we are making the approximation that the medium is well mixed, with all species uniformly distributed; any spatial gradients (and we see in several other chapters that these can play a key role) require the inclusion of diffusion terms and the use of partial differential equations. All of these assumptions or approximations are well known, and in all cases chemists have more elaborate techniques at their disposal for treating these effects more exactly, should that be desirable. Another, less widely appreciated idealization in chemical kinetics is that phenomena take place instantaneously—that a change in [A] at time t generates a change in [B] time t and not at some later time t + τ. On a microscopic level, it is clear that this state of affairs cannot hold.
Less

Mathematically speaking, the most important tools used by the chemical kineticist to study chemical reactions like the ones we have been considering are sets of coupled, first-order, ordinary differential equations that describe the changes in time of the concentrations of species in the system, that is, the rate laws derived from the Law of Mass Action. In order to obtain equations of this type, one must make a number of key assumptions, some of which are usually explicit, others more hidden. We have treated only isothermal systems, thereby obtaining polynomial rate laws instead of the transcendental expressions that would result if the temperature were taken as a variable, a step that would be necessary if we were to consider thermochemical oscillators (Gray and Scott, 1990), for example, combustion reactions at metal surfaces. What is perhaps less obvious is that our equations constitute an average over quantum mechanical microstates, allowing us to employ a relatively small number of bulk concentrations as our dependent variables, rather than having to keep track of the populations of different states that react at different rates. Our treatment ignores fluctuations, so that we may utilize deterministic equations rather than a stochastic or a master equation formulation (Gardiner, 1990). Whenever we employ ordinary differential equations, we are making the approximation that the medium is well mixed, with all species uniformly distributed; any spatial gradients (and we see in several other chapters that these can play a key role) require the inclusion of diffusion terms and the use of partial differential equations. All of these assumptions or approximations are well known, and in all cases chemists have more elaborate techniques at their disposal for treating these effects more exactly, should that be desirable. Another, less widely appreciated idealization in chemical kinetics is that phenomena take place instantaneously—that a change in [A] at time t generates a change in [B] time t and not at some later time t + τ. On a microscopic level, it is clear that this state of affairs cannot hold.