Skip to main content
Top

1989 | Book

Transient Processes in Cell Proliferation Kinetics

Authors: Andrej Yu. Yakovlev, Nikolaj M. Yanev

Publisher: Springer Berlin Heidelberg

Book Series : Lecture Notes in Biomathematics

insite
SEARCH

About this book

A mathematician who has taken the romantic decision to devote himself to biology will doubtlessly look upon cell kinetics as the most simple and natural field of application for his knowledge and skills. Indeed, the thesaurus he is to master is not so complicated as, say, in molecular biology, the structural elements of the system, i. e. ceils, have been segregated by Nature itself, simple considerations of balance may be used for deducing basic equations, and numerous analogies in other areas of science also superficial add to one"s confidence. Generally speaking, this number of impression is correct, as evidenced by the very great theoretical studies on population kinetics, unmatched in other branches of mathematical biology. This, however, does not mean that mathematical theory of cell systems has traversed in its development a pathway free of difficulties or errors. The seeming ease of formalizing the phenomena of cell kinetics not infrequently led to the appearance of mathematical models lacking in adequacy or effectiveness from the viewpoint of applications. As in any other domain of science, mathematical theory of cell systems has its own intrinsic logic of development which, however, depends in large measure on the progress in experimental biology. Thus, during a fairly long period running into decades activities in that sphere were centered on devising its own specific approaches necessitated by new objectives in the experimental in vivo and in vitro investigation of cell population kinetics in different tissues.

Table of Contents

Frontmatter
Introduction
Abstract
A mathematician who has taken the romantic decision to devote himself to biology will doubtlessly look upon cell kinetics as the most simple and natural field of application for his knowledge and skills. Indeed, the thesaurus he is to master is not so complicated as, say, in molecular biology, the structural elements of the system, i.e. cells, have been segregated by Nature itself, simple considerations of balance may be used for deducing basic equations, and numerous analogies in other areas of science also add to one’s confidence. Generally speaking, this superficial impression is correct, as evidenced by the very great number of theoretical studies on population kinetics, unmatched in other branches of mathematical biology. This, however, does not mean that mathematical theory of cell systems has traversed in its development a pathway free of difficulties or errors. The seeming ease of formalizing the phenomena of cell kinetics not infrequently led to the appearance of mathematical models lacking in adequacy or effectiveness from the viewpoint of applications. As in any other domain of science, mathematical theory of cell systems has its own intrinsic logic of development which, however, depends in large measure on the progress in experimental biology. Thus, during a fairly long period running into decades activities in that sphere were centered on devising its own specific approaches necessitated by new objectives in the experimental in vivo and in vitro investigation of cell population kinetics in different tissues.
Andrej Yu. Yakovlev, Nikolaj M. Yanev
I. Some Points of the Theory of Branching Stochastic Processes
Abstract
This chapter outlines (with no proof presented) certain points of the theory of branching stochastic processes which will be of use in reading Chapter II. In addition, we have included here some theorems on the asymptotic behaviour of the Hellman-Harris process as well as some other results most frequently utilized in applications to cell population kinetics. It is presumed that the reader is familiar with the fundamentals of the probability theory in its present-day form. For this reason no further explanations will be given in connection with such terms as probability space, random variable (process, field), distribution function or generating function. However, all concepts and definitions peculiar to the theory of branching processes are given in a form that makes it unnecessary for the reader to refer to corresponding monographs or manuals. A number of excellent books are available on the theory of branching processes. Monographs by Athreya and Ney [2], Harris 147, Mode [9], Sevastyanov [12], Jagers [6] and Assmusen and Hering [1] deserve a special mention. Those were the sources used in the brief review that follows.
Andrej Yu. Yakovlev, Nikolaj M. Yanev
II. Induced Cell Proliferation Kinetics within the Framework of a Branching Process Model
Abstract
Mathematical description of initial stages in the growth of a cell population may be constructed in the following manner.Let us assume that at the moment t=0 there is in the population a certain, generally speaking, random number of cells m. At the moment t=0 the population is acted upon by the proliferative stimulus and all the cells appear to be at the zero age in relation to the mitotic cycle which they afterwards pass through independently of one another. On completion of the mitotic cycle each cell, independently of other cells, generates the random number v of descendants which are immediately involved into the next cycle of division. When it is considered that all the cells have the same distribution of the mitotic cycle duration X and the same distribution of the number of daughter cells v, the variables X and v being independent, it is then reasonable to turn to the model of the Bellman-Harris process defined by means of the distribution function for mitotic cycle duration
$$G\left( t \right)=P\left\{ x\le t \right\}$$
(1)
and the generating function for the number v of total cell progeny
$$h\left( s \right)=E\left\{ {{s}^{v}} \right\}=\sum\limits_{k=0}^{\infty }{P\left\{ v=k \right\}}{{s}^{k}}=\sum\limits_{k=0}^{\infty }{{{P}_{k}}}{{s}^{k}},\left| s \right|\le 1.$$
(2)
Andrej Y. Yakovlev, Nikolaj M. Yanev
III. Semistochastic Models of Cell Population Kinetics
Abstract
From the viewpoint of applications it appears important to modify the approaches to modelling cell population dynamics discussed in the preceding chapter so that they could be extended to a wider range of phenomena without substantially complicating the mathematical aspect of the problem.
Andrej Yu. Yakovlev, Nikolaj M. Yanev
IV. The Fraction Labelled Mitoses Curve in Different States of Cell Proliferation Kinetics
Abstract
The analysis of the fraction labelled mitoses curve (FLM) isone of the most frequently used methods for estimating indirectly the numerical characteristics (mean and variance) of the lengths of the separate phases in the mitotic cycle. Nearly all experimental data on cell population kinetics whether “in vitro” or “in vivo” are interpreted by analysing the structure of FLMs. In the majority of such studies graphical methods are used for the estimation of the mitotic cycle and its phases lengths; these are not based on modern dynamic theory of cell systems. In order to obtain more sound methods it is necessary to construct a mathematical model for FLM and an appropriate procedure for non-linear estimation of its parameters.The basic principle for the indirect estimation of the mitotic cycle temporal parameters consists, therefore, of finding a set of their values which maximize, in some sense, the agreement between the model and the experimentally found FLM.
Andrej Yu. Yakovlev, Nikolaj M. Yanev
V. Applications of Kinetic Analysis. Rat Liver Regeneration
Abstract
From the exposition in Chapter III it follows that a broader scope of kinetic analysis of induced cell proliferation may eventuate from investigating the peculiarities of behaviour of qS(t) and PS(t) indices which make it possible to separately assess the processes of initial and recurrent transition of cells to DNA synthesis after the onset of the effect of a proliferative stimulus. For calculating qS(t) and PS(t) it is necessary to have experimental data on the dynamics of such indices as I S C (t), continuously labelled cells index, IS(t), pulse labelled cells index, and IM(t), mitotic index, as well as estimates of the temporal parameters \( {{\bar{\tau }}_{S}} \), σ S and \( {{\bar{\tau }}_{M}} \). In certain cases the parameters \( {{\bar{\tau }}_{S}} \) and σ S may be evaluated without the labelled mitoses curve (FLM), an instance being given in Chapter III. The method for estimating the parameters of the S-,G2- and M-phases of the mitotic cycle described in Chapter IV is based on optimization of the parameters of theoretical FLM(t) whose construction, in turn, includes as an indispensable step calculation of the q-index for the S-phase. In this way estimating the temporal parameters and constructing the qS- index are combined in a single computation procedure.
Andrej Yu. Yakovlev, Nikolaj M. Yanev
Conclusion
Abstract
At present there are no longer any doubts that adequate characterization of the kinetics of proliferative processes is impossible without employing methods of the present-day mathematical theory of cell systems and staging experiments designed specifically for the application of such methods. In solving concrete problems of cell population kinetics need arises at all times for widening the applicability limits of the existing methods of the cell system theory, as well as for bringing closer together the available theoretical results and accumulated evidence. In other words, it is necessary to consistently adapt the model in use to various known features of the organization of cell proliferation processes and actual potentialities of biological experiment.
Andrej Yu. Yakovlev, Nikolaj M. Yanev
Backmatter
Metadata
Title
Transient Processes in Cell Proliferation Kinetics
Authors
Andrej Yu. Yakovlev
Nikolaj M. Yanev
Copyright Year
1989
Publisher
Springer Berlin Heidelberg
Electronic ISBN
978-3-642-48702-6
Print ISBN
978-3-540-51831-0
DOI
https://doi.org/10.1007/978-3-642-48702-6