A flexible Numerical Matrices Method (NMM) for nonlinear system identification has been developed based on a description of the dynamics of the system in terms of kinetic complexes. A set of related methods are presented that include increasing amounts of prior information about the reaction network structure, resulting in increased accuracy of the reconstructed rate constants. The NMM is based on an analytical least squares solution for a set of linear equations to determine the rate parameters. In the absence of prior information, all possible unimolecular and bimolecular reactions among the species in the system are considered, and the elements of a general kinetic matrix are determined. Inclusion of prior information is facilitated by formulation of the kinetic matrix in terms of a stoichiometry matrix or a more general set of representation matrices. A method for determination of the stoichiometry matrix beginning only with time-dependent concentration data is presented. In addition, we demonstrate that singularities that arise from linear dependencies among the species can be avoided by inclusion of data collected from a number of different initial states. The NMM provides a flexible set of tools for analysis of complex kinetic data, in particular for analysis of chemical and biochemical reaction networks.

The goal of this work was to determine the effect of nonablative syngeneic transplantation of young bone marrow (BM) to laboratory animals (mice) of advanced age upon maximum duration of their lifespan. To do this, transplantation of 100 million nucleated cells from BM of young syngeneic donors to an old nonablated animal was performed at the time when half of the population had already died. As a result, the maximum lifespan (MLS) increased by 28 ± 5%, and the survival time from the beginning of the experiment increased 2.8 ± 0.3-fold. The chimerism of the BM 6 months after the transplantation was 28%.

The method of lifespan extension that is a practical application of the informational theory of aging is proposed. In this theory, the degradation (error accumulation) of the genetic information in cells is considered a main cause of aging. According to it, our method is based on the transplantation of genetically identical (or similar) stem cells with the lower number of genomic errors to the old recipients. For humans and large mammals, this method can be realized by cryopreservation of their own stem cells, taken in a young age, for the later autologous transplantation in old age. To test this method experimentally, we chose laboratory animals of relatively short lifespan (mouse). Because it is difficult to isolate the required amount of the stem cells (e.g., bone marrow) without significant damage for animals, we used the bone marrow transplantation from sacrificed inbred young donors. It is shown that the lifespan extension of recipients depends on level of their genetic similarity (syngeneity) with donors. We have achieved the lifespan increase of the experimental mice by 34% when the transplantation of the bone marrow with high level of genetic similarity was used.

The problem of the degradation and aging of bioorganisms is herein considered from the viewpoint of statistical physics. Two typical timescales in biological systems—the time of metabolic processes and the time of the life cycle—are used. A kinetic equation describing the small timescales of the systems’ characteristic processes in is proposed. Maintaining a biosystem in a time-stable state requires a constant inflow of negative entropy (negentropy). Ratios are proposed to evaluate the aging and degradation of systems in terms of entropy. As an example, the aging of the epithelium is studied. The connection of our approach to the information theory of aging is discussed, as well as theoretical constructions related to the concept of cooperon and its changing with time.

To analyze the mechanisms of action of weak electric and magnetic fields on ion motion in solution, a new approach is outlined allowing for collective interactions of large ionic ensembles with the external field. Bioelectromagnetics 18:25–27, 1997. © 1997 Wiley‐Liss, Inc.

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