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Biomedical subjects

J A Jacquez

Publications and source records attributed to J A Jacquez.

49 records · Page 3Linked to original sources
PubMed1970

Nonequilibrium facilitated oxygen transport in hemoglobin solution.

We have used the quasi-linearization method to obtain numerical solutions to the equations which describe steady-state diffusion of oxygen through layers of hemoglobin solution. The numerical solutions show how the facilitated flux of oxygen depends upon the layer thickness, reaction-rate coefficients, and other parameters of the system. The results indicate that steady-state oxygen diffusion in layers of hemoglobin solution, similar to those studied by Scholander, should be adequately described by the models which assume chemical equilibrium exists throughout the layer, but for layers of concentrated hemoglobin solution about the thickness of a human erythrocyte, the facilitation of oxygen diffusion should be much less than the equilibrium models predict.

Biological Transport↗
PubMedDate not supplied

The stochastic SI model with recruitment and deaths. I. Comparison with the closed SIS model.

We compare the stochastic and deterministic versions of an SI model with recruitment, background deaths, and deaths due to the disease. For the stochastic version, analysis of the mean number of susceptibles, mx, and infecteds, m(y), and of the means conditioned on nonextinction of the infection, m*x and m*y, shows that (1) if R0 < or = 1, the disease dies out monotonically for the deterministic and stochastic models, and (2) if R0 > 1, the disease dies out early with a probability close to (1/R0)a, where a is the number of infecteds introduced, or m(y) rises to a peak and then dies out slowly. For small populations, N, the peak is an obvious maximum. If N > or = 100, the peak in m(y) is hidden in a long, nearly stationary plateau and m*y is close to the deterministic endemic level for a large range of parameter values. The analytical results are illustrated with simulations. The results for the SI model are motivated by and compared with the corresponding results for the closed SIS model.

Communicable Diseases↗
PubMedDate not supplied

Identifiability and parameter estimation.

In experiments on biological systems one often cannot measure all state variables (compartments). Given a particular experiment of that type, a basic kinetic parameter may have no effect on the observations; such a parameter is an insensible parameter for that experiment. A parameter may influence the observations and not be uniquely determinable; such a parameter is nonidentifiable for that experiment. Only identifiable parameters can be estimated uniquely, by that experiment. I review the basic theory to check identifiability for a nominal value of a parameter (local identifiability), and present some examples of problems that may arise in estimation.

Kinetics↗