Semi-mechanistic partial buffer approach to modeling pH, the buffer properties, and the distribution of ionic species in complex solutions.

In many biological science and food processing applications, it is very important to control or modify pH. However, the complex, unknown composition of biological media and foods often limits the utility of purely theoretical approaches to modeling pH and calculating the distributions of ionizable species. This paper provides general formulas and efficient algorithms for predicting the pH, titration, ionic species concentrations, buffer capacity, and ionic strength of buffer solutions containing both defined and undefined components.

Computational model of the cAMP-mediated sensory response and calcium-dependent adaptation in vertebrate olfactory receptor neurons.

We develop a mechanistic mathematical model of the G-protein coupled signaling pathway responsible for generating current responses in frog olfactory receptor neurons. The model incorporates descriptions of ligand-receptor interaction, intracellular transduction events involving the second messenger cAMP, effector ion-channel activity, and calcium-mediated feedback steps. We parameterized the model with respect to suction pipette current recordings from single cells stimulated with multiple odor concentrations.

Energy-based dynamic model for variable temperature batch fermentation by Lactococcus lactis.

We developed a mechanistic mathematical model for predicting the progression of batch fermentation of cucumber juice by Lactococcus lactis under variable environmental conditions. In order to overcome the deficiencies of presently available models, we use a dynamic energy budget approach to model the dependence of growth on present as well as past environmental conditions. When parameter estimates from independent experimental data are used, our model is able to predict the outcomes of three different temperature shift scenarios.