A novel general biophysical model for simulating episodic endocrine gland signaling

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Abstract
A multiple-parameter convolution integral is used to define and generate waveforms that quantitatively and qualitatively resemble the experimentally observed behavior of episodic endocrine signals. Our formulation of the convolution integral in terms of multiple distinct parameters with statistically bounded values allows investigators to quantitatively model variations in the duration, amplitude, frequency, and/or contour of the hormone secretory pulse, as well as alterations in rates of endogenous hormone clearance. Here we demonstrate the applicability of this new concept of endocrine gland signaling to experimentally observed (physiological) endocrine data, parameter sensitivity analysis, the evaluation of statistical errors in hormone peak detection, and the estimation of random-pulse coincidence rates between two independent endocrine series.