Abstract
The secretion of anterior-pituitary hormones is subject to negative feedback. Whether negative feedback evolves dynamically over 24 h is not known. Conventional experimental paradigms to test this concept may induce artifacts due to nonphysiological feedback. These limitations might be overcome by a noninvasive methodology to quantify negative feedback continuously over 24 h without disrupting the axis. The present study exploits a recently validated model-free regularity statistic, approximate entropy (ApEn), which monitors feedback changes with high sensitivity and specificity (both >90%; Pincus SM, Hartman ML, Roelfsema F, Thorner MO, Veldhuis JD. Am J Physiol Endocrinol Metab 273: E948-E957, 1999). A time-incremented moving window of ApEn was applied to LH time series obtained by intensive (10-min) blood sampling for four consecutive days (577 successive measurements) in each of eight healthy men. Analyses unveiled marked 24-h variations in ApEn with daily maxima (lowest feedback) at 1100 +/- 1.7 h (mean +/- SE) and minima (highest feedback) at 0430 +/- 1.9 h. The mean difference between maximal and minimal 24-h LH ApEn was 0.348 +/- 0.018, which differed by P < 0.001 from all three of randomly shuffled versions of the same LH time series, simulated pulsatile data and assay noise. Analyses artificially limited to 24-h rather than 96-h data yielded reproducibility coefficients of 3.7-9.0% for ApEn maxima and minima. In conclusion, a feedback-sensitive regularity statistic unmasks strong and consistent 24-h rhythmicity of the orderliness of unperturbed pituitary-hormone secretion. These outcomes suggest that ApEn may have general utility in probing dynamic mechanisms mediating feedback in other endocrine systems.
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