By Michael L. Johnson, Johannes D. Veldhuis
During this quantity modern equipment designed to supply insights into, mathematical constitution for, and predictive inferences approximately neuroendocrine keep watch over mechanisms are offered. Key good points* Collates an array of latest thoughts for research of neuroendocrine facts* Discusses present difficulties in and suggestions to neurohormone pulse research* Identifies correct software program on hand
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Additional info for Quantitative Neuroendocrinology
Brand and M. L. ), Vol. 210, pp. 539-575. Academic Press, San Diego, 1992. J. D. Veldhuis, F. Fraioli, A. D. Rogol, and M. L. Dufau, J. Clin. Invest. 77, 1122-1128 (1986). J. D. Veldhuis, M. L. Carlson, and M. L. Johnson, Proc. Natl. Acad. Sci. A. 84, 7686-7690 (1987).  Specific Methodological Approaches to Selected Contemporary Issues in Deconvolution Analysis of Pulsatile Neuroendocrine Data Johannes D. Veldhuis and Michael L. Johnson Introduction Neuroendocrine glands and ensembles typically signal remote target cells via an intermittent burstlike release of effector molecules (1-28).
The right-hand graphs give an expanded view. Ages are given in parentheses. 1 ~g/liter. Note expanded scale of right-hand graphs. Adapted with permission from Iranmanesh et al. (106), Low basal and persistent pulsatile growth hormone secretion are revealed in normal and hyposomatotripic men, J. Clin. Endocrinol. Metabol. 78, 84, 1994. 9 The Endocrine Society. 40 QUANTITATIVE NEUROENDOCRINOLOGY because both processes contribute jointly to the resultant overall plasma hormone concentration profile, and because parameters of the two corresponding functions are highly correlated.
Importantly, conditions of the assay should be optimized so as to place all experimentally unknown samples within the detectable range, definitively exceeding the detection limit by 2 SD or more. Moreover, where substantial within-assay variability exists, multiple dose-specific replicates should be carried out, the assay precision enhanced, and/or alternative assay schemes considered. Knowledge of within-assay variability is important analytically, because many curve fitting and other analytical tools utilize one or more measures of intrasample experimental uncertainty to weight the relative contribution of that sample mean to the fit of the data.