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Am J Physiol Regul Integr Comp Physiol 278: R1247-R1257, 2000;
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Vol. 278, Issue 5, R1247-R1257, May 2000

Explicating hypergonadotropism in postmenopausal women: a statistical model

Daniel M. Keenan1 and Johannes D. Veldhuis2,3

1 Department of Statistics, 2 Division of Endocrinology, Health Sciences Center, 3 National Science Foundation Center for Biological Timing, University of Virginia, Charlottesville, Virginia 22908


    ABSTRACT
TOP
ABSTRACT
INTRODUCTION
METHODOLOGY
RESULTS
DISCUSSION
APPENDIX
REFERENCES

Neurohormone secretion is viewed here as a variable (unknown) admixture of basal and pulsatile release mechanisms, convolved with individually fitted biexponential elimination kinetics. This construct allows maximum-likelihood estimates of both (regulated and constitutive) components of hormone secretion. Thereby, we infer that a prolonged slow-component half-life of gonadotropin removal and amplified pulsatile (and total) daily luteinizing hormone (LH) secretion rates jointly explicate the postmenopausal elevation in serum LH concentrations without a necessary rise in basal LH secretion rates. This biomathematical formulation should be useful in exploring other neuroregulatory mechanisms that underlie single or dual alterations in the basal versus pulsatile modes of hormone secretion.

gonadotropin; human; methods; statistics; age; analysis; luteinizing hormone


    INTRODUCTION
TOP
ABSTRACT
INTRODUCTION
METHODOLOGY
RESULTS
DISCUSSION
APPENDIX
REFERENCES

IN VIVO AND IN VITRO STUDIES of endocrine glands suggest the existence of two physiologically distinguishable modes of regulated secretion, namely, time-invariant basal hormone secretion and secretagogue-driven pulsatile hormone release (15). The basal mode may represent a constitutive, unregulated, or slowly varying hormone release process (3, 12, 19, 34, 39, 40). In contrast, pulsatile secretion likely reflects rapid exocytosis of previously accumulated neurohormone (19, 43).

Pulsatile hormone release was recognized shortly after the development of RIAs in the early 1970s. Subsequent studies revealed that, in some cases, the magnitude and/or frequency of a pulse signal is critical to its tissue actions; e.g., in the gonadotropin releasing hormone-luteinizing hormone (GnRH-LH)-gonadal axis; for insulin secretion and action; in the growth hormone-insulin-like growth factor-I (GH-IGF-I) axis, and, for the actions of parathyroid hormone (PTH), oxytocin, or glucagon (15, 17, 29, 31, 35, 36, 38, 41). In contrast, knowledge of the mechanisms underlying basal hormone secretion and its tissue impact has lagged considerably. Indeed, in the case of several hormones, such as GH, physiological basal secretion was not demonstrable until the recent emergence of ultrahigh-sensitivity assays (14). On the other hand, apparently elevated basal hormone release is evident in various neuroendocrine pathologies, such as GH, ACTH, and prolactin-secreting pituitary tumors (12) and aldosteronomas (39).

A variable admixture of basal and pulsatile secretion seems to typify the release of some neurohormones, e.g., prolactin, GnRH during the preovulatory LH surge, and PTH, wherein 30-70% of hormone release appears to be nonpulsatile (10, 14, 23, 34).

Admixed basal and pulsatile hormone release also seems to characterize feedback withdrawn states, e.g., hypersecretion of PTH in hypocalcemia (34) or LH in response to testosterone withdrawal (49). Thus accurately partitioning basal versus pulsatile hormone secretion, albeit technically challenging (44, 47), should aid in separating normal physiology (low basal release), pathophysiology (jointly increased basal and pulsatile secretion), and pathology (elevated basal hormone production). To date, reliable segmentation of basal versus pulsatile release has been confounded technically by strong correlations among hormone half-life and basal and pulsatile secretion rates (44, 47). A recent step toward addressing this impasse is nonparametric or waveform-free half-life-dependent deconvolution techniques (7, 16, 24), which to date have received limited or no validated application to extended hormone profiles. As an alternative strategy, here we illustrate a physiologically motivated analytic construct that embodies variably combined basal and pulsatile hormone release, random secretory bursting, and fitted estimates of slow and fast half-lives.


    METHODOLOGY
TOP
ABSTRACT
INTRODUCTION
METHODOLOGY
RESULTS
DISCUSSION
APPENDIX
REFERENCES

Overall model. Our general formulation defines Z(t) as the hormone secretion rate at time t (units for LH = IU · l-1 · min-1)
<IT>Z</IT>(<IT>t</IT>) = &bgr;<SUB>0</SUB> + <IT>P</IT>(<IT>t</IT>) (1)
where beta 0 is the unknown basal secretion rate and P(·) is the (nonconstant) pulsatile secretion rate. As a disappearance model, we allow for a fast and slow elimination component, where a and - a are their respective proportions. In Ref. 21 we show that rate of change in the blood hormone concentration [X(t)] is then described by differential equations, whose solution is
<IT>X</IT>(<IT>t</IT>) = [<IT>ae</IT><SUP>−&agr;<SUB>1</SUB><IT>t</IT></SUP> + (1 − <IT>a</IT>)<IT>e</IT><SUP>−&agr;<SUB>2</SUB><IT>t</IT></SUP>]<IT>X</IT>(0) 

+ &bgr;<SUB>0</SUB> <FENCE><FR><NU><IT>a</IT></NU><DE>&agr;<SUB>1</SUB></DE></FR> (1 − <IT>e</IT><SUP>−&agr;<SUB>1</SUB><IT>t</IT></SUP>) + <FR><NU>1 − <IT>a</IT></NU><DE>&agr;<SUB>2</SUB></DE></FR> (1 − <IT>e</IT><SUP>−&agr;<SUB>2</SUB><IT>t</IT></SUP>)</FENCE>

+ <LIM><OP>∫</OP><LL>0</LL><UL><IT>t</IT></UL></LIM>(<IT>ae</IT><SUP>−&agr;<SUB>1</SUB>(<IT>t</IT>−<IT>r</IT>)</SUP> + (1 − <IT>a</IT>)<IT>e</IT><SUP>−&agr;<SUB>2</SUB>(<IT>t</IT>−<IT>r</IT>)</SUP>)<IT>P</IT>(<IT>r</IT>) d<IT>r</IT>

≈ &bgr;<SUB>0</SUB> <FENCE><FR><NU><IT>a</IT></NU><DE>&agr;<SUB>1</SUB></DE></FR> + <FR><NU>1 − <IT>a</IT></NU><DE>&agr;<SUB>2</SUB></DE></FR></FENCE> + <LIM><OP>∫</OP><LL>0</LL><UL><IT>t</IT></UL></LIM>(<IT>ae</IT><SUP>−&agr;<SUB>1</SUB>(<IT>t</IT>−<IT>r</IT>)</SUP>

 + (1 − <IT>a</IT>)<IT>e</IT><SUP>−&agr;<SUB>2</SUB>(<IT>t</IT>−<IT>r</IT>)</SUP>)<IT>P</IT>(<IT>r</IT>) d<IT>r</IT>

′′due to basal” + ′′due to pulsatile secretion” (2)

Here, we add the consideration of biexponential fitting of both the elimination process and estimation of each of three constructs of basal secretion (beta 0). The three models are 1) freely varying or analytically fitted beta 0 (F model, above); 2) zero basal (Z model); 3) basal secretion constrained a) to a known steady-state [C(SS) model] hormone concentration (e.g., measured before experimental hormone injections) or b) to a percentage of total secretion [C(gamma ) model, where gamma  is a literature-based population parameter (e.g., gamma  = 11% of the LH concentration for men). If pulsatile secretion is eliminated selectively in equation 2, then the steady-state hormone concentration [X(t)] is the first term. To indirectly estimate basal LH release in models 3a or 3b, we use data from earlier clinical experiments that used GnRH agonists or antagonists to largely eliminate (GnRH stimulated) LH pulses (6, 11, 30). First, we injected a GnRH agonist (leuprolide) to achieve a low known rate of basal LH release, superimposed on which we infused known (pulsatile) amounts of recombinant LH. This experiment identified terms for construct C(SS) above, consisting of a known basal LH. Second, we used our own and literature-based experiments with GnRH antagonists that preferentially disable (GnRH stimulated) pulsatile LH release, thus allowing estimates of (fractional) basal secretion: construct C(gamma ) above. In addition, on the basis of the published biexponential kinetics of highly purified human LH in hypopituitary volunteers (46), we further validated quantitative model recovery from distribution volume estimates.

Clinical methods. Serum immunoreactive LH concentration time series were obtained and reported previously by sampling blood in healthy women at 10-min intervals for 24 h, after provision of written informed consent approved by the Human Investigation Committee (8, 32). Six volunteers were studied in each of the following categories: for each of three separate phases of the normal menstrual cycles [early follicular (EF), late follicular (LF), and midluteal (MI) phases] and estrogen-unreplaced postmenopausal women (ages 55-75). The ranges of the intra- and interassay coefficients of variations in the LH immunoradiometric assay (IRMA) are 4.5-8.3% and 6.8-10%, and assay sensitivity is 0.8 IU/l (First International Reference Preparation).

As one biological validation strategy, we administered the GnRH agonist, leuprolide acetate (3.75 mg im), to downregulate endogenous LH release in five healthy men. Three weeks thereafter, volunteers received intravenous bolus injections of human recombinant LH (Serono Laboratories, Norwell, MA) at 2-h intervals. LH was infused at a fixed dose of 7.5, 15, 30, 50, or 75 IU/pulse over 1 or 8 minutes for a total of four to eight consecutive infusion pulses. Blood was withdrawn at 10-min intervals beginning immediately before the first infused LH pulse (0800 clock time) and throughout the infusion until 3 h after the last injection. Serum was later assayed for LH content by IRMA (above). Preinjection serum testosterone concentrations were <85 ng/dl (2.5 nmol/l) during leuprolide-induced suppression of the gonadotropic axis.


    RESULTS
TOP
ABSTRACT
INTRODUCTION
METHODOLOGY
RESULTS
DISCUSSION
APPENDIX
REFERENCES

In the five LH-suppressed men infused with variable but known amounts of recombinant human LH, we estimated the several masses of LH infused (known amounts were 7.5, 15, 30, 50 and 75 IU/pulse; Serono). To this end, we applied each of the three separate formulations of "basal" LH secretion: 1) freely varying or analytically fitted (F model); 2) zero basal (Z model); 3a) constrained by the preinjection steady-state [C(SS) model] measured serum LH concentration or 3b) constrained by a percentage of total secretion [C(11) model: e.g. 11% for men (30)]. For any model, the calculated slope of the plot of infused LH dose (IU) versus estimated LH pulse mass (IU/l) is the reciprocal of the LH distribution volume, which was determined independently earlier (46). As illustrated in Fig. 1, the slopes for the four models predict LH distribution volumes of 3.7 (F model), 4.2 (Z model), 4.6 [C(SS) model], and 4.8 liters [C(11) model]. The values fall within the estimated adult male range of 3-5 liters based on highly purified human pituitary LH extracts (46), although this could vary depending on LH isoforms and/or gender. The application of all four models of freely varying, zero, and constrained (steady state and 11%) basal secretion is shown. Figure 2 illustrates that, in the experimentally known basal [C(SS)] model, the second (slow)-component LH half-life is proportionate (r = +0.93, P = 0.02) to the dose of recombinant human LH injected.


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Fig. 1.   Plots of linear fits of dose (mass) of recombinant human luteinizing hormone (LH) injected (IU) vs. calculated mass (IU/l) of LH recovered in 5 leuprolide-suppressed men given 1 or 8 min intravenous infusions of 7.5, 15, 30, 50, or 75 IU of LH. LH distribution volume (V0) is estimated by reciprocal of slope.



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Fig. 2.   Plots of mass of human recombinant LH infused vs. first (rapid)- or second (slow)-phase LH half-lives (t1/2) calculated for steady-state constrained (pre-LH injection) model of basal LH secretion for experiment defined in Fig. 1. Linear regression analyses are shown with corresponding correlation coefficients and P values in 5 men evaluated.

Serum LH time series in women sampled every 10 min over 24 h were analyzed next according to the foregoing three formulations of basal secretion: freely varying, zero, or constrained. On the basis of earlier published GnRH antagonist studies in women, constrained basal secretion rates (basal secretion as percentages of total secretion) were taken as nominally 24% in premenopausal females (EF, LF, and ML, respectively) and 34% in postmenopausal women (6, 11). ANOVA applied to the resultant data revealed several major points summarized in Fig. 3, A-E, which shows slow-component LH half-lives; LH pulse frequency; and daily basal, pulsatile, and total LH secretory rates. Illustrative individual women's data (parameter estimates with corresponding estimated SEs) are given in Tables 1-3.






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Fig. 3.   Estimates of daily pulsatile LH secretion (A), slow-component LH half-lives (B), daily basal (absolute) LH secretion (C), daily total (pulsatile plus basal) LH secretion (D), and LH pulse frequency (E) in individual healthy premenopausal women studied in early follicular (EF), late follicular (LF), or midluteal (ML) phases of menstrual cycle and postmenopausal (PM) women. Data are means ± SE of separate estimates for the 3 (or 2) principal models of basal LH secretion 1) zero basal; 2) freely varying (fitted or analytically estimated); and 3) constrained (residual LH secretion continuing after gonadotropin-releasing hormone (GnRH)-antagonist administration; namely, 24% in young and 34% in older women; METHODOLOGY). Each woman underwent blood sampling at 10-min intervals for 24 h beginning at 0800 (clock time). LH measures by IRMA are IU/l (First International Reference Preparation). For each model, P values were determined by ANOVA after logarithmic transformation of data in 4 study groups. Different letters denote significantly different means by post hoc testing by Duncan's new multiple-range test.


                              
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Table 1.   Illustrative LH analyses and SEs of fitted parameters for 1 woman from each of 4 study groups


                              
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Table 2.   Individual parameter estimates and their SEs for LH secretion and elimination in EF female 1 


                              
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Table 3.   Individual parameter estimates and their SEs for LH secretion and elimination in PM female 1 

An unexpected finding was a high within-subject agreement (low variability) among estimates of LH pulse mass (and daily pulsatile LH secretion) across the various basal-secretion models. For example, the median (and range) coefficients of variation (SD/mean × 100%) among the four model-based estimates of LH burst mass within subjects were 3.2 (1.5-9.2%) in EF, 5.4 (3.8-14%) in LF, and 5.8 (2.3-16%) in ML phase young women and 4.5 (1.7-5.0%) in postmenopausal women.

Second, according to all three models, daily pulsatile (and total) LH secretion was maximal in postmenopausal women, and minimal in the ML phase of the menstrual cycle (Fig 3A). Third, two-component LH half-life values fell within the published normal range in the human, namely, for the (freely varying) rapid and slow components, respectively, 7-36 and 46-240 min (8, 46; Fig. 3B). These estimates in women compare with (mean ± SD) values of 18 ± 5 and 90 ± 22 min reported earlier for rapid- and slow-phase LH half-lives in four LH-injected hypopituitary men (46). The corresponding LH half-life ranges were 7-25 (rapid phase) and 58-130 min (slow phase) in the C(SS) model using literature-based GnRH-antagonist data to estimate the percentage basal.

In both non-zero basal models, the calculated percentage basal LH secretion ranged absolutely from 1 to 54% within the four groups of woman studied here (see Tables 1-3). In postmenopausal women, percentage basal LH release (variable, analytically estimated) was 2-52%, similar to the values in younger women (1-54%). Thus (in the non-zero basal models) increased absolute basal LH secretion (but not greater fractional partitioning of basal versus pulsatile LH release) characterized post (versus pre-)-menopausal women (Fig. 3C).

The highest daily total LH secretion rates (freely varying basal model) were attained in older women (260-980 IU · l-1 · 24 h-1). The range of values in LF phase premenopausal women was 47-850 IU · l-1 · 24 h-1, in the EF phase was 63-140 IU · l-1 · 24 h-1, and in ML phase was 25-150 IU · l-1 · 24 h-1 (Fig. 3D).

On the assumption of zero basal LH secretion (daily) LH pulse mass estimates remained remarkably similar to those in the two other models (freely varying vs. literature-constrained basal secretion). In the zero basal model, estimated second-component LH half-lives also tended (P = not significant by ANOVA, P < 0.05 by the Kruskal-Wallis test) to be longer in postmenopausal women and shorter in ML phase young women (Fig. 3B).

Use of a literature-constrained (GnRH antagonist predicted) percentage basal rate of LH secretion sometimes predicted lower basal secretion than freely varying (fitted) estimates and lower slow-phase LH half-lives than the zero basal model. The calculated daily LH pulse mass was similar to those in the other two models (Fig. 3A). Pulse frequency estimates were model independent and showed slowing only in the ML phase (Fig. 3E).

Illustrative observed 24-h serum LH concentration profiles, calculated (fitted) profiles, and estimated pulsatile and basal LH secretion curves are given in Fig. 4 for each of the three different formulations of basal LH release. The individual profiles highlight 1) variability among menstrual contexts and 2) distinctions among the three analytic constructs of basal (LH) secretion.


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Fig. 4.   Illustrative 24-h serum LH concentration profiles in 3 of 18 healthy premenopausal women respectively, 1 individual in each of EF, LF, and ML phases of menstrual cycle) and 1 of 6 PM individuals. There are 2 subpanels for EF, top left; LF, top right; ML, bottom left; and PM, bottom right. Each pair of subpanels shows measured and fitted serum LH concentrations obtained by sampling every 10 min for 24 h beginning at 0800 (clock time) (top line), as well as the model-calculated LH secretory rates (bottom line). Three constructs of basal LH secretion are illustrated by various interrupted lines: dotted, zero basal; dashed-dotted, constrained basal; and dashed, freely varying basal (METHODOLOGY).

As a general modeling comment, which is applicable to Tables 2 and 3, for those parameters that describe the pulsatile structure, mass accumulation (eta 0, eta 1), pulse shape (beta 1, beta 2, beta 3), and the variance of pulse mass random effects (sigma 2A), the precision of their estimators is determined as much by the number of pulses as by the actual number of observations. In Tables 2 and 3, illustrating the individual parameter estimates for an EF female and a postmenopausal female, the number of pulse times were 10 and 16, respectively. In Table 2, particularly, some of the (estimated) SEs are large enough that several of the above parameters could not be individually rejected from being zero. In part, this is the consequence of allowing for the flexibility necessary for describing the broad range of profiles encountered in practice; for example, sometimes two of the three pulse shape parameters will suffice, but which two of the three can vary among individuals, and, in some women, there appears to be large basal secretion, whereas for others there is not. The modeling implication of all of this is somewhat dependent on one's specific goal. If the purpose is to find the most parsimonious model for a particular individual, then one might attempt to eliminate potential parameters in a manner analogous to stepwise regression. However, in the present context, these structural parameters are, in some sense, more like nuisance parameters, whose importance rests in their combination allowing one to soundly estimate total daily pulsatile secretion and to assign a justified SE (Table 1). These resulting aggregates are in general well separated from zero.


    DISCUSSION
TOP
ABSTRACT
INTRODUCTION
METHODOLOGY
RESULTS
DISCUSSION
APPENDIX
REFERENCES

We here present, validate, and then apply a random-effects and maximum-likelihood methodology to evaluate hormone biexponential elimination and pulsatile and basal neurohormone secretion according to different renditions of basal secretory behavior. This new analytic formulation extends our earlier efforts by 1) delineating three distinct possible notions of basal secretion; 2) implementing biexponential kinetics; 3) requiring independent biological validation using recombinant human LH infusions; and 4) analyzing full 24-h-long serum LH concentration profiles in women in different menstrual contexts to clarify normal physiology. Indeed, evaluating LH secretion in a relatively large cohort (n = 24) of healthy pre- and postmenopausal women unmasked an unanticipated, remarkably robust within-subject uniformity of estimates of LH secretory burst mass across the three analytically distinct strategies for defining basal gonadotropin release: 1) zero basal and thus purely pulsatile LH secretion; 2) freely varying analytically estimated basal LH secretion; or 3) constrained or putatively non-GnRH-dependent basal LH release. In particular, in any given menstrual context, the three structurally distinct assumptions regarding basal LH secretion predicted a similar mean mass of LH secreted in pulses for any woman. The median within-subject coefficients of variation of estimated LH pulse mass among the three models fell within the range of 3-6%. This primary observation suggests the thesis that, for a fitted two-compartment LH elimination process, the investigator's choice of a particular model of basal LH secretion does not uniquely dictate the estimate of endogenous LH secretory pulse mass. In accordance with this inference, daily pulsatile LH secretion can be estimated robustly within subject independently of the basal secretion analytic construct, conditional on determinable LH pulse frequency and two-component LH half-lives.

Model-independent within-subject estimation of LH pulse mass has several important implications. First, the pulsatile mode of LH secretion, presumptively activated by hypothalmic GnRH impulses, should be a more robust measurable endpoint of neuroendocrine regulation. Second, unlike our own and other earlier highly parameterized constructs (21), the present more parsimonious formulation of basal and pulsatile LH secretion along with biexponential kinetics obviates some of the strong mathematical confounds that impede maximum-likelihood estimates (44). Third, because the sum of the estimated random mass effects within any given time series is (theoretically) zero (21), we can calculate by maximum-likelihood analysis statistically valid confidence intervals for pulsatile and basal LH secretion and LH half-lives. We showed earlier that this cannot be accomplished reliably for a one-component disappearance idiom (21, 44). Fourth, by comparing basal and pulsatile secretion of LH among reproductive states in healthy women, we could examine gonadotropin regulation across the normal adult human female lifetime.

Comparison of LH profiles disclosed that postmenopausal women have a pronounced augmentation of LH secretory burst mass. In principle, such unleashing of pulsatile LH release in the gonadoprival state may reflect an expanded gonadotroph-cell secretory capacity and/or enhanced endogenous GnRH drive (8). In contrast, in premenopausal women, LH pulse mass remained nearly constant across the menstrual cycle, except for the ML phase.

Half-life variations might occur in postmenopausal versus premenopausal women. In particular, according to the zero-basal and constrained-basal models, the calculated LH half-life rises postmenopausally and falls in the ML phase. The former inference was suggested recently in GnRH antagonist-based studies (37). In this regard, a recent kinetic analysis of 14 human LH isoforms in a heterologous assay disclosed up to a twofold range in their in vivo half-lives (3). Analogously, in the human and animals, gonadal status (e.g., postovariectomy) may alter evident rates of in vivo LH disappearance (1, 3, 5, 27, 47, 49, 50).

Postmenopausally increased basal LH secretion was implied only in the constrained basal model. This is in accord with the literature-based inference that the percentage of basal LH secretion, when defined as non-GnRH dependent, is elevated after a GnRH antagonist in postmenopausal women (6, 11, 30). In contrast, according to a fitted basal secretion model, the absolute, but not percentage, basal LH secretion rate is higher in postmenopausal individuals. In neither construction was the variation in basal LH secretion rate the dominant mechanism regulating total daily LH secretion and hence mean serum LH concentrations in premenopausal women. Because estrogen concentrations vary remarkably across the menstrual cycle, these analyses allow one to conjecture further that estrogen or one of its gonadal covariates controls primarily pulsatile (rather than basal) LH secretion. Estrogen may also influence the slow-component half-life of LH, because the latter is elevated in the face of estrogen withdrawal. Whereas clinical studies with GnRH antagonists have suggested a lower percentage of ostensibly GnRH-independent LH secretion in young versus older women (6, 11, 30), such measures are derived in the face of near-maximal inhibition of endogenous GnRH action and thus, by definition, do not reflect the interpulse rate of basal LH release that actually occurs in the presence of physiological endogenous GnRH drive. Indeed, GnRH itself might contribute in part to maintaining some fraction of basal or nonpulsatile gonadotrope secretory activity. In fact, our freely varying fitted basal secretion construct predicts higher LH interpulse secretion than that suggested by GnRH antagonist studies.

The present strategy of partitioning total daily hormone release into respective basal and pulsatile components, conditional on pulse times and with the inclusion of random LH pulse-mass effects, simplifies several earlier numerical deconvolution approaches (44). Here we estimate approximately seven principal parameters of hormone secretion and two of hormone elimination, rather than 20-30 parameters as required in some previous efforts (8, 44). The core estimates include basal secretion (beta 0); the average rate of interpulse hormone (mass) accumulation (eta 0) and a constant (eta 1) relating this value to the prior interpulse interval; (one or more of) three key features of the secretory burst shape: rate of secretory burst ascent, peakedness, and steepness of descent; a random-effects term, defining stochastic variability in pulse mass accumulation; and the rapid versus slow hormone half-lives. If one used an a priori hormone secretory pulse shape, e.g., as determined by direct venous catheterization (2), this knowledge would eliminate the fitting of pulse-shape parameters, allowing further simplification. Analogously, independent ascertainment of elimination kinetics would obviate the need to solve for these terms in the analysis. Importantly, the foregoing core parameters all mirror basic physiological processes. For example, the rapid increase and slow decrease in secretion rates within a burst would likely correspond to prompt exocytotic discharge of prestored hormone granules and delayed de novo biosynthesis and release of additional hormone, respectively (19). Similarly, the slow component of hormone (LH) removal would seem to reflect its irreversible metabolic clearance from the body (3, 46).

These analyses uncover other challenging issues in appraising basal hormone secretion. First, absolute basal LH secretion rates can vary by severalfold across the reproductive life span and among individuals. Second, independent knowledge of rapid and slow hormone half-lives would aid in distinguishing the contribution of basal secretion from that of the slower half-life to the mean hormone concentration. In addition, accurate a priori defined hormone half-lives could help to discriminate between otherwise statistically comparable models of combined pulsatile and basal secretion. In contrast, we show here that estimation of the pulse mass of hormone secreted is largely basal model free. Because kinetic values are not always easily established for an individual in any particular clinical or experimental setting, we can suggest in the future also implementing a Bayesian modification of the present approach with preconditioning on the expected population hormone half-life and/or anticipated basal secretion rate.

The present LH time series were collected by blood withdrawal every 10 min for 24 h and show good precision in the estimation of daily LH secretion and several key secretory parameters, as well as the more prolonged half-life phase (see Table 1-3). Pulse shape is less well estimated, in view of relatively infrequent sampling compared with the brevity of LH secretory pulses. Similarly, the rapid half-life component can only be estimated with an adequate sampling interval, Delta t. That is, the half-life cannot be less than log(2) × Delta t; thus, for Delta t = 10 min, the lower bound is 6.93 min.

Although the random-effects maximum-likelihood appraisal of basal and pulsatile LH secretion is illustrated here only in healthy women, this analytic strategem should have relevance in other contexts, e.g., in assessing LH pathophysiology in various study populations and in evaluating the secretory control of other neurohormones. In addition, by incorporating relevant physiological linkages and dose-response interfaces, e.g., as suggested earlier for the integrated male GnRH-LH-testosterone feedforward and feedback axis (20), this core construct might be extended to allow appraisal of joint secretion by coupled glands within an interconnected endocrine network.

Perspectives

The challenge of correctly partitioning an unknown admixture of episodic and basal (nonpulsatile) neurohormone secretion into the two corresponding contributions has been difficult to surmount analytically (44). Here, we extend the notion of dissecting comingled pulsatile and nonpulsatile hormone release given serial measurements of their combined output convolved with elimination processes in peripheral blood. Critical factors making such estimates possible include first the introduction of a biexponential (and hence 2 compartmental) disappearance function, which incorporates several unobserved features of the dissipation phenomenon. Second, both the number and cross-correlated nature of secretion parameters are restricted in the analysis by conditioning the deconvolution solution on predetermined pulse times estimated independently (18). Available a priori knowledge of the biexponential kinetics or the percentage admixture of pulsatile and basal components in the release process would aid further. However, major issues remain unresolved. For example, to date there are few objective in vivo validation strategies that combine constant neurohormone infusions with superimposed pulselike injections of varying defined amplitudes (33). Analogously, more studies are needed that sample blood at high frequency and over a prolonged duration near the site of neurohormone outflow to monitor the patterns of joint basal and pulsatile secretion directly (4, 9, 26, 28, 42). Moreover, more refined analyses will need to incorporate the nonlinear impact of one or multiple binding proteins in plasma and/or tissues on the partitioning of hormone removal (47a, 48). Indeed, empirical biexponential kinetics oversimplify the true physics and physiology that presumably underlie the hormone dispersal process in the circulatory tree. For example, one might envision rapid postsecretory diffusion of molecules in the aqueous space of blood, high-velocity advection along the primary direction of flow in the arterial and proximal venous systems, geometric dilution of hormone molecules by the arborizing vasculature, capillary transit, and secondary confluence into proximal venous trunks. Within this whole body circuitry, there is the region-specific irreversible removal of hormone molecules (e.g., in liver, spleen, kidney, etc.) at some probability level. We reason that an empirically estimated biexponential elimination model approximates the aggregate of these nonlinear processes. Another strategy to be considered will be the simultaneous analytic evaluation of two or more physiologically interlinked hormone series. Joint analyses could allow for more statistically reliable reconstruction of secretion and removal processes, while incorporating the necessary feedback and feedforward relationships between the hormones. For example, this concept might be implemented in relation to corelease of LH and testosterone (men) and LH, progesterone, and/or estradiol (women). In addition, enhanced understanding of the cellular mechanisms that govern constitutive versus regulated facets of nonpulsatile (basal) hormone secretion should also be useful. In principle, combining several of the foregoing strategies could allow insights into and predictions about the dynamic behavior of unobserved signals within the feedback system, such as the hypothalamic release of GnRH in the case of threefold interrelated GnRH, LH, and sex steroid feedback regulation. Therefore, continuing interdisciplinary efforts in integrative physiology and supporting analytic tools should engender continuing new insights into the operating properties of more complex neurophysiological networks. Indeed, more comprehensive biomathematical constructs should eventually encapsulate the full array of functionally interdependent processes within a macroscopic physiological axis, including the intracellular biosynthesis and release of secretory molecules; their postsecretory association with transport proteins; intravascular aqueous diffusion, rapid advection, geometric dispersion, partial recirculation and site-specific saturable removal from the bloodstream; time-delayed feedforward actions on selected target tissues; and the subsequent feedback-controlled synthesis and secretion of new effector molecules.


    APPENDIX
TOP
ABSTRACT
INTRODUCTION
METHODOLOGY
RESULTS
DISCUSSION
APPENDIX
REFERENCES

Structural Features of the Basal Secretion Models

General structure of secretory formulation. As defined in equation 1 (METHODOLOGY), beta 0 is the basal and P( · ) the pulsatile hormone secretion rate. We reason that the cellular basis for basal secretion is constitutive hormone release and for pulsatile secretion is the discharge of available intracellular (peptide) hormone contained within secretory granules, which accumulate during the interpulse interval. Hormone molecules synthesized in the cell starting at pulse time Tj-1 are stored until the next pulse time, Tj. As reviewed in Refs. 8, 19, and 47, several techniques have been validated to estimate GnRH-LH pulse times. Here, we evaluate secretion conditional on the pulse times, as determined in Ref. 19. We define the mass of the jth pulse Mj to be the amount of hormone accumulated between pulse times Tj-1 and Tj. Here, we assume that the LH pulse masses are given by
<IT>M</IT><SUP><IT>j</IT></SUP> <LIM><OP><ARROW>=</ARROW></OP><UL>def</UL></LIM> &eegr;<SUB>0</SUB> + &eegr;<SUB>1</SUB> × (<IT>T</IT><SUP><IT>j</IT></SUP> − <IT>T</IT><SUP><IT>j</IT>−1</SUP>) + <IT>A</IT><SUP><IT>j</IT></SUP>
where eta 0 is the basal (intracellular) accumulation rate, and eta 1 is a constant, which relates pulse mass accumulation to the immediately preceding interpulse interval length. This relationship reflects the fact that gonadotrope cells accumulate more LH during prolonged interpulse intervals (8). We assume that the Ajs are independent and identically distributed normal random variables with mean zero and variance sigma 2A, thus allowing for stochastic variability (random effects) in pulse mass. To accommodate variably skewed pulse shape(s), a function psi ( · ) is specified, which is the normalized rate of secretion given as hormone mass per unit distribution volume per unit time, as a Generalized-Gamma family of densities (i.e., normalized to integrate to 1)
&psgr;(<IT>s</IT>) = <FR><NU>&bgr;<SUB>3</SUB></NU><DE>&Ggr;(&bgr;<SUB>1</SUB>)(&bgr;<SUB>2</SUB>)<SUP>(&bgr;<SUB>1</SUB>&bgr;<SUB>3</SUB>)</SUP></DE></FR> <IT>s</IT><SUP>(&bgr;<SUB>1</SUB>&bgr;<SUB>3</SUB>)−1</SUP><IT>e</IT><SUP>−(<IT>s</IT>/&bgr;<SUB>2</SUB>)<SUP>&bgr;<SUB>3</SUB></SUP></SUP> (A1)
where beta 1 > 0, beta 2 > 0, and beta 3 > 0 are three parameters that delimit the secretory burst shape. The resulting overall secretion rate [Z(t)] is thus given by
<IT>Z</IT>(<IT>t</IT>) = &bgr;<SUB>0</SUB> + <IT>P</IT>(<IT>t</IT>) = &bgr;<SUB>0</SUB> + <LIM><OP>∑</OP><LL><IT>T<SUP>j</SUP></IT>≤<IT>t</IT></LL><UL> </UL></LIM> <IT>M</IT><SUP><IT>j</IT></SUP>&psgr;(<IT>t</IT> − <IT>T</IT><SUP><IT>j</IT></SUP>)
In the case of two elimination components, the foregoing formulation results in equation 2 (METHODOLOGY). Infusions of human pituitary LH have suggested that the rapid LH half-life component is approximated by a approx  0.63 and a half-life of approx 18 min [alpha 1 = log(2)/18] and the longer half-life component by (1 - aapprox  0.37 and a half-life of approx 90 min [alpha 2 = log(2)/90] (46). Here, we initially fix a approx  0.63 for the kinetic estimates.

What is then observed is a discrete time sampling of this process, plus measurement error
<IT>Y</IT><SUB><IT>k</IT></SUB> <LIM><OP><ARROW>=</ARROW></OP><UL>def</UL></LIM> <IT>X</IT>(<IT>t</IT><SUB><IT>k</IT></SUB>) + &egr;<SUB><IT>k</IT></SUB>  <IT>k</IT> = 1, … , <IT>n</IT>
where epsilon ks represent measurement error (e.g., due to assaying). In Refs. 21 and 51, the asymptotic normality is shown for the maximum-likelihood estimators of the above parameters beta 0, alpha 1, alpha 2, eta 0, eta 1, beta 1, beta 2, beta 3, sigma 2A, sigma 2e. More importantly, their variances and covariances are estimable, as well as variances and covariances for such constructions as total daily secretion and its partition into total daily basal secretion and total daily pulsatile secretion. For example, to calculate total daily LH secretion, we integrate the (reconstructed) LH secretion rate, Z( · ), from 0 to 1,440 min
<LIM><OP>∫</OP><LL>0</LL><UL>1,440</UL></LIM> <IT>Z</IT>(<IT>t</IT>) d<IT>t</IT> = <LIM><OP>∫</OP><LL>0</LL><UL>1,440</UL></LIM> &bgr;<SUB>0</SUB> d<IT>t</IT> + <LIM><OP>∫</OP><LL>0</LL><UL>1,440</UL></LIM> <IT>P</IT>(<IT>t</IT>) d<IT>t</IT>

Total daily secretion =  total daily basal 

+ total daily pulsatile

= &bgr;<SUB>0</SUB> × 1,440 + <LIM><OP>∫</OP><LL>0</LL><UL>1,440</UL></LIM> <IT>P</IT>(<IT>t</IT>) d<IT>t</IT>

Models of basal secretion. Given the foregoing, we next consider three models for basal secretion. In our original construction (19, 21, 51), basal secretion was free to vary (beta 0 was unconstrained) and we allowed a single exponential elimination process. The three models evaluated here are 1) freely varying, i.e., analytically fitted (F model); 2) zero basal (Z model); 3a) constrained by preinjection steady-state [C(SS) model] measured serum LH concentration; or 3b) constrained by a percentage of total secretion [C(gamma ) model, where gamma  is a literature-based population parameter]. The zero basal (Z) model is a minor adaptation of the estimation methodology for that of the freely varying basal model; there is one fewer parameter (no basal term: beta 0), and the modifications necessary for the appropriate formulas are minor. SEs can be calculated for the parameter estimates and for such constructions as total daily secretion, mass per pulse, etc. These standard errors are given in Tables 1-3.

The constrained basal (C) model is, however, slightly different, and below we describe its framework briefly. In the constrained basal (C) model, the proportion of (daily) basal secretion to total (basal plus pulsatile) secretion is assumed to be constrained; let gamma  be the proportionality constant, a literature-based population parameter. On the basis of published estimates, for premenopausal women gamma  was assumed to be ~24%, and for postmenopausal women, 34%. This model differs from the preceding, because the constraint is global. For example, total daily secretion, total daily basal secretion, and the basal rate (beta 0) are now functions of total daily pulsatile secretion
<LIM><OP>∫</OP><LL>0</LL><UL>1,440</UL></LIM> &bgr;<SUB>0</SUB> d<IT>t</IT> = &ggr; <LIM><OP>∫</OP><LL>0</LL><UL>1,440</UL></LIM> <IT>Z</IT>(<IT>t</IT>) d<IT>t</IT> and

<LIM><OP>∫</OP><LL>0</LL><UL>1,440</UL></LIM> <IT>Z</IT>(<IT>t</IT>) d<IT>t</IT> = <FR><NU>1</NU><DE>1 − &ggr;</DE></FR> <LIM><OP>∫</OP><LL>0</LL><UL>1,440</UL></LIM> <IT>P</IT>(<IT>t</IT>) d<IT>t</IT>, hence

&bgr;<SUB>0</SUB> = <FR><NU>&ggr;</NU><DE>1,440 (1 − &ggr;)</DE></FR> <LIM><OP>∫</OP><LL>0</LL><UL>1,440</UL></LIM> <IT>P</IT>(<IT>t</IT>) d<IT>t</IT>

= <FR><NU>&ggr;</NU><DE>1,440 (1 − &ggr;)</DE></FR> <LIM><OP>∫</OP><LL>0</LL><UL>1,440</UL></LIM>  <LIM><OP>∑</OP><LL><IT>T<SUP>j</SUP>≤t</IT></LL></LIM>

× [&eegr;<SUB>0</SUB> + &eegr;<SUB>1</SUB> × (<IT>T</IT><SUP><IT>j</IT></SUP> − <IT>T</IT><SUP><IT>j</IT>−1</SUP>)]&psgr;(<IT>t</IT> − <IT>T</IT><SUP><IT>j</IT></SUP>) d<IT>t</IT>

+ <FR><NU>&ggr;</NU><DE>1,440 (1 − &ggr;)</DE></FR> <LIM><OP>∫</OP><LL>0</LL><UL>1,440</UL></LIM> <LIM><OP>∑</OP><LL><IT>T</IT><SUP><IT>j</IT></SUP>≤<IT>t</IT></LL></LIM> <IT>A</IT><SUP><IT>j</IT></SUP>&psgr;(<IT>t</IT> − <IT>T</IT><SUP><IT>j</IT></SUP>) d<IT>t</IT>

= a deterministic part + a random part (A2)
The basal rate beta 0 is now a random variable, as a consequence of the random effects: Ajs in the pulsatile secretion rate P( · ). Because the global constraint (equation A2) is a linear constraint, the resulting model is still Gaussian and the likelihood function is of the same basic form as that derived in Ref. 21, but with the mean function and covariances modified. The general asymptotic results of Refs. 21 and 51 are still applicable and were implemented in the estimation algorithms. Because total daily secretion and total daily basal secretion are now multiples of total daily pulsatile secretion, their SEs are multiples of the SE of total daily pulsatile secretion. Thus, in the constrained [C(24) and C(34)] model entries in Table 1, the SE for total daily secretion is now the sum of the SEs of total daily basal secretion and pulsatile secretion.


    ACKNOWLEDGEMENTS

We thank Dr. William S. Evans (University of Virginia) for sharing reanalysis of the female LH data sets in this study, Dr. Thomas Mulligan (Virginia Commonwealth University) for allowing use of the LH infusion data, Paula P. Azimi for assistance in data presentation and graphics, and Patsy Craig for manuscript assembly.


    FOOTNOTES

This work was supported by the National Science Foundation Center for Biological Timing, the General Clinical Research Center (RR-00847), National Institutes of Health (NIH) Research Career Development Award 1K04-HD-00634, NIH Center for Specialized Reproduction Research U54 HD-96008, and NIH R01 AG-14799.

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. §1734 solely to indicate this fact.

Address for reprint requests and other correspondence: J. D. Veldhuis, Dept. of Medicine, Dir. Endocrinology and Metabolism, Univ. of VA Health Sciences Center, Box 202, McKim Hall, Charlottesville VA 22908 (E-mail: jdv{at}virginia.edu).

Received 28 July 1999; accepted in final form 18 October 1999.


    REFERENCES
TOP
ABSTRACT
INTRODUCTION
METHODOLOGY
RESULTS
DISCUSSION
APPENDIX
REFERENCES

1.   Akbar, AM, Nett TM, and Niswender GD. Metabolic clearance and secretion rates of gonadotropins at different stages of the estrous cycle in ewes. Endocrinology 94: 1318-1324, 1974[ISI][Medline].

2.   Alexander, SL, and Irvine CH. Secretion rates and short-term patterns of gonadotrophin-releasing hormone, FSH and LH throughout the periovulatory period in the mare. J Endocrinol 114: 351-362, 1987[Abstract].

3.   Burgon, PG, Stanton PG, and Robertson DM. In vivo bioactivities and clearance patterns of highly purified luteinizing hormone isoforms. Endocrinology 137: 4827-4836, 1996[Abstract].

4.   Clarke, IJ, and Cummins JT. The temporal relationship between gonadotropin-releasing hormone (GnRH) and luteinizing hormone (LH) secretion in ovariectomized ewes. Endocrinology 111: 1737-1739, 1982[ISI][Medline].

5.   Conn, PM, Cooper R, McNamara C, Rogers DC, and Shoenhardt L. Qualitative change in gonadotropin during aging in the male rat. Endocrinology 106: 1549-1553, 1980[Abstract].

6.   Davis, MR, Veldhuis JD, Rogol AD, Dufau ML, and Catt KJ. Sustained inhibitory actions of a potent antagonist of gonadotropin-releasing hormone in postmenopausal women. J Clin Endocrinol Metab 64: 1268-1274, 1987[Abstract].

7.   De Nicolao, G, and Liberati D. Linear and nonlinear techniques for the deconvolution of hormone time-series. IEEE Trans Biom Engineer 40: 440-445, 1993.

8.   Evans, WS, Christiansen E, Urban RJ, Rogol AD, Johnson ML, and Veldhuis JD. Contemporary aspects of discrete peak detection algorithms: II. The paradigm of the luteinizing hormone pulse signal in women. Endocrin Rev 13: 81-104, 1992[ISI][Medline].

9.   Frohman, LA, Downs TR, Clarke IJ, and Thomas GB. Measurement of growth hormone-releasing hormone and somatostatin in hypothalamic-portal plasma of unanesthetized sheep: spontaneous secretion and response to insulin-induced hypoglycemia. J Clin Invest 86: 17-24, 1990.

10.   Haak, T, Jungmann E, Schoffling K, and Usadel KH. Evidence for pulsatile secretion of human atrial natriuretic peptide in healthy subjects. Exp Clin Endocrinol 99: 108-109, 1992[ISI][Medline].

11.   Hall, JE, Taylor AE, Martin KA, Rivier J, Schoenfield DA, and Crowley WF, Jr. Decreased release of gonadotropin-releasing hormone during the preovulatory midcycle luteinizing hormone surge in normal women. Proc Natl Acad Sci USA 91: 6894-6898, 1994[Abstract/Free Full Text].

12.   Hartman, ML, Pincus SM, Johnson ML, Matthews DH, Faunt LM, Vance ML, Thorner MO, and Veldhuis JD. Enhanced basal and disorderly growth hormone (GH) secretion distinguish acromegalic from normal pulsatile GH release. J Clin Invest 94: 1277-1288, 1994.

13.   Hartman, ML, Veldhuis JD, Johnson ML, Lee MM, Alberti KG, Samojlik E, and Thorner MO. Augmented growth hormone (GH) secretory burst frequency and amplitude mediate enhanced GH secretion during a two-day fast in normal men. J Clin Endocrinol Metab 74: 757-765, 1992[Abstract].

14.   Iranmanesh, A, Grisso B, and Veldhuis JD. Low basal and persistent pulsatile growth hormone secretion are revealed in normal and hyposomatotropic men studied with a new ultrasensitive chemiluminescence assay. J Clin Endocrinol Metab 78: 526-535, 1994[Abstract].

15.   Isgaard, J, Carlsson L, Isaksson OGP, and Jansson JO. Pulsatile intravenous growth hormone (GH) infusion to hypophysectomized rats increases serum-like growth factor I messenger ribonucleic acid in skeletal tissues more effectively than continuous infusion. Endocrinology 123: 2605-2610, 1988[Abstract].

16.   Johnson, ML, and Veldhuis JD. Evolution of deconvolution analysis as a hormone pulse detection method. Methods Neurosc 28: 1-24, 1995.

17.   Jorgensen, JO, Moller N, Lauritzen T, and Christiansen JS. Pulsatile versus continuous intravenous administration of growth hormone (GH) in GH-deficient patients: effects on circulating insulin-like growth factor-I and metabolic indices. J Clin Endocrinol Metab 70: 1616-1623, 1990[Abstract].

18.  Keenan DM, Sun W, and Veldhuis JD. A stochastic biomathematical model of the male reproductive hormone system. SIAM J Appl Math. In press.

19.   Keenan, D, and Veldhuis JD. Stochastic model of admixed basal and pulsatile hormone secretion as modulated by a deterministic oscillator. Am J Physiol Regulatory Integrative Comp Physiol 273: R1182-R1192, 1997[Abstract/Free Full Text].

20.   Keenan, DM, and Veldhuis JD. A biomathematical model of time-delayed feed-back in the human male hypothalamic-pituitary-Leydig cell axis. Am J Physiol Endocrinol Metab 275: E157-E176, 1998[Abstract/Free Full Text].

21.   Keenan, DM, Veldhuis JD, and Yang R. Joint recovery of pulsatile and basal hormone secretion by stochastic nonlinear random-effects analysis. Am J Physiol Regulatory Integrative Comp Physiol 44: R1939-R1949, 1998.

22.   Kushler, RH, and Brown MB. A model for the identification of hormone pulses. Stat Med 10: 329-340, 1991[ISI][Medline].

23.   Lang, DA, Matthews DR, Peto J, and Turner RC. Cyclic oscillations of basal plasma glucose and insulin concentrations in human beings. N Engl J Med 301: 1023-1027, 1979[Abstract].

24.   Matthews, DR, Hindmarsh PC, Pringle PJ, and Brook CJD A distribution method for analysing the baseline pulsatile endocrine signals as exemplified by 24 hour growth hormone profiles. Clin Endocrinol 35: 245-252, 1991[Medline].

25.   Midgley, AR, Jr, and Jaffe RB. Regulation of hormone gonadotropins. X. Episodic fluctuation of LH during the menstrual cycle. J Clin Endocrinol 33: 962-969, 1971[ISI][Medline].

26.   Moenter, SM, Caraty A, Locatelli A, and Karsch FJ. Pattern of gonadotropin-releasing hormone (GnRH) secretion leading up to ovulation in the ewe: existence of a preovulatory GnRH surge. Endocrinology 129: 1175-1182, 1991[Abstract].

27.   Montgomery, GW, Martin GB, Croable SF, and Pelletier J. Reproduction in Sheep. Canberra: Australian Academic Science, 1984, p. 22-25.

28.   Padmanabhan, V, McFadden K, Mauger DT, Karsch FJ, and Midgley AR, Jr. Neuroendocrine control of follicle-stimulating hormone (FSH) secretion. I. Direct evidence for separate episodic and basal components of FSH secretion. Endocrinology 138: 424-432, 1997[Abstract/Free Full Text].

29.   Paolisso, G, Buonocore S, Gentile S, Sgambato S, Varricchio M, Scheen A, D'Onofrio F, and Lefebvre PJ. Pulsatile glucagon has greater hyperglycaemic, lipolytic and ketogenic effects than continuous hormone delivery in man: effect of age. Diabetologia 33: 272-277, 1990[ISI][Medline].

30.   Pavlou, SN, Veldhuis JD, Lindner J, Souza KH, Urban RJ, Rivier JE, Vale WW, and Stallard DJ. Persistence of concordant LH, testosterone and alpha subunit pulses following LHRH antagonist administration in normal men. J Clin Endocrinol Metab 70: 1472-1478, 1990[Abstract].

31.   Perales, AJ, Diago VJ, Monleon-Sancho J, Grifol R, Dominguez R, Minguez JA, and Monleon J. Pulsatile versus continuous oxytocin infusion for the oxytocin challenge test. Arch Gynecol Obstet 255: 119-123, 1994[ISI][Medline].

32.   Pincus, SM, Veldhuis JD, Mulligan T, Iranmanesh A, and Evans WS. Effects of age on the irregularity of LH and FSH serum concentrations in women and men. Am J Physiol Endocrinol Metab 273: E989-E995, 1997[Abstract/Free Full Text].

33.   Porksen, N, Munn S, Steers J, Veldhuis JD, and Butler P. Impact of sampling technique on appraisal of pulsatile insulin secretion by deconvolution and Cluster analysis. Am J Physiol Endocrinol Metab 269: E1106-E1114, 1995[Abstract/Free Full Text].

34.   Schmitt, CP, Schaefer F, Bruch A, Veldhuis JD, Schmidt-Gayk H, Stein G, Ritz E, and Mehls O. Control of pulsatile and tonic parathyroid hormone secretion by ionized calcium. J Clin Endocrinol Metab 81: 4236-4243, 1996[Abstract].

35.   Schmitz, O, Porksen N, Nyholm B, Skjaerback C, Butler PC, Veldhuis JD, and Pincus SM. Disorderly and nonstationary insulin secretion in glucose-tolerant relatives of patients with NIDDM. Am J Physiol Endocrinol Metab 35: E218-E226, 1997.

36.   Shapiro, BH, MacLeod JN, Pampori NA, Morrissey JJ, Lapenson DP, and Waxman DJ. Signaling elements in the ultradian rhythm of circulating growth hormone regulating expression of sex-dependent forms of hepatic cytochrome P450. Endocrinology 125: 2935-2944, 1989[Abstract].

37.   Sharpless, JL, Supko JG, Martin KA, and Hall JA. Disappearance of endogenous luteinizing hormone is prolonged in postmenopausal women. J Clin Endocrinol Metab 84: 688-694, 1999[Abstract/Free Full Text].

38.   Shupnik, MA. Effects of gonadotropin gene transcription in vitro: requirement for pulsatile administration for luteinizing hormone-B gene stimulation. Mol Endocrinol 4: 1444-1450, 1990[Abstract].

39.   Siragy, HM, Vieweg WVR, Pincus SM, and Veldhuis JD. Increased disorderliness and amplified basal and pulsatile aldosterone secretion in patients with primary aldosteronism. J Clin Endocrinol Metab 80: 28-33, 1995[Abstract].

40.   Van den Berg, G, Frolich M, Veldhuis JD, and Roelfsema F. Combined amplification of the pulsatile and basal modes of adrenocorticotropin and cortisol secretion in patients with Cushing's disease: evidence for down-regulation of the adrenal glands. J Clin Endocrinol Metab 80: 3750-3756, 1996[Abstract].

41.   Van den Berg, G, Veldhuis JD, Frolich M, and Roelfsema F. An amplitude-specific divergence in the pulsatile mode of GH secretion underlies the gender difference in mean GH concentrations in men and premenopausal women. J Clin Endocrinol Metab 81: 2460-2466, 1996[Abstract].

42.   Veldhuis, JD. Methods in Neuroendocrinology: The Cellular and Molecular Neuropharmacology Series. Boca Raton, FL: CRC, 1998, p. 181-203.

43.   Veldhuis, JD, Carlson ML, and Johnson ML. The pituitary gland secretes in bursts: appraising the nature of glandular secretory impulses by simultaneous multiple-parameter deconvolution of plasma hormone concentrations. Proc Natl Acad Sci USA 84: 7686-7690, 1987[Abstract/Free Full Text].

44.   Veldhuis, JD, Evans WS, and Johnson ML. Complicating effects of highly correlated model variables on nonlinear least-squares estimates of unique parameter values and their statistical confidence intervals: estimating basal secretion and neurohormone half-life by deconvolution analysis. Methods Neurosci 28: 130-138, 1995.

46.   Veldhuis, JD, Fraioli F, Rogol AD, and Dufau ML. Metabolic clearance of biologically active luteinizing hormone in man. J Clin Invest 77: 1122-1128, 1986.

47.   Veldhuis, JD, and Johnson ML. Specific methodological approaches to selected contemporary issues in deconvolution analysis of pulsatile neuroendocrine data. Methods Neurosci 28: 25-92, 1995.

47a.   Veldhuis, JD, and Johnson ML. Analysis of nonequilibrium facets of pulsatile sex-steroid secretion in the presence of plasma-binding proteins. Methods Enzymol. 321: 239-263, 2000[ISI][Medline].

48.   Veldhuis, JD, Johnson ML, Faunt LM, Mercado M, and Baumann G. Influence of the high-affinity growth hormone (GH)-binding protein on plasma profiles of free and bound GH and on the apparent half-life of GH. J Clin Invest 91: 629-641, 1993.

49.   Veldhuis, JD, Zwart AD, and Iranmanesh A. Neuroendocrine mechanisms by which selective Leydig-cell castration unleashes increased pulsatile LH release in the human: an experimental paradigm of short-term ketoconazole-induced hypoandrogenemia and deconvolution-estimated LH secretory enhancement. Am J Physiol Regulatory Integrative Comp Physiol 272: R464-R474, 1997[Abstract/Free Full Text].

50.   Weick, RF. A comparison of the disappearance rates of luteinizing hormone from intact and ovariectomized rats. Endocrinology 101: 157-161, 1977[Abstract].

51.   Yang, R. Maximum Likelihood Estimation Asymptotics for Parameter-Dependent Mixed Effects Models with Applications to Hormone Data (Ph.D. thesis). Charlottesville, VA: Division of Statistics, Department of Mathematics, University of Virginia, 1997.