Regularity Analysis

Homeostasis in an endocrine axis requires repeated decremental and incremental adjustments in secretion (39,82,83). (see Fig. 1). In the male gonadal axis, core home-ostatic signals include (at least) GnRH, LH, and testosterone, which enforce adaptations over a rapid (minute-by-minute) time course (108). Orderliness of the resultant subpatterns of hormone release can be quantitated objectively via a regularity statistic, approximate entropy (ApEn) (30,109-111). ApEn is calculated on a desktop computer as a single number, which exploits accurate probabilistic accounting to quantitate the reproducibility of successive measurements in a time series (111) (see Fig. 9A). Higher ApEn denotes heightened irregularity of minute-by-minute hormone release, which, in turn, signifies deterioration or adaptation of feedback and feedforward adjustments (110,113,114).

In a clinical context, ApEn identifies highly disorderly patterns of tumoral hormone release, which denotes autonomy from normal regulatory adjustments (21,110). In addition, ApEn delineates irregular secretion of LH, testosterone, GH, adrenocorticotropic hormone (ACTH), cortisol, and insulin in older compared with young individuals, thus defining age-related deterioration of adaptive control (28,30-32,35,76,115) (see Fig. 9B). For example, elevated ApEn of LH and testosterone release patterns unmask disruption of one or more key signaling elements within the interlinked GnRH-LH-testosterone axis (30,39,40,113). Interventional studies are necessary to localize the individual and joint sites of statistically inferred regulatory defects.

The cross-ApEn statistic extends the concept of appraising single-hormone regularity to quantitating two-hormone (pairwise) synchrony (30). Cross-ApEn unveils significant loss of bihormonal synchrony between LH and testosterone secretion in

Pulsutile Gnrh Signaling

Fig. 8. Concept of deconvolution analysis as a family of methods designed to quantitate unobserved secretion and/or kinetics from fluctuating hormone concentrations. (A) A Gaussian or slightly skewed secretory-burst model (top left) provides estimates of time-delimited, burst-like discharge of molecules with individual release velocities driving a pulse. A secretory burst is defined by its position in time, maximum (amplitude), and half-duration (duration at half-maximal height) (102,104). The time integral of the convolution product of the secretory burst (left) and disappearance function (middle) yields the pulsatile hormone concentration (right). The reverse process of deducing underlying secretion and elimination from observed concentrations is termed deconvolution analysis. (B) A waveform-independent approach allows one to calculate sample secretion rates (bottom) from measured hormone concentrations (top) based on a priori biexponential kinetics (interrupted decay curves). Experimental errors inherent in hormone measurements and the populational half-life estimate are combined to determine statistical confidence limits for each sample secretion rate (103,105). (Figure continues)

Fig. 8. Concept of deconvolution analysis as a family of methods designed to quantitate unobserved secretion and/or kinetics from fluctuating hormone concentrations. (A) A Gaussian or slightly skewed secretory-burst model (top left) provides estimates of time-delimited, burst-like discharge of molecules with individual release velocities driving a pulse. A secretory burst is defined by its position in time, maximum (amplitude), and half-duration (duration at half-maximal height) (102,104). The time integral of the convolution product of the secretory burst (left) and disappearance function (middle) yields the pulsatile hormone concentration (right). The reverse process of deducing underlying secretion and elimination from observed concentrations is termed deconvolution analysis. (B) A waveform-independent approach allows one to calculate sample secretion rates (bottom) from measured hormone concentrations (top) based on a priori biexponential kinetics (interrupted decay curves). Experimental errors inherent in hormone measurements and the populational half-life estimate are combined to determine statistical confidence limits for each sample secretion rate (103,105). (Figure continues)

Time Time

Fig. 8. (Continued) (C) Flexible deconvolution construct of a generalized Gamma-density (variable) secretory-pulse waveform is used to encapsulate burst timing, number, shape and size, basal secretion, and rapid and slow-phase hormone elimination kinetics simultaneously with random effects (81,83). Random effects arise from sampling uncertainty, assay error, stochastic admixture of secreted hormone in the bloodstream, unpredictable pulse times, and varying effector-response interface properties (39,82). (Unpublished illustrative schema.)

Nocturnal Penile Tumescence

Fig. 8. (Continued) (C) Flexible deconvolution construct of a generalized Gamma-density (variable) secretory-pulse waveform is used to encapsulate burst timing, number, shape and size, basal secretion, and rapid and slow-phase hormone elimination kinetics simultaneously with random effects (81,83). Random effects arise from sampling uncertainty, assay error, stochastic admixture of secreted hormone in the bloodstream, unpredictable pulse times, and varying effector-response interface properties (39,82). (Unpublished illustrative schema.)

older men (see Fig. 9C). This measure further documents deterioration of coordinate patterns of LH release and oscillations of each of PRL, FSH, nocturnal penile tumescence, and sleep stage (31,39,40). According to this idea, brainstem regulatory centers oversee synchronous secretion of GnRH, LH, FSH, and PRL; sleep-stage transitions, and autonomic control of NPT cycles. Thus, the foregoing findings establish multilevel disruption of central nervous system (CNS)-dependent neurohormone outflow in older men.

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Diabetes 2

Diabetes 2

Diabetes is a disease that affects the way your body uses food. Normally, your body converts sugars, starches and other foods into a form of sugar called glucose. Your body uses glucose for fuel. The cells receive the glucose through the bloodstream. They then use insulin a hormone made by the pancreas to absorb the glucose, convert it into energy, and either use it or store it for later use. Learn more...

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