Mulligan T, Delemarre-van de Waal H A, Johnson M L, Veldhuis J D
Hunter Holmes McGuire Department of Veterans Affairs Medical Center, Medical College of Virginia, Richmond 23249.
Am J Physiol. 1994 Jul;267(1 Pt 2):R202-11. doi: 10.1152/ajpregu.1994.267.1.R202.
Deconvolution methods constitute a class of analytic tools to quantitate hormone secretion and/or clearance in vivo. Although mathematically rigorous, deconvolution techniques have assumed, rather than proven, validity. Accordingly, we tested the validity of deconvolution analysis on true-positive human, animal (sheep and monkey), and computer-simulated data using the luteinizing hormone (LH) pulse signal as a relevant paradigm. We found that multiparameter deconvolution analysis has high discriminative sensitivity (human data 91%, animal 81%, computer-stimulated 95%) and specificity (human 90%, animal 81%, computer-simulated 100%). Sensitivity was impaired by low secretory burst amplitude (< 0.1 IU.l-1.min-1), short interpulse interval (< 60 min), infrequent venous sampling (every 20-30 min), and high random experimental variation (e.g., noise > 15%). Specificity was hindered by noise. Deconvolution accurately characterized the unknown hormone half-life (r = +0.994) and production rate (r = +0.990). Interoperator reliability was high when statistically based criteria for secretory pulse detection were applied. We conclude that multiparameter deconvolution, within recognizable constraints, is a valid and reliable tool for in vivo investigation of hormone secretion and half-life.
反卷积方法是一类用于体内定量激素分泌和/或清除率的分析工具。尽管反卷积技术在数学上很严谨,但其有效性是假设的而非经过验证的。因此,我们以促黄体生成素(LH)脉冲信号作为相关范例,对真实的人类、动物(绵羊和猴子)以及计算机模拟数据进行反卷积分析的有效性测试。我们发现多参数反卷积分析具有较高的判别敏感性(人类数据为91%,动物为81%,计算机模拟为95%)和特异性(人类为90%,动物为81%,计算机模拟为100%)。低分泌突发幅度(<0.1 IU·l-1·min-1)、短脉冲间期(<60分钟)、不频繁的静脉采样(每20 - 30分钟一次)以及高随机实验变异(例如,噪声>15%)会损害敏感性。噪声会阻碍特异性。反卷积能够准确地描述未知激素的半衰期(r = +0.994)和产生率(r = +0.990)。当应用基于统计的分泌脉冲检测标准时,不同操作者之间的可靠性较高。我们得出结论,在可识别的限制范围内,多参数反卷积是用于体内激素分泌和半衰期研究的有效且可靠的工具。