PDF(Pubmed)
Abstract：
Core body temperature (T c) is a critical aspect of homeostasis in birds and mammals and is increasingly used as a biomarker of the fitness of an animal to its environment. Periodogram and cosinor analysis can be used to estimate the characteristics of the circadian rhythm of T c from data obtained on loggers that have limited memory capacity and battery life. The sampling interval can be manipulated to maximise the recording period, but the impact of sampling interval on the output of periodogram or cosinor analysis is unknown. Some basic guidelines are available from signal analysis theory, but those guidelines have never been tested on T c data. We obtained data at 1-, 5- or 10-min intervals from nine avian or mammalian species, and re-sampled those data to simulate logging at up to 240-min intervals. The period of the rhythm was first analysed using the Lomb-Scargle periodogram, and the mesor, amplitude, acrophase and adjusted coefficient of determination (R 2) from the original and the re-sampled data were obtained using cosinor analysis. Sampling intervals longer than 60 min did not affect the average mesor, amplitude, acrophase or adjusted R 2, but did impact the estimation of the period of the rhythm. In most species, the period was not detectable when intervals longer than 120 min were used. In all individual profiles, a 30-min sampling interval modified the values of the mesor and amplitude by less than 0.1°C, and the adjusted R 2 by less than 0.1. At a 30-min interval, the acrophase was accurate to within 15 min for all species except mice. The adjusted R 2 increased as sampling frequency decreased. In most cases, a 30-min sampling interval provides a reliable estimate of the circadian T c rhythm using periodogram and cosinor analysis. Our findings will help biologists to select sampling intervals to fit their research goals.
摘要：
核心体温（Tc）是鸟类和哺乳动物体内平衡的关键方面，并且越来越多地用作动物对其环境适应性的生物标志物。周期图和余弦分析可用于根据在具有有限的存储容量和电池寿命的记录器上获得的数据来估计Tc的昼夜节律的特征。可以操纵采样间隔以最大化记录周期，但是采样间隔对周期图或余弦分析输出的影响是未知的。信号分析理论提供了一些基本准则，但这些指南从未在Tc数据上进行过测试。我们在1-，来自9种鸟类或哺乳动物的5-或10-min间隔，并重新采样这些数据，以长达240分钟的间隔模拟测井。首先使用Lomb-Scargle周期图来分析节律的周期，和介子，振幅,使用余弦分析获得原始和重新采样数据的顶相和调整后的决定系数（R2）。大于60分钟的采样间隔不影响平均测量值，振幅,顶期或调整后的R2，但确实影响了对节律周期的估计。在大多数物种中,当使用超过120分钟的间隔时,无法检测到该时间段.在所有单个配置文件中，30分钟的采样间隔将介观和振幅的值修改小于0.1°C，调整后的R2小于0.1。间隔30分钟,除小鼠外，所有物种的顶相都精确到15分钟内。调整后的R2随着采样频率的降低而增加。在大多数情况下,30分钟的采样间隔使用周期图和余弦分析提供了对昼夜节律的可靠估计。我们的发现将帮助生物学家选择采样间隔以符合他们的研究目标。
