Wijchman J G, de Wolf B T, Graafe R, Arts E G
Department of Obstetrics and Gynaecology, University Hospital and University of Groningen, The Netherlands.
J Androl. 2001 Sep-Oct;22(5):773-80.
The development of computer-aided semen analysis (CASA) has made it possible to study sperm motility characteristics objectively and longitudinally. In this 2-year study of 8 sperm donors, we used CASA to measure 7 semen parameters (concentration, percentage of motile spermatozoa, curvilinear velocity, average path velocity, straight-line velocity, amplitude of lateral head displacement, and beat/cross frequency). The frequency distributions of the 7 parameters in the semen samples of each donor were investigated. All parameters but one were normally distributed; concentration was distributed log-normally. Variation within individual donors and between donors was studied. Analysis of variance demonstrated that variation between donors was not explained by the longitudinal variation within individual donors. Variations in motility characteristics between donors were substantial, which may make motility characteristics of limited value as a tool for establishing fertility. Strong correlations were found between the 7 parameters, partly because by definition, motility characteristics are interdependent. Fisher's discriminant analysis demonstrated that each donor appeared to have his own set of semen characteristics and, more specifically, his own motility signature. From this data set it can be predicted that in order to find population means among sperm, it may be more efficient to measure more subjects than to increase the number of samples per subject.
计算机辅助精液分析（CASA）的发展使得客观且纵向地研究精子活力特征成为可能。在这项针对8名精子捐献者的为期2年的研究中，我们使用CASA测量了7项精液参数（浓度、活动精子百分比、曲线速度、平均路径速度、直线速度、头部侧摆幅度以及鞭打/交叉频率）。研究了每个捐献者精液样本中这7项参数的频率分布。除一项参数外，所有参数均呈正态分布；浓度呈对数正态分布。研究了个体捐献者内部以及捐献者之间的差异。方差分析表明，捐献者之间的差异无法用个体捐献者内部的纵向差异来解释。捐献者之间的活力特征差异很大，这可能使活力特征作为确定生育能力的工具价值有限。发现这7项参数之间存在很强的相关性，部分原因是根据定义，活力特征是相互依存的。费舍尔判别分析表明，每个捐献者似乎都有自己独特的精液特征集，更具体地说，有自己的活力特征。从这个数据集可以预测，为了找到精子的总体均值，测量更多的受试者可能比增加每个受试者的样本数量更有效。
