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利用采样组织切片优化估计肝细胞灶数量

Optimal use of sampled tissue sections for estimating the number of hepatocellular foci.

作者信息

Nychka D, Pugh T D, King J H, Koen H, Wahba G, Chover J, Goldfarb S

出版信息

Cancer Res. 1984 Jan;44(1):178-83.

PMID:6360345
Abstract

Statistical techniques were applied to computer-simulated data to evaluate the importance of various factors that may affect the estimation of the number of hepatocellular foci from foci transections. The simulations were modeled after mouse foci for which three-dimensional size distributions and densities were determined from serial section reconstructions. The foci had been induced in male C57BL/6 X C3H F1 mice at 20 and 28 weeks after a single injection, in infancy, of diethylnitrosamine. In an earlier report, we had shown that the number of foci per cu cm could be accurately estimated from profiles using a conditional estimator when the investigator is unable to identify profiles smaller than a certain size (epsilon). In the present study, emphasis was placed on assessing the value of step serial sections in order to make optimal use of the small tissue samples in mouse liver. Since all mathematical estimators of N3 are based on measurement of sampled profiles (n2') and ultimately derive from the fundamental relationship. N3' = N2'/2mu, (where N3' is the number of foci per cu cm, N2' is the number of profiles per sq cm, and mu, is the average adjusted focus radius), the relative importance of N2' and mu, on the conditional estimator was evaluated. This was accomplished by comparing the errors resulting from use of the conditional estimator with those resulting from use of two other estimators. The latter two estimators consisted of a "sampled focus estimator," which used sampled intact foci to estimate N3, and a "reference estimator," which used profiles from foci with a mu, that was known. Additionally, in order to provide a stable variance for the conditional estimator, we adopted a simple smoothing procedure. As expected, none of the estimators showed any significant bias. However, somewhat surprising was the finding that the standard deviations from use of all three estimators were almost identical. Consequently, it appears that the variance resulting from application of the smoothed conditional estimator to large sets of profile data is not due to difficulty in estimating mu epsilon. In these instances, the faulty estimates of N2' resulted almost entirely from the variability in sampling foci from tissue blocks which constituted only about 1/25 of the liver volume. In addition, the ability to reduce the error in estimating the number of foci by increasing the number of profiles was also evaluated. We simulated a sectioning protocol for the 28-week mouse livers in which the distances between the 5-micron-thick step sections in a 1-mm block of liver were progressively decreased from 1000 to 50 micron.(ABSTRACT TRUNCATED AT 400 WORDS)

摘要

统计技术应用于计算机模拟数据,以评估各种因素对通过病灶横切面估计肝细胞病灶数量的重要性。这些模拟是根据小鼠病灶建模的,其三维大小分布和密度通过连续切片重建确定。病灶是在雄性C57BL/6×C3H F1小鼠幼年时单次注射二乙基亚硝胺后20周和28周诱导产生的。在早期的一份报告中,我们已经表明,当研究者无法识别小于一定大小(ε)的轮廓时,使用条件估计器可以从轮廓中准确估计每立方厘米的病灶数量。在本研究中,重点是评估阶梯连续切片的价值,以便最佳利用小鼠肝脏中的小组织样本。由于所有N3的数学估计器都基于对采样轮廓(n2')的测量,最终源于基本关系N3' = N2'/2μ(其中N3'是每立方厘米的病灶数量,N2'是每平方厘米的轮廓数量,μ是平均调整后的病灶半径),因此评估了N2'和μ对条件估计器的相对重要性。这是通过比较使用条件估计器产生的误差与使用其他两种估计器产生的误差来完成的。后两种估计器包括一个“采样病灶估计器”,它使用采样的完整病灶来估计N3,以及一个“参考估计器”,它使用来自已知μ的病灶的轮廓。此外,为了为条件估计器提供稳定的方差,我们采用了一种简单的平滑程序。正如预期的那样,没有一个估计器显示出任何显著的偏差。然而,有点令人惊讶的是,发现使用所有三种估计器的标准差几乎相同。因此,似乎将平滑条件估计器应用于大量轮廓数据产生的方差不是由于估计με的困难。在这些情况下,N2'的错误估计几乎完全源于从仅占肝脏体积约1/25的组织块中采样病灶的变异性。此外,还评估了通过增加轮廓数量来减少病灶数量估计误差的能力。我们模拟了28周龄小鼠肝脏的切片方案,其中在1毫米厚的肝脏块中5微米厚的阶梯切片之间的距离从1000微米逐渐减小到50微米。(摘要截于400字)

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