IMPROVED ANALYSIS OF ELECTRON-MICROSCOPIC AUTORADIOGRAMS

拟议工作的广泛目标是实施和扩大一个新的 电子显微镜放射自显影（EMA）分析方法， 可以被生物医学研究者广泛使用。 新方法 已经在模拟和实际数据中得到了广泛的应用。 新方法 基于统计学的最大似然方法，并使用 期望最大化算法，这导致递归方程， 在其最初的表述中，计算要求太高， 对于传统计算机来说是实用的。 最近重新拟订的 算法使其在小型PC级计算机上具有计算实用性 通常可供实验室研究人员使用。 具体目标是：（1）在小型计算机上实现新方法， 一种广义的形式，可以容纳广泛的共同 （2）开发现有的机器，并将其提供给国家社区; 一个EMA模拟器，它使用实验数据来产生与每个 显微照片集的分析，可靠性的统计测量 产生的估计，并作为一个效用， 确定测试所需的实验要求 生物学假设;（3）确定的基本解决能力 该方法以及它如何受到影响点扩散的因素的影响， 不同的放射性同位素;以及（4）开发自动化EM图像 分割（结构描绘）方法，以减少繁琐 这是当前手动数据采集方法所固有的。 新方法的意义在于，与交叉火力相比， 方法（1）它产生示踪剂浓度的估计， 准确性，（2）它能够产生生物学意义的结果， 更少的EM图像和/或更低的放射性水平，（3）它 保证最大似然估计的全局收敛，从而 消除了对特别的“边缘隔室”的需要。“新的力量 方法已被证明在肌膜摄取的研究， 花生四烯酸损伤的肌细胞，这产生了新的见解， 缺血性心肌损伤的发病机制。

The broad goal of the proposed work is to implement and extend a new method for electron-microscopic autoradiographic (EMA) analysis so that it can be made widely available to biomedical investigators. The new method has been shown in simulation and real-data general use. The new method is based on the maximum-likelihood method of statistics and uses the expectation-maximization algorithm, which leads to recursive equation that was, in its original formulation, too computationally demanding to be practical for conventional computers. Recent reformulations of the algorithm render it computationally practical on small PC-class computers generally available to laboratory investigators. Specific aims are: (1) to implement the new method for small computers in a generalized form that can be accommodated by a wide range of commonly available machines, and offer it to the national community; (2) to develop an EMA simulator which uses the experimental data to produce with every analysis of sets of micrographs, a statistical measure of the reliability of the estimates produced, and which functions as a utility for establishing the experimental requirements necessary for testing biological hypotheses; (3) to determine the fundamental resolving power of the method and how it is influenced by factors affecting point-spread for different radio-isotopes; and (4) to develop an automated EM-image segmentation (structure delineation) method in order to reduce the tedium inherent in current manual methods for data acquisition. The significance of the new method is that in comparison to the cross-fire method (1) it yields estimates of tracer concentrations with much greater accuracy, (2) it is able to produce biologically meaningful results from far fewer EM images and/or at much lower levels of radioactivity, (3) it guarantees global convergence on the maximum-likelihood estimate, thereby eliminating the need for ad hoc "rim compartments." The power of the new method has been demonstrated in a study of sarcolemmal uptake of arachidonic acid by injured myocytes, which has yielded new insights into the pathogenesis of ischemic myocardial injury.