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A matching algorithm for the distribution of human pancreatic islets

机译:人胰岛分布的匹配算法

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The success of human pancreatic islet transplantation in a subset of type 1 diabetic patients has led to an increased demand for this tissue in both clinical and basic research, yet the availability of such preparations is limited and the quality highly variable. Under the current process of islet distribution for basic science experimentation nationwide, specialized laboratories attempt to distribute islets to one or more scientists based on a list of known investigators. This local decision making (LDM) process has been found to be ineffective and suboptimal. To alleviate these problems, a computerized Matching Algorithm for Islet Distribution (MAID) was developed to better match the functional, morphological, and quality characteristics of islet preparations to the criteria desired by basic research laboratories, i.e., requesters. The algorithm searches for an optimal combination of requesters using detailed screening, sorting, and search procedures. When applied to a data set of 68 human islet preparations distributed by the Islet Cell Resource (ICR) Center Consortium, MAID reduced the number of requesters that (a) did not receive any islets, and (b) received mis-matched shipments. These results suggest that MAID is an improved more efficient approach to the centralized distribution of human islets within a consortium setting.
机译:在1型糖尿病患者的一部分中,人类胰岛移植的成功导致在临床和基础研究中对该组织的需求增加,但是此类制剂的可用性受到限制,并且质量变化很大。在目前全国基础科学实验的胰岛分布过程中,专业实验室试图根据已知研究者的名单将胰岛分布给一个或多个科学家。已经发现此本地决策(LDM)过程无效且不理想。为了减轻这些问题,开发了一种用于胰岛分布的计算机匹配算法(MAID),以使胰岛制剂的功能,形态和质量特征更好地与基础研究实验室(即请求者)所需的标准相匹配。该算法使用详细的筛选,排序和搜索过程来搜索请求者的最佳组合。当将其应用于由胰岛细胞资源(ICR)中心联盟分发的68种人类胰岛制剂的数据集时,MAID减少了(a)没有接收任何胰岛和(b)接收到不匹配货物的请求者数量。这些结果表明,MAID是一种改进的更有效的方法,用于在财团环境中集中分布人类胰岛。

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