Abramson Sascha D, Alexe Gabriela, Hammer Peter L, Kohn Joachim
Department of Chemistry and Chemical Biology, and the New Jersey Center for Biomaterials, Rutgers, The State University of New Jersey, New Brunswick, New Jersey 09803, USA.
J Biomed Mater Res A. 2005 Apr 1;73(1):116-24. doi: 10.1002/jbm.a.30266.
A predictive model that can correlate the chemical composition of a biomaterial with the biological response of cells that are in contact with that biomaterial would represent a major advance and would facilitate the rational design of new biomaterials. As a first step toward this goal, we report here on the use of Logical Analysis of Data (LAD) to model the effect of selected polymer properties on the growth of two different cell types, rat lung fibroblasts (RLF, a transformed cell line), and normal foreskin fibroblasts (NFF, nontransformed human cells), on 112 surfaces obtained from a combinatorially designed library of polymers. LAD is a knowledge extraction methodology, based on using combinatorics, optimization, and Boolean logic. LAD was trained on a subset of 62 polymers and was then used to predict cell growth on 50 previously untested polymers. Experimental validation indicated that LAD correctly predicted the high and low cell growth polymers and found optimal ranges for polymer chemical composition, surface chemistry, and bulk properties. Particularly noteworthy is that LAD correctly identified high-performing polymer surfaces, which surpassed commercial tissue culture polystyrene as growth substratum for normal foreskin fibroblasts. Our results establish the feasibility of using computational modeling of cell growth on flat polymeric surfaces to identify promising "lead" polymers for applications that require either high or low cell growth.
一种能够将生物材料的化学成分与接触该生物材料的细胞的生物学反应相关联的预测模型，将代表一项重大进展，并将有助于合理设计新型生物材料。作为朝着这一目标迈出的第一步，我们在此报告使用数据逻辑分析（LAD）来模拟所选聚合物特性对两种不同细胞类型（大鼠肺成纤维细胞（RLF，一种转化细胞系）和正常包皮成纤维细胞（NFF，未转化的人类细胞））在从聚合物组合设计库中获得的112个表面上生长的影响。LAD是一种基于组合学、优化和布尔逻辑的知识提取方法。LAD在62种聚合物的子集上进行训练，然后用于预测50种先前未测试的聚合物上的细胞生长。实验验证表明，LAD正确地预测了高细胞生长和低细胞生长的聚合物，并找到了聚合物化学成分、表面化学和本体性能的最佳范围。特别值得注意的是，LAD正确地识别出了高性能的聚合物表面，这些表面作为正常包皮成纤维细胞的生长基质超过了商业组织培养聚苯乙烯。我们的结果确立了使用平面聚合物表面上细胞生长的计算模型来识别适用于需要高细胞生长或低细胞生长应用的有前景的“先导”聚合物的可行性。
