Engineering Gelation Kinetics in Living Silk Hydrogels by Differential Dynamic Microscopy Microrheology and Machine Learning
Engineering Gelation Kinetics in Living Silk Hydrogels by Differential Dynamic Microscopy Microrheology and Machine Learning
复制标题
通过微分动态显微镜、微流变学和机器学习工程设计活丝水凝胶的凝胶动力学
DOI：
10.1002/adbi.202101070
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发表时间：
2022
期刊：
影响因子：
3.7
通讯作者：
Gupta, Maneesh K.
中科院分区：
文献类型：
--
作者：
Martineau, Rhett L.;Bayles, Alexandra V.;Hung, Chia‐Suei;Reyes, Kristofer G.;Helgeson, Matthew E.;Gupta, Maneesh K.
嵌入水凝胶中的微生物构成了一种形式的生命物质。发现配方，平衡潜在的竞争的机械和生物性能的活水凝胶，例如，凝胶时间的水凝胶配方和嵌入的生物体的生存能力可能是具有挑战性的。在这项研究中，开发了一个流水线，以自动化表征水凝胶制剂的凝胶时间。利用该管道，由酶交联的丝和嵌入的E。大肠杆菌-在4D参数空间内配制-被设计成在预先选择的时间范围内凝胶。使用微分动态显微镜（DDM）的微流变学分析的一种新的适应，估计甘精时间。为了加快凝胶化状态边界的发现，贝叶斯机器学习模型在不确定性下进行了最佳决策。人工智能（AI）辅助规划和人类规划之间的学习速度各不相同，在一轮人类规划之后的AI辅助规划期间，学习速度最快。对于在5-15分钟的目标时间范围内胶凝的制剂的子集，在包埋的细胞内的荧光团产生在治疗中基本上是相似的，这证明胶凝时间可以独立于其他材料性质调节-至少在有限的范围内-同时保持生物活性。
Microbes embedded in hydrogels comprise one form of living material. Discovering formulations that balance potentially competing for mechanical and biological properties in living hydrogels—for example, gel time of the hydrogel formulation and viability of the embedded organisms—can be challenging. In this study, a pipeline is developed to automate the characterization of the gel time of hydrogel formulations. Using this pipeline, living materials comprised of enzymatically crosslinked silk and embeddedE. coli—formulated from within a 4D parameter space—are engineered to gel within a pre‐selected timeframe. Gelation time is estimated using a novel adaptation of microrheology analysis using differential dynamic microscopy (DDM). In order to expedite the discovery of gelation regime boundaries, Bayesian machine learning models are deployed with optimal decision‐making under uncertainty. The rate of learning is observed to vary between artificial intelligence (AI)‐assisted planning and human planning, with the fastest rate occurring during AI‐assisted planning following a round of human planning. For a subset of formulations gelling within a targeted timeframe of 5–15 min, fluorophore production within the embedded cells is substantially similar across treatments, evidencing that gel time can be tuned independent of other material properties—at least over a finite range—while maintaining biological activity.
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影响因子：
14
作者：
Davis, Nicolynn E.;Beenken-Rothkopf, Liese N.;Mirsoian, Annie;Kojic, Nikola;Kaplan, David L.;Barron, Annelise E.;Fontaine, Magali J.
通讯作者：
Fontaine, Magali J.
影响因子：
29.4
作者：
Epps, Robert W.;Bowen, Michael S.;Abolhasani, Milad
通讯作者：
Abolhasani, Milad
DOI：
10.1002/jbm.b.31686
发表时间：
2010-10
影响因子：
3.4
作者：
Chao, Pen-Hsiu Grace;Yodmuang, Supansa;Wang, Xiaoqin;Sun, Lin;Kaplan, David L.;Vunjak-Novakovic, Gordana
通讯作者：
Vunjak-Novakovic, Gordana
影响因子：
14
作者：
Siwei Zhao;Ying Chen;Benjamin P. Partlow;Annie Golding;P. Tseng;J. Coburn;M. Applegate;J. Moreau;F. Omenetto;D. Kaplan
通讯作者：
Siwei Zhao;Ying Chen;Benjamin P. Partlow;Annie Golding;P. Tseng;J. Coburn;M. Applegate;J. Moreau;F. Omenetto;D. Kaplan
影响因子：
5.6
作者：
Ohlendorf, Robert;Vidavski, Roee R.;Moeglich, Andreas
通讯作者：
Moeglich, Andreas