Gradient Material Strategies for Hydrogel Optimization in Tissue Engineering Applications.

Q2 Biochemistry, Genetics and Molecular Biology High-Throughput Pub Date : 2018-01-04 DOI:10.3390/ht7010001
Laura A Smith Callahan
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Abstract

Although a number of combinatorial/high-throughput approaches have been developed for biomaterial hydrogel optimization, a gradient sample approach is particularly well suited to identify hydrogel property thresholds that alter cellular behavior in response to interacting with the hydrogel due to reduced variation in material preparation and the ability to screen biological response over a range instead of discrete samples each containing only one condition. This review highlights recent work on cell-hydrogel interactions using a gradient material sample approach. Fabrication strategies for composition, material and mechanical property, and bioactive signaling gradient hydrogels that can be used to examine cell-hydrogel interactions will be discussed. The effects of gradients in hydrogel samples on cellular adhesion, migration, proliferation, and differentiation will then be examined, providing an assessment of the current state of the field and the potential of wider use of the gradient sample approach to accelerate our understanding of matrices on cellular behavior.

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组织工程应用中优化水凝胶的梯度材料策略。
虽然目前已开发出多种组合/高通量方法用于生物材料水凝胶的优化,但梯度取样方法特别适合用于确定水凝胶特性阈值,这种阈值会改变细胞与水凝胶相互作用时的行为,因为材料制备过程中的变化较少,而且能够在一定范围内筛选生物反应,而不是每个样品只包含一种条件。本综述重点介绍了近期采用梯度材料样品方法研究细胞与水凝胶相互作用的工作。将讨论可用于研究细胞-水凝胶相互作用的成分、材料和机械性能以及生物活性信号梯度水凝胶的制作策略。然后将研究水凝胶样品中的梯度对细胞粘附、迁移、增殖和分化的影响,评估该领域的现状以及更广泛地使用梯度样品方法的潜力,以加快我们对细胞行为基质的了解。
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来源期刊
High-Throughput
High-Throughput Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.60
自引率
0.00%
发文量
0
审稿时长
9 weeks
期刊介绍: High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: -Microarrays -DNA Sequencing -RNA Sequencing -Protein Identification and Quantification -Cell-based Approaches -Omics Technologies -Imaging -Bioinformatics -Computational Biology/Chemistry -Statistics -Integrative Omics -Drug Discovery and Development -Microfluidics -Lab-on-a-chip -Data Mining -Databases -Multiplex Assays
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