利用微/纳米操作技术测定细胞的内在电学和机械性能。

IF 2.8 3区 化学 Q3 CHEMISTRY, PHYSICAL
Soft Matter Pub Date : 2025-07-23 DOI:10.1039/D5SM00529A
Wenfeng Liang, Dan Dang, Xieliu Yang and Hemin Zhang
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引用次数: 0

摘要

单模生物物理指纹在分析细胞异质性时具有特定的重叠。这些参数之间的交叉敏感性导致基于一维特征的细胞表型分类存在明显的模糊区间,难以准确分离具有相似生物物理特征但不同功能亚群的细胞簇。因此,开发活细胞参数跨尺度多模态同步检测技术,构建基于机器学习的多维参数耦合分析模型,将是突破细胞异质性精准分析瓶颈的关键路径。因此,本文综述了五种微纳操作方法来确定细胞的内在电学和力学性能。对这些方法的工作原理进行了详细的说明,并介绍了它们在提取细胞的内在电学和力学特性方面的应用。本文还讨论了最近出现的人工智能辅助方法。本文最后对这五种方法的发展前景进行了讨论。我们的结论是,了解细胞内在电学和力学特性的多模态谱将是揭示疾病异质性和建立个性化诊断和治疗系统的重大突破。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Determination of intrinsic cellular electrical and mechanical properties using micro/nano manipulation techniques

Determination of intrinsic cellular electrical and mechanical properties using micro/nano manipulation techniques

Single-mode biophysical fingerprints have specific overlap when cell heterogeneity is analyzed. The cross-sensitivity between these parameters results in significant fuzzy intervals in cell phenotype classification based on one-dimensional features, making it difficult to accurately separate cell clusters with similar biophysical characteristics but different functional subgroups. Therefore, developing cross-scale multi-modal synchronous detection technology for live cell parameters and building a machine learning-based multi-dimensional parameter coupling analysis model will be a key path to breaking through the bottleneck in the accurate analysis of cell heterogeneity. Hence, this review presents five micro/nano manipulation methods for determining intrinsic cellular electrical and mechanical properties. The working principles of these methods are thoroughly explained, together with their applications for extracting the intrinsic cellular electrical and mechanical properties of cells. Recently emerged artificial intelligence-facilitated methods are also discussed. This review finishes with a discussion of the future prospects of these five methods. Our conclusion is that understanding the multi-modal spectrum of intrinsic cellular electrical and mechanical properties will be a major breakthrough in uncovering the heterogeneity of diseases and building personalized diagnosis and treatment systems.

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来源期刊
Soft Matter
Soft Matter 工程技术-材料科学:综合
CiteScore
6.00
自引率
5.90%
发文量
891
审稿时长
1.9 months
期刊介绍: Soft Matter is an international journal published by the Royal Society of Chemistry using Engineering-Materials Science: A Synthesis as its research focus. It publishes original research articles, review articles, and synthesis articles related to this field, reporting the latest discoveries in the relevant theoretical, practical, and applied disciplines in a timely manner, and aims to promote the rapid exchange of scientific information in this subject area. The journal is an open access journal. The journal is an open access journal and has not been placed on the alert list in the last three years.
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