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相关概念视频

Cell-matrix's Response to Mechanical Forces01:13

Cell-matrix's Response to Mechanical Forces

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In animal cells, the extracellular matrix allows cells within tissues to withstand external stresses and transmits signals from the outside of the cell to the inside. The extracellular matrix is extensive, and its composition varies between different types of tissues. For example, the reticular fibers and ground substance make up the ECM in loose connective tissue, while collagen and bone minerals make up the ECM of bone tissue. 
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Cells migrating in response to external stimuli form lamellipodia, which are thin membrane protrusions supported by a mesh of linked, branched, or unbranched actin filaments. These actin filaments interact with myosin motor proteins, creating the dynamic actomyosin complex within the cytoskeleton. Contractility, or the ability to generate contractile stress, is inherent to the actomyosin complex. It helps cells detect the stiffness of the surrounding ECM and exert contractile force for...
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The adherens junctions that anchor cells together are multi-protein complexes that dynamically adapt to mechanical stimuli such as tensile forces and shear stress. Mechanosensory proteins in these junctions can sense such mechanical stimuli and undergo a shift in their conformation, resulting in an altered function — a process called mechanotransduction.
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T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
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相关实验视频

Updated: Sep 13, 2025

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading
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Quantitative Analysis of Cell Edge Dynamics during Cell Spreading

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从细胞扩散预测机械敏感T细胞扩张.

Xin Wang1, Ruiting Xu1, Shiqi Hu1

  • 1Department of Biomedical Engineering, Columbia University, New York, 10027, USA.

Advanced healthcare materials
|July 28, 2025
PubMed
概括
此摘要是机器生成的。

短期的T细胞扩散预测了采用细胞免疫疗法 (ACT) 的长期扩张. 一个深度学习模型准确地区分健康细胞和慢性淋巴细胞白血病 (CLL) 细胞,并预测T细胞功能.

关键词:
在T细胞,T细胞.生物材料是一种生物材料.细胞免疫疗法细胞免疫疗法机器学习是机器学习.机械感知机械感知机器

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相关实验视频

Last Updated: Sep 13, 2025

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading
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Measuring Cell-Edge Protrusion Dynamics during Spreading using Live-Cell Microscopy
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科学领域:

  • 生物技术是生物技术.
  • 免疫学 免疫学 免疫学
  • 细胞工程 细胞工程

背景情况:

  • T细胞的性能变化挑战了采用细胞免疫疗法 (ACT) 的疗效.
  • 由于个体差异和疾病状态,T细胞扩张的失败可能会发生.
  • 调节基质硬度可以改善T细胞扩张,但最佳硬度因人而异.

研究的目的:

  • 基于短期测试,开发长期T细胞扩张的预测模型.
  • 评估细胞扩散作为机械敏感T细胞扩张的预测因素的实用性.
  • 使用细胞形态学区分健康和慢性淋巴细胞白血病 (CLL) T 细胞.

主要方法:

  • 测量短期T细胞在不同机械硬度的基板上扩散.
  • 使用深度学习 (DL) 模型进行分类和预测任务.
  • 关联短期细胞扩散与长期T细胞扩张潜力.

主要成果:

  • 短期的细胞扩散有效地预测了随后的机器敏感T细胞扩张.
  • 一个DL模型准确地分类了来自健康捐赠者的T细胞与CLL患者.
  • 该系统成功地根据细胞源和基质刚度预测了长期T细胞扩张.

结论:

  • 短期细胞扩散是ACT中长期T细胞功能的可靠预测指标.
  • 基于深度学习的细胞扩散分析可以提高T细胞生产的可靠性.
  • 这种方法提高了免疫治疗的疗效,使得从小的诊断样本进行预测.