用拓扑分析揭示酪蛋白凝胶微观结构演化与流变性能的关系
Topological texture analysis of microscopy images of dynamic casein gelation and its relation to rheological properties
- 结合拓扑数据分析等多方法，追踪蛋白网络形成过程
- 发现凝胶化前有分散聚集体滞后期，后出现网络重构阶段
- 适合食品与材料科学中微结构动态研究者使用
本文提出一种新型计算工具箱，整合拓扑数据分析（TDA）、差分盒计数（DBC）、多重分形分割（MFP）和局部二值模式（LBP），应用于30℃与40℃下、1.8%和3.5% w/v两种GDL浓度诱导的酪蛋白酸钠凝胶化过程的时序超分辨率STED显微图像。通过最大贝蒂数1曲线追踪拓扑环结构，揭示了分散聚集体的滞后期、网络连通性突变与流变学观测的溶-凝转变一致、以及凝胶后网络重构阶段的上升趋势。这些拓扑转变得到DBC和MFP验证，二者可分辨结构复杂度与空间异质性的变化。该工具箱在模拟分形图像上预先验证，对细微微结构转变敏感，而传统流变测量仅反映平均力学响应。该集成方法为食品与材料科学中动态微结构提供了可靠定量分析手段。代码已开源：https://github.com/Zahratabatabaei/Delifood_CV_paper.git
原文摘要 · Abstract (English)
We propose a novel computational toolbox that integrates Topological Data Analysis (TDA), Differential Box Counting (DBC), Multifractal Partition (MFP), and Local Binary Patterns (LBP), applied to time-lapse super-resolution STED microscopy images of sodium caseinate gelation induced by glucono-delta-lactone (GDL) at 30 °C and 40 °C and two GDL concentrations (1.8% and 3.5% w/v). TDA tracked topological loops, closed ring-like structures reflecting protein network interconnectivity, via max-Betti-1 curves, which revealed a lag phase of dispersed aggregates, a sharp decay coinciding with network percolation and the rheologically observed sol-gel transition, and a post-gelation increase corresponding to network rearrangements. These topological transitions were corroborated by DBC and MFP as these methods were able to resolve changes in structural complexity and spatial heterogeneity. The toolbox was validated on simulated fractal images prior to experimental application. Together, these descriptors provided sensitivity to subtle microstructural transitions that bulk rheology captured as averaged bulk mechanical responses. This integrated approach provides a robust quantitative tool for characterizing complex microstructure in food and material science with evolving microstructural dynamics. Code is available at https://github.com/Zahratabatabaei/Delifood_CV_paper.git
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