Significance: Collagen is the most abundant protein in vertebrates and is found in tissues that regularly experience tension, compression, and shear forces. However, the underlying mechanism of collagen fibril formation and remodeling is poorly understood. Aim: We explore how a collagen monomer is visualized using fluorescence microscopy and how its spatial orientation is determined. Defining the orientation of collagen monomers is not a trivial problem, as the monomer has a weak contrast and is relatively small. It is possible to attach fluorescence tags for contrast, but the size is still a problem for detecting orientation using fluorescence microscopy. Approach: We present two methods for detecting a monomer and classifying its orientation. A modified Gabor filter set and an automatic classifier trained by convolutional neural network based on a synthetic dataset were used. Results: By evaluating the performance of these two approaches with synthetic and experimental data, our results show that it is possible to determine the location and orientation with an error of ∼37 deg of a single monomer with fluorescence microscopy. Conclusions: These findings can contribute to our understanding of collagen monomers interaction with collagen fibrils surface during fibril formation and remodeling.

中文翻译：

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荧光显微镜中胶原单体取向的测量方法

意义：胶原蛋白是脊椎动物中含量最丰富的蛋白质，存在于经常承受张力、压缩力和剪切力的组织中。然而，对胶原纤维形成和重塑的潜在机制知之甚少。目的：我们探索如何使用荧光显微镜观察胶原单体以及如何确定其空间方向。定义胶原单体的方向不是一个小问题，因为单体具有弱对比度并且相对较小。可以附加荧光标签进行对比，但尺寸仍然是使用荧光显微镜检测方向的问题。方法：我们提出了两种检测单体并对其方向进行分类的方法。使用改进的 Gabor 过滤器集和基于合成数据集的卷积神经网络训练的自动分类器。结果：通过使用合成和实验数据评估这两种方法的性能，我们的结果表明，可以用荧光显微镜确定单个单体的位置和方向，误差约为 37 度。结论：这些发现有助于我们了解在原纤维形成和重塑过程中胶原单体与胶原原纤维表面的相互作用。