UCIBIO-Applied Molecular Biosciences Unit, Laboratory of Toxicology, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal.
i4HB-Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal.
Int J Mol Sci. 2023 Feb 24;24(5):4508. doi: 10.3390/ijms24054508.
Immunohistochemical staining of cell and molecular targets in brain samples is a powerful tool that can provide valuable information on neurological mechanisms. However, post-processing of photomicrographs acquired after 3,3'-Diaminobenzidine (DAB) staining is particularly challenging due to the complexity associated with the size, samples number, analyzed targets, image quality, and even the subjectivity inherent to the analysis by different users. Conventionally, this analysis relies on the manual quantification of distinct parameters (e.g., the number and size of cells and the number and length of cell branching) in a large set of images. These represent extremely time-consuming and complex tasks, defaulting the processing of high amounts of information. Here we describe an improved semi-automatic method to quantify glial fibrillary acidic protein (GFAP)-labelled astrocytes in immunohistochemistry images of rat brains, at magnifications as low as 20×. This method is a straightforward adaptation of the Young & Morrison method, using ImageJ's plugin Skeletonize, coupled with intuitive data processing in datasheet-based software. It allows swifter and more efficient post-processing of brain tissue samples, regarding astrocyte size and number quantification, the total area occupied, as well as astrocyte branching and branch length (indicators of astrocyte activation), thus contributing to better understand the possible inflammatory response developed by astrocytes.
脑样本中细胞和分子靶标的免疫组织化学染色是一种强大的工具，可以提供有关神经机制的有价值信息。然而，由于与大小、样本数量、分析靶标、图像质量甚至不同用户分析的固有主观性相关的复杂性，DAB 染色后获得的显微照片的后处理特别具有挑战性。传统上，这种分析依赖于对大量图像中的不同参数（例如，细胞的数量和大小以及细胞分支的数量和长度）进行手动量化。这些代表了极其耗时且复杂的任务，默认处理大量信息。在这里，我们描述了一种改进的半自动化方法，用于量化大鼠脑免疫组织化学图像中 GFAP 标记的星形胶质细胞，放大倍数低至 20×。该方法是 Young & Morrison 方法的简单改编，使用 ImageJ 的插件 Skeletonize，并结合基于数据表的软件进行直观的数据处理。它允许更快、更有效地处理脑组织样本，用于量化星形胶质细胞的大小和数量、总占空比，以及星形胶质细胞的分支和分支长度（星形胶质细胞激活的指标），从而有助于更好地理解星形胶质细胞可能发生的炎症反应。
