快速可靠的图像分析流水线,用于半自动化定量中枢神经系统细胞类型。

IF 2.3 4区 医学 Q2 BIOCHEMICAL RESEARCH METHODS
Adrian Castellanos-Molina , Juliette Ferry , Ana Boisvert , Alexandre Chamberland , Nicolas Vallières , Steve Lacroix
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引用次数: 0

摘要

背景:研究中枢神经系统细胞反应对于理解疾病、损伤和开发有效的治疗方法至关重要。虽然免疫荧光和转基因报告模型允许特异性标记,但由于组织异质性,自动定量仍然很困难。因此,大多数分析都是手动进行的,这就引入了用户偏见并限制了可重复性。新方法:我们开发了一种基于matlab的半自动工作流程,用于定量免疫荧光染色的CNS细胞,重点是核信号检测。该管道使用DAPI掩蔽和imfindcircles函数来检测圆核,需要最少的用户输入。结果:该管道实现了cns驻留细胞的稳健定量。脑和脊髓组织切片的自动分析与人工定量非常相似,误差最小。在小鼠挫裂性脊髓损伤模型中,发现病灶中心的髓鞘性少突胶质细胞呈直立-尾侧下降,证实了该方法在检测损伤引起的细胞变化方面的准确性和敏感性。与现有方法的比较:与许多常用的基于量化的软件不同,这种新型管道不进行完整的图像分割。相反,它使用核形态学来检测圆形。此外,该管道是专门为CNS细胞的定量设计和优化的,其异质性和细胞结构对现有的更普遍的方法提出了具体的挑战。结论:本研究提出了一种经典分割模型的替代方案,通过使用核形态学对cns驻留细胞进行可重复的量化。它的简单性,最小的输入要求,减少了半自动化定量的时间,以及对中枢神经系统组织的特异性,使其成为研究健康和病理背景下细胞反应的有价值的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rapid and reliable image analysis pipeline for semi-automated quantification of CNS cell types in MATLAB

Background

Studying CNS cell responses is essential for understanding disease, injury, and developing effective therapies. While immunofluorescence and transgenic reporter models allow for specific labeling, automated quantification remains difficult due to tissue heterogeneity. Consequently, most analyses are conducted manually, introducing user bias and limiting reproducibility.

New method

We developed a MATLAB-based semi-automated workflow for quantifying immunofluorescence-stained CNS cells, focusing on nuclear signal detection. The pipeline uses DAPI masking and the imfindcircles function to detect round nuclei, requiring minimal user input.

Results

The pipeline enabled robust quantification of CNS-resident cells. Automated analyses of brain and spinal cord tissue sections closely resembled manual quantification, with minimal error. In a mouse model of contusion spinal cord injury, it revealed a rostro-caudal decline in myelinating oligodendrocytes from the lesion epicenter, confirming the method’s accuracy and sensitivity in detecting injury-induced cellular changes.

Comparison with existing methods

Unlike many commonly used quantification-based software, this novel pipeline does not perform full image segmentation. Instead, it uses nuclear morphology to detect round shapes. Moreover, the pipeline has been specifically designed and optimized for the quantification of CNS cells, whose heterogeneity and cytoarchitecture pose specific challenges to existing methods that are more generalized.

Conclusions

This study presents an alternative to classical segmentation models by offering a reproducible quantification of CNS-resident cells using nuclear morphology. Its simplicity, minimal input requirements, reduced time for semi-automated quantification, and specificity for CNS tissues make it a valuable tool for studying cellular responses in both healthy and pathological contexts.
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来源期刊
Journal of Neuroscience Methods
Journal of Neuroscience Methods 医学-神经科学
CiteScore
7.10
自引率
3.30%
发文量
226
审稿时长
52 days
期刊介绍: The Journal of Neuroscience Methods publishes papers that describe new methods that are specifically for neuroscience research conducted in invertebrates, vertebrates or in man. Major methodological improvements or important refinements of established neuroscience methods are also considered for publication. The Journal''s Scope includes all aspects of contemporary neuroscience research, including anatomical, behavioural, biochemical, cellular, computational, molecular, invasive and non-invasive imaging, optogenetic, and physiological research investigations.
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