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一种新的基于网络的肌肉组织学自动分析方法。

A new web-based method for automated analysis of muscle histology.

机构信息

Laboratory of Molecular Myology, Friedrich-Baur-Institute, Department of Neurology, Ludwig-Maximilians-Universität München, Germany.

出版信息

BMC Musculoskelet Disord. 2013 Jan 16;14:26. doi: 10.1186/1471-2474-14-26.

Abstract

BACKGROUND

Duchenne muscular dystrophy is an inherited degenerative neuromuscular disease characterised by rapidly progressive muscle weakness. Currently, curative treatment is not available. Approaches for new treatments that improve muscle strength and quality of life depend on preclinical testing in animal models. The mdx mouse model is the most frequently used animal model for preclinical studies in muscular dystrophy research. Standardised pathology-relevant parameters of dystrophic muscle in mdx mice for histological analysis have been developed in international, collaborative efforts, but automation has not been accessible to most research groups. A standardised and mainly automated quantitative assessment of histopathological parameters in the mdx mouse model is desirable to allow an objective comparison between laboratories.

METHODS

Immunological and histochemical reactions were used to obtain a double staining for fast and slow myosin. Additionally, fluorescence staining of the myofibre membranes allows defining the minimal Feret's diameter. The staining of myonuclei with the fluorescence dye bisbenzimide H was utilised to identify nuclei located internally within myofibres. Relevant structures were extracted from the image as single objects and assigned to different object classes using web-based image analysis (MyoScan). Quantitative and morphometric data were analysed, e.g. the number of nuclei per fibre and minimal Feret's diameter in 6 month old wild-type C57BL/10 mice and mdx mice.

RESULTS

In the current version of the module "MyoScan", essential parameters for histologic analysis of muscle sections were implemented including the minimal Feret's diameter of the myofibres and the automated calculation of the percentage of internally nucleated myofibres. Morphometric data obtained in the present study were in good agreement with previously reported data in the literature and with data obtained from manual analysis.

CONCLUSIONS

A standardised and mainly automated quantitative assessment of histopathological parameters in the mdx mouse model is now available. Automated analysis of histological parameters is more rapid and less time-consuming. Moreover, results are unbiased and more reliable. Efficacy of therapeutic interventions, e.g. within the scope of a drug screening or therapeutic exon skipping, can be monitored. The automatic analysis system MyoScan used in this study is not limited exclusively to dystrophin-deficient mice but also represents a useful tool for applications in the research of other dystrophic pathologies, various other skeletal muscle diseases and degenerative neuromuscular disorders.

摘要

背景

杜氏肌营养不良症是一种遗传性进行性神经肌肉疾病,其特征是肌肉力量迅速减弱。目前,尚无治愈方法。改善肌肉力量和生活质量的新治疗方法的方法取决于在动物模型中的临床前测试。mdx 小鼠模型是肌肉营养不良症研究中最常用的临床前研究动物模型。在国际合作努力中,已经为 mdx 小鼠的肌肉病理学相关参数制定了标准化的病理学分析标准,但大多数研究小组无法实现自动化。需要对 mdx 小鼠模型中的组织病理学参数进行标准化和主要自动化评估,以允许实验室之间进行客观比较。

方法

免疫和组织化学反应用于获得快肌和慢肌的双重染色。此外,肌纤维膜的荧光染色允许定义最小 Feret 直径。利用荧光染料双苯并咪唑 H 对肌核进行染色,用于识别位于肌纤维内部的核。使用基于网络的图像分析(MyoScan)从图像中提取相关结构作为单个对象,并将它们分配到不同的对象类。分析了定量和形态计量学数据,例如 6 月龄野生型 C57BL/10 小鼠和 mdx 小鼠的每根纤维的核数和最小 Feret 直径。

结果

在当前版本的“ MyoScan”模块中,已经实现了用于肌肉切片组织学分析的基本参数,包括肌纤维的最小 Feret 直径和自动计算有核肌纤维的百分比。本研究中获得的形态计量学数据与文献中先前报道的数据以及从手动分析中获得的数据非常吻合。

结论

现在可以对 mdx 小鼠模型中的组织病理学参数进行标准化和主要自动化评估。组织学参数的自动分析更快,耗时更少。此外,结果更客观,更可靠。可以监测治疗干预的效果,例如在药物筛选或治疗性外显子跳跃的范围内。在这项研究中使用的自动分析系统 MyoScan 不仅限于肌营养不良蛋白缺乏的小鼠,而且还代表了在其他肌肉病理、各种其他骨骼肌疾病和退行性神经肌肉疾病研究中的有用工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2d08/3560198/34ccf13f097a/1471-2474-14-26-1.jpg

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