The evaluation of large experimental datasets is a fundamental aspect of research in every scientific field. Streamlining this process can improve the reliability of results while making data analysis more efficient and faster to execute. In biomedical research it is often very important to determine the type of cell death after various treatments. Thus, differentiating between viable, apoptotic, and necrotic cells provide critical insights into the treatment efficacy, a key aspect in the field of drug development. Fluorescent microscopy is perceived as a widely used technique for cell metabolism assessment and can therefore be used to investigate treatment outcomes after staining samples with cell death detection kit. However, accurate evaluation of therapeutic results requires quantitative analysis, often necessitating extensive postprocessing of imaging data. In this study, we introduce a complementary tool designed as a macro for the Fiji platform, enabling the automated postprocessing of fluorescent microscopy images to accurately distinguish and quantify viable, apoptotic, and necrotic cells.
ApoNecV: A macro for cell death type differentiation.
ApoNecV:用于细胞死亡类型分化的宏
阅读:9
作者:Kolarikova Marketa, Hosikova Barbora, Tesarik Jiri, Langova Katerina, Kolarova Hana
| 期刊: | Journal of Microscopy | 影响因子: | 1.900 |
| 时间: | 2025 | 起止号: | 2025 Apr;298(1):17-26 |
| doi: | 10.1111/jmi.13386 | 研究方向: | 细胞生物学 |
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