组织芯片技术在干细胞研究中的应用。

Alberto La Spada, Barnaba Rainoldi, Andrea De Blasio, Ida Biunno
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引用次数: 6

摘要

实际上,组织微阵列(TMA)在基础和临床研究以及最终诊断方面的应用是无限的。然而,为了评估新标记的功能重要性,研究人员经常转向细胞系模型系统。正确选择细胞系通常是一项艰巨的任务,但使用细胞微阵列(CMA)技术可以快速筛选不同来源细胞中的几种标记物,模拟基因组规模的分析。为了提高CMA载玻片的形态学评价,我们通过常规胰蛋白酶化、机械刮削和盖片上生长的细胞来收获细胞。我们发现,机械刮削是一种很好的评价方法,因为它保持了覆盖物的真实形态与生长在覆盖物上的形态非常相似。免疫荧光图像质量更高,便于生物标记物的细胞和亚细胞定位。在这里,我们描述了干细胞研究中的CMA技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Application of Tissue Microarray Technology to Stem Cell Research.

Application of Tissue Microarray Technology to Stem Cell Research.

Application of Tissue Microarray Technology to Stem Cell Research.

Application of Tissue Microarray Technology to Stem Cell Research.

There is virtually an unlimited number of possible Tissue Microarray (TMA) applications in basic and clinical research and ultimately in diagnostics. However, to assess the functional importance of novel markers, researchers very often turn to cell line model systems. The appropriate choice of a cell line is often a difficult task, but the use of cell microarray (CMA) technology enables a quick screening of several markers in cells of different origins, mimicking a genomic-scale analysis. In order to improve the morphological evaluations of the CMA slides we harvested the cells by conventional trypsinization, mechanical scraping and cells grown on coverslips. We show that mechanical scraping is a good evaluation method since keeps the real morphology very similar to those grown on coverslips. Immunofluorescence images are of higher quality, facilitating the reading of the biomarker cellular and subcellular localization. Here, we describe CMA technology in stem cell research.

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来源期刊
自引率
0.00%
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0
审稿时长
11 weeks
期刊介绍: High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: Microarrays, DNA Sequencing, RNA Sequencing, Protein Identification and Quantification, Cell-based Approaches, Omics Technologies, Imaging, Bioinformatics, Computational Biology/Chemistry, Statistics, Integrative Omics, Drug Discovery and Development, Microfluidics, Lab-on-a-chip, Data Mining, Databases, Multiplex Assays.
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