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首页> 外文期刊>Current drug targets. Cardiovascular & haematological disorders >Observations on the use of the avian chorioallantoic membrane (CAM) model in investigations into angiogenesis.
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Observations on the use of the avian chorioallantoic membrane (CAM) model in investigations into angiogenesis.

机译:使用禽绒膜尿囊膜(CAM)模型进行血管生成研究的观察结果。

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摘要

The chorioallantoic membrane (CAM) is widely used as a model to examine angiogenesis, and anti-angiogenesis. Its advantages over mammalian systems include low cost, and ease of preparation, as well as the absence of a mature immune system. Although the use of this model presents a major opportunity to compare data generated in different laboratories, thereby expediting the evaluation of new drugs, angiogenic potential of cells and tissues, and body fluids, as well as to provide meaningful information concerning the molecular mechanisms involved, the wide range of methodologies used, especially in the quantification of the response, make any comparison essentially invalid. In this review, the major methodologies for all aspects of the use of the CAM in angiogenesis-related studies have been described. These include the source of the CAM, the methods for culture, and methods for evaluation of normal growth and of the response to an intervention. Methods for applying an intervention, the age for intervention and the duration of an intervention are documented. The structure and growth characteristics, the nature of possible responses to stimulation and inhibition of angiogenesis, and the complications of non-specific reactions have been examined. The need for a standardized approach to the use of the CAM model is obvious. One set of possible parameters is suggested.
机译:绒毛膜尿囊膜(CAM)被广泛用作检查血管生成和抗血管生成的模型。它相对于哺乳动物系统的优势包括低成本,易于制备以及不存在成熟的免疫系统。尽管使用此模型为比较不同实验室产生的数据提供了主要机会,从而加快了对新药的评估,细胞和组织以及体液的血管生成潜力,并提供了有关所涉及的分子机制的有意义的信息,广泛使用的方法,尤其是在响应的量化中,使得任何比较都实质上是无效的。在这篇综述中,已经描述了在血管生成相关研究中使用CAM各个方面的主要方法。其中包括CAM的来源,培养方法以及评估正常生长和对干预措施反应的方法。记录了实施干预的方法,干预的年龄和持续时间。已经检查了结构和生长特征,对刺激和抑制血管生成的可能反应的性质以及非特异性反应的并发症。对于使用CAM模型的标准化方法的需求显而易见。建议使用一组可能的参数。

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