Suppr超能文献

生物活性骨材料中重组人骨形态发生蛋白2(rhBMP2)的定量分析。

Quantification of rhBMP2 in bioactive bone materials.

作者信息

Lian Huan, Wang Han, Han Qianqian, Wang Chunren

机构信息

Division of Biomaterials, Department of Medical Devices, National Institutes for Food and Drug Control, No. 31 Huatuo Road, Beijing 102629, China.

出版信息

Regen Biomater. 2020 Feb;7(1):71-75. doi: 10.1093/rb/rbz038. Epub 2019 Dec 16.

Abstract

Bone morphogenetic protein (BMP), belongs to transforming growth factor-β (TGF-β) superfamily except BMP-1. Implanting BMP into muscular tissues induces ectopic bone formation at the site of implantation, which provides opportunity for the treatment of bone defects. Recombinant human BMP-2 (rhBMP-2) has been used clinically, but the lack of standard methods for quantifying rhBMP-2 biological activity greatly hindered the progress of commercialization. In this article, we describe an rhBMP-2 quantification method, as well as the data analyzation pipeline through logistic regression in RStudio. Previous studies indicated that alkaline phosphatase (ALP) activity of C2C12 cells was significantly increased when exposed to rhBMP-2, and showed dose-dependent effects in a certain concentration range of rhBMP-2. Thus, we chose to quantify ALP activity as an indicator of rhBMP-2 bioactivity . A sigmoid relationship between the ALP activity and concentration of rhBMP-2 was discovered. However, there are tons of regression models for such a non-linear relationship. It has always been a major concern for researchers to choose a proper model that not only fit data accurately, but also have parameters representing practical meanings. Therefore, to fit our rhBMP-2 quantification data, we applied two logistic regression models, three-parameter log-logistic model and four-parameter log-logistic model. The four-parameter log-logistic model (adj- > 0.98) fits better than three-parameter log-logistic model (adj- > 0.75) for the sigmoid curves. Overall, our results indicate rhBMP-2 quantification can be accomplished by detecting ALP activity and fitting four-parameter log-logistic model. Furthermore, we also provide a highly adaptable R script for any additional logistic models.

摘要

骨形态发生蛋白(BMP),除BMP-1外,属于转化生长因子-β(TGF-β)超家族。将BMP植入肌肉组织可在植入部位诱导异位骨形成,这为骨缺损的治疗提供了机会。重组人BMP-2(rhBMP-2)已在临床上使用,但缺乏量化rhBMP-2生物活性的标准方法极大地阻碍了商业化进程。在本文中,我们描述了一种rhBMP-2定量方法,以及通过RStudio中的逻辑回归进行数据分析的流程。先前的研究表明,C2C12细胞暴露于rhBMP-2时碱性磷酸酶(ALP)活性显著增加,并且在rhBMP-2的一定浓度范围内呈现剂量依赖性效应。因此,我们选择将ALP活性量化作为rhBMP-2生物活性的指标。发现ALP活性与rhBMP-2浓度之间呈S形关系。然而,对于这种非线性关系有大量的回归模型。选择一个不仅能准确拟合数据,而且具有代表实际意义参数的合适模型一直是研究人员的主要关注点。因此,为了拟合我们的rhBMP-2定量数据,我们应用了两个逻辑回归模型,即三参数对数逻辑模型和四参数对数逻辑模型。对于S形曲线,四参数对数逻辑模型(调整后 > 0.98)比三参数对数逻辑模型(调整后 > 0.75)拟合得更好。总体而言,我们的结果表明rhBMP-2定量可以通过检测ALP活性并拟合四参数对数逻辑模型来完成。此外,我们还为任何其他逻辑模型提供了一个高度适应性的R脚本。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e451/7053258/827e6dea36a9/rbz038f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验