Suppr超能文献

JSFit:一种用于拟合和预测J形及S形浓度-反应曲线的方法。

JSFit: a method for the fitting and prediction of J- and S-shaped concentration-response curves.

作者信息

Wang Ze-Jun, Liu Shu-Shen, Qu Rui

机构信息

Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University Shanghai 200092 China

State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University Shanghai 200092 China.

出版信息

RSC Adv. 2018 Feb 9;8(12):6572-6580. doi: 10.1039/c7ra13220d. eCollection 2018 Feb 6.

Abstract

Most monotonic S-shaped concentration-response curves (CRCs) can be satisfactorily described by a classical Hill equation. However, the Hill equation cannot effectively describe the non-monotonic J-shaped CRCs that display stimulation at low concentrations and inhibition at high concentrations. On the other hand, the physical meaning of the model parameters in current models describing the J-shaped CRCs is not very clear. It is well known that both toxicity experiments and the fitting process inevitably produce uncertainty. To effectively deal with the J-shaped concentration-response data with uncertainty and make the model parameters meaningful, we developed a method for the fitting of the J-shaped and/or S-shaped concentration-response data (simply called JSFit). The JSFit first uses one Hill equation (S-shaped) or combines with two Hill equations (J-shaped) for fitting, then nonlinear least squares fitting is performed by means of the Levenberg-Marquardt algorithm, and finally the observation-based confidence intervals of the fitting curve are constructed by the delta procedure. For the convenience of application, we wrote a computational program (JSFit) using the MATAB programming language and introduced automation of the initial parameters into the program. The JSFit was then successfully used in the fitting and prediction of the toxic data of pesticides, ionic liquids, antibiotics, and personal skin-care products on sp.-Q67.

摘要

大多数单调的S形浓度-反应曲线(CRCs)可以用经典的希尔方程得到令人满意的描述。然而,希尔方程不能有效地描述非单调的J形CRCs,这种曲线在低浓度时表现出刺激作用,在高浓度时表现出抑制作用。另一方面,当前描述J形CRCs的模型中模型参数的物理意义不是很明确。众所周知,毒性实验和拟合过程不可避免地会产生不确定性。为了有效处理具有不确定性的J形浓度-反应数据并使模型参数有意义,我们开发了一种用于拟合J形和/或S形浓度-反应数据的方法(简称为JSFit)。JSFit首先使用一个希尔方程(S形)或结合两个希尔方程(J形)进行拟合,然后通过列文伯格-马夸尔特算法进行非线性最小二乘拟合,最后通过德尔塔法构建拟合曲线基于观测的置信区间。为了便于应用,我们使用MATAB编程语言编写了一个计算程序(JSFit),并将初始参数的自动化引入该程序。然后,JSFit成功地用于农药、离子液体、抗生素和个人护肤品对sp.-Q67的毒性数据的拟合和预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff1f/9078288/5755940a9e9e/c7ra13220d-f1.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