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采用三种建模方法分析环境参数对肉毒梭菌达到毒性所需时间的影响。

Analysis of the influence of environmental parameters on Clostridium botulinum time-to-toxicity by using three modeling approaches.

作者信息

Schaffner D W, Ross W H, Montville T J

机构信息

Department of Food Science, Rutgers-The State University of New Jersey, New Brunswick, New Jersey 08901-8520, USA.

出版信息

Appl Environ Microbiol. 1998 Nov;64(11):4416-22. doi: 10.1128/AEM.64.11.4416-4422.1998.

Abstract

This study used the technique of waiting time modeling to analyze the combined effects of temperature, pH, carbohydrate, protein, and lipid on the time-to-toxicity of Clostridium botulinum 56A. Waiting time models can be used whenever the time to the occurrence of some event is the variable of interest. In the case of the time-to-toxicity data, the variable is the time from the beginning of an experiment until a tube is identified as positive. The statistical analysis used the SAS procedure LIFEREG and included determination of the form of the response surface, identification of the error distribution, and simplification of the response surface. We found that increasing the macromolecule concentration decreased the probability of toxin formation. The probability of toxin formation also decreased at lower temperatures and at pHs further from the optimum. The waiting time modeling approach to developing models for botulinal toxin formation compared favorably with other approaches but had one specific advantage. Waiting time models have the inherent advantage that safety concerns regarding predictions are automatically quantified in the analysis by formally identifying a distribution of times-to-toxicity. The use of this time-to-toxicity distribution permits a customizable margin of safety (e.g., one in a million) not possible with other approaches.

摘要

本研究采用等待时间建模技术,分析温度、pH值、碳水化合物、蛋白质和脂质对肉毒杆菌56A毒性产生时间的综合影响。只要某个事件发生的时间是感兴趣的变量,就可以使用等待时间模型。对于毒性产生时间的数据,该变量是从实验开始到某一试管被确定为阳性的时间。统计分析使用SAS程序LIFEREG,包括确定响应面的形式、识别误差分布以及简化响应面。我们发现,增加大分子浓度会降低毒素形成的概率。在较低温度和远离最佳pH值的情况下,毒素形成的概率也会降低。与其他方法相比,开发肉毒杆菌毒素形成模型的等待时间建模方法具有优势且有一个特定优点。等待时间模型具有内在优势,即通过正式确定毒性产生时间的分布,在分析中自动量化与预测相关的安全问题。使用这种毒性产生时间分布允许设定可定制的安全边际(例如百万分之一),这是其他方法无法实现的。

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本文引用的文献

1
Growth of Proteolytic Clostridium botulinum in Process Cheese Products: II. Predictive Modeling.
J Food Prot. 1995 Oct;58(10):1100-1108. doi: 10.4315/0362-028X-58.10.1100.
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Model for the Aerobic Growth of Aeromonas hydrophila K144.嗜水气单胞菌K144需氧生长模型
J Food Prot. 1991 Jun;54(6):429-435. doi: 10.4315/0362-028X-54.6.429.
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Time-to-turbidity model for non-protective type B Clostridium botulinum.非保护性B型肉毒梭菌的浑浊时间模型
Int J Food Microbiol. 1997 Apr 29;36(1):49-60. doi: 10.1016/s0168-1605(96)01244-5.
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The effect of temperature on the germination of single spores of Clostridium botulinum 62A.
J Appl Microbiol. 1997 Jan;82(1):48-56. doi: 10.1111/j.1365-2672.1997.tb03296.x.

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