在微生物和化学风险评估中的定量工具
Deyan Stratev1, Vasilis P Valdramidis2
1Department of Food Quality and Safety and Veterinary Legislation, Faculty of Veterinary Medicine Trakia University Stara Zagora Bulgaria.
EFSA journal. European Food Safety Authority
|December 4, 2023
概括
这项研究对风险评估的预测微生物学工具进行了培训. 使用光密度测量对Vibrio parahaemolyticus的定量表征证明是可靠的,用于暴露评估和抗生素疗效的确定.
科学领域:
- 微生物学 微生物学
- 风险评估 风险评估
- 量化微生物学 量化微生物学
背景情况:
- 欧盟-FORA计划提供了微生物和化学风险评估的定量工具培训.
- 关键领域包括预测微生物学,建模策略,实验设计和MATLAB,GInaFiT和DMFit等软件工具.
研究的目的:
- 培训用于风险评估的定量微生物学技术.
- 应用这些技术来表征*Vibrio parahaemolyticus*的生长和对抗生素的敏感性.
主要方法:
- 用MATLAB进行培训,以使用Ratkowsky模型确定最大特异增长率 (μmax).
- 使用GInaFiT进行细菌无活化建模,使用DMFit进行生长参数估计.
- 进行V. parahaemolyticus培养物的光学密度测量,以获得生长动力学.
- 估计氨基糖化抗生素的最小抑制度 (MIC) 和非抑制度 (NIC).
主要成果:
- 从光密度测量中估计了 *V. parahaemolyticus* 的最大特定生长率 (μmax).
- 测量了光密度与时间曲线的部分面积,以确定MIC和NIC.
- 对*V. parahaemolyticus*的定量表征产生了适合暴露评估的可靠数据.
结论:
- 应用的定量方法为微生物风险评估提供了可靠的数据.
- 度测试对于估计MIC和NIC是有效的,证明了抗生素的有效性.
- 对预测微生物学工具的培训提高了对微生物风险评估的能力.
关键词:
这种病毒是Vibrio parahaemolyticus.最大特定增长率的最高增长率.最低抑制度的最小抑制度.没有抑制的度.预测性微生物学 预测性微生物学风险评估 风险评估 风险评估软件工具 软件工具 软件工具更多相关视频
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