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"CLADE-FINDER": 金刚谱系分析确定由里埃变换红外光谱学和人工神经网络

Carlotta Magrì¹, Elena De Carolis¹, Vittorio Ivagnes¹

¹Dipartimento di Scienze di Laboratorio ed Ematologiche, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, 00168 Rome, Italy.

|November 27, 2024

概括

一个名为CLADE-FINDER的新工具使用富里埃变换红外光谱学和人工神经网络来快速识别Candida auris菌群. 这种方法为对这种迫切的真菌威胁的流行病学监测提供了更快的替代方案.

科学领域:

* 菌群学 * 菌群学
* 传染病传染病
* 计算生物学 * 计算生物学

背景情况:

* *Candida auris*是由于其多药性耐药性而造成的迫切威胁.
*基因组监测对于管理*C. auris*传播至关重要.
*如WGS目前的方法是耗时和昂贵的.

研究的目的:

* 开发一种快速且具有成本效益的方法来确定 *C. auris* 类.
* 创建一个实时流行病学监测工具.
* 验证开发工具的准确性.

主要方法:

* 福里埃变换红外光谱法 (FTIR) 用于生物化学指纹.
*使用了一个人工神经网络 (ANN) 算法.
分析了来自五个类 (I-V) 的74个*C. auris*分离物.

主要成果:

* CLADE-FINDER工具准确地分类了验证集中的96%的分离物.
* 该系统成功地区分了四个主要的*C. auris*类 (I-IV).
*FTIR光谱与ANN结合,提供了一个可靠的基因型化方案.

结论:

* CLADE-FINDER提供了一种快速且易于使用的方法来识别 *C. auris* 类.
* 这种工具可以在实时流行病学监测和管理C. auris*疫情方面发挥重要作用.
* 该方法补充了现有的基因组监测的黄金标准技术.

关键词:

C. aurisis 这种虫子发现者发现者发现者美国的FTIR是FTIR.克莱德斯是什么意思疫情爆发管理管理

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