线性判别分析
肺结核
色谱法
结核菌素
牛结核病
医学
结核分枝杆菌
牛分枝杆菌
病理
化学
人工智能
计算机科学
作者
Sophie E. Lellman,C.K. Reynolds,A. K. Jones,Nick Taylor,Rainer Cramer
标识
DOI:10.1021/acs.jafc.3c01879
摘要
Detecting bovine tuberculosis (bTB) primarily relies on the tuberculin skin test, requiring two separate animal handling events with a period of incubation time (normally 3 days) between them. Here, we present the use of liquid atmospheric pressure (LAP)-MALDI for the identification of bTB infection, employing a three-class prediction model that was obtained by supervised linear discriminant analysis (LDA) and tested with bovine mastitis samples as disease-positive controls. Noninvasive collection of nasal swabs was used to collect samples, which were subsequently subjected to a short (<4 h) sample preparation method. Cross-validation of the three-class LDA model from the processed nasal swabs provided a sensitivity of 75.0% and specificity of 90.1%, with an overall classification accuracy of 85.7%. These values are comparable to those for the skin test, showing that LAP-MALDI MS has the potential to provide an alternative single-visit diagnostic platform that can detect bTB within the same day of sampling.
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