Feasibility of a Clinical Chemical Analysis Approach to Predict Misuse of Growth Promoting Hormones in Cattle

Rodat Cunningham, Mark Mooney, X.L. Xia, S. Crooks, D. Matthews, M.O. Keeffe, Kang Li, Christopher Elliott

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)
12 Downloads (Pure)

Abstract

A study was performed to determine if targeted metabolic profiling of cattle sera could be used to establish a predictive tool for identifying hormone misuse in cattle. Metabolites were assayed in heifers (n ) 5) treated with nortestosterone decanoate (0.85 mg/kg body weight), untreated heifers (n ) 5), steers (n ) 5) treated with oestradiol benzoate (0.15 mg/kg body weight) and untreated steers (n ) 5). Treatments were administered on days 0, 14, and 28 throughout a 42 day study period. Two support vector machines (SVMs) were trained, respectively, from heifer and steer data to identify hormonetreated animals. Performance of both SVM classifiers were evaluated by sensitivity and specificity of treatment prediction. The SVM trained on steer data achieved 97.33% sensitivity and 93.85% specificity while the one on heifer data achieved 94.67% sensitivity and 87.69% specificity. Solutions of SVM classifiers were further exploited to determine those days when classification accuracy of the SVM was most reliable. For heifers and steers, days 17-35 were determined to be the most selective. In summary, bioinformatics applied to targeted metabolic profiles generated from standard clinical chemistry analyses, has yielded an accurate, inexpensive, high-throughput test for predicting steroid abuse in cattle.
Original languageEnglish
Pages (from-to)977-983
Number of pages7
JournalAnalytical Chemistry
Volume81
Issue number3
Early online date07 Jan 2009
DOIs
Publication statusPublished - 01 Feb 2009

ASJC Scopus subject areas

  • Analytical Chemistry

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