Predicting the influence of multiple components on microbial inhibition using a logistic response model - a novel approach

Show simple item record

dc.contributor.author Henley-Smith, Cynthia Joan
dc.contributor.author Steffens, Francois E.
dc.contributor.author Botha, Francien Susanna
dc.contributor.author Lall, Namrita
dc.date.accessioned 2014-09-09T07:51:12Z
dc.date.available 2014-09-09T07:51:12Z
dc.date.issued 2014-06-13
dc.description The University of Pretoria holds a provisional South African patent (ZA2013/ 06534) relating to the content of the manuscript. No financial benefits have been received by the authors. en_US
dc.description.abstract BACKGROUND: There are several synergistic methods available. However, there is a vast discrepancy in the interpretation of the synergistic results. Also, these synergistic methods do not assess the influence the tested components (drugs, plant and natural extracts), have upon one another, when more than two components are combined. METHODS: A modified checkerboard method was used to evaluate the synergistic potential of Heteropyxis natalensis, Melaleuca alternifolia, Mentha piperita and the green tea extract known as TEAVIGO™. The synergistic combination was tested against the oral pathogens, Streptococcus mutans, Prevotella intermedia and Candida albicans. Inhibition data obtained from the checkerboard method, in the form of binary code, was used to compute a logistic response model with statistically significant results (p < 0.05). This information was used to construct a novel predictive inhibition model. RESULTS: Based on the predictive inhibition model for each microorganism, the oral pathogens tested were successfully inhibited (at 100% probability) with their respective synergistic combinations. The predictive inhibition model also provided information on the influence that different components have upon one another, and on the overall probability of inhibition. CONCLUSIONS: Using the logistic response model negates the need to ‘calculate’ synergism as the results are statistically significant. In successfully determining the influence multiple components have upon one another and their effect on microbial inhibition, a novel predictive model was established. This ability to screen multiple components may have far reaching effects in ethnopharmacology, agriculture and pharmaceuticals. en_US
dc.description.librarian am2014 en_US
dc.description.sponsorship The University of Pretoria and the Gen Foundation. en_US
dc.description.uri http://www.biomedcentral.com/bmccomplementalternmed en_US
dc.identifier.citation Henley-Smith, CJ, Steffens, FE, Botha, FS & Lall, N 2014, 'Predicting the influence of multiple components on microbial inhibition using a logistic response model - a novel approach', BMC Complementary and Alternative Medicine, vol. 14, art. 90, pp. 1-10. en_US
dc.identifier.issn 1472-6882
dc.identifier.other 10.1186/1472-6882-14-190
dc.identifier.uri http://hdl.handle.net/2263/41951
dc.language.iso en en_US
dc.publisher BioMed Central en_US
dc.rights © 2014 Henley-Smith et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License. en_US
dc.subject Synergism en_US
dc.subject Oral pathogens en_US
dc.subject Checkerboard method en_US
dc.subject Heteropyxis natalensis en_US
dc.subject Melaleuca alternifolia en_US
dc.subject Mentha piperita en_US
dc.subject TEAVIGO™ en_US
dc.title Predicting the influence of multiple components on microbial inhibition using a logistic response model - a novel approach en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record