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Modelling a Mixture of Diabetes Mellitus Herbal Treatment

机译:模拟糖尿病草药治疗的混合物

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Mixture designs are special cases of response surface designs with prediction and optimization as the main goals. When using a mixture of herbs, the most desirable interactions are those that can result in additional therapeutic benefits. The combined effect of the herbs can either be synergistic or antagonistic. In this study, a mixture experiment was set up involving three herbs: Cinnamomum verum, Azadirachta indica and Gymnema sylvestre that have been known to singly lower blood sugar level.The aim of the study was to obtain a prediction model for the change in blood sugar level resulting from given proportions of the three herbal components in the mixture. A simplex centroid design was employed in this experiment. The data obtained was divided into two sets: train data that took 75% and test data that formed the remaining 25% of the original data. The test data was used to fit a special cubic Scheffé model and the test data was used for testing the fitted model. R statistical software was used to analyse the data. The seven term special cubic model fitted the data fairly well but the tertiary blend was not statistically significant. The model was thus reduced to a six term model that was more suitable for prediction. The single herbs caused significant reduction in blood sugar level. However, the binary and tertiary blends had antagonistic activity. This study recommends that mixture experiments be used as a means to investigate reinforcement and counteraction effects among combined herbs.
机译:混合物设计是响应面设计的特殊情况,具有预测和优化作为主要目标。当使用草药的混合物时,最期望的相互作用是可能导致额外治疗益处的相互作用。草药的综合作用可以是协同或拮抗的。在这项研究中,建立了一种混合物实验,涉及三种草药:肉桂瘤,Azadirachta indica和Gymnema Sylvestre,已知为单独降低血糖水平。该研究的目的是获得血糖变化的预测模型给出了混合物中三种草药组分的比例所产生的水平。本实验中使用了单纯形质心设计。获得的数据分为两组:培训数据,培养75%并测试数据,该数据形成剩余的25%的原始数据。测试数据用于符合特殊的立方Scheffé模型,并且测试数据用于测试拟合模型。 R统计软件用于分析数据。七个术语特殊立方模型相当好,但第三次混合物没有统计学意义。因此,该模型降低到更适合于预测的六个术语模型。单一草药造成血糖水平的显着降低。然而,二元和三级混合物具有拮抗活性。本研究建议使用混合物实验作为研究组合草药之间的增强和反应效应的手段。

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