Efficacious rat model displays non-toxic effect with Korean beechwood creosote: a possible antibiotic substitute.

Wood creosote, an herbal anti-diarrheal and a mixture of major volatile compounds, was tested for its non-toxicological effects, using a rat model, with the objective to use the creosote as an antibiotic substitute. A total of 30 Sprague-Dawley rats were studied to form five groups with 6 rats each. Korea beechwood creosote was supplemented into three test groups with 0.03 g/kg, 0.07 g/kg and 0.1 g/kg body weight/day without antibiotic support, along with a positive control of Apramycin sulphate (at 0.5% of the daily feed) and a negative control. Korean beechwood creosote supplementation showed no negative effect on the body weight gain in comparison to the negative and the positive control groups and the feed conversion ratio was also comparable with that of the control groups. The clinical pathology parameters studied were also under the umbrella of normal range, including liver specific enzymes, blood glucose, total protein, blood urea nitrogen (BUN), which indicated no toxic effect of creosote at the given doses. The non-hepatotoxic effect was also confirmed using hepatic damage specific molecular markers like Tim-p1, Tim-p2 and Tgf-ß1. The results suggested that Korean beechwood may be used as antibiotic substitute in weanling pigs feed without any toxic effect on the body. Although the antimicrobial properties of creosote were not absolutely similar to those of apramycin sulphate, they were comparable.

Incorporating interaction terms in multivariate linear regression for post-event flood waste estimation.

Multivariate linear regression methodology has been conceived as a viable technique in flood waste estimation. The fundamental assumption of the conventional flood waste model, independence between input variables, may not work in reality. As an alternative, we evaluated the effectiveness of including interaction terms in flood waste modeling. The secondary objectives include to suggest the strategy in flood waste mitigation and to explore a plausible explanation to the modeling results. In the scheme of model development and assessment, ninety flood cases in South Korea were statistically analyzed. Input variables for regression analysis were selected from available datasets in the national disaster information system and the selected variables were flood damage variables used to quantify the amount of flood waste. According to the results, incorporating the interaction terms improved the estimation accuracy of the model. The single-variable sensitivity analysis revealed that mitigating damage to rivers and croplands would most efficiently reduce potential flood waste generation. The interaction terms appeared to compensate for the over/underestimated waste amounts by single terms, and they explained the nonlinear response of waste generation. Observations made throughout the field survey revealed that the nonlinear and interactive pattern of flood waste generation corresponded to the results from the regression analysis. In a practical aspect, incorporating the interaction terms would be an effective method to enhance the flood waste estimation model without costly works for further variables exploration.