Quality Evaluation of Traditional Chinese Medicine Mylabris Based on Heavy Metal Risk Assessment and Analysis of Pharmacological Component Contents

As a highly representative traditional Chinese anti-tumor medicinal material, the biomass of Mylabris is collected from the wild. However, the living environments of Mylabris is differ, so Mylabris may be contaminated by heavy metal pollution depending on the environment. These environments may also affect the amount of biosynthesis of its medicinal ingredient, cantharidin, there by affecting the quality of Mylabris. In this study, we determined the heavy metal content in Mylabris from different origins by using ICP-MS, evaluated the risk posed by these heavy metals, and recommended theoretical maximum limits of heavy metals in medicinal Mylabris. The results show that the Cu content in Mylabris is substantially higher than that in Cr, As, Pb, Cd, and Hg. A quantitative risk assessment showed that Mylabris poses no noncarcinogenic risks. The results of the total carcinogenic risk value showed that origins S12 and S13 pose carcinogenic risk by Cr and As, and the rest of the origins were in the human-tolerable carcinogenic risk range. We found large differences in the cantharidin content in Mylabris from different origins. In general, the Mylabris from origins S2, S3 and S4 had a higher in vivo cantharidin content, which proved that the quality of the medicinal materials was higher here than in other production areas. Finally, we providing a reference for the quality evaluation of medicinal Mylabris materials.     

Robust Clustering Using Exponential Power Mixtures

Summary Clustering is a widely used method in extracting useful information from gene expression data, where unknown correlation structures in genes are believed to persist even after normalization. Such correlation structures pose a great challenge on the conventional clustering methods, such as the Gaussian mixture (GM) model, k‐means (KM), and partitioning around medoids (PAM), which are not robust against general dependence within data. Here we use the exponential power mixture model to increase the robustness of clustering against general dependence and nonnormality of the data. An expectation–conditional maximization algorithm is developed to calculate the maximum likelihood estimators (MLEs) of the unknown parameters in these mixtures. The Bayesian information criterion is then employed to determine the numbers of components of the mixture. The MLEs are shown to be consistent under sparse dependence. Our numerical results indicate that the proposed procedure outperforms GM, KM, and PAM when there are strong correlations or non‐Gaussian components in the data.     

Intensified rainfall in the wet season alters the microbial contribution to soil carbon storage

Plant and Soil - Precipitation patterns in the tropics of southern China are predicted to change with an increase of the rainfall in the wet season (WW) and a delay of the wet season into autumn...     

五个猕猴桃种的皮孔、气孔器和叶片下表皮微观特征

为了探讨不同种类猕猴桃皮孔、气孔器和叶片下表皮特征的差异及其分类学意义,该文利用光学显微镜观察五个猕猴桃种共计9份样品材料的一年生枝条韧皮部上皮孔的形态,结果发现供试猕猴桃皮孔呈长椭圆形或长梭形,不同种皮孔的长×宽、皮孔密度、皮孔面积和皮孔面积的百分比值存在差异但与种类划分无明显规律,皮孔的宽可明显区分所选4个中华猕猴...     

Assessment of body mapping sportswear using a manikin operated in constant temperature mode and thermoregulatory model control mode

Regional sweating patterns and body surface temperature differences exist between genders. Traditional sportswear made from one material and/or one fabric structure has a limited ability to provide athletes sufficient local wear comfort. Body mapping sportswear consists of one piece of multiple knit structure fabric or of different fabric pieces that may provide athletes better wear comfort. In this study, the ‘modular’ body mapping sportswear was designed and subsequently assessed on a ‘Newton’ type sweating manikin that operated in both constant temperature mode and thermophysiological model control mode. The performance of the modular body mapping sportswear kit and commercial products were also compared. The results demonstrated that such a modular body mapping sportswear kit can meet multiple wear/thermal comfort requirements in various environmental conditions. All body mapping clothing (BMC) presented limited global thermophysiological benefits for the wearers. Nevertheless, BMC showed evident improvements in adjusting local body heat exchanges and local thermal sensations.     

Effect of temperature difference between manikin and wet fabric skin surfaces on clothing evaporative resistance: how much error is there?

Clothing evaporative resistance is one of the inherent factors that impede heat exchange by sweating evaporation. It is widely used as a basic input in physiological heat strain models. Previous studies showed a large variability in clothing evaporative resistance both at intra-laboratory and inter-laboratory testing. The errors in evaporative resistance may cause severe problems in the determination of heat stress level of the wearers. In this paper, the effect of temperature difference between the manikin nude surface and wet textile skin surface on clothing evaporative resistance was investigated by both theoretical analysis and thermal manikin measurements. It was found that the temperature difference between the skin surface and the manikin nude surface could lead to an error of up to 35.9% in evaporative resistance of the boundary air layer. Similarly, this temperature difference could also introduce an error of up to 23.7% in the real clothing total evaporative resistance (R _{et_real}  < 0.1287 kPa m²/W). Finally, it is evident that one major error in the calculation of evaporative resistance comes from the use of the manikin surface temperature instead of the wet textile fabric skin temperature.