Analysis of Thoracic Aorta Injury in 27 Road Traffic Accident Deaths.

OBJECTIVES: To analyze the characteristics of thoracic aorta injury in road traffic accidents, to provide data reference for forensic identification. METHODS: The data of 27 traffic accident death cases with thoracic aorta injury were analyzed according to relevant parameters including sex, age, mode of transportation, and thoracic aorta injury. RESULTS: Aortic injury in traffic accidents was significantly more in males than females, and 74.1% cases were in the age range of 31-70 years. The most common mode of transportation was the motorcycle, followed by electric bike, most of which crashed with trucks. Most cases were accompanied by rib fractures and lung injuries. Thoracic aorta injury was the most common in ascending aorta, followed by aortic arch and thoracic aorta. Ascending aorta injury was most likely to occur in the range of 0-<1.6 cm from the aortic valve, while it was rare over 2.6 cm. Taking the aortic valve as the reference, the most common locations of injury were the anterior semilunar valve, followed by the right posterior semilunar valve and the left posterior semilunar valve. Thoracic aortic rupture occurred in 63.0% cases, and intima and media lacerations only occurred in 37.0% cases. A few deceased had aortic diseases. CONCLUSIONS: The proximal part of the ascending aorta is prone to be injured because of the large external force of traffic accidents. The medical examiner should carefully examine the aortic injury in traffic accident deaths, and evaluate the relationship between the injury and the disease according to the condition and degree of aortic injury.

[A Feasibility Study on the Discrimination of the Propolis Varieties Based on Near Infrared Spectroscopy].

Botanical origins of propolis are significant factors affecting biological and pharmacological activities because of different components in propolis. Until now, the determination of propolis botanical origins is mainly based on different varieties and the content of the compositions with great limitations. Therefore, it is important to discriminate different botanical origins of propolis quickly and accurately. In this study, Near-infrared (NIR) spectra of propolis varieties based on principal component analysis mahalanobis distance (PCA-mahalanobis distance) model and canonical discriminant analysis model were built for the classification of three botanical origins (poplar propolis，brich propolis and rubber propolis). The models were built based on the optimal pretreatment method and bands of first derivative + Savitzky-Golay (7) filter and 4500~12 000-1, which were selected in advance. After the principal component analysis, the correct classification rates of calibration sets and validation sets in analysis mahalanobis distance models were 93.62% and 82.61%, respectively. The discrimination rate and the cross-validation rate of canonical discrimination models were 91.4% and 88.6%, respectively. Therefore, NIR spectroscopy with chemometric methods is not only feasible but also practical for rapid and accurate identification of varieties of propolis.

[Application of inductively coupled plasma mass spectrometry with chemometric methods in classification of honeys according to their types].

In order to identify honeys according to their floral origin, inductively coupled plasma mass spectrometry (ICP-MS) combined with principal component analysis (PCA) and discriminant analysis (DA) were employed in the present study. Three kinds of honeys such as acacia honey samples, sunflower honey samples and rape honey samples were selected. It was pretreated by wet-acid digestionand measured 20 kinds of mineral elements in honey samples by ICP-MS. The result showed that the accuracy of the inductively coupled plasma mass spectrometrymeted the requirements. The result of principal component analysis demonstrated that the acacia honey samples were performed a trend of certain gather. The trend of the sunflower honey samples and the rape honey samples are not obvious. Ten kinds of mineral elements including Na, Mg, K, Ca, Sr, Ba, V, Fe, Ni, Sb can be regarded as honey varieties of characteristic elements. Seven kinds of mineral elements such as Mg, Sr, Ba, Sb, Ni, Cr and Na could be selected through stepwise discriminant analysis. Using bayes discriminant analysis, A linear discriminant function can be recieved. The discrimination rate of honey samples such as acacia honey samples, sunflower samples and rape honey samples were 100%, 80% and 90. 9% respectively. Two sunflower honey samples was misclassified into rape honey samples an-done rape honey samples are also misclassified into acacia honey sample. The total rate of discriminant model cross validation was 90. 3%. It is concluded that the mineral elements in honey varieties with good classification. The present study can provide theoretical basis and the relationship between thetypes of honey samples with mineral elements. The method what this study used had simple, accurate and stablecharacteristics, which can be used as a reliable method of honey sample identification.