Zakrzewska Helena, Machoy-Mokrzyńska Anna, Materny Maria, Gutowska Izabela, Machoy Zygmunt
Department of Biochemistry, Agriculture Academy, Szczecin, Poland.
Arch Oral Biol. 2005 Mar;50(3):309-16. doi: 10.1016/j.archoralbio.2004.08.012.
Animals from areas contaminated by industrial emissions containing fluoride may accumulate it predominantly in hard tissues. Therefore, an analysis was performed for the determination of fluoride content in mandibles and teeth of deer living at large in different areas in Western Pomerania (Poland). Samples of hard tissues obtained with a dental drill, were dissolved in perchloric acid and analyzed for fluoride content with an ion-selective electrode. Using the Generalized Regression Neural Network (GRNN), it was possible to arrange definite variables according to their order of importance concerning the fluoride mean content in investigated bone material. Parametric analysis revealed in which sites of mandibles and teeth the fluoride accumulation was the highest. In our calculation, the traditional statistic as well as artificial neural network was applied.
One of the interesting properties of fluoride is its balancing accumulation in the hard and soft tissues. In this paper, we decided estimate how the changeable doses of fluoride in natural environment influence on fluoride distribution and accumulation in the examined sites of mandible and teeth.
The material consist of 103 mandibles of red deer (Cervus elaphus L.) from five forestry districts of Western Pomerania in Poland, which are located near or far away from two major industrial plants: Police Chemical Work and the Dolna Odra Coal Power Plant. Samples (10 mg of powdered bone or tooth) were dissolved in perchloric acid and the fluoride content was determined with an ion-selective electrode. Comparisons were done with the Statistica 5.5 and Statistica Neural Networks.
Animals living in Western Pomerania (Poland) have high fluoride contents in their bones. Fluoride accumulation in mandibles and teeth is irregular. The higher content of fluoride show incisal area, but coronoid process of the mandible was not sensitive to different exposure of environmental fluoride at all. Parametric analysis revealed that the accumulation pattern of fluorine was different in the two groups of deer.
Many biological and environmental factors may influence on incessant fluoride accumulation in osseous tissue of ruminants living at large. The use of artificial neural networks enables a more accurate insight into the process of fluorine accumulation in the mandible and teeth and helps in the ranking of factors influencing this process.
来自受含氟工业排放物污染地区的动物,可能主要在硬组织中蓄积氟。因此,对生活在波兰西波美拉尼亚不同地区的野生鹿的下颌骨和牙齿中的氟含量进行了分析测定。用牙钻获取的硬组织样本溶解于高氯酸中,并用离子选择性电极分析氟含量。使用广义回归神经网络(GRNN),可以根据各变量对所研究骨材料中氟平均含量的重要性顺序对其进行排列。参数分析揭示了下颌骨和牙齿的哪些部位氟蓄积量最高。在我们的计算中,应用了传统统计学方法以及人工神经网络。
氟的一个有趣特性是它在硬组织和软组织中的平衡蓄积。在本文中,我们决定评估自然环境中可变剂量的氟如何影响下颌骨和牙齿检测部位的氟分布和蓄积。
材料包括来自波兰西波美拉尼亚五个林区的103个马鹿(Cervus elaphus L.)下颌骨,这些林区距离两个主要工厂——波利斯化学工厂和下奥得拉煤矿发电厂——或近或远。样本(10毫克骨粉或牙粉)溶解于高氯酸中,并用离子选择性电极测定氟含量。使用Statistica 5.5和Statistica神经网络进行比较。
生活在波兰西波美拉尼亚的动物骨骼中氟含量较高。下颌骨和牙齿中的氟蓄积不规则。切牙区氟含量较高,但下颌骨的冠突对环境氟的不同暴露根本不敏感。参数分析表明,两组鹿的氟蓄积模式不同。
许多生物和环境因素可能影响野生反刍动物骨组织中氟的持续蓄积。使用人工神经网络能够更准确地洞察氟在下颌骨和牙齿中的蓄积过程,并有助于对影响该过程的因素进行排序。