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Optimization of Dopaminergic Neuron Counting in Substantia Nigra of Parkinsonian Mice

机译:帕金森病小鼠黑质中多巴胺能神经元计数的优化

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Parkinson's disease (PD) results from the degeneration of dopaminergic (DA-ergic) neurons of substantia nigra pars compacta (SNc). The disease is modeled in mice by the administration of a neurotoxin precursor l-methyl-4-phenyl-l,2,3,6-tetrahydropyridine (MPTP). Neurotoxin efficiency is estimated by reduced number of DA-ergic neurons in SNc. Cell counting on serial sections is very laborious and expensive and, therefore, is not widely used in spite of its high precision. The well-known Konigsmark's formula (KF) allows one to perform counting on sections chosen with a certain interval rather than to utilize serial sections. However, its precision decreases with increasing interval and other parameters. In this paper, we described the mathematical method of approximation (MA) by improving KF. MA maintains counting precision and allows one to reduce the time and expenses for material processing and analysis. Two groups of C56/BL mice were used in this study. The first group received 8 mg/kg MPTP twicewith a 1-week interval and showed a 20% decrease in the DA-ergic neurons in SNc. The second group received 12 mg/kg MPTP four times with a 2-h interval and showed a 40% decrease in DA-ergic neurons in SNc. Degeneration was obvious mostly within the middle part of SNc in rostracaudal direction and was more apparent in animals exposed to the high neurotoxin dose. Dramatic differences were observed in the number of neurons between sections, which substantially decreased the precision of FK (6% error withcounting in every 5th section), whereas the precision of MA was fairly good (4% error with counting in every 7th section). Thus, we developed anMA that allows one to decrease time and material expenses for estimating the DA-ergic number of cells in SNc of parkinsonian mice.
机译:帕金森氏病(PD)是由黑质致密部(SNc)的多巴胺能(DA能量)神经元变性引起的。通过给予神经毒素前体1-甲基-4-苯基-1,2,3,6-四氢吡啶(MPTP)在小鼠中模拟该疾病。通过减少SNc中DA能神经元的数量来估计神经毒素的效率。在连续切片上进行细胞计数非常费力且昂贵,因此尽管其精度很高,但并未得到广泛使用。著名的Konigsmark公式(KF)允许对以一定间隔选择的部分执行计数,而不是利用串行部分。但是,其精度会随着间隔和其他参数的增加而降低。在本文中,我们描述了通过改进KF的数学近似方法(MA)。 MA保持计数精度,并可以减少材料处理和分析的时间和费用。本研究使用了两组C56 / BL小鼠。第一组以1周的间隔两次接受8 mg / kg MPTP,并在SNc中显示出DA能神经元减少20%。第二组以2小时间隔接受四次12 mg / kg MPTP,SNc中的DA能神经元减少40%。退变主要在鼻尾方向在SNc的中部,在暴露于高神经毒素剂量的动物中更明显。在各节之间的神经元数量上观察到显着差异,这大大降低了FK的精度(每5个节中有6%的错误),而MA的精度相当好(每7个节中有4%的错误)。因此,我们开发了一种可以减少帕金森氏症小鼠SNc中DA能量细胞数量的时间和材料费用的anMA。

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