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极低频电磁场可以改变大脑脂质的构成 | BMC Neuroscience |
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论文标题:Extremely low frequency electromagnetic field exposure and restraint stress induce changes on the brain lipid profile of Wistar rats
期刊:
作者:Jesús Martínez-Sámano, Alan Flores-Poblano, Leticia Verdugo-Díaz, Marco Antonio Juárez-Oropeza and Patricia V. Torres-Durán
发表时间:2018/05/21
数字识别码:10.1186/s12868-018-0432-1
原文链接:
微信链接:
大脑脂质在结构、功能和代谢等方面具有多种功能,约占脑组织干重的一半重量。大脑中存在脂肪酸和胆固醇,这些脂肪酸是饱和或不饱和的长链一元羧酸;其中最普遍的不饱和脂肪酸家族是n-3,n-6和n-9系列,并且含有一些不常见的脂肪酸如极长链脂肪酸。脂肪酸能够与其他化合物结合形成甘油磷脂和鞘脂。这些脂质在脑生理方面具有重要作用,例如,参与跨膜的信号转导,脂筏的形成,以及将细胞膜锚定至细胞外基质。此外,脂质还能与蛋白质共价偶联,将标记蛋白锚定在膜内。
胆固醇和磷脂是生物膜的主要成分。膜脂含量的变化通常与脂质稳态的失衡有关。 在中枢神经系统(CNS)中,脂质失衡会导致功能的改变,从而引起多种疾病:如阿尔茨海默病、亨廷顿病和帕金森病。
应激是通过由应激因子诱导产生的一些生理和适应性应答来调节稳态的过程。下丘脑 - 垂体 - 肾上腺(HPA)轴和自主神经系统能分别增强血浆中的应激激素和糖皮质激素/儿茶酚胺。 此外,应激也会引起大脑深层次的变化。已有研究显示,慢性应激与一些氧化参数的提升密切相关,例如,蛋白和脂质过氧化的提升,以及皮层、海马和小脑中抗氧化酶的活性增加。然而,目前还没有对脑脂质的应激效应进行过全面的阐述。
如今,电磁场日益渗透着我们的日常生活,越来越多的人开始关注这种非电离辐射的潜在不利影响;其中属极低频电磁场(ELF-EMF)最为瞩目。在发表于BMC Neuroscience上的一篇文章中,作者探讨了极低频电磁场和应激抑制对Wistar大鼠大脑脂质构成的影响。虽然作者还不清楚ELF-EMF对生物系统具体有什么影响,但是鉴于某些脑癌和情绪障碍的高发生率,还是能在一些流行病学研究中窥见它的一些效应。最近的研究发现,ELF-EMF可能通过活性氧簇的作用在脑中产生氧化效应。一些研究者认为ELF-EMF是一种轻度应激源,并且对其相关的效应进行了综合阐述。本研究的目的是评估慢性极低频电磁场(ELF-EMF)、限制应激(RS)或这两者(RS + ELF-EMF)的共同作用对Wistar大鼠皮层、小脑和皮层下结构中的脂质谱和脂质过氧化状态的影响。
研究人员将24只年轻雄性Wistar大鼠分成4组:对照组,RS组,ELF-EMF组和RS + ELF-EMF组,各组均处理21天。处理后,对大鼠实施安乐死,取血液用于定量血浆皮质酮浓度,解剖获得皮质、小脑和皮质下结构,用于分析胆固醇、三酰甘油、总游离脂肪酸和硫代巴比妥酸反应性物质(TBARS)。此外,还利用气相色谱鉴定了脂肪酸甲酯(FAME)的含量。
实验发现,在RS和ELF-EMF组中血浆皮质酮值均有所升高(p <0.05),这种效应在RS + ELF-EMF组中更为明显(相对于对照组p <0.05)。
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图2. 慢性暴露于EMF和RS对血浆皮质酮的影响。结果是每组6只动物的平均值±SD(与C组相比* p <0.05,与RS组相比#p <0.05)
慢性ELF-EMF提升了小脑中总脂质和皮质中总胆固醇的水平,但降低了皮质中的极性脂质。在皮质下结构中, RS + ELF-EMF组的非酯化脂肪酸浓度增加。
FAME分析显示,在ELF-EMF组大鼠中,多不饱和脂肪酸在小脑中减少但在皮层下结构中增加。与对照组相比,所有处理组的脂质中TBARS浓度都有所增加,这在皮质和小脑区域中尤为明显。
图3. 结果是每组6只动物的平均值±SD。 总脂质,相对于对照组:** p <0.01、相对于RS和RS + EMF组:* p <0.05、相对于C组:p <0.05、相对于RS和EMF组:#p <0.05;总胆固醇和极性脂质,相对于照组:* p <0.05、相对于RS组:p <0.05;NEFAS,相对于对照组:p <0.01、相对于RS和EMF组:#p <0.05。
本研究中发现的变化与前人的手机版一致,表明了慢性应激对脑脂质代谢的影响,长期暴露于ELF-EMF环境能产生与生理应激相似的效应,诱导脑脂质谱发生变化。
摘要:
Background
Exposure to electromagnetic fields can affect human health, damaging tissues and cell homeostasis. Stress modulates neuronal responses and composition of brain lipids. The aim of this study was to evaluate the effects of chronic extremely low frequency electromagnetic field (ELF-EMF) exposure, restraint stress (RS) or both (RS + ELF-EMF) on lipid profile and lipid peroxidation in Wistar rat brain.
Methods
Twenty-four young male Wistar rats were allocated into four groups: control, RS, ELF-EMF exposure, and RS + ELF-EMF for 21 days. After treatment, rats were euthanized, the blood was obtained for quantitate plasma corticosterone concentration and their brains were dissected in cortex, cerebellum and subcortical structures for cholesterol, triacylglycerols, total free fatty acids, and thiobarbituric acid reactive substances (TBARS) analysis. In addition, fatty acid methyl esters (FAMEs) were identified by gas chromatography.
Results
Increased values of plasma corticosterone were found in RS and ELF-EMF exposed groups (p < 0.05), this effect was higher in RS + ELF-EMF group (p < 0.05, vs. control group). Chronic ELF-EMF exposure increased total lipids in cerebellum, and total cholesterol in cortex, but decreased polar lipids in cortex. In subcortical structures, increased concentrations of non-esterified fatty acids were observed in RS + ELF-EMF group. FAMEs analysis revealed a decrease of polyunsaturated fatty acids of cerebellum and increases of subcortical structures in the ELF-EMF exposed rats. TBARS concentration in lipids was increased in all treated groups compared to control group, particularly in cortex and cerebellum regions.
Conclusions
These findings suggest that chronic exposure to ELF-EMF is similar to physiological stress, and induce changes on brain lipid profile.
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期刊介绍:
BMC Neuroscience (, 2.173 - 2.756 - ) is an open access, peer-reviewed journal that considers articles on all aspects of the nervous system, including molecular, cellular, developmental and animal model studies, as well as cognitive and behavioral research, and computational modeling.
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