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The Use of Signal-Transduction and Metabolic Pathways to Predict Human Disease Targets from Electric and Magnetic Fields Using in vitro Data in Human Cell Lines

机译:利用信号转导和代谢途径利用人体细胞系中的体外数据从电场和磁场预测人类疾病靶标

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摘要

Using in vitro data in human cell lines, several research groups have investigated changes in gene expression in cellular systems following exposure to extremely low frequency (ELF) and radiofrequency (RF) electromagnetic fields (EMF). For ELF EMF, we obtained five studies with complete microarray data and three studies with only lists of significantly altered genes. Likewise, for RF EMF, we obtained 13 complete microarray datasets and 5 limited datasets. Plausible linkages between exposure to ELF and RF EMF and human diseases were identified using a three-step process: (a) linking genes associated with classes of human diseases to molecular pathways, (b) linking pathways to ELF and RF EMF microarray data, and (c) identifying associations between human disease and EMF exposures where the pathways are significantly similar. A total of 60 pathways were associated with human diseases, mostly focused on basic cellular functions like JAK–STAT signaling or metabolic functions like xenobiotic metabolism by cytochrome P450 enzymes. ELF EMF datasets were sporadically linked to human diseases, but no clear pattern emerged. Individual datasets showed some linkage to cancer, chemical dependency, metabolic disorders, and neurological disorders. RF EMF datasets were not strongly linked to any disorders but strongly linked to changes in several pathways. Based on these analyses, the most promising area for further research would be to focus on EMF and neurological function and disorders.
机译:利用人体细胞系中的体外数据,几个研究小组研究了细胞系统在暴露于极低频(ELF)和射频(RF)电磁场(EMF)后的基因表达变化。对于ELF EMF,我们获得了五项具有完整微阵列数据的研究,以及三项仅具有明显改变的基因列表的研究。同样,对于RF EMF,我们获得了13个完整的微阵列数据集和5个有限的数据集。使用三步过程确定了暴露于ELF和RF EMF与人类疾病之间的合理联系:(a)将与人类疾病类别相关的基因链接到分子途径,(b)将途径链接到ELF和RF EMF微阵列数据,以及(c)找出途径明显相似的人类疾病与EMF暴露之间的关联。共有60种与人类疾病相关的途径,主要集中在基本细胞功能(如JAK–STAT信号转导)或代谢功能(如细胞色素P450酶的异源代谢)。 ELF EMF数据集偶尔与人类疾病相关,但没有明确的模式出现。各个数据集显示出与癌症,化学依赖性,代谢紊乱和神经系统疾病有一定联系。 RF EMF数据集与任何疾病均不密切相关,但与几种途径的变化均密切相关。基于这些分析,最有希望进行进一步研究的领域将集中在EMF和神经功能与疾病上。

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