...
首页> 外文期刊>American Journal of Analytical Chemistry >Evaluation of Fourier Transform Infrared Spectroscopy for Diagnosis of Peroxisomal Diseases with Abnormal Very-Long-Chain Fatty Acid Metabolism
【24h】

Evaluation of Fourier Transform Infrared Spectroscopy for Diagnosis of Peroxisomal Diseases with Abnormal Very-Long-Chain Fatty Acid Metabolism

机译:傅里叶变换红外光谱法在超长链脂肪酸代谢异常的过氧化物酶体疾病诊断中的评价

获取原文

摘要

Very long chain fatty acids (VLCFAs) are accumulated in cells and blood in patients with peroxisomal diseases, such as adrenoleukodystrophy (ALD) and Zellwger Syndrome (ZS). The purpose of this study is to investigate usefulness of Fourier transform infrared spectroscopy (FTIR) with attenuated total reflection (ATR) analysis method for clinical diagnosis of those diseases, thereby we measured the infrared spectra of the sera of patients and healthy controls. Correlation coefficients between 2nd derivative FTIR spectra of the serum samples and the VLCFA content ratio which is used as a clinical parameter to date were comprehensively calculated to investigate which wavenumber showed high correlation with the VLCFA ratio. Multiple regression analysis using the serum FTIR spectra showed that high correlations were observed with VLCFA ratios (C26:0/C22:0 ratio), and we could construct a suitable regression model (R2 = 0.97, p ﹣19). In addition, the model system using various VLCFAs in newborn bovine serum also showed that several FTIR peaks in 800 ~ 900 cm﹣1 region were found to have good correlation with VLCFA ratios. Our results support that FTIR analysis is useful for diagnosis of peroxisomal diseases.
机译:过氧化物酶体疾病,例如肾上腺皮质营养不良(ALD)和Zellwger综合征(ZS),患者的细胞和血液中会积聚非常长的脂肪酸(VLCFA)。这项研究的目的是研究具有衰减全反射(ATR)分析方法的傅里叶变换红外光谱(FTIR)在这些疾病的临床诊断中的用途,从而我们测量了患者和健康对照者血清的红外光谱。全面计算了血清样品的二阶FTIR光谱与迄今为止用作临床参数的VLCFA含量比之间的相关系数,以研究哪个波数与VLCFA比值具有高度相关性。使用血清FTIR光谱进行的多元回归分析表明,与VLCFA比率(C26:0 / C22:0比率)具有高度相关性,我们可以构建一个合适的回归模型(R2 = 0.97,p p19)。此外,在新生牛血清中使用各种VLCFA的模型系统还显示,在800〜900 cm﹣1区域中发现了几个FTIR峰与VLCFA比率具有良好的相关性。我们的结果支持FTIR分析可用于诊断过氧化物酶体疾病。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号