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Infrared spectroscopy: A new diagnostic tool in Alzheimer disease.

机译:红外光谱:阿尔茨海默病的新诊断工具。

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摘要

Biological markers play an evolving role in the diagnosis of Alzheimer disease (AD). We compare conventional measurements of cerebrospinal fluid (CSF) tau and beta-amyloid(1-42) proteins to a novel approach - Fourier transformed infrared (FT-IR) spectroscopy - a simple technique derived from chemical and physical sciences that characterizes intramolecular bonds. For automatic diagnostic analysis, we developed an artificial neural network (ANN). We examined 71 patients with a clinical diagnosis of AD and 66 controls. beta-Amyloid(1-42) was decreased (sensitivity 80% and specificity 78%); tau was elevated (sensitivity 76% and specificity 88%) in CSF of AD patients. The combined tau/beta-amyloid(1-42) quotient was able to distinguish healthy from diseased subjects with 99% sensitivity and 86% specificity. The ANN could separate FT-IR spectroscopy data with 88.5% sensitivity and 80% specificity. FT-IR spectroscopy proved to be cost-effective and simple to perform. Diagnostic sensitivity and specificity is in the range of CSF tau and beta-amyloid(1-42) protein analysis. Larger sample numbers for ANN training and validation could increase diagnostic accuracy and thus prove to be a useful screening tool.
机译:生物标志物在阿尔茨海默病(AD)的诊断中起着不断发展的作用。我们将传统测量的脑脊液(CSF)tau和β-淀粉样蛋白(1-42)蛋白与一种新方法-傅立叶变换红外(FT-IR)光谱法-一种从化学和物理科学衍生而来的简单技术来表征分子内键。对于自动诊断分析,我们开发了人工神经网络(ANN)。我们检查了71名临床诊断为AD的患者和66名对照。 β-淀粉样蛋白(1-42)降低(敏感性80%,特异性78%); AD患者的CSF中tau升高(敏感性76%,特异性88%)。 tau /β-淀粉样蛋白(1-42)的组合商能够以99%的敏感性和86%的特异性区分健康人和患病受试者。人工神经网络可以以88.5%的灵敏度和80%的特异性分离FT-IR光谱数据。 FT-IR光谱证明具有成本效益,并且易于执行。诊断敏感性和特异性在CSF tau和β-淀粉样蛋白(1-42)蛋白分析范围内。用于ANN训练和验证的更大样本数量可以提高诊断准确性,因此被证明是一种有用的筛选工具。

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