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基于动态纳米粒子的柔性传感器:从呼气中诊断卵巢癌。

Dynamic Nanoparticle-Based Flexible Sensors: Diagnosis of Ovarian Carcinoma from Exhaled Breath.

机构信息

Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology , Haifa 3200003, Israel.

Gynecological Oncology and Surgery Unit, Carmel Medical Center , Haifa 3436212, Israel.

出版信息

Nano Lett. 2015 Oct 14;15(10):7023-8. doi: 10.1021/acs.nanolett.5b03052. Epub 2015 Sep 11.

Abstract

Flexible sensors based on molecularly modified gold nanoparticles (GNPs) were integrated into a dynamic cross-reactive diagnostic sensing array. Each bending state of the GNP-based flexible sensor gives unique nanoparticle spatial organization, altering the interaction between GNP ligands and volatile organic compounds (VOCs), which increases the amount of data obtainable from each sensor. Individual dynamic flexible sensor could selectively detect parts per billion (ppb) level VOCs that are linked with ovarian cancers in exhaled breath and discriminate them from environmental VOCs that exist in exhaled breath samples, but do not relate to ovarian cancer per se. Strain-related response successfully discriminated between exhaled breath collected from control subjects and those with ovarian cancer, with data from a single sensor being sufficient to obtain 82% accuracy, irrespective of important confounding factors, such as tobacco consumption and comorbidities. The approach raises the hope of achieving an extremely simple, inexpensive, portable, and noninvasive diagnostic procedure for cancer and other diseases.

摘要

基于分子修饰金纳米粒子 (GNPs) 的柔性传感器被集成到一个动态交叉反应诊断传感阵列中。基于 GNP 的柔性传感器的每个弯曲状态都赋予独特的纳米粒子空间组织,改变 GNP 配体与挥发性有机化合物 (VOCs) 之间的相互作用,从而增加每个传感器可获得的数据量。单个动态柔性传感器可以选择性地检测与呼出气体中的卵巢癌相关的十亿分之几 (ppb) 水平的 VOCs,并将其与存在于呼出气体样本中的环境 VOCs 区分开来,而这些环境 VOCs本身与卵巢癌无关。与应变相关的响应成功地区分了来自对照组和卵巢癌患者的呼出气体,单个传感器的数据足以获得 82%的准确率,而不管重要的混杂因素,如吸烟和合并症。该方法有望实现一种极其简单、廉价、便携和非侵入性的癌症和其他疾病诊断程序。

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