Chronoprints: Identifying Samples by Visualizing How They Change over Space and Time

Chronoprints: Identifying Samples by Visualizing How They Change over Space and Time
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Chronoprints:通过可视化样本随空间和时间的变化来识别样本

DOI:
10.1021/acscentsci.8b00860
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发表时间:
2019
影响因子:
18.2
通讯作者:
Grover, William H.
Grover, William H.
中科院分区:
化学1区
文献类型:
--
作者:
McKenzie, Brittney A.;Robles-Najar, Jessica;Duong, Eric;Brisk, Philip;Grover, William H.

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现代化学工具擅长识别样品,但这些仪器的成本,尺寸,复杂性和功耗通常使其无法在资源有限的环境中使用。在这项工作中,我们展示了一个简单的和低成本的方法,用于识别一个样本的基础上可视化的样本如何在空间和时间上的变化,以响应扰动。可以使用不同类型的扰动,在这个概念验证中,我们使用动态温度梯度,以不同的速率快速冷却样品的不同部分。我们首先将几个样品加载到“微流体温度计芯片”上的长平行通道中。然后,我们将芯片的一端浸入液氮中,沿着通道沿着产生动态温度梯度,我们使用一个便宜的USB显微镜来记录样品如何响应变化的温度梯度的视频。然后将视频转换为几个位图图像(每个样本一个),这些图像捕获每个样本对空间(y轴;沿动态温度梯度的沿着距离)和时间(x轴)扰动的响应;我们将这些图像称为每个样本的“时间指纹”或“时间指纹”。如果两个样品的时间印记相似,这表明样品是相同的化学物质或混合物,但如果两个样品的时间印记显著不同,这证明样品的化学性质不同。由于计时打印只是位图图像,因此可以使用计算机科学中的各种技术进行比较,在这项工作中,我们使用三种不同的图像比较算法来量化计时打印相似性。为了展示计时打印的多功能性,我们将其用于三种不同的应用:辨别真假橄榄油(超过100亿美元的全球食品欺诈问题的一个例子),识别掺假或假冒药物(约占低收入和中等收入国家所有药物的10%),以及区分偶尔混淆的药物成分甘油和二甘醇(其意外或故意的替代已导致数百人死亡)。计时打印的简单性和多功能性应该使它们成为各种不同领域的宝贵分析工具。
The modern tools of chemistry excel at identifying a sample, but the cost, size, complexity, and power consumption of these instruments often preclude their use in resource-limited settings. In this work, we demonstrate a simple and low-cost method for identifying a sample based on visualizing how the sample changes over space and time in response to a perturbation. Different types of perturbations could be used, and in this proof-of-concept we use a dynamic temperature gradient that rapidly cools different parts of the sample at different rates. We accomplish this by first loading several samples into long parallel channels on a “microfluidic thermometer chip.” We then immerse one end of the chip in liquid nitrogen to create a dynamic temperature gradient along the channels, and we use an inexpensive USB microscope to record a video of how the samples respond to the changing temperature gradient. The video is then converted into several bitmap images (one per sample) that capture each sample’s response to the perturbation in both space (they-axis; the distance along the dynamic temperature gradient) and time (thex-axis); we call these images “chronological fingerprints” or “chronoprints” of each sample. If two samples’ chronoprints are similar, this suggests that the samples are the same chemical substance or mixture, but if two samples’ chronoprints are significantly different, this proves that the samples are chemically different. Since chronoprints are just bitmap images, they can be compared using a variety of techniques from computer science, and in this work we use three different image comparison algorithms to quantify chronoprint similarity. As a demonstration of the versatility of chronoprints, we use them in three different applications: distinguishing authentic olive oil from adulterated oil (an example of the over $10 billion global problem of food fraud), identifying adulterated or counterfeit medication (which represents around 10% of all medication in low- and middle-income countries), and distinguishing the occasionally confused pharmaceutical ingredients glycerol and diethylene glycol (whose accidental or intentional substitution has led to hundreds of deaths). The simplicity and versatility of chronoprints should make them valuable analytical tools in a variety of different fields.
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