Fang Cheng, Awoyemi Olalekan Simon, Luo Yunlong, Naidu Ravi
Global Centre for Environmental Remediation (GCER), University of Newcastle, Callaghan, NSW 2308, Australia.
Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE), University of Newcastle, Callaghan, NSW 2308, Australia.
Environ Health (Wash). 2023 Jun 21;1(1):63-71. doi: 10.1021/envhealth.3c00051. eCollection 2023 Jul 21.
Most teenagers experience orthodontic treatment, but we do not know the possible adverse effect of the released microplastics and nanoplastics that are recently categorized as emerging contaminants. Herein, we test the rubber band that has been employed to improve the biting of teeth during the orthodontic process to confirm the release of microplastics and nanoplastics. We improve the characterization of microplastics and nanoplastics by (i) Raman imaging, to extract and map the signal from the scanning spectrum matrix or the hyperspectral matrix and to enhance the signal-to-noise ratio statistically. To effectively extract the signal, (ii) chemometrics such as principal component analysis (PCA) are explored to convert the hyperspectral matrix to an image with an increased certainty. The nonsupervised PCA is intentionally corrected, via (iii) the algebra-based algorithm, to further increase the certainty to image the microplastics and nanoplastics. Once the signal is weak, (iv) an additional algorithm of image reconstruction via deconvolution is developed to average the background noise and smooth the image. By doing so, we estimate that millions of microplastics and nanoplastics are released daily in potential from a rubber band applied in a teenager's mouth, which might be a big concern. Overall, our approach provides a suitable option to characterize the microplastics and nanoplastics from a complex background.
大多数青少年都经历过正畸治疗，但我们不知道最近被归类为新兴污染物的释放微塑料和纳米塑料可能产生的不良影响。在此，我们对正畸过程中用于改善牙齿咬合的橡皮筋进行测试，以确认微塑料和纳米塑料的释放情况。我们通过以下方法改进微塑料和纳米塑料的表征：(i) 拉曼成像，从扫描光谱矩阵或高光谱矩阵中提取并绘制信号，并从统计学上提高信噪比。为了有效提取信号，(ii) 探索了化学计量学方法，如主成分分析 (PCA)，将高光谱矩阵转换为确定性更高的图像。通过 (iii) 基于代数的算法对无监督PCA进行有意校正，以进一步提高对微塑料和纳米塑料成像的确定性。一旦信号较弱，(iv) 开发一种通过去卷积进行图像重建的附加算法，以平均背景噪声并平滑图像。通过这样做，我们估计青少年口腔中使用的一根橡皮筋每天可能会释放数百万个微塑料和纳米塑料，这可能是一个令人担忧的大问题。总体而言，我们的方法为从复杂背景中表征微塑料和纳米塑料提供了一个合适的选择。
