Department of Toxico/Pharmacology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Niayesh Highway, Valiasr Ave, Tehran, Iran.
Analyst. 2019 Sep 23;144(19):5810-5828. doi: 10.1039/c9an00811j.
Fourier transform infrared (FTIR) spectroscopy is a well-known method of analysis, with various applications, including promising potential for analyzing biological samples. In the bio-spectroscopy of cells, Mie scattering may increase, which then causes spectral distortion, due to the similarity of cell size with the IR medium-wavelength. These changes make the spectrum unreliable. In previous scattering elimination studies, questionable estimations were considered. For instance, all cells were considered as spherical objects or cell size was estimated randomly. In an attempt to provide the best equation based on the natural existence of cells for the FTIR Mie scattering correction, we examined the actual biological data of cells - as opposed to those yielded from mathematical manipulations. So five biological factors: cell size, shape, granularity, circularity, and edge irregularities, for each cell line were considered as factors which cause scattering. For measuring cell size, roundness and edge irregularity, microscopy images were obtained and processed. For evaluating cell line granularity, flow cytometry was used. Finally, by including these factors, an algorithm was designed. To assess the accuracy of the proposed algorithm, the trypsinized cell spectrum was considered as the high scattering spectrum. Cells were also cultured on a MirrIR slide, and their ATR-FTIR spectrum was considered as the minimum scattering spectrum. The algorithm using the abovementioned five characteristics was used for 13 different cell lines, and in some cases the corrected spectrum demonstrated more than 97% resemblance with the ATR spectra of the same cells. A comparison between the results of this algorithm with the Bassan et al. (2017) algorithm for scattering correction that is freely available on the Internet was then conducted on two different cell lines, clearly showing the advantages of our algorithm, in terms of accuracy and precision. Therefore, this method can be viewed as a more suitable solution for scattering correction in cell investigations.
傅里叶变换红外（FTIR）光谱是一种众所周知的分析方法，具有多种应用，包括在分析生物样本方面具有很大的潜力。在细胞的生物光谱学中，米氏散射可能会增加，从而导致光谱失真，因为细胞大小与 IR 介质的中波长相似。这些变化使得光谱不可靠。在以前的散射消除研究中，考虑了一些有争议的估计。例如，所有细胞都被视为球形物体，或者细胞大小是随机估计的。为了尝试提供基于细胞自然存在的最佳 FTIR 米氏散射校正方程，我们研究了细胞的实际生物数据，而不是来自数学运算的数据。因此，我们考虑了五个生物学因素：每个细胞系的细胞大小、形状、粒度、圆度和边缘不规则性，这些因素都会导致散射。为了测量细胞大小、圆度和边缘不规则性，我们获得并处理了显微镜图像。为了评估细胞系的粒度，我们使用了流式细胞术。最后，通过包含这些因素，我们设计了一个算法。为了评估所提出算法的准确性，我们将胰蛋白酶化细胞的光谱视为高散射光谱。我们还将细胞培养在 MirrIR 载玻片上，并将其 ATR-FTIR 光谱视为最小散射光谱。我们使用上述五个特征的算法对 13 种不同的细胞系进行了测试，在某些情况下，校正后的光谱与同一细胞的 ATR 光谱的相似度超过 97%。然后，我们将该算法的结果与互联网上免费提供的 Bassan 等人（2017 年）的散射校正算法进行了比较，结果表明，在准确性和精度方面，我们的算法具有优势。因此，这种方法可以被视为细胞研究中散射校正的更合适的解决方案。
