Abstract

This study aims to evaluate the ability of absorbance spectra in the near-infrared (NIR) region to predict the number of cells for different cell lines. The cancerous cell lines were human cervix adenocarcinoma (HeLa) and human prostate carcinoma (DU145), and L929 was a normal mouse skin fibroblast. The number of cells varied from 50,000 to 275,000 with an interval of 25,000 for each cell line. Vis-NIR absorbance spectra (400–1100 nm) at each number of cells (50,000–275,000) for L929, DU145, and HeLa cell lines cultured in media with and without phenol red were recorded. Multiple linear regression (MLR) and partial least squares regression (PLSR) models were developed in the NIR region (680–1050 nm) to quantify the number of cells for the three cell lines. The outcomes showed that the quantification analysis of the number of cells using MLR and PLSR models produced high prediction accuracy with R2≥ 93%. The best results were obtained using PLSR for the preprocessed spectra using an orthogonal signal correction method. It was found that the presence of phenol red in the culture medium improved the prediction accuracy in the case of HeLa (SECV = 271 cells) and DU145 (SECV = 250 cells) cell lines, but the accuracy was higher when phenol red was not present for the L929 cell line (SECV = 24 cells). In addition, the existence of phenol red boosted the accuracy when the global PLSR model was built, irrespective of the cell type (SECV = 7,754 cells). The effect of phenol red was explained in the terms of its impact on the water molecular structure of the cells’ culture medium which influences the light scattering.

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