4.7 Article

Novel semi-automated fluorescence microscope imaging algorithm for monitoring IgG aggregates in serum

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SCIENTIFIC REPORTS
卷 11, 期 1, 页码 -

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NATURE RESEARCH
DOI: 10.1038/s41598-021-90623-7

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资金

  1. Centre of Excellence for Biopharmaceutical Technology grant from the Department of Biotechnology, Ministry of Science and Technology [BT/COE/34/ SP15097/2015]
  2. Council of Scientific and Industrial Research, New Delhi [09/086(1312)/2018-EMR-I]

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The analysis of therapeutic IgG aggregates in serum using a novel fluorescence microscopy-based image processing approach offers an effective method for removing noise and retaining analyte sizes. This proposed algorithm simplifies implementation and complements existing approaches for analyzing aggregates in serum.
Analysis of therapeutic IgG aggregates in serum is a potential area of investigation as it can give deeper insights about the function, immunogenic issues and protein interaction associated with the aggregates. To overcome various complexities associated with the existing analytical techniques for analyzing aggregates in serum, a novel florescence microscopy-based image processing approach was developed. The monoclonal antibody (mAb) was tagged with a fluorescent dye, fluorescein isothiocyanate (FITC). Aggregates, generated by stirring, were spiked into serum and images were captured at various time points. After denoising, thresholding by weighted median, 1D Otsu, and 2D Otsu was attempted and a modified 2D Otsu, a new mode of thresholding, was developed. This thresholding method was found to be highly effective in removing noises and retaining analyte sizes. Out of 0-255, the optimized threshold value obtained for the images discussed in modified 2D Otsu was 9 while 2D Otsu's overestimated values were 38 and 48. Other morphological operations were applied after thresholding and the area, perimeter, circularity, and radii of the aggregates in these images were calculated. The proposed algorithm offers an approach for analysis of aggregates in serum that is simpler to implement and is complementary to existing approaches.

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