Anticentromere antibody induced by immunization with centromere protein and Freund’s complete adjuvant may interfere with mouse early-stage embryo

Background Anticentromere antibody (ACA) is a member of the antinuclear antibody spectrum (ANAs) which has been speculated to be associated with subfertility. Thus, the present study aimed to investigate the induction of ACA production and its potential interference with early-stage embryos. Methods Recombinant centromere protein-A (CENP-A) or centromere protein-B (CENP-B) and complete Freund’s adjuvant (CFA) were used to immunize mice. Serum ACA level was then evaluated by using an indirect immunofluorescence test. Immunofluorescence assay was performed to detect IgG in follicles in ovarian tissues and early-stage embryos. Results Following treatment, serum positive ACA was observed in mice treated with CENP and CFA. Furthermore, IgG were detected in follicular fluid and early-stage embryos from mice treated with CENP and CFA. Conclusions This study preliminarily indicated that ACA induced by CENP and CFA may penetrate into the living embryos of early-stage in mice.

Fast Multi-Focus Fusion Based on Deep Learning for Early-Stage Embryo Image Enhancement

Background: Cell detection and counting is of essential importance in evaluating the quality of early-stage embryo. Full automation of this process remains a challenging task due to different cell size, shape, the presence of incomplete cell boundaries, partially or fully overlapping cells. Moreover, the algorithm to be developed should process a large number of image data of different quality in a reasonable amount of time. Methods: Multi-focus image fusion approach based on deep learning U-Net architecture is proposed in the paper, which allows reducing the amount of data up to 7 times without losing spectral information required for embryo enhancement in the microscopic image. Results: The experiment includes the visual and quantitative analysis by estimating the image similarity metrics and processing times, which is compared to the results achieved by two wellknown techniques—Inverse Laplacian Pyramid Transform and Enhanced Correlation Coefficient Maximization. Conclusion: Comparatively, the image fusion time is substantially improved for different image resolutions, whilst ensuring the high quality of the fused image.