From the Understanding of Maternal Molecules and Mechanisms to Predicting Embryonic Development

Background: Embryo quality is a critical determinant of successful outcomes in assisted reproductive technology (ART). Various molecular and cellular mechanisms in oocytes influence embryo quality, and their understanding can lead to the establishment of selection criteria for enhancing implantation rates. Methods: This review summarizes current knowledge on oocyte factors influencing embryo quality, including organelle function, chromosome segregation, maternal transcripts, metabolism, and gene regulation. We also discuss emerging techniques for assessing the fate of embryonic development, such as time-lapse imaging, preimplantation genetic testing for aneuploidy (PGT-A), and artificial intelligence (AI) or machine learning-based prediction models. Main Findings: Embryo quality is often determined by maternal factors-driven mechanisms that affect developmental potentials. Advanced technologies such as omics-based profiling and AI-driven analyses offer promising non-invasive assessment tools for embryo quality. Conclusion: Integrating molecular diagnostics of maternal factors with traditional morphological evaluation can refine embryo selection, improving ART success rates. Future research should focus on minimally invasive biomarkers and personalized prediction models.