ReviewReproductive medicine and biology
From the Understanding of Maternal Molecules and Mechanisms to Predicting Embryonic Development.
Review in Reproductive medicine and biology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- When Fertilization Is Not Enough: Maternal-Zygotic Transition as a Determinant of Embryo Competence in IVF.International journal of molecular sciences · 2026Review
- Review
- From the Understanding of Maternal Molecules and Mechanisms to Predicting Embryonic Development.Reproductive medicine and biologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.