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Abstract

Nearly one in eight couples are affected by infertility, with many relying on assisted reproductive technologies (ART) to conceive. However, selecting the highest-quality embryo in ART remains a major challenge, as current assessment methods are often subjective, or invasive, and lack precision. Here, we introduce a novel strategy that analyses embryo-derived polyadenylated RNA in blastocoel fluid to more accurately predict pregnancy outcomes. Elevated RNA levels were strongly associated with implantation failure, particularly in embryos from women over the age of 34. Our predictive model developed using our sample cohort, incorporating both RNA and maternal age, demonstrated exceptional performance, achieving 76% accuracy in the training set and 73% in independent validation in predicting implantation outcome-- highlighting a promising advancement in embryo selection and ART success.

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