ArticleNature communications2026
Embryo metabolite analysis and implantation potential prediction using chemiluminescent microfluidic chips with dielectric wetting valves.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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
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Who cites it
2 citing papers in PubMed.
- Metabolic imaging for gamete and embryo assessment through advanced microscopy technologies: a novel avenue for artificial intelligence?Human reproduction (Oxford, England) · 2026Review
- Surface-enhanced Raman spectroscopy analysis of glucose in spent embryo culture medium: correlation with embryo developmental potential.Frontiers in cell and developmental biology · 2026Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Analysis of embryo metabolites offers a promising non-invasive strategy for assessing preimplantation developmental potential, yet the limited performance of current sensing platforms restricts physiological insights. Here we report a capillary-driven chemiluminescence microfluidic device equipped with three electrowetting valves, enabling simultaneous, offline quantification of glucose, lactate and pyruvate from as little as 3 μL of spent blastocyst culture medium (SBCM). Using a training set (n = 61) and validation set (n = 108) of human embryo transfers, we systematically recorded morphological development and clinical pregnancy outcomes. Metabolic flux analysis revealed that embryos with higher developmental potential consumed more glucose and pyruvate while producing more lactate. Integration of metabolic and morphological data yielded a predictive model of implantation potential with an area under the curve (AUC) of 92.0%, demonstrating robust performance. This platform establishes a powerful tool for embryo selection and may inform clinical decision-making in assisted reproduction.
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Registered trials
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