Probing morphological, genetic and metabolomic changes of in vitro embryo development in a microfluidic device
Bibliographic record
Abstract
Assisted reproduction technologies for clinical and research purposes rely on a brief in vitro embryo culture which, despite decades of progress, remain suboptimal in comparison to the physiological environment. One promising tool to improve this technique is the development of bespoke microfluidic chambers. Here we present and validate a new microfluidic device in polydimethylsiloxane (PDMS) for the culture of early mouse embryos. Device material and design resulted embryo compatible and elicit minimal stress. Blastocyst formation, hatching, attachment and outgrowth formation on fibronectin-coated devices were similar to traditional microdrop methods. Total blastocyst cell number and allocation to the trophectoderm and inner cell mass lineages were unaffected. The devices were designed for culture of 10-12 embryos. Development rates, mitochondrial polarization and metabolic turnover of key energy substrates glucose, pyruvate and lactate were consistent with groups of 10 embryos in microdrop controls. Increasing group size to 40 embryos per device was associated with increased variation in development rates and altered metabolism. Device culture did not perturb blastocyst gene expression but did elicit changes in embryo metabolome, which can be ascribed to substrate leaching from PDMS and warrant further investigation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".