Toward embryo cryopreservation-on-a-chip: A standalone microfluidic platform for gradual loading of cryoprotectants to minimize cryoinjuries
Bibliographic record
Abstract
Embryo vitrification is a fundamental practice in assisted reproduction and fertility preservation. A key step of this process is replacing the internal water with cryoprotectants (CPAs) by transferring embryos from an isotonic to a hypertonic solution of CPAs. However, this applies an abrupt osmotic shock to embryos, resulting in molecular damages that have long been a source of concern. In this study, we introduce a standalone microfluidic system to automate the manual process and minimize the osmotic shock applied to embryos. This device provides the same final CPA concentrations as the manual method but with a gradual increase over time instead of sudden increases. Our system allows the introduction of the dehydrating non-permeating CPA, sucrose, from the onset of CPA-water exchange, which in turn reduced the required time of CPA loading for successful vitrification without compromising its outcomes. We compared the efficacy of our device and the conventional manual procedure by studying vitrified-warmed mouse blastocysts based on their re-expansion and hatching rates and transcription pattern of selected genes involved in endoplasmic reticulum stress, oxidative stress, heat shock, and apoptosis. While both groups of embryos showed comparable re-expansion and hatching rates, on-chip loading reduced the detrimental gene expression of cryopreservation. The device developed here allowed us to automate the CPA loading process and push the boundaries of cryopreservation by minimizing its osmotic stress, shortening the overall process, and reducing its molecular footprint.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".