Mimicking the oviductal fluid viscosity improves the quality of in vitro–produced bovine embryos
Bibliographic record
Abstract
The oviductal fluid (OF) provides essential nutritional, mechanical, and physical support during the first four days of embryonic development. Among its physical properties, viscosity has been largely overlooked in embryo in vitro culture (IVC) media due to limited available data. In this study, we measured the viscosity of bovine OF from ex vivo samples and mimicked it during in vitro embryo culture. OF viscosity remained consistent across estrous cycle stages and between oviductal antimeres, and was over three times higher than that of standard IVC media (3.4 ± 1 vs. 0.9 ± 0 mPa·s, P < 0.05). To replicate this property, in vitro bovine embryos were cultured in media supplemented with sodium alginate (0%, 0.25%, or 0.75% w/v), corresponding to low (control), physiological (3.3 ± 0.1 mPa·s), and supraphysiological (6.8 ± 0.02 mPa·s) viscosity levels. While cleavage and blastocyst rates were unaffected, embryos cultured at physiological viscosity (0.25%) showed improved quality indicators: increased total cell number, lower apoptosis, reduced reactive oxygen species, and decreased global DNA methylation compared to the high-viscosity (0.75%) group. Notably, embryos in the 0.25% group also showed lower apoptosis and inner cell mass methylation than controls. These findings suggest that standard IVC media fail to replicate key rheological features of the oviductal environment and that alginate is a safe, non-Newtonian viscosity modulator. Mimicking OF viscosity during IVC improves embryo quality and epigenetic outcomes and may represent a valuable refinement in assisted reproductive technologies.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".