Characterisation of an in vitro system to study maternal communication with spermatozoa
Bibliographic record
Abstract
In vivo, gamete maturation, fertilisation and early embryonic development take place inside the oviduct. Several studies have indicated that local responses towards gametes and embryos are generated by the maternal reproductive tract. However, no defined in vitro model currently exists to allow detailed and systematic investigation of maternal communications with gametes and embryos. Therefore, we characterised an in vitro model based on the interaction of boar spermatozoa with an immortalised porcine oviduct epithelial cell line to evaluate different factors that may affect this model. The factors tested were sperm viability, source of spermatozoa, cell passage effect and the effect of reproductive and non-reproductive epithelial cells in the interaction with spermatozoa. After 24 h of co-incubation, RNA was extracted and used to synthesise cDNA for quantitative real-time PCR. Alteration in the expression of genes such as adrenomedullin, heat-shock 70-kDa protein 8 and prostaglandin E synthase was considered as the end point of this assay. The results showed that sperm viability and cell passage number had an effect on oviductal gene expression in response to spermatozoa. Oviductal cells showed significant alterations in gene expression when compared with non-reproductive epithelial cells. The simple in vitro system described here has potential application for further studies in our understanding of mechanisms involved in maternal interactions with spermatozoa.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".