Cadherins in maternal–foetal interactions: red queen with a green beard?
Bibliographic record
Abstract
Cadherins are homophilic cell surface adhesion proteins, some of which mediate interactions between maternal and foetal tissues during mammalian pregnancy. David Haig suggested that these proteins may exhibit 'green-beard gene' effects, whereby the nature of binding between identical alleles in mother and foetus leads to differential levels of resource transfer. The selfish effects of such self-recognizing alleles should, however, be suppressed over evolutionary time by unlinked genes, which is expected to lead to antagonistic coevolution between placentally expressed cadherins and unlinked modifiers. Such molecular coevolution should leave a signature of positive selection, with high ratios of non-synonymous to synonymous amino acid substitution. We present evidence that three placentally expressed cadherin genes, E-cadherin, P-cadherin and VE-cadherin, have been subject to positive selection. By contrast, a 'control' cadherin that is not expressed in the placenta, H-cadherin, showed no evidence of selection. These results provide support for the hypothesis that the cadherin genes involved in maternal-foetal interactions have been subject to green-beard-effect mutations over the course of evolutionary history, leading to antagonistic coevolution with suppressing elements from the parliament of genes.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".