New functions for old factors: the role of polyamines during the establishment of pregnancy
Bibliographic record
Abstract
Implantation is essential for the establishment of a successful pregnancy, and the preimplantation period plays a significant role in ensuring implantation occurs in a timely and coordinated manner. This requires effective maternal-embryonic signalling, established during the preimplantation period, to synchronise development. Although multiple factors have been identified as present during this time, the exact molecular mechanisms involved are unknown. Polyamines are small cationic molecules that are ubiquitously expressed from prokaryotes to eukaryotes. Despite being first identified over 300 years ago, their essential roles in cell proliferation and growth, including cancer, have only been recently recognised, with new technologies and interest resulting in rapid expansion of the polyamine field. This review provides a summary of our current understanding of polyamine synthesis, regulation and function with a focus on recent developments demonstrating the requirements for polyamines during the establishment of pregnancy up to the implantation stage, in particular the role of polyamines in the control of embryonic diapause and the identification of an alternative pathway for their synthesis in sheep pregnancy. This, along with other novel discoveries, provides new insights into the control of the peri-implantation period in mammals and highlights the complexities that exist in regulating this critical period of pregnancy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".