Pulse of α-2-macroglobulin and lipocalin-1 in the pregnant uterus of European polecats ( <i>Mustela putorius</i> ) at the time of implantation
Bibliographic record
Abstract
Abstract Uterine secretory proteins protect the uterus and conceptuses against infection, facilitate implantation, control cellular damage resulting from implantation, and supply embryos with nutrients. The early conceptus of the European polecat ( Mustela putorius ) grows and develops free in the uterus until implanting at about 12 days after mating. Using a proteomics approach we found that the proteins appearing in the uterus leading up to and including the time of implantation changed dramatically with time. Several of the proteins identified have been found in pregnant uteri of other placental mammals, such as α 1 -antitrypsin, serum albumin, lactoferrin, cathepsin L1, uteroferrin, and ectonucleotide pyrophosphatase. The broad-spectrum proteinase inhibitor α 2 -macroglobulin rose from relatively low abundance initially to dominate the protein profile by the time of implantation. Its functions may be to limit damage caused by the release of proteinases during implantation, and to control other processes around the site of implantation. Lipocalin-1 (also known as tear lipocalin) has not previously been recorded as a uterine secretion in pregnancy, and also increased substantially in concentration. If polecat lipocalin-1 has similar biochemical properties to the human form, then it may have a combined function in transporting or scavenging lipids, and antimicrobial activities. The changes in the uterine secretory proteome of Euroepan polecats may be similar in those species of mustelid that engage in embryonic diapause, but possibly only following reactivation of the embryo.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".