Expression of chemokine decoy receptors and their ligands at the porcine maternal–fetal interface
Bibliographic record
Abstract
Successful pregnancy requires coordinated maternal-fetal cross-talk to establish vascular connections that support conceptus growth. In pigs, two waves of spontaneous fetal loss occur and 30-40% of conceptuses are lost before parturition. Previous studies associated these losses with decreased angiogenic and increased inflammatory cytokines. Chemokines, a sub-category of cytokines, and decoy receptors control leukocyte trafficking, angiogenesis and development. The availability of chemokines is regulated by three non-signalling decoy receptors: chemokine decoy receptor (D6), Duffy antigen receptor for chemokines (DARC) and Chemocentryx decoy receptor (CCX CKR). We hypothesized that the expression of these receptors and their chemokine ligands regulate the porcine pregnancy success or failure. Here, we describe for the first time the transcription and translation of all three decoy receptors and several chemokine ligands in endometrium and trophoblast associated with healthy and arresting conceptuses at gestation day (gd) 20 and gd50. Among decoy receptors, transcripts for DARC were significantly reduced in endometrium, whereas that for CCX CKR were significantly increased in endometrium and trophoblast at gd50 arresting compared with healthy sites. However, western blot analysis revealed no differences in decoy receptor expression between healthy and arresting tissues. Transcripts for decoy receptor ligands CCL2, CCL3, CCL4, CCL5, CCL11, CCL19, CCL21, CXCL2 and CXCL8 were stable between healthy and arresting littermates. Quantification by SearchLight chemiluminescent protein array confirmed ligand expression at the protein level. These data indicate that decoy receptors and ligands are expressed at the porcine maternal-fetal interface and dysregulation of decoy receptor (DARC and CCX CKR) transcripts occurs at sites of fetal arrest.
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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 | 0.001 | 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".