Atypical Chemokine Receptor ACKR2 Mediates Chemokine Scavenging by Primary Human Trophoblasts and Can Regulate Fetal Growth, Placental Structure, and Neonatal Mortality in Mice
Bibliographic record
Abstract
Inflammatory chemokines produced in the placenta can direct the migration of placental leukocytes using chemokine receptors that decorate the surface of these cells. Fetal trophoblasts can also express receptors for inflammatory chemokines, and they are one of the few cell types that express atypical chemokine receptor 2 (ACKR2), previously known as D6. ACKR2 binds many inflammatory CC chemokines but cannot stimulate cell migration or activate signaling pathways used by conventional chemokine receptors. Existing evidence suggests that ACKR2 is a specialized chemokine scavenger, but its function in primary human trophoblasts has not been explored. In mice, ACKR2 is thought to be dispensable for the reproductive success of unchallenged females that have conceived naturally, but it can suppress inflammation-induced abortion and aid the survival of implanted allogeneic embryos. In this article, we demonstrate that cultured primary human trophoblasts express ACKR2 far more strongly than genes encoding conventional receptors for inflammatory CC chemokines. Moreover, these cells are capable of the rapid internalization and efficient scavenging of extracellular chemokine, and this is mediated by ACKR2. We also report that in unchallenged DBA/1j mice, Ackr2 deficiency increases the incidence of stillbirth and neonatal death, leads to structural defects in the placenta, and can decrease fetal weight. Loss of Ackr2 specifically from fetal cells makes a key contribution to the placental defects. Thus, primary human trophoblasts use ACKR2 to scavenge chemokines, and ACKR2 deficiency can cause abnormal placental structure and reduced neonatal survival.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".