Coordinated Regulation of Human Trophoblast Invasiveness by Macrophages and Interleukin 101
Bibliographic record
Abstract
Trophoblast invasion and modification of the spiral arterioles are essential for the establishment of adequate uteroplacental blood flow during pregnancy. However, such vascular remodeling is deficient in preeclampsia. This disease is also associated with increased maternal levels of circulating proinflammatory cytokines such as tumor necrosis factor (TNF) and reduced levels of immunoregulatory cytokines such as interleukin 10 (IL10). We have previously shown that activated macrophages inhibit trophoblast invasiveness in vitro. The present study demonstrates that IL10 interferes with the invasion-inhibitory effect that activated macrophages exert on trophoblast cells. Co-culture experiments revealed that human lipopolysaccharide (LPS)-activated macrophages inhibited the ability of immortalized HTR-8/SVneo human trophoblast cells to invade through reconstituted extracellular matrix. This effect of activated macrophages on trophoblast invasiveness was paralleled by decreased expression of urokinase plasminogen activator receptor (PLAUR) on the surface of trophoblast cells, and by increased secretion of plasminogen activator inhibitor type 1 (SERPINE1). Exposure of LPS-treated macrophages to IL10 prior to co-culture prevented their ability to inhibit trophoblast invasion, PLAUR expression, and to stimulate SERPINE1 secretion. Interleukin 10 prevented macrophage activation by LPS as determined by the lack of secretion of TNF in the culture medium, and a neutralizing TNF antibody completely blocked the effect of macrophages on trophoblast invasion. These results indicate that decreased circulating levels of IL10 associated with preeclampsia may contribute to inadequate trophoblast invasion and remodeling of the uterine spiral arterioles.
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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".