Decidual natural killer cells promote extravillous trophoblast developmental pathways: evidence from trophoblast organoid co-cultures
Bibliographic record
Abstract
The placenta an essential extraembryonic organ that supports the fetus throughout gestation. The interactions between the placenta and the maternal immune system during the first trimester have not been wholly characterized despite their close physical association and hemi-allogeneic relationship. The most abundant type of immune cell in the uterus in the first trimester is the decidual natural killer cell (dNK). Despite their name, dNKs play supportive roles during pregnancy by remodelling uterine spiral arteries. We present evidence suggesting that the matrix metalloproteinases (MMPs) that dNKs secrete to promote this remodelling also drive placental development. This study used a novel co-culture system of dNKs and trophoblast organoids, which are mini-organs representing two to three different cell types of the human placenta. We found that co-cultures for one week led to significant (p=0.020) increases in the organoid area. We also observed significant decreases in trophoblast stemness markers and upregulation of gene sets associated with extravillous trophoblast (EVT) development through bulk RNA sequencing and immunohistochemical examinations. These changes were accompanied by significant (p<0.001) increases in collagen subunit gene expression in the organoids, with simultaneous significant decreases (p<0.001) in the proportion of organoid area occupied by collagen as determined through Massons Trichrome. Cultures containing dNKs also contained significantly higher MMP1, 3, 9, and 10 levels in their culture media, each of which can break down collagen. These findings demonstrate that dNKs promote changes concordant with trophoblast differentiation towards EVTs and villous branching morphogenesis.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".