Decidual Stromal Cell Necroptosis Contributes to Polyinosinic-Polycytidylic Acid-Triggered Abnormal Murine Pregnancy
Bibliographic record
Abstract
the maternal blood or by ascending the genito-urinary tract, and then initially colonizing the maternal decidua. Decidual stromal cells (DSCs) are the major cellular component of the decidua. Although DSCs at the maternal-fetal interface contribute to the regulation of immunity in pregnancy in the face of immunological and physiological challenges, the roles of these DSCs during viral infection remain ill defined. Here, we characterized the response of DSCs to a synthetic double-stranded RNA molecule, polyinosinic-polycytidylic acid [poly(I:C)], which is a mimic of viral infection. We demonstrated that both transfection of cells with poly(I:C) and addition of extracellular (non-transfected) poly(I:C) trigger the necroptosis of DSCs and that this response is dependent on RIG-I-like receptor/IPS-1 signaling and the toll-like receptor 3/TIR-domain-containing adapter-inducing interferon-β pathway, respectively. Furthermore, following poly(I:C) challenge, pregnant mixed lineage kinase domain-like protein-deficient mice had fewer necrotic cells in the mesometrial decidual layer, as well as milder pathological changes in the uterine unit, than did wild-type mice. Collectively, our results establish that necroptosis is a contributing factor in poly(I:C)-triggered abnormal pregnancy and thereby indicate a novel therapeutic strategy for reducing the severity of the adverse effects of viral infections in pregnancy.
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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 | 0.000 |
| 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 | 0.001 |
| 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".