Interleukin-15 is required for maximal lipopolysaccharide-induced abortion
Bibliographic record
Abstract
The maternal immune response during pregnancy is critical for the survival of the fetus yet can be detrimental during infection and inflammation. Previously, IL-15 has been observed to mediate inflammation during LPS-induced sepsis. Therefore, we sought to determine whether IL-15 mediates the inflammatory process during LPS-induced abortion through the use of IL-15(-/-) and WT mice. Administration of 2.5 μg LPS i.p. on gd 7.5 drastically reduced fetal viability in WT mice, whereas it had a minimal effect on fetal survival in IL-15(-/-) mice. The uteroplacental sites of LPS-treated WT mice were characterized by vast structural degradation and inflammation compared with treated IL-15(-/-) and untreated controls. This suggests that IL-15 may mediate the inflammation responsible for LPS-induced resorption. As IL-15(-/-) mice are deficient in NK cells and resistant to LPS-induced abortion, these effects suggest that IL-15 may mediate abortion through their homeostatic and/or activation effects on NK cells. WT uteroplacental units exposed to LPS had an increase in the overall number and effector number of NK cells compared with their control counterparts. Furthermore, NK cell depletion before administration of LPS in WT mice partially restored fetal viability. Overall, this paper suggests that IL-15 mediates the inflammatory environment during LPS-induced fetal resorption, primarily through its effects on NK cells.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".