Hypoxia and oxidative stress induce sterile placental inflammation in vitro
Bibliographic record
Abstract
Fetal growth restriction (FGR) and stillbirth are associated with placental dysfunction and inflammation and hypoxia, oxidative and nitrative stress are implicated in placental damage. Damage-associated molecular patterns (DAMPs) are elevated in pregnancies at increased risk of FGR and stillbirth and are associated with increase in pro-inflammatory placental cytokines. We hypothesised that placental insults lead to release of DAMPs, promoting placental inflammation. Placental tissue from uncomplicated pregnancies was exposed in vitro to hypoxia, oxidative or nitrative stress. Tissue production and release of DAMPs and cytokines was determined. Oxidative stress and hypoxia caused differential release of DAMPs including uric acid, HMGB1, S100A8, cell-free fetal DNA, S100A12 and HSP70. After oxidative stress pro-inflammatory cytokines (IL-1α, IL-1β, IL-6, IL-8, TNFα, CCL2) were increased both within explants and in conditioned culture medium. Hypoxia increased tissue IL-1α/β, IL-6, IL-8 and TNFα levels, and release of IL-1α, IL-6 and IL-8, whereas CCL2 and IL-10 were reduced. IL1 receptor antagonist (IL1Ra) treatment prevented hypoxia- and oxidative stress-induced IL-6 and IL-8 release. These findings provide evidence that relevant stressors induce a sterile inflammatory profile in placental tissue which can be partially blocked by IL1Ra suggesting this agent has translational potential to prevent placental inflammation evident in FGR and stillbirth.
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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 | 0.001 |
| 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".