Maternal Innate Immune Reprogramming After Complicated Pregnancy
Bibliographic record
Abstract
PROBLEM: Preeclampsia (PE) and fetal growth restriction (FGR) are often associated with maternal inflammation and an increased risk of cardiovascular and metabolic disease in the affected mothers. The mechanism responsible for this increased risk of subsequent disease may involve reprogramming of innate immune cells, characterized by epigenetic modifications. METHOD OF STUDY: Circulating monocytes from women with PE, FGR, or uncomplicated pregnancies (control) were isolated before labor. Cytokine release from monocytes following exposure to lipopolysaccharide (LPS) and the presence of lysine 4-trimethylated histone 3 (H3K4me3) within TNF promoter sequences were evaluated. Single-cell transcriptomic profiles of circulating monocytes from women with PE or uncomplicated pregnancies were assessed. RESULTS: Monocytes from women with PE or FGR exhibited increased IL-10 secretion and decreased IL-1β and GM-CSF secretion in response to LPS. While TNFα secretion was not significantly different in cultures of control monocytes versus those from complicated pregnancies with or without LPS exposure, monocytes from complicated pregnancies had significantly decreased levels of H3K4me3 associated with TNF promoter sequences. Cluster quantification and pathway analysis of differentially expressed genes revealed an increased proportion of anti-inflammatory myeloid cells and a lower proportion of inflammatory non-classical monocytes among the circulating monocyte population in women with PE. CONCLUSIONS: Monocytes from women with PE and FGR exhibit an immune tolerance phenotype before initiation of labor. Further investigation is required to determine whether this tolerogenic phenotype persists after the affected pregnancy and contributes to increased risk of subsequent disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".