Distinct inflammatory profile in preeclampsia and postpartum preeclampsia reveal unique mechanisms†
Bibliographic record
Abstract
Preeclampsia (PE) is a poorly understood pregnancy complication. It has been suggested that changes in the maternal immune system may contribute to PE, but evidence of this remains scarce. Whilst PE is commonly experienced prepartum, it can also occur in the postpartum period (postpartum PE-PPPE), and the mechanisms involved are unknown. Our goal was to determine whether changes occur in the maternal immune system and placenta in pregnancies complicated with PE and PPPE, compared to normal term pregnancies. We prospectively recruited women and collected blood samples to determine the circulating immune profile, by flow cytometry, and assess the circulating levels of inflammatory mediators and angiogenic factors. Placentas were collected for histological analysis. Levels of alarmins in the maternal circulation showed increased uric acid in PE and elevated high-mobility group box 1 in PPPE. Analysis of maternal immune cells revealed distinct profiles in PE vs PPPE. PE had increased percentage of lymphocytes and monocytes whilst PPPE had elevated NK and NK-T cells as well. Elevated numbers of immune cells (CD45+) were detected in placentas from women that developed PPPE, and those were macrophages (CD163+). This work reveals changes within the maternal immune system in both PE and PPPE, and indicate a striking contrast in how this occurs. Importantly, elevated immune cells in the placenta of women with PPPE strongly suggest a prenatal initiation of the pathology. A better understanding of these changes will be beneficial to identify women at high risk of PPPE and to develop novel therapeutic targets.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".