Changes in systemic type 1 and type 2 immunity in normal pregnancy and pre‐eclampsia may be mediated by natural killer cells
Bibliographic record
Abstract
A bias of T cell immunity towards type 2 (Th2) is thought to be critical for normal pregnancy. Pathological pregnancies, such as pre-eclampsia, are characterised by cell-mediated (Th1) immune dominance. The Th1/Th2 paradigm, however, is too simplistic. Normal pregnancy is associated with a systemic inflammatory response which increases throughout gestation. This inflammatory response is exaggerated in pre-eclampsia, a syndrome of the third trimester. T helper (Th) cells are considered the primary mediators of these altered immune responses, and other T cells, i.e. T cytotoxic (Tc) cells, and lymphocytes of the innate immune system, i.e. natural killer (NK) and NKT cells, have been largely disregarded. In this study, we have used novel pan type 1 (IL-18 receptor) and pan type 2 (ST2L) lymphocyte function markers in four-colour flow cytometry to broadly characterise peripheral blood lymphocyte populations from non-pregnant, normal pregnant and pre-eclamptic women. There were no changes in the Th1/Th2 or Tc1/Tc2 cell ratios between the three groups; however, the NK1/NK2 and NKT1/NKT2 cell ratios were significantly decreased in normal pregnancy compared with non-pregnant (p <0.001 and p <0.01, respectively) and pre-eclamptic women (p <0.05). These results confirm that immunoregulation occurs in pregnancy, but suggest a dominant role of the innate rather than the adaptive immune system.
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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 | 0.000 |
| 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".