Abstracts of the Joint Annual Meeting of Immunology of the Austrian and German Societies (ÖGAI, DGfI), Vienna, September 3–6, 2008
Bibliographic record
Abstract
Pre-eclampsia is a systemic disease of unknown aetiology.It is the leading cause of morbidity and mortality in pregnancy.Preeclampsia has been suggested to represent rejection of the fetus by the maternal immune system, as a consequence of imbalances within the T helper cell subsets.In this study we analysed intracellular expression of FoxP3, IFNγ, IL-10 and IL-17 within the CD4 subsets by flow cytometry.These subsets were compared between nonpregnant women, and women at the end of the third trimester in healthy and pre-eclamptic pregnancies, both in peripheral blood and decidual tissue.Circulating CD4+FoxP3+ Treg frequencies in healthy pregnancies were comparable to non-pregnant controls (6.63% +/-1.91 vs. 6.69%+/-1.29),but were markedly reduced in preeclampsia (4.29% +/-1.97).Functional differences in Treg cells were not observed between the different cohorts.The cytokine patterns within the CD4+ T cell subset showed a significantly higher proportion of Th17 cells in patients with pre-eclampsia, when compared to healthy pregnancies (1.03% +/-0.53 vs 0.41% +/-0.38).Consequently, the ratios of IL17+/IFNγ+ cells as well as IL17+/IL10+ cells were significantly higher in pre-eclamptic compared to healthy pregnancies.In addition, decidual CD4+FoxP3+ Tregs and Th17 cells were maintained at comparable levels in healthy pregnancies and in pregnancies with pre-eclampsia.We now provide evidence that the Treg/Th17 balance of circulating lymphocytes is skewed towards the Th17 cell lineage in preeclampsia.These results are suggestive that Treg/Th17 homeostasis might be essential for the semiallogeneic fetus to be tolerated within the maternal environment. -Blockade of inducible costimulator (ICOS) inhibits accumulation of polyfunctional Th1/Th17cCells and prevents autoimmune arthritis
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.124 | 0.075 |
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".