Th1- and Th2-like cytokine production by first trimester decidual large granular lymphocytes is influenced by HLA-G and HLA-E
Bibliographic record
Abstract
During normal early pregnancy, a particular immune environment in the decidua and the expression of non-classical HLA-G and HLA-E molecules on the invading trophoblast are assumed to be essential for the tolerance of the fetus. To assess whether HLA-G and HLA-E influence the cytokine production of their putative target cells [large granular lymphocytes (LGL)], we analysed the concentrations of tumour necrosis factor (TNF-alpha), interferon (IFN)-gamma, interleukin (IL)-10, IL-13 and granulocyte-macrophage colony stimulating factor (GM-CSF) in supernatants of isolated first trimester LGL co-cultured with HLA-G or HLA-E transfected K-562 leukaemia cells lacking the classical HLA class I and II molecules. In comparison with that observed with untransfected K-562 cells, co-culture of LGL with HLA-G-expressing cells significantly reduced the concentration of all cytokines investigated (TNF-alpha, IL-10 and GM-CSF, P < 0.01; IFN-gamma and IL-13, P < 0.05). In contrast, co-culture of LGL with HLA-E-expressing cells significantly (P < 0.01) decreased only IL-10 production, although a strong tendency towards reduced IL-13 levels was also observed. In the co-culture system presented, membrane-bound HLA-G and, to a lesser extent, HLA-E expression affected cytokine release by decidual LGL in a manner not consistent with the Th1/Th2 paradigm. In conclusion, our data are indicative of a general immune-suppressive effect of HLA-G on LGL activity.
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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 | 0.001 | 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".