HLA‐G has a concentration‐dependent effect on the generation of an allo‐CTL response
Bibliographic record
Abstract
Human leucocyte antigen (HLA) -G is expressed on trophoblast cells during pregnancy, suggesting a role in protection of the semiallogeneic fetus. Published data suggest that HLA-G protects a cell against natural killer cell lysis. It has been hypothesized that HLA-G may also protect the fetus by preventing allo-cytotoxic T lymphocyte (CTL) responses. To test this hypothesis, we assayed the effects of various concentrations of purified HLA-G on CTL response in a mixed lymphocyte culture (MLC) system. We found that concentrations > or =0.1 microg/ml of HLA-G suppressed the allo-CTL response by 30-100% over the control, but, paradoxically, concentrations of 0.01-0.05 microg/ml of HLA-G augmented the allo-CTL response by 25-50% over the control. Concentrations < or = 0.001 microg/ml HLA-G had no effect. Addition of HLA-G to preprimed allo-CTL effector cells did not affect their killing ability. Allo-CTL suppressive doses of HLA-G induced a T helper type 2 (Th2) cytokine response, whereas allo-CTL-enhancing doses of HLA-G induced a Th1-type cytokine response. HLA-G purified from first-trimester placenta does not affect allo-proliferative responses nor does it alter the percentage of CD4+ or CD8+ T cells in MLCs. These findings support a potential role for HLA-G-mediated suppression of allo-CTL formation in normal pregnancies. In addition, the effects observed at lower concentrations of HLA-G may have interesting implications for the condition of pre-eclampsia in which concentrations of this HLA class I molecule are reduced.
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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) | 0.001 | 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".