Induction of latency‐associated peptide (transforming growth factor‐β<sub>1</sub>) expression on CD4<sup>+</sup> T cells reduces Toll‐like receptor 4 ligand‐induced tumour necrosis factor‐α production in a transforming growth factor‐β‐dependent manner
Bibliographic record
Abstract
CD4(+) T cells expressing the latent form of transforming growth factor-β [latency-associated peptide (LAP) (TGF-β(1))] play an important role in the modulation of immune responses. Here, we identified a novel peptide ligand (GPC(81-95) ) with an intrinsic ability to induce membrane-bound LAP (TGF-β(1)) expression on a subpopulation of human CD4(+) T cells (using flow cytometry; ranging from 0·8% to 2·6%) and stimulate peripheral blood mononuclear cells to release LAP (TGF-β(1) ) (using ELISPOT assay; ranging from 0·03% to 0·16%). In spite of this low percentage of responding cells, GPC(81-95) significantly reduced Toll-like receptor 4 ligand-induced tumour necrosis factor-α production in a TGF-β(1) - and CD4(+) T-cell-dependent manner. The results demonstrate that GPC(81-95) is a useful tool to study the functional properties of a subpopulation of LAP (TGF-β(1))(+) CD4(+) T cells and suggest a pathway that can be exploited to suppress inflammatory response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".