Embryonic stem cell-derived factors inhibit T effector activation and induce T regulatory cells by modulating PKC-θ activation. (63.29)
Bibliographic record
Abstract
Abstract Embryonic stem cells (ESC) possess immune privileged properties and have the capacity to modulate immune activation. However, the mechanisms by which ESC inhibit immune activation remain mostly unknown. We have previously shown that ESC derived factors block dendritic cell maturation and thereby affect T cell activation indirectly. Our ongoing studies have elucidated that ESC derived factors also have a direct effect on T cell activation. In mixed lymphocyte reaction assays, ESC derived factors significantly down-regulated IL-2 and IFN-γ expression, while up-regulating IL-10 and TGF-β expression. Also, ESC derived factors suppressed the expression of Th1 transcription factor Tbet, while enhancing the expression of Treg transcription factor Foxp3. Furthermore, PBMC/purified T cells activated with CD3/CD28, ConA and PMA proliferated poorly in the presence of ESC derived factors, while proliferation in response to ionomycin was not affected. Western blot analysis indicated that ESC derived factors prevented PKC-θ phosphorylation without influencing total PKC-θ levels. Moreover, IκB-α degradation was abrogated, confirming absence of PKC-θ activity. Incubation of ESC derived factors with recombinant GST-PKC-θ resulted in the pull-down of four proteins. The purified proteins are currently being analyzed by mass spectrometry. In conclusion, ESC’s are able to directly impact T cell activation and polarization, likely by negatively regulating PKC-θ through potentially novel factors.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".