T Cell-Dendritic Cell Immunological Synapses Contain TCR-dependent CD28-CD80 Clusters That Recruit Protein Kinase Cθ
Bibliographic record
Abstract
Short-lived TCR microclusters and a longer-lived protein kinase Ctheta-focusing central supramolecular activation cluster (cSMAC) have been defined in model immunological synapses (IS). In different model systems, CD28-mediated costimulatory interactions have been detected in microclusters, the cSMAC, or segregated from the TCR forming multiple distinct foci. The relationship between TCR and costimulatory molecules in the physiological IS of T cell-dendritic cell (DC) is obscure. To study the dynamic relationship of CD28-CD80 and TCR interactions in the T cell-DC IS during Ag-specific T cell activation, we generated CD80-eCFP mice using bacterial artificial chromosome transgenic technology. In splenic DCs, endogenous CD80 and CD80-eCFP localized to plasma membrane and Golgi apparatus, and CD80-eCFP was functional in vivo. In the OT-II T cell-DC IS, multiple segregated TCR, CD80, and LFA-1 clusters were detected. In the T cell-DC synapse CD80 clusters were colocalized with CD28 and PKCtheta, a characteristic of the cSMAC. Acute blockade of TCR signaling with anti-MHC Ab resulted in a rapid reduction in Ca(2+) signaling and the number and size of the CD80 clusters, a characteristic of TCR microclusters. Thus, the T cell-DC interface contains dynamic costimulatory foci that share characteristics of microclusters and cSMACs.
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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 | 0.001 |
| 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".