Signaling through HLA‐DR induces PKCβ‐dependent B cell death outside rafts
Bibliographic record
Abstract
Signals through HLA-DR molecules contribute to optimal activation of antigen-presenting cells (APC) during T cell/APC interactions participating in the generation of productive interactions, and to the induction of APC death, which has been postulated to play a role in the termination of the immune response. To understand how these molecules accommodate both cellular responses, we studied the not yet well-defined signaling events and the biochemical requirements for HLA-DR-mediated death. We demonstrate that in B cells the HLA-DR-activated protein kinase C (PKC) beta is required for HLA-DR-mediated death whereas the HLA-DR-activated Src family of PTK is redundant. In contrast to HLA-DR-mediated activation of Src kinase Lyn, the aggregation of HLA-DR molecules in lipid rafts is not required for HLA-DR-mediated PKC beta activation nor for the induction of cell death. Indeed, the bulk of HLA-DR-activated PKC beta reside outside rafts. This is the first report showing that HLA-DR-induced PKC beta activation is essential for the induction of B cell death via HLA-DR, and that these HLA-DR-mediated events do not require the integrity of rafts.
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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 | 0.001 |
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".