T cell-intrinsic protein kinase D3 is dispensable for the cells’ activation
Bibliographic record
Abstract
Protein kinases D (PKDs) are implicated in T cell receptor (TCR) signaling. Of the two T cell-expressed isoforms PKD2 and PKD3, however, only the former one is rather well understood in this immune cell type. Recently, we have observed a putative hyper-phenotype of T cells from conventional PKD3-knockout mice, which we explained as a secondary effect due to a skewed T cell compartment from naïve towards effector/memory T cells already under steady state conditions. Nonetheless, to this end it is not clear whether these aberrations are mediated by a T cell-intrinsic or -extrinsic function of PKD3. To address this question, we have investigated mice lacking PKD3 specifically in the T cell compartment. We could show that T cells from CD4-Cre-driven conditional knockout mice did not phenocopy the ones from conventional PKD3-knockout mice. In brief, no skewing in the T cell compartment of peripheral lymphoid organs, no hyper-activation upon stimulation in vitro or in vivo as well as no aberrations in follicular helper T cells (TFH) upon immunization were observed. Hence, although PKD3 is strongly regulated upon TCR stimulation, in T cells this kinase seems to be dispensable for their activation. The described skewing in the T cell compartment of conventional PKD3-deficient mice seems to be mediated by T cell-extrinsic mechanisms, thus once more emphasizing the importance of cell type-specific mouse models.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".