Constitutive LcK activity drives sensitivity differences between CD8+ memory T cell subsets
Bibliographic record
Abstract
Abstract CD8+ T cells develop increased sensitivity following antigen experience, and differences in sensitivity exist between T cell memory subsets. How differential T cell receptor (TCR) signaling between memory subsets contributes to sensitivity differences is unclear. We show that constitutive activity of lymphocyte-specific protein tyrosine kinase (Lck) is greater in effector memory T cells (TEM) compared with central memory T cells (TCM), leading to enhanced activation signaling, including Zeta-chain-associated protein kinase 70 (Zap-70) phosphorylation and intracellular calcium influx, and resulting in increased cytotoxic effector function in TEM. We provide evidence that the differences in Lck activity between CD8+ TCM and TEM are due to differential regulation by SH2 domain-containing phosphatase-1 (Shp-1) and C-terminal Src kinase (Csk). Together, this work demonstrates a role for constitutive Lck activity in controlling antigen sensitivity, and suggests that differential activities of TCR-proximal signaling components may contribute to establishing the divergent effector properties of TCM and TEM.
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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 | 0.000 |
| 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".