The pool of preactivated Lck in the initiation of T‐cell signaling: a critical re‐evaluation of the Lck standby model
Bibliographic record
Abstract
The initiation of T-cell receptor (TCR) signaling, based on the cobinding of TCR and CD4-Lck heterodimer to a peptide-major histocompatibility complex II on antigen presenting cells, represents a classical model of T-cell signaling. What is less clear however, is the mechanism which translates TCR engagement to the phosphorylation of immunoreceptor tyrosine-based activation motifs on CD3 chains and how this event is coupled to the delivery of Lck function. Recently proposed 'standby model of Lck' posits that resting T-cells contain an abundant pool of constitutively active Lck (pY394(Lck)) required for TCR triggering, and this amount, upon TCR engagement, remains constant. Here, we show that although maintenance of the limited pool of pY394(Lck) is necessary for the generation of TCR proximal signals in a time-restricted fashion, the total amount of this pool, ~2%, is much smaller than previously reported (~40%). We provide evidence that this dramatic discrepancy in the content of pY394(Lck)is likely the consequence of spontaneous phosphorylation of Lck that occurred after cell solubilization. Additional discrepancies can be accounted for by the sensitivity of different pY394(Lck)-specific antibodies and the type of detergents used. These data suggest that reagents and conditions used for the quantification of signaling parameters must be carefully validated and interpreted. Thus, the limited size of pY394(Lck) pool in primary T-cells invites a discussion regarding the adjustment of the quantitative parameters of the standby model of Lck and reevaluation of the mechanism by which this pool contributes to the generation of proximal TCR signaling.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".