Actinin‐4 controls survival signaling in B cells by limiting the lateral mobility of B‐cell antigen receptors
Bibliographic record
Abstract
The structure and dynamics of F-actin networks in the cortical area of B cells control the signal efficiency of B-cell antigen receptors (BCRs). Although antigen-induced signaling has been studied extensively, the role of cortical F-actin in antigen-independent tonic BCR signaling is less well understood. Because these signals are essential for the survival of B cells and are consequently exploited by several B-cell lymphomas, we assessed how the cortical F-actin structure influences tonic BCR signal transduction. We employed genetic variants of a primary cell-like B-cell line that can be rendered quiescent to show that cross-linking of actin filaments by α-actinin-4 (ACTN4), but not ACTN1, is required to preserve the dense architecture of F-actin in the cortical area of B cells. The reduced cortical F-actin density in the absence of ACTN4 resulted in increased lateral BCR diffusion. Surprisingly, this was associated with reduced tonic activation of BCR-proximal effector proteins, extracellular signal-regulated kinase, and pro-survival pathways. Accordingly, ACTN4-deficient B-cell lines and primary human B cells exhibit augmented apoptosis. Hence, our findings reveal that cortical F-actin architecture regulates antigen-independent tonic BCR survival signals in human B cells.
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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".