Regulation of Cell Death by Recycling Endosomes and Golgi Membrane Dynamics via a Pathway Involving Src-family kinases, Cdc42 and Rab11a
Bibliographic record
Abstract
Actin dynamics and membrane trafficking influence cell commitment to programmed cell death through largely undefined mechanisms. To investigate how actin and recycling endosome (RE) trafficking can engage death signaling, we studied the death program induced by the adenovirus early region 4 open reading frame 4 (E4orf4) protein as a model. We found that in the early stages of E4orf4 expression, Src-family kinases (SFKs), Cdc42, and actin perturbed the organization of the endocytic recycling compartment and promoted the transport of REs to the Golgi apparatus, while inhibiting recycling of protein cargos to the plasma membrane. The resulting changes in Golgi membrane dynamics that relied on actin-regulated Rab11a membrane trafficking triggered scattering of Golgi membranes and contributed to the progression of cell death. A similar mobilization of RE traffic mediated by SFKs, Cdc42 and Rab11a also contributed to Golgi fragmentation and to cell death progression in response to staurosporine, in a caspase-independent manner. Collectively, these novel findings suggest that diversion of RE trafficking to the Golgi complex through a pathway involving SFKs, Cdc42, and Rab11a plays a general role in death signaling by mediating regulated changes in Golgi dynamics.
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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) | 0.000 | 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".