The Dynamics of Mammalian P Body Transport, Assembly, and Disassembly In Vivo
Bibliographic record
Abstract
Exported mRNAs are targeted for translation or can undergo degradation by several decay mechanisms. The 5'-->3' degradation machinery localizes to cytoplasmic P bodies (PBs). We followed the dynamic properties of PBs in vivo and investigated the mechanism by which PBs scan the cytoplasm. Using proteins of the decapping machinery, we asked whether PBs actively scan the cytoplasm or whether a diffusion-based mechanism is sufficient. Live-cell imaging showed that PBs were anchored mainly to microtubules. Quantitative single-particle tracking demonstrated that most PBs exhibited spatially confined motion dependent on microtubule motion, whereas stationary PB pairs were identified at the centrosome. Some PBs translocated in long-range movements on microtubules. PB mobility was compared with mitochondria, endoplasmic reticulum, peroxisomes, SMN bodies, and stress granules, and diffusion coefficients were calculated. Disruption of the microtubule network caused a significant reduction in PB mobility together with an induction of PB assembly. However, FRAP measurements showed that the dynamic flux of assembled PB components was not affected by such treatments. FRAP analysis showed that the decapping enzyme Dcp2 is a nondynamic PB core protein, whereas Dcp1 proteins continuously exchanged with the cytoplasm. This study reveals the mechanism of PB transport, and it demonstrates how PB assembly and disassembly integrate with the presence of an intact cytoskeleton.
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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".