Mitotic accumulations of PML protein contribute to the re-establishment of PML nuclear bodies in G1
Bibliographic record
Abstract
Although the mechanism of chromosomal segregation is well known, it is unclear how other nuclear compartments such as promyelocytic leukemia (PML) nuclear bodies partition during mitosis and re-form in G1. We demonstrate that PML nuclear bodies partition via mitotic accumulations of PML protein (MAPPs), which are distinct from PML nuclear bodies in their dynamics, biochemistry and structure. During mitosis PML nuclear bodies lose biochemical components such as SUMO-1 and Sp100. We demonstrate that MAPPs are also devoid of Daxx and these biochemical changes occur prior to chromatin condensation and coincide with the loss of nuclear membrane integrity. MAPPs are highly mobile, yet do not readily exchange PML protein as demonstrated by fluorescence recovery after photo-bleaching (FRAP). A subset of MAPPs remains associated with mitotic chromosomes, providing a possible nucleation site for PML nuclear body formation in G1. As the nuclear envelope reforms in late anaphase, these nascent PML nuclear bodies accumulate components sequentially, for example Sp100 and SUMO-1 before Daxx. After cytokinesis, MAPPs remain in the cytoplasm long after the reincorporation of splicing components and their disappearance coincides with new PML nuclear body formation even in the absence of new protein synthesis. The PML protein within MAPPs is not degraded during mitosis but is recycled to contribute to the formation of new PML nuclear bodies in daughter nuclei. The recycling of PML protein from one cell cycle to the next via mitotic accumulations may represent a common mechanism for the partitioning of other nuclear bodies during mitosis.
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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 | 0.001 |
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".