Size, position and dynamic behavior of PML nuclear bodies following cell stress as a paradigm for supramolecular trafficking and assembly
Bibliographic record
Abstract
The promyelocytic leukemia (PML) protein has been implicated in many cellular pathways, but it is unclear whether the accumulation of PML and other proteins into PML nuclear bodies is a regulated or random process. In this paper we have used a variety of physiological stresses, including heat stress, Cd+2 exposure and adenovirus E1A expression, as tools to study the principles underlying the assembly/disassembly, integrity and dynamic behavior of PML bodies. Using live-cell imaging and immunofluorescence microscopy, we observe that PML bodies are positionally stable over time intervals of a few hours. After stress, however, microstructures form as a result of fission or budding from the surface of 'parental' PML bodies. Since new PML bodies do not form at new locations, and the relative sizes observed before heat shock are preserved after recovery, we conclude that there are pre-determined locations for PML bodies, and that they are not random accumulations of protein. Over-expression of small ubiquitin-like modifier (SUMO-1) prevents stress-induced disassembly of PML bodies, implicating SUMO-1 as a key regulator of PML body integrity. Stress-induced fission of SUMO-1-deficient microstructures from parental PML bodies may be a mechanism to change local chromatin domain environments by the dispersal of protein factors. PML bodies may provide a useful paradigm for the dynamics and integrity of other supramolecular protein complexes involved in processes such as transcription, RNA processing DNA repair and replication.
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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".