Comparative ultrastructure of CRM1-Nucleolar bodies (CNoBs), Intranucleolar bodies (INBs) and hybrid PML/p62 bodies uncovers new facets of nuclear body dynamic and diversity
Bibliographic record
Abstract
In order to gain insights on the nuclear organization in mammalian cells, we characterized ultrastructurally nuclear bodies (NBs) previously described as fluorescent foci. Using high resolution immunoelectron microscopy (I-EM), we provide evidence that CNoBs (CRM1-Nucleolar bodies) and INBs (Intranucleolar bodies) are distinct genuine nucleolar structures in untreated HeLa cells. INBs are fibrillar and concentrate the post-translational modifiers SUMO1 and SUMO-2/3 as strongly as PML bodies. In contrast, the smallest CRM1-labeled CNoBs are vitreous, preferentially located at the periphery of the nucleolus and, intricately linked to the chromatin network. Upon blockage of the CRM1-dependent nuclear export by leptomycin B (LMB), CNoBs disappear while p62/SQSTM1-containing fibrillar nuclear bodies are induced. These p62 bodies are enriched in ubiquitinated proteins. They progressively associate with PML bodies to form hybrid bodies of which PML decorates the periphery while p62/SQSTM1 is centrally-located. Our study is expanding the repertoire of nuclear bodies; revealing a previously unrecognized composite nucleolar landscape and a new mode of interactions between ubiquitous (PML) and stress-induced (p62) nuclear bodies, resulting in the formation of hybrid bodies.
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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".