Promyelocytic Leukemia (Pml) Nuclear Bodies Are Protein Structures That Do Not Accumulate RNA
Bibliographic record
Abstract
The promyelocytic leukemia (PML) nuclear body (also referred to as ND10, POD, and Kr body) is involved in oncogenesis and viral infection. This subnuclear domain has been reported to be rich in RNA and a site of nascent RNA synthesis, implicating its direct involvement in the regulation of gene expression. We used an analytical transmission electron microscopic method to determine the structure and composition of PML nuclear bodies and the surrounding nucleoplasm. Electron spectroscopic imaging (ESI) demonstrates that the core of the PML nuclear body is a dense, protein-based structure, 250 nm in diameter, which does not contain detectable nucleic acid. Although PML nuclear bodies contain neither chromatin nor nascent RNA, newly synthesized RNA is associated with the periphery of the PML nuclear body, and is found within the chromatin-depleted region of the nucleoplasm immediately surrounding the core of the PML nuclear body. We further show that the RNA does not accumulate in the protein core of the structure. Our results dismiss the hypothesis that the PML nuclear body is a site of transcription, but support the model in which the PML nuclear body may contribute to the formation of a favorable nuclear environment for the expression of specific genes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.001 | 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".