Nuclear pore rearrangements and nuclear trafficking in cardiomyocytes from rat and human failing hearts
Bibliographic record
Abstract
AIMS: During cardiac hypertrophy, cardiomyocytes (CMs) increase in the size and expression of cytoskeletal proteins while reactivating a foetal gene programme. The process is proposed to be dependent on increased nuclear export and, since nuclear pore trafficking has limited capacity, a linked decrease in import. Our objective was to investigate the role of nuclear import and export in control of hypertrophy in rat and human heart failure (HF). METHODS AND RESULTS: In myocardial tissue and isolated CMs from patients with dilated cardiomyopathy, nuclear size was increased; Nucleoporin p62, cytoplasmic RanBP1, and nuclear translocation of importins (α and β) were decreased while Exportin-1 was increased. CM from a rat HF model 16 weeks after myocardial infarction (MI) reproduced these nuclear changes. Nuclear import, determined by the rate of uptake of nuclear localization sequence (NLS)-tagged fluorescent substrate, was also decreased and this change was observed from 4 weeks after MI, before HF has developed. Treatment of isolated rat CMs with phenylephrine (PE) for 48 h produced similar cell and nuclear size increases, nuclear import and export protein rearrangement, and NLS substrate uptake decrease through p38 MAPK and HDAC-dependent pathways. The change in NLS substrate uptake occurred within 15 min of PE exposure. Inhibition of nuclear export with leptomycin B reversed established nuclear changes in PE-treated rat CMs and decreased NLS substrate uptake and cell/nuclear size in human CMs. CONCLUSIONS: Nuclear transport changes related to increased export and decreased import are an early event in hypertrophic development. Hypertrophy can be prevented, or even reversed, by targeting import/export, which may open new therapeutic opportunities.
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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) | 0.002 | 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".