Intracellular sequestration of amiodarone: role of vacuolar ATPase and macroautophagic transition of the resulting vacuolar cytopathology
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Tissue deposits of the anti-arrhythmic drug amiodarone are a major source of side effects (skin discoloration, etc.). We addressed the mechanism of the concentration of amiodarone in cells, and characterized the resulting vacuolar cytopathology and its evolution towards macroautophagy. EXPERIMENTAL APPROACH: Sequestration of amiodarone in human cells (macrophages, smooth muscle cells, HEK 293a cells) was evaluated using its violet fluorescence and cytopathology using GFP-conjugated subcellular markers. Autophagic signalling was probed by immunoblotting for the effector protein LC3. A patient biopsy of amiodarone-induced blue-gray skin discoloration was investigated for the presence of macroautophagy (immunofluorescence for LC3). KEY RESULTS: Most of the amiodarone (1-20 microM, 4-24 h) captured by cultured cells (macrophages were most avid) was present in enlarged vacuoles. The specific vacuolar ATPase (V-ATPase) inhibitors, bafilomycin A1 or FR167356, prevented vacuolization and drug uptake. Vacuoles in HEK 293a cells were positive for markers of late endosomes and lysosomes (GFP-Rab7, -CD63) and for an effector of macroautophagy, GFP-LC3. The vacuoles accumulated endogenous LC3 and filled with lipids (Nile red staining) following longer amiodarone treatments (> or =24 h). The electrophoretic mobility of both GFP-LC3 and endogenous LC3 changed, showing activation in response to amiodarone. Paraffin tissue sections of the pigmented skin exhibited granular LC3 accumulation in superficial dermis macrophages. CONCLUSION AND IMPLICATIONS: Vacuolar sequestration of amiodarone occurs at concentrations close to therapeutic levels, is mediated by V-ATPase and evolves towards persistent macroautophagy and phospholipidosis. This cytopathology is not cell type specific, but tissue macrophages appear to be particularly susceptible.
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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 | 0.000 |
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".