Effect of rapamycin on mitochondria and lysosomes in fibroblasts from patients with mtDNA mutations
Bibliographic record
Abstract
Maintaining mitochondrial function and dynamics is crucial for cellular health. In muscle, defects in mitochondria result in severe myopathies where accumulation of damaged mitochondria causes deterioration and dysfunction. Importantly, understanding the role of mitochondria in disease is a necessity to determine future therapeutics. One of the most common myopathies is mitochondrial encephalopathy lactic acidosis stroke-like episodes (MELAS), which has no current treatment. Recently, patients with MELAS treated with rapamycin exhibited improved clinical outcomes. However, the cellular mechanisms of rapamycin effects in patients with MELAS are currently unknown. In this study, we used cultured skin fibroblasts as a window into the mitochondrial dysfunction evident in MELAS cells, as well as to study the mechanisms of rapamycin action, compared with control, healthy individuals. We observed that mitochondria from patients were fragmented, had a threefold decline in the average speed of motility, a twofold reduced mitochondrial membrane potential, and a 1.5- to 2-fold decline in basal respiration. Despite the reduction in mitochondrial function, mitochondrial import protein Tim23 was elevated in patient cell lines. MELAS fibroblasts exhibited increased MnSOD levels and lysosomal function when compared with healthy controls. Treatment of MELAS fibroblasts with rapamycin for 24 h resulted in increased mitochondrial respiration compared with control cells, a higher lysosome content, and a greater localization of mitochondria to lysosomes. Our studies suggest that rapamycin has the potential to improve cellular health even in the presence of mtDNA defects, primarily via an increase in lysosomal content.
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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".