Low-Concentration Methylene Blue Maintains Energy Production and Strongly Improves Survival of Leigh Syndrome French Canadian Skin Fibroblasts
Bibliographic record
Abstract
Leigh syndrome French Canadian (LSFC) is a recessive disease caused by mutations in the LRPPRC gene (leucine-rich pentatricopeptide repeat containing protein). These mutations induce a cytochrome c oxidase (COX) deficiency resulting in episodes of acute acidotic crisis that will often lead to death. There is no effective treatment. Methylene blue (MB) is a redox dye that increases COX content and activity in vitro and in vivo suggesting that MB could prevent and treat LSFC. In this study, the protective effect of low-concentration MB was tested on two LSFC cell lines, including LSFC-F1, homozygous for the mutation A354V, and LSFC-F2 a compound heterozygous for the mutations A354V and C12775STOP. MB effect on metabolic activity was assessed on both LSFC cells in stable and acidotic conditions. For LSFC-F1, results showed that metabolic activity drastically decline after 96 hours in both conditions but not LSFC-F2 and normal cells. MB completely prevents the decrease of metabolic activity in LSFC-F1. Intracellular ATP content was also measured in both culture media. After 96 hours in acidotic medium, ATP content was almost completely depleted for both LSFC cells. Interestingly, MB completely restores ATP content in LSFC-F1 and LSFC-F2 cells. Finally, MB strongly improves the survival of both LSFC cells.
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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".