Methylene Blue Protects against TDP-43 and FUS Neuronal Toxicity in C. elegans and D. rerio
Bibliographic record
Abstract
The DNA/RNA-binding proteins TDP-43 and FUS are found in protein aggregates in a growing number of neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and related dementia, but little is known about the neurotoxic mechanisms. We have generated Caenorhabditis elegans and zebrafish animal models expressing mutant human TDP-43 (A315T or G348C) or FUS (S57Δ or R521H) that reflect certain aspects of ALS including motor neuron degeneration, axonal deficits, and progressive paralysis. To explore the potential of our humanized transgenic C. elegans and zebrafish in identifying chemical suppressors of mutant TDP-43 and FUS neuronal toxicity, we tested three compounds with potential neuroprotective properties: lithium chloride, methylene blue and riluzole. We identified methylene blue as a potent suppressor of TDP-43 and FUS toxicity in both our models. Our results indicate that methylene blue can rescue toxic phenotypes associated with mutant TDP-43 and FUS including neuronal dysfunction and oxidative stress.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".