Targeting tau mitigates mitochondrial fragmentation and oxidative stress in amyotrophic lateral sclerosis
Bibliographic record
Abstract
Abstract Understanding the mechanisms underlying amyotrophic lateral sclerosis (ALS) is crucial for the development of new therapies. Recent evidence suggest that tau may be involved in ALS pathogenesis. Here, we demonstrated that hyperphosphorylated tau (pTau-S396) is mis-localized to synapses in human post-mortem motor cortex (mCTX) across ALS subtypes. Treatment with ALS synaptoneurosomes (SNs) derived from post-mortem mCTX, enriched in pTau-S396, increased oxidative stress, induced mitochondrial fragmentation, and altered mitochondrial connectivity in vitro . Furthermore, our findings revealed that pTau-S396 interacts with the pro-fission dynamin-related protein (DRP1), and similar to pTau-S396, DRP1 accumulated in ALS SNs across ALS subtypes. Lastly, reducing tau with a specific bifunctional degrader, QC-01-175, prevented ALS SNs-induced mitochondrial fragmentation and oxidative stress in vitro . Collectively, our findings suggest that increases in pTau-S396 may lead to mitochondrial fragmentation and oxidative stress in ALS and decreasing tau may provide a novel strategy to mitigate mitochondrial dysfunction in ALS. Graphical abstract pTau-S396 mis-localizes to synapses in ALS. ALS synaptoneurosomes (SNs), enriched in pTau-S396, increase oxidative stress and induce mitochondrial fragmentation in vitro . pTau-S396 interacts with the pro-fission GTPase DRP1 in ALS. Reducing tau with a specific degrader, QC-01-175, mitigates ALS SNs-induced mitochondrial fragmentation and increases in oxidative stress in vitro .
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".