Bibliographic record
Abstract
Many neurodegenerative conditions have oxidative stress burdens where levels of reactive oxygen species (ROS) exceed the antioxidant capacity of the neuron. ROS can induce wide-ranging damage in a cell and this is prevented by the activation of antioxidant responses including autophagy. Jun-kinase (JNK) is stimulated by ROS and mediates antioxidant responses via the activation of the transcriptional activators Fos and Jun (AP-1). In recently published work we examined Drosophila mutants with overgrown larval neuromuscular synapses, mutants that also show all the hallmarks of lysosomal storage disease (LSD). We find that we can reverse this synaptic overgrowth by reducing the oxidative stress burden, and that synaptic overgrowth is mediated by autophagy and JNK-AP-1 activity. We also examined animals defective for protection from oxidative stress and found that they too have synapse overgrowth generated by JNK-AP-1 activity. Treatment of larvae with a known ROS-generating toxin, paraquat, yielded similar synaptic responses. The observations that oxidative stress responses, potentially acting through autophagy, can generate synaptic growth suggest that ROS may be a potent regulator of synapse size and function. These findings have intriguing implications for aging neurons, neurodegenerative conditions and the interpretation of metabolic demand during learning and memory.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".