Insulin signaling in the aging of healthy and proteotoxically stressed mechanosensory neurons
Bibliographic record
Abstract
Insulin signaling is central to cellular metabolism and organismal aging. However, the role of insulin signaling in natural and proteotoxically stressed aging neurons has yet to be fully described. We studied aging of Caenorbaditis elegans mechanosensory neurons expressing a neurotoxic expanded polyglutamine transgene (polyQ128), or lacking this proteotoxicity stressor (polyQ0), under conditions in which the insulin signaling pathway was disrupted by RNA interference (RNAi). We describe specific changes in lifespan, mechanosensory neuronal morphologies, and mechansensory function following RNAi treatment targeting the insulin signaling pathway. Overall, we confirmed that transcription factor DAF-16 is neuroprotective in the proteotoxically stressed model, though not strikingly in the naturally aging model. Decreased insulin signaling through daf-2 RNAi improved mechanosensory function in both models and decreased protein aggregation load in polyQ128, yet showed opposing effects on accumulation of neuronal aberrations in both strains. Decreased daf-2 signaling slightly enhanced mechanosensation while greatly enhancing branching of the mechanosensory neuron axons and dendrites in polyQ0 animals, suggesting that branching is an adaptive response in natural aging. These effects in polyQ0 did not appear to involve DAF-16, suggesting the existence of a non-canonical DAF-2 pathway for the modulation of morphological adaptation. However, in polyQ128 animals, decreased daf-2 signaling significantly enhanced mechanosensation while decreasing neuronal aberrations. Unlike other interventions that reduce the strength of insulin signaling, daf-2 RNAi dramatically redistributed large polyQ128 aggregates to the cell body, away from neuronal processes. Our results suggest that insulin signaling strength can differentially affect specific neurons aging naturally or under proteotoxic stress.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".