Activated SKN-1 alters the aging trajectories of long-lived <i>Caenorhabditis elegans</i> mutants
Bibliographic record
Abstract
In the presence of stressful environments, the SKN-1 cytoprotective transcription factor is activated to induce the expression of gene targets that can restore homeostasis. However, chronic activation of SKN-1 results in diminished health and a reduction of lifespan. Here, we demonstrate the necessity of modulating SKN-1 activity to maintain the longevity-promoting effects associated with genetic mutations that impair daf-2/insulin receptor signaling, the eat-2 model of dietary restriction, and glp-1-dependent loss of germ cell proliferation. A hallmark of animals with constitutive SKN-1 activation is the age-dependent loss of somatic lipids, and this phenotype is linked to a general reduction in survival in animals harboring the skn-1gf allele. Surprisingly, daf-2lf; skn-1gf double mutant animals do not redistribute somatic lipids, which suggests the insulin signaling pathway functions downstream of SKN-1 in the maintenance of lipid distribution. As expected, the eat-2lf allele, which independently activates SKN-1, continues to display somatic lipid depletion in older ages with and without the skn-1gf activating mutation. In contrast, the presence of the skn-1gf allele does not lead to somatic lipid redistribution in glp-1lf animals that lack a proliferating germline. Taken together, these studies support a genetic model where SKN-1 activity is an important regulator of lipid mobilization in response to nutrient availability that fuels the developing germline by engaging the daf-2/insulin receptor pathway.
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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 | 0.001 |
| 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".