MEKK-3 Acts Cooperatively with NSY-1 in SKN-1-Dependent Manner against Oxidative Stress and Aging in Caenorhabditis elegans
Bibliographic record
Abstract
Oxidative stress resulting from reactive oxygen species and other toxic metabolites is involved in human diseases, and it plays an important role in aging. In Caenorhabditis elegans, SKN-1 is required for protection against oxidative stress and aging. As p38 mitogen-activated protein kinase signaling is activated in response to oxidative stress, SKN-1 accumulates in intestinal nuclei and induces phase II detoxification genes. However, NSY-1, a well-known mitogen-activated protein kinase kinase kinase (MAPKKK) of C. elegans, acts as a partial regulator of the SKN-1-induced oxidative stress signaling pathway, suggesting that the regulator for optimal activation of SKN-1 remains unknown. Here, we report a MAPKKK, MEKK-3, as a new regulator required for full activation of SKN-1-mediated resistance against oxidative stress and aging. In RNA-interference-based screening, we found that the simultaneous knockdown of mekk-3 and nsy-1 significantly decreased the oxidative stress resistance and survival of SKN-1 transgenic worms. MEKK-3 was induced in response to oxidative stress. Mechanistic analysis revealed that double knockdown of mekk-3 and nsy-1 completely suppressed the nuclear localization of SKN-1. These results were reproduced in mutant worms in which SKN-1 is constitutively localized to intestinal nuclei. In addition, mekk-3 and nsy-1 were required for optimal induction of SKN-1 target genes such as gcs-1 and trx-1. These data indicate that MEKK-3 plays an essential role in the SKN-1-dependent signaling pathway involved in oxidative stress resistance and longevity by cooperating with NSY-1.
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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) | 0.001 | 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".