A Damage Sensor Associated with the Cuticle Coordinates Three Core Environmental Stress Responses in<i>Caenorhabditis elegans</i>
Bibliographic record
Abstract
Abstract Although extracellular matrices function as protective barriers to many types of environmental insult, their role in sensing stress and regulating adaptive gene induction responses has not been studied carefully... Extracellular matrix barriers and inducible cytoprotective genes form successive lines of defense against chemical and microbial environmental stressors. The barrier in nematodes is a collagenous extracellular matrix called the cuticle. In Caenorhabditis elegans, disruption of some cuticle collagen genes activates osmolyte and antimicrobial response genes. Physical damage to the epidermis also activates antimicrobial responses. Here, we assayed the effect of knocking down genes required for cuticle and epidermal integrity on diverse cellular stress responses. We found that disruption of specific bands of collagen, called annular furrows, coactivates detoxification, hyperosmotic, and antimicrobial response genes, but not other stress responses. Disruption of other cuticle structures and epidermal integrity does not have the same effect. Several transcription factors act downstream of furrow loss. SKN-1/Nrf and ELT-3/GATA are required for detoxification, SKN-1/Nrf is partially required for the osmolyte response, and STA-2/Stat and ELT-3/GATA for antimicrobial gene expression. Our results are consistent with a cuticle-associated damage sensor that coordinates detoxification, hyperosmotic, and antimicrobial responses through overlapping, but distinct, downstream signaling.
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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 | 0.000 |
| 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".