The FMRFamide Neuropeptide FLP-20 Acts as a Systemic Signal for Starvation Responses in Caenorhabditis elegans
Bibliographic record
Abstract
Most animals face frequent periods of starvation throughout their entire life and thus need to appropriately adjust their behavior and metabolism during starvation for their survival.Such adaptive responses are regulated by a complex set of systemic signals, including hormones and neuropeptides.While much progress has been made in identifying pathways that regulate nutrient-excessive states, it is still incompletely understood how animals systemically signal their nutrient-deficient states.Here, we showed that the FMRFamide neuropeptide FLP-20 modulates a systemic starvation response in Caenorhabditis elegans.We found that mutation of flp-20 rescued the starvation hypersensitivity of the G protein β-subunit gpb-2 mutants by suppressing excessive autophagy.FLP-20 acted in AIB neurons, where the metabotropic glutamate receptor MGL-2 also functions to modulate a systemic starvation response.Furthermore, FLP-20 modulated starvation-induced fat degradation in a manner dependent on the receptor-type guanylate cyclase GCY-28.Collectively, our results reveal a circuit that senses and signals nutrient-deficient states to modulate a systemic starvation response in multicellular organisms.
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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 | 0.000 |
| 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 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".