RNAi of the elastomeric protein resilin reduces jump velocity and resilience to damage in locusts
Bibliographic record
Abstract
Resilin, an elastomeric protein with remarkable physical properties that outperforms synthetic rubbers, is a near-ubiquitous feature of the power amplification mechanisms used by jumping insects. Catapult-like mechanisms, which incorporate elastic energy stores formed from a composite of stiff cuticle and resilin, are frequently used by insects to translate slow muscle contractions into rapid-release recoil movements. The precise role of resilin in these jumping mechanisms remains unclear, however. We used RNAi to reduce resilin deposition in the principal energy-storing springs of the desert locust ( Schistocerca gregaria ) before measuring jumping performance. Knockdown reduced the amount of resilin-associated fluorescence in the semilunar processes (SLPs) by 44% and reduced the cross-sectional area of the tendons of the hind leg extensor-tibiae muscle by 31%. This affected jumping in three ways: First, take-off velocity was reduced by 15% in knockdown animals, which could be explained by a change in the extrinsic stiffness of the extensor-tibiae tendon caused by the decrease in its cross-sectional area. Second, knockdown resulted in permanent breakages in the hind legs of 29% of knockdown locusts as tested by electrical stimulation of the extensor muscle, but none in controls. Third, knockdown locusts exhibited a greater decline in distance jumped when made to jump in rapid succession than did controls. We conclude that stiff cuticle acts as the principal elastic energy store for insect jumping, while resilin protects these more brittle structures against breakage from repeated use.
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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) | 0.002 | 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".