Muscle in the caterpillar<i>Manduca sexta</i>responds to an immune challenge, but at a cost, suggesting a physiological trade-off
Bibliographic record
Abstract
Although skeletal muscle is a specialized tissue that provides the motor for movement, it also participates in other functions, including the immune response. However, little is known about the effects of this multitasking on muscle. We show that muscle loses some of its capacity while it is participating in the immune response. Caterpillars (Manduca sexta) were exposed to an immune challenge, predator stress or a combination of immune challenge and predator stress. The expression of immune genes (toll-1, domeless, cactus, tube and attacin) increased in body wall muscle after exposure to an immune challenge. Muscle also showed a reduction in the amount of the energy storage molecule glycogen. During an immune challenge, the force of the defensive strike, an important anti-predator behaviour in M. sexta, was reduced. Caterpillars were also less able to defend themselves against a common enemy, the wasp Cotesia congregata, suggesting that the effect on muscle is biologically significant. Our results support the concept of an integrated defence system in which life-threatening events activate organism-wide responses. We suggest that increased mortality from predation is a non-immunological cost of infection in M. sexta. Our study also suggests that one reason non-immunological costs of infection exist is because of the participation of diverse organs, such as muscle, in immunity.
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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) | 0.001 | 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".