Flexible diet choice offsets protein costs of pathogen resistance in a caterpillar
Bibliographic record
Abstract
Mounting effective resistance against pathogens is costly in terms of energy and nutrients. However, it remains unexplored whether hosts can offset such costs by adjusting their dietary intake so as to recoup the specific resources involved. We test this possibility by experimentally challenging caterpillars (Spodoptera littoralis) with a highly virulent entomopathogen (nucleopolyhedrovirus), under dietary regimes varying in the content of protein and digestible carbohydrate. We found that dietary protein influenced both resistance to pathogen attack and constitutive immune function to a greater extent than did dietary carbohydrate, indicating higher protein costs of resistance than energy costs. Moreover, when allowed to self-compose their diet, insects surviving viral challenge increased their relative intake of protein compared with controls and those larvae dying of infection, thus demonstrating compensation for protein costs associated with resistance. These results suggest that the change in the host's nutritional demands to fight infection induces a compensatory shift in feeding behaviour.
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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 | 0.001 | 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".