Predator stress-induced immunosuppression: trade-off, immune redistribution or immune reconfiguration?
Bibliographic record
Abstract
Although predator exposure increases the risk of wound infections, it typically induces immunosuppression. A number of non-mutually exclusive hypotheses have been put forward to explain this immunosuppression, including: trade-offs between the immune system and other systems required for anti-predator behaviour, redistribution of immune resources towards mechanisms needed to defend against wound infections, and reconfiguration of the immune system to optimize defense under the physiological state of fight-or-flight readiness. We tested the ability of each hypothesis to explain the effects of chronic predator stress on the immune system of the caterpillar Manduca sexta. Predator stress induced defensive behaviours, reduced weight gain, increased development time and increased the concentration of the stress neurohormone octopamine. It had no significant effect on: hemocyte number, melanization rate, phenoloxidase activity, lysozyme-like activity, or nodule production. Predator stress reduced hemolymph glutathione concentrations. It also increased constitutive expression of the antimicrobial peptide attacin-1 but reduced attacin-1 expression in response to an immune challenge. These results best fit the immune reconfiguration hypothesis, although the other hypotheses are also consistent with some results. Interpreting stress related changes in immune function may require an examination at the level of the whole organism.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".