Is there an energetic-based trade-off between thermoregulation and the acute phase response in zebra finches?
Bibliographic record
Abstract
There has been recent interest in understanding trade-offs between immune function and other fitness-related traits. At proximate levels, such trade-offs are presumed to result from the differential allocation of limited energy resources. Whether the costs of immunity are sufficient to necessitate such energy reallocation remains unclear. We tested the metabolic and behavioural response of male zebra finches (Taeniopygia guttata) to the combined effects of thermoregulation and generation of an acute phase response (APR). The APR is the first line of defence against pathogens, and is considered energetically costly. We predicted that at cold temperatures zebra finches would exhibit an attenuated APR when compared with individuals at thermoneutrality. We challenged individuals with bacterial lipopolysaccharide (LPS), an immunogenic compound that stimulates an APR. Following LPS injection, we measured changes in food intake, body mass, activity, and resting and total energy expenditure. When challenged with LPS under ad libitum food, individuals at both temperatures decreased food intake and activity, resulting in similar mass loss. In contrast to predicted energetic trade-offs, cold-exposed individuals injected with LPS increased their nocturnal resting energy expenditure more than did individuals held at thermoneutrality, yet paradoxically lost less mass overnight. Although responding to LPS was energetically costly, resulting in a 10% increase in resting expenditure and 16% increase in total expenditure, there were few obvious energetic trade-offs. Our data support recent suggestions that the energetic cost of an immune response may not be the primary mechanism driving trade-offs between immune system function and other fitness-related traits.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".