Energetic costs of mounting an immune response in a coral reef damselfish (<i>Pomacentrus amboinensis</i>)
Bibliographic record
Abstract
While immune responses can be energetically costly, quantifying these costs is challenging. We tested the metabolic costs of immune activation in damselfish ( Pomacentrus amboinensis Bleeker, 1868) following a mass-adjusted injection of lipopolysaccharide (LPS) endotoxin. Fish were divided into eight treatments: two controls (handling and saline injection) and six LPS groups with concentrations ranging from 3 to 100 mg kg−1. We used intermittent flow respirometry to measure differences in oxygen uptake (delta ṀO2) 20 h before versus 20 h after LPS injection and changes in metabolic traits (lowest, routine, and peak metabolic rates) as proxies of the aerobic costs of metabolism. Spleen somatic index (SSI) and gene expression in spleens were measured to assess immune activation. We found no difference in metabolic traits or SSI but observed different nonlinear patterns of delta ṀO2 in fish exposed to 50 and 100 mg kg−1 LPS compared to lower doses and controls. Fish exposed to high doses of LPS also had lower residual aerobic scope compared to controls and lower LPS doses. Fish exposed to doses of 3, 50, and 100 mg kg−1 showed altered gene expression compared to the handling control. Overall, our results suggest that immune activation has measurable effects on metabolic traits that are both dose- and time-dependent.
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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".