Competition between immune function and lipid transport for the protein apolipophorin III leads to stress-induced immunosuppression in crickets
Bibliographic record
Abstract
Intense physical activity results in transient immunosuppression in a wide range of animals. We tested the hypothesis that competition between immune function and lipid transport for the protein apolipophorin III (apoLpIII) can cause transient immunosuppression in crickets. Both flying, an energetically demanding behavior, and an immune challenge reduced the amount of monomeric (free) apoLpIII in the hemolymph of crickets. Because both immune function and flying depleted free apoLpIII, these two phenomena could be in competition for this protein. We showed that immune function was sensitive to the amount of free apoLpIII in the hemolymph. Reducing the amount of free apoLpIII in the hemolymph using adipokinetic hormone produced immunosuppression. Increasing apoLpIII levels after flight by pre-loading animals with trehalose reduced immunosuppression. Increasing post-flight apoLpIII levels by injecting purified apoLpIII also reduced flight-induced immunosuppression. These results show that competition between lipid transport and immune function for the same protein can produce transient immunosuppression after flight-or-fight behavior. Intertwined physiological systems can produce unexpected trade-offs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".