The Effects of Stress Hormones on Immune Function May be Vital for the Adaptive Reconfiguration of the Immune System During Fight-or-Flight Behavior
Bibliographic record
Abstract
Intense, short-term stress (i.e., robust activation of the fight-or-flight response) typically produces a transient decline in resistance to disease in animals across phyla. Chemical mediators of the stress response (e.g., stress hormones) help induce this decline, suggesting that this transient immunosuppression is an evolved response. However, determining the function of stress hormones on immune function is difficult because of their complexity. Nevertheless, evidence suggests that stress hormones help maintain maximal resistance to disease during the physiological changes needed to optimize the body for intense physical activity. Work on insects demonstrates that stress hormones both shunt resources away from the immune system during fight-or-flight responses as well as reconfigure the immune system. Reconfiguring the immune system minimizes the impact of the loss of these resources and reduces the increased costs of some immune functions due to the physiological changes demanded by the fight-or-flight response. For example, during the stress response of the cricket Gryllus texensis, some molecular resources are shunted away from the immune system and toward lipid transport, resulting in a reduction in resistance to disease. However, insects' immune cells (hemocytes) have receptors for octopamine (the insect stress neurohormone). Octopamine increases many hemocyte functions, such as phagocytosis, and these changes would tend to mitigate the decline in immunity due to the loss of molecular resources. Moreover, because the stress response generates oxidative stress, some immune responses are probably more costly when activated during a stress response (e.g., those that produce reactive molecules). Some of these immune responses are depressed during stress in crickets, while others, whose costs are probably not increased during a stress response, are enhanced. Some effects of stress hormones on immune systems may be better understood as examples of reconfiguration rather than as mediating a trade-off.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".