Endocannabinoid Signaling in the Stress Response of Male and Female Songbirds
Bibliographic record
Abstract
Endocannabinoid (eCB) signaling plays an important role in the stress response pathways of the mammalian brain, yet its role in the avian stress response has not been described. Understanding eCB signaling in avian species (such as the European starling, Sturnus vulgaris) allows a model system that exhibits natural attenuation of hypothalamic-pituitary-adrenal (HPA) responsiveness to stressors. Specifically, seasonally breeding birds exhibit the highest HPA activity during the breeding season and subsequently exhibit a robust HPA down-regulation during molt. Because eCB signaling in mammals has an overall inhibitory effect on HPA activity, we expected shifts in eCB signaling to regulate the seasonal HPA down-regulation during molt. However, our data did not support a role for eCB signaling in the molt-related suppression of HPA activity. For example, injection of the cannabinoid receptor (CB1) antagonist, AM251, did not potentiate molt-suppressed HPA activity. Instead, our data suggest eCB regulation of HPA plasticity as birds transition from breeding to molt. In support of this hypothesis, birds in the late breeding season demonstrated a more dynamic response at the level of avian amygdala eCB content in response to acute stress. The response and directionality of this effect match that seen in mammals. Overall, our data suggest that eCB signaling may allow for a dynamic range in HPA responsiveness (eg, breeding), but the signaling pathway's role may be limited when the HPA response is restrained (eg, molt). This first characterization of eCB signaling in the avian stress response also emphasizes that although the system functions similarly to other species, its exact role may be species specific.
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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".