Aerobic Fitness Is Associated with Cerebral μ-Opioid Receptor Activation in Healthy Humans
Bibliographic record
Abstract
INTRODUCTION: Central μ-opioid receptors (MORs) modulate affective responses to physical exercise. Individuals with higher aerobic fitness report greater exercise-induced mood improvements than those with lower fitness, but the link between cardiorespiratory fitness and the MOR system remains unresolved. Here we tested whether maximal oxygen uptake (V̇O2peak) and physical activity level are associated with cerebral MOR availability and whether these phenotypes predict endogenous opioid release after a session of exercise. METHODS: We studied 64 healthy lean men who performed a maximal incremental cycling test for V̇O2peak determination, completed a questionnaire assessing moderate-to-vigorous physical activity (MVPA; in minutes per week), and underwent positron emission tomography with [11C]carfentanil, a specific radioligand for MOR. A subset of 24 subjects underwent additional positron emission tomography scan also after a 1-h session of moderate-intensity exercise and 12 of them also after a bout of high-intensity interval training. RESULTS: Higher self-reported MVPA level predicted greater opioid release after high-intensity interval training, and both V̇O2peak and MVPA level were associated with a larger decrease in cerebral MOR binding after aerobic exercise in the ventral striatum, orbitofrontal cortex, and insula. That is, more trained individuals showed greater opioid release acutely after exercise in brain regions especially relevant for reward and cognitive processing. Fitness was not associated with MOR availability. CONCLUSIONS: We conclude that regular exercise training and higher aerobic fitness may induce neuroadaptation within the MOR system, which might contribute to improved emotional and behavioral responses associated with long-term exercise.
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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) | 0.002 | 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".