Aerobic fitness is associated with cerebral mu-opioid receptor availability and activation in healthy humans
Bibliographic record
Abstract
ABSTRACT 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 (VO 2peak ) and physical activity level are associated with cerebral MOR availability, and whether these phenotypes predict endogenous opioid release following aerobic exercise. We studied 64 healthy lean men who performed a maximal incremental cycling test for VO 2peak determination, completed a questionnaire assessing moderate-to-vigorous physical activity (MVPA, min/week), and underwent positron emission tomography with [ 11 C]carfentanil, a specific radioligand for MOR. A subset of 24 subjects underwent additional PET scan also after a one-hour session of moderate-intensity exercise. Higher VO 2peak and self-reported MVPA level was associated with larger decrease in cerebral MOR binding after aerobic exercise in ventral striatum, orbitofrontal cortex and insula. That is, higher fit and more trained individuals showed greater opioid release acutely following exercise in brain regions especially relevant for reward and cognitive processing. Higher VO 2peak also associated with lower baseline BP ND in the reward and pain circuits, i.e., in frontal and cingulate cortices as well as in temporal lobes and subcortically in thalamus and putamen. We conclude that higher aerobic fitness and regular exercise training may induce neuroadaptation within the MOR system which might contribute to improved emotional and behavioural 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".