Sucrose intake lowers μ-opioid and dopamine D2/3 receptor availability in porcine brain
Bibliographic record
Abstract
Abstract Excessive sucrose consumption elicits addiction-like craving that may underpin the obesity epidemic. Opioids and dopamine mediate the rewarding effects of drugs of abuse, and of natural rewards from stimuli such as palatable food. We investigated the effects of sucrose using PET imaging with [11C]carfentanil (μ-opioid receptor agonist) and [11C]raclopride (dopamine D2/3 receptor antagonist) in seven female anesthetized Göttingen minipigs. We then gave minipigs access to sucrose solution for one hour on 12 consecutive days and performed imaging again 24 hours after the final sucrose access. In a smaller sample of five minipigs, we performed an additional [11C]carfentanil PET session after the first sucrose exposure. We calculated voxel-wise binding potentials (BPND) using the cerebellum as a region of non-displaceable binding, analyzed differences with statistical non-parametric mapping, and performed a regional analysis. After 12 days of sucrose access, BPND of both tracers had declined significantly in striatum, nucleus accumbens, thalamus, amygdala, cingulate cortex and prefrontal cortex, consistent with down-regulation of receptor densities. After a single exposure to sucrose, we found decreased binding of [11C]carfentanil in nucleus accumbens and cingulate cortex, consistent with opioid release. The lower availability of opioid and dopamine receptors may explain the addictive potential associated with intake of sucrose.
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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".