BMI Modulates Calorie-Dependent Dopamine Changes in Accumbens from Glucose Intake
Bibliographic record
Abstract
OBJECTIVE: Dopamine mediates the rewarding effects of food that can lead to overeating and obesity, which then trigger metabolic neuroadaptations that further perpetuate excessive food consumption. We tested the hypothesis that the dopamine response to calorie intake (independent of palatability) in striatal brain regions is attenuated with increases in weight. METHOD: We used positron emission tomography with [11C]raclopride to measure dopamine changes triggered by calorie intake by contrasting the effects of an artificial sweetener (sucralose) devoid of calories to that of glucose to assess their association with body mass index (BMI) in nineteen healthy participants (BMI range 21-35). RESULTS: Neither the measured blood glucose concentrations prior to the sucralose and the glucose challenge days, nor the glucose concentrations following the glucose challenge vary as a function of BMI. In contrast the dopamine changes in ventral striatum (assessed as changes in non-displaceable binding potential of [11C]raclopride) triggered by calorie intake (contrast glucose - sucralose) were significantly correlated with BMI (r = 0.68) indicating opposite responses in lean than in obese individuals. Specifically whereas in normal weight individuals (BMI <25) consumption of calories was associated with increases in dopamine in the ventral striatum in obese individuals it was associated with decreases in dopamine. CONCLUSION: These findings show reduced dopamine release in ventral striatum with calorie consumption in obese subjects, which might contribute to their excessive food intake to compensate for the deficit between the expected and the actual response to food consumption.
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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".