Carbohydrate Craving by Alcohol‐Dependent Men During Sobriety: Relationship to Nutrition and Serotonergic Function
Bibliographic record
Abstract
BACKGROUND: Several studies report reduced serotonin (5HT) in alcohol-dependent subjects. Furthermore, alcohol increases 5HT in animals. Thus, alcohol dependence may be an attempt to self-medicate reduced 5HT. Relevant to this, reducing 5HT increases carbohydrate intake, and several studies report increased carbohydrate intake in alcohol-dependent subjects. Like alcohol, carbohydrate increases 5HT. We hypothesized that a subgroup of the alcohol-dependent population self-medicates reduced 5HT with alcohol and alternatively with carbohydrate when not drinking. METHODS: Three groups were recruited: a high carbohydrate craving alcohol-dependent group (n = 10), a low carbohydrate craving alcohol-dependent group (n = 11), and a nonaddicted control group (n = 12). All groups were placed on a high-carbohydrate, low-protein diet for 2 days and then a high-protein, low-carbohydrate diet for 2 days. The effects of diet on mood, alcohol craving, stress, and 5HT were measured. RESULTS: Although both alcohol-dependent groups had similar alcohol cravings at baseline, only the carbohydrate-craving alcohol-dependent group craved alcohol significantly more when under the stress of the research protocol. The carbohydrate-craving alcohol-dependent subjects presented with distinct personality disorders and were uniquely sensitive to the adverse effects of carbohydrate on mood. Diet had a unique effect on 5HT in the high carbohydrate craving alcohol-dependent group. The results of platelet 5HT uptake demonstrated that the high-protein, low-carbohydrate diet significantly increased Km values of high carbohydrate craving alcohol-dependent subjects, whereas it reduced the Km values of both non-carbohydrate-craving alcohol-dependent subjects and nonaddicted controls. CONCLUSION: Carbohydrate-craving alcohol-dependent subjects are a distinct subgroup of the alcohol-dependent population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".