Incubation of neural alcohol cue reactivity after withdrawal and its blockade by naltrexone
Bibliographic record
Abstract
During the first weeks of abstinence, alcohol craving in patients may increase or "incubate." We hypothesize that Naltrexone (NTX) blocks this incubation effect. Here, we compared NTX effects on neural alcohol cue reactivity (CR) over the first weeks of abstinence and on long-term clinical outcomes to standard treatment. Male alcohol-dependent patients (n = 55) and healthy controls (n = 35) were enrolled. Participants underwent baseline psychometric testing and functional magnetic resonance imaging (fMRI) assessment of mesolimbic alcohol CR. Patients participated in a standard treatment program with the option of adjuvant NTX. They received another scan after 2 weeks of treatment. We found higher CR in several brain regions in patients versus healthy controls. CR significantly increased over 2 weeks in the standard treatment group (n = 13) but not in the NTX group (n = 22). NTX significantly attenuated CR in the left putamen and reduced relapse risk to heavy drinking within 3 months of treatment. Additionally, increased CR in the left putamen and its course over time predicted both NTX response and relapse risk. Carrier status for the functional OPRM1 variant rs1799971:A > G was considered but had no effect on NTX efficacy. In conclusion, NTX was most effective in patients with high CR in the left putamen. While the results from our naturalistic study await further confirmation from prospective randomized trials, they support a potential role of neural CR as a biomarker in the development of precision medicine approaches with NTX.
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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) | 0.001 | 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 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".