In search of a new pharmacological treatment for drug and alcohol addiction: N-methyl-d-aspartate (NMDA) antagonists
Bibliographic record
Abstract
The most challenging aspect of treating alcohol and drug addiction is the relapsing course of these disorders. Although substitution therapies for nicotine and opioid dependence have proven to be relatively effective, there is a need for new pharmacotherapies designed to decrease the frequency and severity of relapse. The aim of this paper is to provide an overview of the potential utility of N-methyl-D-aspartate (NMDA) receptor antagonists as treatments for substance abuse as shown in preclinical models and preliminary clinical trials. It is hypothesized that NMDA receptors mediate the common adaptive processes that are involved the development, maintenance, and expression of drug and alcohol addiction. Modulation of glutamatergic neurotransmission with NMDA receptor antagonists offers a novel treatment approach. It is proposed that NMDA antagonists may have multiple functions in treating addictions, including an attenuation of withdrawal effects, normalization of the affective changes following initiation of abstinence which arise from neurochemical changes resulting from chronic addiction, and an attenuation of conditioned responses arising from drug-related stimuli.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".