Stress and Relapse to Drug Seeking: Studies in Laboratory Animals Shed Light on Mechanisms and Sources of Long‐Term Vulnerability
Bibliographic record
Abstract
Relapse is a major characteristic of drug addiction disorders and remains the primary problem for treatment. Recently, there has been hope that these disorders may be amenable to pharmacological treatments that have successfully treated other psychopathological disorders. Pharmacological approaches to drug abuse have tended to be guided by the primary drug used by the individual, though substitution has been the guiding principle in some instances, as in the case of methadone maintenance in opioid addiction. Alternatively, blockade or antagonism of the effects of the primary drug being abused has been tried, as in the case of using naltrexone to treat opioid or alcohol addiction. Though reportedly successful in some populations, it is not clear that these approaches effectively control craving for 'highs' or euphoric experiences or a return to drug use as a response to stressful life experiences. Recent experimental studies of the factors that induce craving and relapse to drug use in both humans and laboratory animals, such as drug-related cues, re-exposure to the drug itself, or exposure to stressful events, have shown that the effects of these different events are mediated by dissociable neurochemical circuitry. Another finding that emerges from these studies is that the motivation underlying drug seeking induced by events that precipitate relapse is intensified by the duration and amount of pre-exposure to a drug and the passage of time since withdrawal of the drug. One implication of such findings for the treatment of addiction is that whatever approach is taken, treatment will have to be multifaceted and maintained over an extended period of time after the initial termination of drug use.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".