Peroxisome Proliferator-Activated Receptor (PPAR) Agonists as Promising New Medications for Drug Addiction: Preclinical Evidence
Bibliographic record
Abstract
This review examines the growing literature on the role of peroxisome proliferator-activated receptors (PPARs) in addiction. There are two subtypes of PPAR receptors that have been studied in addiction: PPAR-α and PPAR-γ. The role of each PPAR subtype in common models of addictive behavior, mainly pre-clinical models, is summarized. In particular, studies are reviewed that investigated the effects of PPAR-α agonists on relapse, sensitization, conditioned place preference, withdrawal and drug intake, and effects of PPAR-γ agonists on relapse, withdrawal and drug intake. Finally, studies that investigated the effects of PPAR agonists on neural pathways of addiction are reviewed. Taken together these preclinical data indicate that PPAR agonists are promising new medications for drug addiction treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".