The Dopamine Allosteric Agent, PAOPA, Demonstrates Therapeutic Potential in the Phencyclidine NMDA Pre-clinical Rat Model of Schizophrenia
Bibliographic record
Abstract
PAOPA, a potent analog of prolyl-leucyl-glycinamide, has shown therapeutic potential at the preclinical stage for dopaminergic related illnesses, including animal models of schizophrenia, Parkinson's disease and haloperidol-induced extrapyramidal movement disorders. PAOPA's unique allosteric mechanism and dopamine D2 receptor specificity provide a unique composition of properties for the development of potential therapeutics for neuropsychiatric illnesses. We sought to investigate PAOPA's therapeutic prospects across the spectrum of schizophrenia-like symptoms represented in the established phencyclidine-induced rat model of schizophrenia, (5 mg/kg PCP twice daily for 7 days, followed by 7 days of drug withdrawal). PAOPA was assessed for its effect on brain metabolic activity and across a battery of behavioral tests including, hyperlocomotion, social withdrawal, sensorimotor gating, and novel object recognition. PAOPA showed therapeutic efficacy in behavioral paradigms representing the negative (social withdrawal) and cognitive-like (novel object recognition) symptoms of schizophrenia. Interestingly, some behavioral indices associated with the positive symptoms of schizophrenia that were ameliorated in PAOPA's prior examination in the amphetamine-sensitized model of schizophrenia were not ameliorated in the PCP model; suggesting that the deficits induced by amphetamine and PCP-while phenotypically similar-are mechanistically different and that PAOPA's effects are restricted to certain mechanisms and systems. These studies provide insight on the potential use of PAOPA for the safe and effective treatment of schizophrenia.
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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) | 0.000 | 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 | 0.001 |
| 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 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".