A preclinical assessment of d.l-govadine as a potential antipsychotic and cognitive enhancer
Bibliographic record
Abstract
Tetrahydroprotoberberines (THPBs) are compounds derived from traditional Chinese medicine and increasing preclinical evidence suggests efficacy in treatment of a wide range of symptoms observed in schizophrenia. A receptor-binding profile of the THPB, d.l-govadine (d.l-Gov), reveals high affinity for dopamine and noradrenaline receptors, efficacy as a D2 receptor antagonist, brain penetrance in the 10-300 ng/g range, and thus motivated an assessment of the antipsychotic and pro-cognitive properties of this compound in the rat. Increased dopamine efflux in the prefrontal cortex and nucleus accumbens, measured by microdialysis, is observed following subcutaneous injection of the drug. d.l-Gov inhibits both conditioned avoidance responding (CAR) and amphetamine-induced locomotion (AIL) at lower doses than clozapine (CAR ED50: d.l-Gov 0.72 vs. clozapine 7.70 mg/kg; AIL ED50: d.l-Gov 1.70 vs. clozapine 4.27 mg/kg). Catalepsy is not detectable at low biologically relevant doses, but is observed at higher doses. Consistent with previous reports, acute d-amphetamine disrupts latent inhibition (LI) while a novel finding of enhanced LI is observed in sensitized animals. Treatment with d.l-Gov prior to conditioned stimulus (CS) pre-exposure restores LI to levels observed in controls in both sensitized animals and those treated acutely with d-amphetamine. Finally, possible pro-cognitive properties of d.l-Gov are assessed with the spatial delayed win-shift task. Subcutaneous injection of 1.0 mg/kg d.l-Gov failed to affect errors at a 30-min delay, but decreased errors observed at a 12-h delay. Collectively, these data provide the first evidence that d.l-Gov may have antipsychotic properties in conjunction with pro-cognitive effects, lending further support to the hypothesis that THPBs are a class of compounds which merit serious consideration as novel treatments for schizophrenia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".