Low-dose prazosin in combination with 5-HT<sub>6</sub> antagonist PRX-07034 has antipsychotic effects
Bibliographic record
Abstract
An extensive amount of research has focused on the development of new pharmacological agents to treat schizophrenia. Varying from person to person, schizophrenia is a heterogeneous disease with symptoms of positive, negative, and cognitive deficits. PRX-07034, a 5-hydroxytryptamine6 (5-HT6) receptor antagonist has been evaluated for its potential in treating obesity and cognitive deficits. This study evaluated PRX-07034 (0.1, 0.3, and 1.0 mg/kg body mass, by intraperitoneal (i.p.) injection), in combination with a low dose of prazosin (0.3 mg/kg, i.p.), for its antipsychotic potential. The research utilized a stereotypy assay, an open field test, an object recognition task, and prepulse inhibition. Dizocilpine, a non-competitive N-methyl-d-aspartate (NMDA) antagonist, was also administered in the above-mentioned assays as a psychomimetic. The combination of PRX-07034 and prazosin alleviated stereotypy and hyperlocomotor activity while enhancing memory in an object recognition task, and reversed sensory-gating deficits induced by dizocilpine. Examination of the medial prefrontal cortex revealed that a combination of PRX-07034 and prazosin reduced the dizocilpine-mediated increase of 5-HT. These results suggest that the combination of a 5-HT6 antagonist with low doses of prazosin could have therapeutic potential in the 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".