Superiority of the Triple-Acting 5-HT<sub>6</sub>R/5-HT<sub>3</sub>R Antagonist and MAO-B Reversible Inhibitor <b>PZ-1922</b> over 5-HT<sub>6</sub>R Antagonist Intepirdine in Alleviation of Cognitive Deficits in Rats
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The multifactorial origin and neurochemistry of Alzheimer’s disease (AD) call for the development of multitarget treatment strategies. We report a first-in-class triple acting compound that targets serotonin type 6 and 3 receptors (5-HT-Rs) and monoamine oxidase type B (MAO-B) as an approach for treating AD. The key structural features required for MAO-B inhibition and 5-HT 6 R antagonism and interaction with 5-HT 3 R were determined using molecular dynamic simulations and cryo-electron microscopy, respectively. Bioavailable PZ-1922 reversed scopolamine-induced cognitive deficits in the novel object recognition test. Furthermore, it displayed superior pro-cognitive properties compared to intepirdine (a 5-HT 6 R antagonist) in the AD model, which involved intracerebroventricular injection of an oligomeric solution of amyloid-β peptide (oAβ) in the T-maze test in rats. PZ-1922, but not intepirdine, restored levels of biomarkers characteristic of the debilitating effects of oAβ. These data support the potential of a multitarget approach involving the joint modulation of 5-HT 6 R/5-HT 3 R/MAO-B in AD.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".