GEBR-7b, a novel PDE4D selective inhibitor that improves memory in rodents at non-emetic doses
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Strategies designed to enhance cerebral cAMP have been proposed as symptomatic treatments to counteract cognitive deficits. However, pharmacological therapies aimed at reducing PDE4, the main class of cAMP catabolizing enzymes in the brain, produce severe emetic side effects. We have recently synthesized a 3-cyclopentyloxy-4-methoxybenzaldehyde derivative, structurally related to rolipram, and endowed with selective PDE4D inhibitory activity. The aim of the present study was to investigate the effect of the new drug, namely GEBR-7b, on memory performance, nausea, hippocampal cAMP and amyloid-β (Aβ) levels. EXPERIMENTAL APPROACH: To measure memory performance, we performed object recognition tests on rats and mice treated with GEBR-7b or rolipram. The emetic potential of the drug, again compared with rolipram, was evaluated in rats using the taste reactivity test and in mice using the xylazine/ketamine anaesthesia test. Extracellular hippocampal cAMP was evaluated by intracerebral microdialysis in freely moving rats. Levels of soluble Aβ peptides were measured in hippocampal tissues and cultured N2a cells by elisa. KEY RESULTS: GEBR-7b increased hippocampal cAMP, did not influence Aβ levels and improved spatial, as well as object memory performance in the object recognition tests. The effect of GEBR-7b on memory was 3 to 10 times more potent than that of rolipram, and its effective doses had no effect on surrogate measures of emesis in rodents. CONCLUSION AND IMPLICATIONS: Our results demonstrate that GEBR-7b enhances memory functions at doses that do not cause emesis-like behaviour in rodents, thus offering a promising pharmacological perspective for the treatment of memory impairment.
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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) | 0.002 | 0.001 |
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".