5‐Hydroxytryptamine type 7 receptor neuroprotection against NMDA‐induced excitotoxicity is PDGFβ receptor dependent
Bibliographic record
Abstract
The serotonin (5-HT) type 7 receptor is expressed throughout the CNS including the hippocampus. Long-term (2-24 h) activation of 5-HT7 receptors regulates growth factor receptor expression, including the expression of platelet-derived growth factor (PDGF) β receptors. Direct activation of PDGFβ receptors in primary hippocampal and cortical neurons inhibits NMDA receptor activity and attenuates NMDA receptor-induced neurotoxicity. Our objective was to investigate whether the 5-HT7 receptor-induced increase in PDGFβ receptor expression would be similarly neuroprotective. We demonstrate that 5-HT7 receptor agonist treatment in primary hippocampal neurons also increases the expression of phospholipase C (PLC) γ, a downstream effector of PDGFβ receptors associated with the inhibition of NMDA receptor activity. To determine if the up-regulation of PDGFβ receptors is neuroprotective, primary hippocampal neurons were incubated with the 5-HT7 receptor agonist, LP 12, for 24 h. Indeed, LP 12 treatment prevented NMDA-induced neurotoxicity and this effect was dependent on PDGFβ receptor kinase activity. Treatment of primary neurons with LP 12 also differentially altered NMDA receptor subunit expression, reducing the expression of NR1 and NR2B, but not NR2A. These findings demonstrate the potential for providing growth factor receptor-dependent neuroprotective effects using small-molecule ligands of G protein-coupled receptors.
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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) | 0.001 | 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".