Platelet activating factor‐induced neuronal apoptosis is initiated independently of its G‐protein coupled PAF receptor and is inhibited by the benzoate orsellinic acid
Bibliographic record
Abstract
The bioactive lipid mediator platelet activating factor (PAF) is recognized as a key effecter of neuronal apoptosis, yet it is not clear whether its G-protein coupled receptor (PAFR) initiates or prevents PAF neurotoxicity. Using PAFR-/- and congenic wild-type mice, we show that PAF triggers caspase-3/7 activity and neuronal death in PAFR-/- but not PAFR+/+ cerebellar granule neurons. Restoring receptor expression by recombinant adenoviral infection protected cells from PAF challenge. Neuronal death was not mediated by nitric oxide or N-methyl-d-aspartate receptor signaling given that N-nitro-l-arginine methyl ester and MK-801 did not inhibit PAF-induced neuronal loss in PAFR-/- neurons. To intervene in PAFR-independent neurotoxicity, the anti-apoptotic actions of three structurally distinct PAF antagonists were compared to a panel of plant and fungal benzoic acid derivatives. We found that the PAF antagonist BN 52021 but not FR 49175 or CV 3988 inhibited PAFR-independent neurotoxicity. Orsellinic acid, a fungal-derived benzoic acid, blocked PAF-mediated neuronal apoptosis without affecting PAFR-mediated neuroprotection. These findings demonstrate that PAF can transduce apoptotic death in primary neurons independently of its G-protein coupled receptor, that PAFR activation is neuroprotective, and that orsellinic acid effectively attenuates PAFR-independent neuronal apoptosis.
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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) | 0.001 | 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".