Pituitary adenylate cyclase‐activating polypeptide prevents C2‐ceramide‐induced apoptosis of cerebellar granule cells
Bibliographic record
Abstract
The sphingolipid metabolites, ceramides, are critical mediators of the cellular stress response and play an important role in the control of programmed cell death. In particular, ceramides have been shown to induce apoptosis of cerebellar granule cells. We show that pituitary adenylate cyclase-activating polypeptide (PACAP) prevents C2-ceramide-induced apoptosis. The neuroprotective effect of PACAP was dose-dependent and blocked by its antagonist, PACAP6-38, whereas the PACAP-related peptide VIP was inactive. The effect of PACAP on cell survival was mimicked by dibutyryl-cAMP (dbcAMP) and forskolin and prevented by the MEK inhibitor U0126, indicating that both the adenylyl-cyclase and MAP-kinase pathways contribute to the neuroprotective action of the peptide. C2-ceramide and PACAP induced opposite effects on phosphorylated forms of ERK and JNK without affecting the total amounts of ERK and JNK, suggesting that a balance between these two MAP-kinases is critical for the cell survival/death decision. The effect of PACAP on ERK phosphorylation was blocked by U0126, but was not affected by H89 or chelerythrine indicating that PACAP activates ERK through a PKA- and PKC-independent mechanism. C2-ceramide induced a time-dependent activation of caspase-3, enhanced the amount of cleaved caspase-3 and stimulated the DNA fragmentation process, while PACAP strongly inhibited the C2-ceramide-induced activation of caspase-3, reduced the expression of cleaved caspase-3 and blocked DNA fragmentation. Taken together, the present results show that C2-ceramide induces apoptosis of cerebellar granule cells through a mechanism involving activation of caspase-3. Our data also demonstrate that PACAP is a potent inhibitor of C2-ceramide-induced 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) | 0.001 | 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) | 0.001 | 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".