The neurotrophic effects of PACAP in PC12 cells: control by multiple transduction pathways
Bibliographic record
Abstract
Pituitary adenylate cyclase-activating polypeptide (PACAP) and vasoactive intestinal polypeptide (VIP) are closely related members of the secretin superfamily of neuropeptides expressed in both the brain and peripheral nervous system, and they exhibit neurotrophic and neurodevelopmental effects in vivo. Like the index member of the Trk receptor ligand family, nerve growth factor (NGF), PACAP promotes the differentiation of PC12 cells, a well-established cell culture model, to investigate neuronal differentiation, survival and function. Stimulation of catecholamine secretion and enhanced neuropeptide biosynthesis are effects exerted by PACAP at the adrenomedullary synapse in vivo and on PC12 cells in vitro through stimulation of the specific PAC1 receptor. Induction of neuritogenesis, growth arrest, and promotion of cell survival are effects of PACAP that occur in developing cerebellar, hippocampal and cortical neurons, as well as in the more tractable PC12 cell model. Study of the mechanisms through which PACAP exerts its various effects on cell growth, morphology, gene expression and survival, i.e. its actions as a neurotrophin, in PC12 cells is the subject of this review. The study of neurotrophic signalling by PACAP in PC12 cells reveals that multiple independent pathways are coordinated in the PACAP response, some activated by classical and some by novel or combinatorial signalling mechanisms.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".