Identification of Proteins Regulated by PACAP in PC12 Cells by 2D Gel Electrophoresis Coupled to Mass Spectrometry
Bibliographic record
Abstract
The rat pheochromocytoma PC12 cell line has been widely used as a model to study neuronal differentiation. In particular, after serum depletion, PC12 cells stop to proliferate and undergo apoptosis. Under such conditions, treatment with pituitary adenylate cyclase-activating polypeptide (PACAP) promotes cell survival and induces neurite outgrowth. The identification of the proteins regulated by PACAP in PC12 cells under apoptotic conditions should provide valuable information concerning the mechanisms controlling neuronal cell survival and differentiation. To this aim, PC12 cells cultured in serum-free medium were treated with PACAP (10(-7) M), proteins were extracted, separated by two-dimensional gel electrophoresis (2-DE), and identified by MALDI-ToF mass spectrometry. The comparison between 16 2-DE maps led to the characterization of 110 proteins regulated by PACAP among which 22 have been identified by automatic query of the Mascot, Aldente, and Profound servers with the ProGeR-CDD database. Seventy-six percent of these proteins, including the p17 subunit of caspase-3, the heat shock protein hsp60, and the GTPase ran were found to be repressed whereas the others notably hsp27, tubulin beta-5, and calmodulin were overexpressed. Investigation of the putative functions indicated that some of the proteins regulated by PACAP and identified in the present article could control cell survival or differentiation.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".