Platelet-derived Growth Factor-mediated Induction of the Synaptic Plasticity Gene Arc/Arg3.1
Bibliographic record
Abstract
Platelet-derived growth factor (PDGF) is a pleiotropic protein with critical roles in both developmental as well as pathogenic processes. In the central nervous system specifically, PDGF is critical for neuronal proliferation and differentiation and has also been implicated as a neuroprotective agent. Whether PDGF also plays a role in synaptic plasticity, however, remains poorly understood. In the present study we demonstrated that in the rat hippocampal neurons PDGF regulated the expression of Arc/Arg3.1 gene that has been implicated in both synapse plasticity and long term potentiation. Relevance of these findings was further confirmed in vivo by injecting mice with intracerebral inoculations of PDGF, which resulted in a rapid induction of Arc in the hippocampus of the injected mice. PDGF induced long term potentiation in rat hippocampal slices, which was abolished by PDGF receptor-tyrosine kinase inhibitor STI-571. We also present evidence that PDGF-mediated induction of Arc/Arg3.1 involved activation of the MAPK/ERK (MEK) pathway. Additionally, induction of Arc/Arg3.1 also involved the upstream release of intracellular calcium stores, an effect that could be blocked by thapsigargin but not by EGTA. Pharmacological approach using inhibitors specific for either MAPK/ERK phosphorylation or calcium release demonstrated that the two pathways converged downstream at a common point involving activation of the immediate early gene Egr-1. Chromatin immunoprecipitation assays demonstrated the binding of Egr-1, but not Egr-3, to the Arc promoter. These findings for the first time, thus, suggest an additional role of PDGF, that of induction of Arc.
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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 | 0.001 |
| 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".