Versican G3 Domain Regulates Neurite Growth and Synaptic Transmission of Hippocampal Neurons by Activation of Epidermal Growth Factor Receptor
Bibliographic record
Abstract
Versican is one of the major extracellular matrix (ECM) proteins in the brain. ECM molecules and their cleavage products critically regulate the growth and arborization of neurites, hence adjusting the formation of neural networks. Recent findings have revealed that peptide fragments containing the versican C terminus (G3 domain) are present in human brain astrocytoma. The present study demonstrated that a versican G3 domain enhanced cell attachment, neurite growth, and glutamate receptor-mediated currents in cultured embryonic hippocampal neurons. In addition, the G3 domain intensified dendritic spines, increased the clustering of both synaptophysin and the glutamate receptor subunit GluR2, and augmented excitatory synaptic activity. In contrast, a mutated G3 domain lacking the epidermal growth factor (EGF)-like repeats (G3deltaEGF) had little effect on neurite growth and glutamatergic function. Treating the neurons with the G3-conditioned medium rapidly increased the levels of phosphorylated EGF receptor (pEGFR) and phosphorylated extracellular signal-regulated kinase (pERK), indicating an activation of EGFR-mediated signaling pathways. Blockade of EGFR prevented the G3-induced ERK activation and suppressed the G3-provoked enhancement of neurite growth and glutamatergic function but failed to block the G3-mediated enhancement of cell attachment. These combined results indicate that the versican G3 domain regulates neuronal attachment, neurite outgrowth, and synaptic function of hippocampal neurons via EGFR-dependent and -independent signaling pathway(s). Our findings suggest a role for ECM proteolytic products in neural development and regeneration.
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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 | 0.000 |
| 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".