<i>Lymnaea</i>Epidermal Growth Factor Promotes Axonal Regeneration in CNS Organ Culture
Bibliographic record
Abstract
Members of the epidermal growth factor (EGF) family are frequently implicated in the injury response of the mammalian nervous system. Although this implication is supported by extensive molecular evidence, it is not underpinned by conclusive functional data. Recently, we found that expression of an EGF homolog from the pond snail Lymnaea stagnalis (L-EGF) is upregulated after axotomy in the adult CNS, suggesting a role for this molecule in the injury response of the CNS. In the present study we asked whether L-EGF can promote axonal regeneration of three types of identified neurons in organ-cultured CNS. Treatment with purified L-EGF substantially enhanced axonal regeneration of all three types of neurons, an effect inhibited by submicromolar doses of PD153035, a specific EGF receptor (EGFR) tyrosine kinase inhibitor. In addition, PD153035 and K252a, a nonspecific kinase inhibitor, also reduced the degree of axonal regeneration that occurs without L-EGF supplementation, indicating that L-EGF or other EGFR ligands synthesized in the CNS participate in the regenerative response. An intriguing aspect of these results is that axonal regeneration of different, intrinsically L-EGF responsive and unresponsive neurons occurred in a coordinated manner. This observation suggests that indirect in addition to direct actions contribute to the beneficial effect of L-EGF. In conclusion, we provide functional evidence that an EGF homolog can promote axonal regeneration, substantiating existing molecular evidence implicating the EGF family in peripheral nerve regeneration and emphasizes the therapeutic potential of these molecules.
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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 | 0.001 |
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".