The role of CRMP4 in nerve regenerations
Bibliographic record
Abstract
The inability of CNS neurons to regenerate and reform functional connections following spinal cord injury has devastating clinical consequences. The failure of CNS neurons to spontaneously regenerate following injury can be partially attributed to the expression of neurite outgrowth inhibitory myelin associated inhibitors (MAIs). MAIs signal through a tripartite receptor complex to activate the cytosolic protein RhoA and influence cytoskeletal dynamics. RhoA antagonists promote neuronal survival and regeneration in animal models of nerve injury. However, RhoA's potential as a therapeutic target may be limited by its widespread roles in multiples cellular processes and cell types. In an attempt to discover more specific therapeutic targets to promote nerve regeneration, our lab identified the cytosolic phosphoprotein CRMP4b (Collapsin Response Mediator Protein 4b) as a protein that functionally interacts with RhoA to mediate neurite outgrowth inhibition. siRNA-mediated knockdown of CRMP4 and blockade of the RhoA-CRMP4b interaction with a competitive peptide (C4RIP) attenuates myelin-dependent neurite outgrowth inhibition. Analysis of the proximal tip of extending axons (growth cones) by time lapse video microscopy reveals that C4RIP regulates filopodial dynamics indicating that C4RIP modulates the actin cytoskeleton. We are currently investigating the in vivo roles of CRMP4 in regeneration in an optic nerve injury model by developing readily deliverable C4RIP and a CRMP4 knockout mouse. Elucidating the role of CRMP4 in nerve regeneration may provide insight into the molecular mechanisms following nervous system injury.
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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 | 0.001 |
| 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".