Molecular mechanisms of myelin-associated glycoprotein (MAG)- and Nogo-induced Smad2 phosphorylation
Bibliographic record
Abstract
The myelin-associated inhibitors (MAIs) Nogo-A and myelin-associated glycoprotein (MAG) are potent inhibitors of regeneration in the central nervous system (CNS). They effect inhibition through signaling pathways initiated by activation of the Nogo-66 receptor 1 (NgR1) complex, low-density lipoprotein (LDL) receptor-related protein-1 (LRP1), or paired immunoglobulin-like receptor B (PirB). The Smad2 protein, which is phosphorylated in response to transforming growth factor-β (TGFβ) receptor activation, has been shown to have a role in myelin-mediated inhibition of neurite outgrowth in cerebellar granule neurons (CGNs). We demonstrate that MAG and Nogo strongly induce Smad2 phosphorylation and that inhibiting TGFβ receptor activation abolishes this response in CGNs treated with MAG or Nogo. We have hypothesized that this receptor is being transactivated by another receptor such as NgR1, LRP1, or PirB. siRNA knockdown of NgR1 or LRP1 in CGNs did not result in significant reduction of Smad2 phosphorylation in response to MAG or Nogo. Similarly, CGNs from PirB-/- mice displayed no significant reduction in levels of phosphorylated Smad2 following treatment with MAG or Nogo. TGFβ receptor activation by MAIs is thus mediated through an unidentified receptor, and discovering this receptor may provide a novel target for pharmacological intervention as a means of promoting regeneration in the CNS following 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".