Exosomes Mediate Mobilization of Autocrine Wnt10b to Promote Axonal Regeneration in the Injured CNS
Bibliographic record
Abstract
Developing strategies that promote axonal regeneration within the injured CNS is a major therapeutic challenge, as axonal outgrowth is potently inhibited by myelin and the glial scar. Although regeneration can be achieved using the genetic deletion of PTEN, a negative regulator of the mTOR pathway, this requires inactivation prior to nerve injury, thus precluding therapeutic application. Here, we show that, remarkably, fibroblast-derived exosomes (FD exosomes) enable neurite growth on CNS inhibitory proteins. Moreover, we demonstrate that, upon treatment with FD exosomes, Wnt10b is recruited toward lipid rafts and activates mTOR via GSK3β and TSC2. Application of FD exosomes shortly after optic nerve injury promoted robust axonal regeneration, which was strongly reduced in Wnt10b-deleted animals. This work uncovers an intercellular signaling pathway whereby FD exosomes mobilize an autocrine Wnt10b-mTOR pathway, thereby awakening the intrinsic capacity of neurons for regeneration, an important step toward healing the injured CNS.
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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 | 0.001 | 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".