Expression and Manipulation of the APC-β-Catenin Pathway During Peripheral Neuron Regeneration
Bibliographic record
Abstract
Molecules and pathways that suppress growth are expressed in postmitotic neurons, a potential advantage in mature neural networks, but a liability during regeneration. In this work, we probed the APC (adenomatous polyposis coli)-β-catenin partner pathway in adult peripheral sensory neurons during regeneration. APC had robust expression in the cytoplasm and perinuclear region of adult DRG sensory neurons both before and after axotomy injury. β-catenin was expressed in neuronal nuclei, neuronal cytoplasm and also in perineuronal satellite cells. In injured dorsal root ganglia (DRG) sensory neurons and their axons, we observed paradoxical APC upregulation, despite its role as an inhibitor of growth whereas β-catenin was downregulated. Inhibition of APC in adult sensory neurons and activation of β-catenin, LEF/TCF transcriptional factors were associated with increased neuronal plasticity in vitro. Local knockdown of APC, at the site of sciatic nerve crush injury enhanced evidence for electrophysiological, behavioural and structural regeneration in vivo. This was accompanied by upregulation of β-catenin. Collectively, the APC-β-catenin-LEF/TCF transcriptional pathway impacts intrinsic mechanisms of axonal regeneration and neuronal plasticity after injury, offering new options for addressing axon 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".