Intrinsic neuronal properties control selective targeting of regenerating motoneurons
Bibliographic record
Abstract
Despite advances in microsurgical techniques, recovery of motor function after peripheral nerve injury is often poor because many regenerating axons reinnervate inappropriate targets. Consequently, surgical repair must include treatment strategies that improve motor axon targeting. Development of such treatments will require a better understanding of the molecular mechanisms governing selective motor axon targeting. This study used a well-established model of nerve transection and repair to examine (1) whether intrinsic differences exist between different pools of motoneurons after peripheral nerve injury, (2) if such differences regulate selective axon targeting, (3) if regenerating motor axons must express polysialic acid (PSA) in order to preferentially reinnervate muscle and (4) whether brief electrical stimulation improves regeneration accuracy because it increases PSA expression on regenerating axons. We found that different motor pools differentially express PSA after injury and that the capacity to re-express PSA appears to be an intrinsic neuronal property established during development. Second, motoneuron pools not up-regulating PSA did not preferentially reinnervate muscle after injury. Third, brief electrical stimulation of the proximal nerve stump immediately after injury only improved selective motor axon targeting if the motoneurons were capable of up-regulating PSA. Finally, the benefits of stimulation were completely abolished if PSA was removed from the regenerating axons. These results indicate that (1) intrinsic neuronal differences between motor pools must be considered in the development of treatments designed to improve axon targeting and (2) therapeutics aimed at increasing PSA levels on regenerating motor axons may lead to superior functional outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".