The Microvascular Impact of Focal Nerve Trunk Injury
Bibliographic record
Abstract
The microvascular supply of the peripheral nerve trunk may be rendered vulnerable by acute focal injuries, particularly if they are associated with direct injury to the epineurial blood supply. In this work we tracked the impact of three clinically relevant forms of focal nerve trunk injury on serial measures of epineurial weighted erythrocyte flux and endoneurial blood flow: short-length crush injuries, long-segmental crush injuries, and crush injuries with superimposed vascular stripping to model added direct epineurial damage. Red blood cell (RBC) flux was measured using quantitative multiple sampling laser doppler flowmetry, and endoneurial blood flow by microelectrode hydrogen clearance polarography. Both short and long crush injuries transiently reduced epineurial RBC flux, most prominently in long injuries, to 34% by 1 h after injury. The changes were less prominent when deeper flux was examined, whereas endoneurial blood flow was not altered by either injury. Long crush injury with added stripping of the epineurial blood supply was associated with more profound declines in epineurial RBC flux, to 16% by 3 h, with recovery at 14 days to 70% of that of the contralateral intact nerve trunk. There was, however, only a minimal impact on endoneurial flow: mild reductions immediately and at 1 h after injury, with rebound hyperemia by 48 h. Despite the presence of prominent epineurial ischemia, regenerative sprouting was not impaired by longer segmental injuries with or without epineurial vascular stripping. Axon sprouting was more prominent in both of these types of injuries compared to short-crush lesions. Taken together, these results indicate that focal nerve trunk injury is remarkably resistant to endoneurial ischemia, and that it can sustain regenerative sprouting in spite of prolonged alterations in the epineurial circulation. Approaches to augment epineurial microvascular viability after nerve injury may not support better 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) | 0.002 | 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".