Loss of Innervation and Axon Plasticity Accompanies Impaired Diabetic Wound Healing
Bibliographic record
Abstract
Loss of cutaneous innervation from sensory neuropathy is included among mechanisms for impaired healing of diabetic skin wounds. The relationships between cutaneous axons and their local microenvironment during wound healing are challenged in diabetes. Here, we show that secondary wound closure of the hairy dorsal skin of mice is delayed by diabetes and is associated with not only a pre-existing loss of cutaneous axons but substantial retraction of axons around the wound. At 7d following a 3mm punch wound, a critical period of healing and reinnervation, both intact skin nearby the wound and skin directly at the wound margins had over 30-50% fewer axons and a larger deficit of ingrowing axons in diabetics. These findings contrasted with a pre-existing 10-15% deficit in axons. Moreover, new diabetic ingrowing axons had less evidence of plasticity. Unexpectedly, hair follicles adjacent to the wounds had a 70% reduction in their innervation associated with depleted expression of hair follicular stem cell markers. These impairments were associated with the local upregulation of two established axon regenerative 'roadblocks': PTEN and RHOA, potential but thus far unexplored mediators of these changes. The overall findings identify striking and unexpected superimposed cutaneous axon loss or retraction beyond that expected of diabetic neuropathy alone, associated with experimental diabetic skin wounding, a finding that prompts new considerations in diabetic wounds.
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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 | 0.001 |
| 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".