Microcirculation surrounding <scp>end‐stage</scp> human chronic skin wounds is associated with endoglin/<scp>CD146</scp>/<scp>ALK</scp>‐1 expression, endothelial cell proliferation and an absence of <scp>p16<sup>Ink4a</sup></scp>
Bibliographic record
Abstract
Abstract Angiogenesis is an essential part of normal skin healing, re‐establishing blood flow in developing granulation tissue. Non‐healing skin wounds are associated with impaired angiogenesis and although the role of re‐establishing macroscopic blood flow to limbs to prevent wound chronicity is well investigated, less is known about vascular alterations at the microcirculatory level. We hypothesised that significant phenotypic changes would be evident in blood vessels surrounding chronic skin wounds. Wound edge tissue, proximal to wound (2 cm from wound edge) and non‐involved skin (>10 cm from wound edge) was harvested under informed consent from 20 patients undergoing elective amputation due to critical limb ischemia. To assess blood vessel structure and viability, tissue was prepared for histological analysis and labelled with antibodies specific for PECAM‐1 (CD31), CD146, endoglin, ALK‐1, ALK‐5, and p16Ink4a as a marker of cellular senescence. Density of microvasculature was significantly increased in wound edge dermis, which was concomitant with increased labelling for endoglin and CD146. The number of CD31 positive vessel density was unchanged in wound edge tissue relative to non‐involved tissue. Co‐labelling of endoglin with the transforming growth factor receptor ALK‐1, and to a lesser extent ALK‐5, demonstrated activation of endothelial cells which correlated with PCNA labelling indicative of proliferation. Analysis of p16Ink4a staining showed a complete lack of immunoreactivity in the vasculature and dermis, although staining was evident in sub‐populations of keratinocytes. We conclude that the endoglin‐ALK‐1‐endothelial proliferation axis is active in the vasculature at the edge of chronic skin wounds and is not associated with p16Ink4a mediated senescence. This information could be further used to guide treatment of chronic skin wounds and optimise debridement protocols.
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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".