Biological characteristics of stem cells derived from burned skin—a comparative study with umbilical cord stem cells
Bibliographic record
Abstract
INTRODUCTION: Burned human skin, which is routinely excised and discarded, contains viable mesenchymal stromal/stem cells (burn-derived mesenchymal stromal/stem cells; BD-MSCs). These cells show promising potential to enable and aid wound regeneration. However, little is known about their cell characteristics and biological function. OBJECTIVES: This study had two aims: first, to assess critical and cellular characteristics of BD-MSCs and, second, to compare those results with multipotent well-characterized MSCs from Wharton's jelly of human umbilical cords (umbilical cord mesenchymal stromal/stem cells, UC-MSCs). METHODS: BD- and UC-MSCs were compared using immunophenotyping, multi-lineage differentiation, seahorse analysis for glycolytic and mitochondrial function, immune surface markers, and cell secretion profile assays. RESULTS: When compared to UC-MSCs, BD-MSCs demonstrated a lower mesenchymal differentiation capacity and altered inflammatory cytokine secretomes at baseline and after stimulation with lipopolysaccharides. No significant differences were found in population doubling time, colony formation, cell proliferation cell cycle, production of reactive oxygen species, glycolytic and mitochondrial function, and in the expression of major histocompatibility complex I and II and toll-like receptor (TLR). IMPORTANCE, TRANSLATION: This study reveals valuable insights about MSCs obtained from burned skin and show comparable cellular characteristics with UC-MSCs, highlighting their potentials in cell therapy and skin 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 | 0.001 | 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".