Stem Cell Therapy for Burns: Story so Far
Bibliographic record
Abstract
Burn injuries affect approximately 11 million people annually, with fatalities amounting up to 180,000. Burn injuries constitute a global health issue associated with high morbidity and mortality. Recent years have seen advancements in regenerative medicine for burn wound healing encompassing stem cells and stem cell-derived products such as exosomes and conditioned media with promising results compared to current treatment approaches. Sources of stem cells used for treatment vary ranging from hair follicle stem cells, embryonic stem cells, umbilical cord stem cells, to mesenchymal stem cells, such as adipose-derived mesenchymal stem cells, bone marrow-derived mesenchymal stem cells, and even stem cells harvested from discarded burn tissue. Stem cells utilize various pathways for wound healing, such as PI3/AKT pathway, WNT-β catenin pathway, TGF-β pathway, Notch and Hedgehog signaling pathway. Due to the paracrine signaling mechanism of stem cells, exosomes and conditioned media derived from stem cells have also been utilized in burn wound therapy. As exosomes and conditioned media are cell-free therapy and contain various biomolecules that facilitate wound healing, they are gaining popularity as an alternative treatment strategy with significant improvement in outcomes. The treatment is provided either as direct injections or embedded in a natural/artificial scaffold. This paper reviews in detail the different sources of stem cells, stem cell-derived products, their efficacy in burn wound repair, associated signaling pathways and modes of delivery for wound healing.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 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 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".