Characteristics of Serum Exosomes after Burn Injury and Dermal Fibroblast Regulation by Exosomes In Vitro
Bibliographic record
Abstract
(1) Background: Exosomes (EXOs) have been considered a new target thought to be involved in and treat wound healing. More research is needed to fully understand EXO characteristics and the mechanisms of EXO-mediated wound healing, especially wound healing after burn injury. (2) Methods: All EXOs were isolated from 85 serum samples of 29 burn patients and 13 healthy individuals. We characterized the EXOs for morphology and density, serum concentration, protein level, marker expression, size distribution, and cytokine content. After a confirmation of EXO uptake by dermal fibroblasts, we also explored the functional regulation of primary human normal skin and hypertrophic scar fibroblast cell lines by the EXOs in vitro, including cell proliferation and apoptosis. (3) Results: EXOs dynamically changed their morphology, density, size, and cytokine level during wound healing in burn patients, which were correlated with burn severity and the stages of wound healing. EXOs both from burn patients and healthy individuals stimulated dermal fibroblast proliferation and apoptosis. (4) Conclusions: EXO features may be important signals that influence wound healing after burn injury; however, to understand the mechanisms by which EXOs regulates the fibroblasts in healing wounds, further studies will be required.
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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".