Augmented Wound-Healing Effect of Sodium Thiosulfate-Infused Cosmetic Creams in Frostbite
Bibliographic record
Abstract
Background: Frostbite injury is a thermal injury where ice crystals form in skin tissues and subsequently lead to damage due to prolonged exposure to cold temperatures below 0 °C. The extremities are mostly affected, leading to potential amputation. As there is no pharmacological treatment of frostbite injury, we recently reported that non-clinically viable hydrogen sulfide (H2S) donors promote frostbite wound healing in mice. In this study, we investigated whether commonly used cosmetic creams supplemented with sodium thiosulfate (STS), a clinically viable H2S donor drug, also promote healing of frostbite wounds. Methods: Frozen magnets (−80 °C) were placed on the dorsal skin of 40 C57BL/6 mice for 3 min to induce frostbite injury. Next, commercially available cosmetic creams (Aveeno, Dove, Neutrogena, and Nivea) were topically applied on frostbite wounds daily for 14 days with or without 150 µM of STS supplementation. The mice were sacrificed on day 15 after induction of frostbite injury, and samples of the injured dorsal skin tissue were collected for analysis. Results: Addition of STS enhanced frostbite wound healing, as evidenced by progressive and significantly reduced wound area by about 50% and inflammation (p < 0.05), and markedly increased granulation tissue formation by >45%, fibroblast maturation by >28%, and re-epithelialization by >63% compared to control groups (p < 0.05), with Nivea producing a superior wound-healing effect. Also, STS supplementation significantly upregulated the expression of CD31 (by >25%), KI-67 (by >25%), CD163 (by >20%), fibronectin (by >14%), and cytokeratin (by >50%) in frostbite wounds compared to control groups, with Aveeno and Nivea producing a better wound-healing effect than Dove and Neutrogena creams. Conclusions: In conclusion, STS accelerated healing of frostbite wounds. Therefore, it could be considered as a novel pharmacological treatment of clinical frostbite.
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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) | 0.001 | 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) | 0.000 | 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".