Human saliva stimulates skin and oral wound healing in vitro
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite continuous exposure to environmental pathogens, injured mucosa within the oral cavity heals faster and almost scar free compared with skin. Saliva is thought to be one of the main contributing factors. Saliva may possibly also stimulate skin wound healing. If so, it would provide a novel therapy for treating skin wounds, for example, burns. This study aims to investigate the therapeutic wound healing potential of human saliva in vitro. Human saliva from healthy volunteers was filter sterilized before use. Two different in vitro wound models were investigated: (a) open wounds represented by 2D skin and gingiva cultures were used to assess fibroblast and keratinocyte migration and proliferation and (b) blister wounds represented by introducing freeze blisters into organotypic reconstructed human skin and gingiva. Re-epithelialization and differentiation (keratin K10, K13, K17 expression) under the blister and inflammatory wound healing mediator secretion was assessed. Saliva-stimulated migration of skin and oral mucosa fibroblasts and keratinocytes, but only fibroblast proliferation. Topical saliva application to the blister wound on reconstructed skin did not stimulate re-epithelization because the blister wound contained a dense impenetrable dead epidermal layer. Saliva did promote an innate inflammatory response (increased CCL20, IL-6, and CXCL-8 secretion) when applied topically to the flanking viable areas of both wounded reconstructed human skin and oral mucosa without altering the skin specific keratin differentiation profile. Our results show that human saliva can stimulate oral and skin wound closure and an inflammatory response. Saliva is therefore a potential novel therapeutic for treating open skin wounds.
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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 | 0.000 | 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 it