Evaluation of Fluorescent Light Energy for the Treatment of Acute Second-degree Burns
Bibliographic record
Abstract
INTRODUCTION: The use of photobiomodulation has been proposed to improve wound healing for the last two decades. Recent development in photobiomodulation has led to the development of a novel biophotonic platform that utilizes fluorescent light energy (FLE) within the visible spectrum of light for healing of skin inflammation and wounds. MATERIALS AND METHODS: In this article, FLE was used in preliminary analysis on 18 case studies of acute second-degree burns and in a pilot study using an ex vivo human skin model. Efficacy of FLE on wound healing and tissue remodeling was evaluated by monitoring improvements in the treated tissues, assessing pain for the patients, and by performing human genome microarray analysis of FLE-treated human skin samples. RESULTS: Healing was reported for all 18 patients treated with FLE for acute second-degree burns without reported adverse effects or development of infections. Furthermore, preliminary ex vivo skin model data suggest that FLE impacts different cellular pathways including essential immune-modulatory mechanisms. CONCLUSIONS: The results presented in this article are encouraging and suggest that FLE balances different stages of wound healing, which opens the door to initiating randomized controlled clinical trials for establishing the efficacy of FLE treatment in different phases of wound healing of second-degree burns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".