QUANTATIVE ASSESSMENT OF WOUND HEALING OF MICE TREATED WITH COMBINATIONS OF LASER IRRADIATIONS AND ANTIBIOTICS VIA EXPONENTIAL MATHEMATICAL MODELLING

Introduction: Photodynamic therapy (PDT) is based on the dye-sensitized photooxidation of biological matter in the target tissue to be treated. The investigations of various wound healing treatments through the application of an exponential decay mathematical model have been tried by analyzing the healing progression of uninfected and infected wounds subjected to different therapeutic interventions. Methodology: Different therapeutic interventions including cefotaxime, providine-iodine, laser irradiation and their combinations were carried out. The mathematical decay model was utilized in the present study for prediction of wound healing over time. Results: Laser in combination with either cefotaxime or providine- iodine was significantly accelerate wound healing. The best significant results were obtained with the using laser-providine iodine- cefotaxime combination. The findings of decay modeling demonstrated the model's capacity to capture diverse healing trajectories and highlight the impact of different therapeutic interventions on wound healing rates. The calculated λ values varied across the dataset, reflecting differences in healing rates as positive λ values indicated a decrease in healing score over time. Conclusions: The best period of exposure in vivo was found to be 0.5 minute once exposure each 3 days. The present findings revealed that treatments incorporating laser therapy, particularly when combined with providine-iodine and/or cefotaxime, exhibited negative λ values, signifying enhanced healing rates. Treatments without laser components generally showed positive λ values, indicating a slower healing progression. These results underscore the potential of the exponential decay model as a quantitative tool for assessing and comparing the effectiveness of wound healing treatments. The model facilitated a deeper understanding of healing dynamics, enabling health workers to make informed decisions in selecting optimal therapeutic strategies.