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Despite artificial intelligence used in skin dermatology diagnosis is booming, application in oral pathology remains to be developed. Early diagnosis and therefore early management, remain key points in the successful management of oral mucosa cancers. The objective was to develop and evaluate a machine learning algorithm that allows the prediction of oral mucosa lesions diagnosis. This cohort study included patients followed between January 2015 and December 2020 in the oral mucosal pathology consultation of the Toulouse University Hospital. Photographs and demographic and medical data were collected from each patient to constitute clinical cases. A machine learning model was then developed and optimized and compared to 5 models classically used in the field. A total of 299 patients representing 1242 records of oral mucosa lesions were used to train and evaluate machine learning models. Our model reached a mean accuracy of 0.84 for diagnostic prediction. The specificity and sensitivity range from 0.89 to 1.00 and 0.72 to 0.92, respectively. The other models were proven to be less efficient in performing this task. These results suggest the utility of machine learning-based tools in diagnosing oral mucosal lesions with high accuracy. Moreover, the results of this study confirm that the consideration of clinical data and medical history, in addition to the lesion itself, appears to play an important role. [ABSTRACT FROM AUTHOR]

Cold Atmospheric Plasma (CAP) is an emerging technology with great potential for biomedical applications such as sterilizing equipment and antitumor strategies. CAP has also been shown to improve skin wound healing in vivo, but the biological mechanisms involved are not well known. Our study assessed a possible effect of a direct helium jet CAP treatment on keratinocytes, in both the immortalized N/TERT-1 human cell line and primary keratinocytes obtained from human skin samples. The cells were covered with 200 µL of phosphate buffered saline and exposed to the helium plasma jet for 10–120 s. In our experimental conditions, micromolar concentrations of hydrogen peroxide, nitrite and nitrate were produced. We showed that long-time CAP treatments (≥60 s) were cytotoxic, reduced keratinocyte migration, upregulated the expression of heat shock protein 27 (HSP27) and induced oxidative cell stress. In contrast, short-term CAP treatments (<60 s) were not cytotoxic, did not affect keratinocyte proliferation and differentiation, and did not induce any changes in mitochondria, but they did accelerate wound closure in vitro by improving keratinocyte migration. In conclusion, these results suggest that helium-based CAP treatments improve wound healing by stimulating keratinocyte migration. The study confirms that CAP could be a novel therapeutic method to treat recalcitrant wounds. [ABSTRACT FROM AUTHOR]