The accuracy of artificial intelligence (AI)-assisted discrimination of oral cancerous lesions from normal mucosa based on mucosal images was evaluated. Two authors independently reviewed the database until June 2022. Oral mucosal disorder, as recorded by photographic images, autofluorescence, and optical coherence tomography (OCT), was compared with the reference results by histology findings. True-positive, true-negative, false-positive, and false-negative data were extracted. Seven studies were included for discriminating oral cancerous lesions from normal mucosa. The diagnostic odds ratio (DOR) of AI-assisted screening was 121.66 (95% confidence interval [CI], 29.60; 500.05). Twelve studies were included for discriminating all oral precancerous lesions from normal mucosa. The DOR of screening was 63.02 (95% CI, 40.32; 98.49). Subgroup analysis showed that OCT was more diagnostically accurate (324.33 vs. 66.81 and 27.63) and more negatively predictive (0.94 vs. 0.93 and 0.84) than photographic images and autofluorescence on the screening for all oral precancerous lesions from normal mucosa. Automated detection of oral cancerous lesions by AI would be a rapid, non-invasive diagnostic tool that could provide immediate results on the diagnostic work-up of oral cancer. This method has the potential to be used as a clinical tool for the early diagnosis of pathological lesions.

Background: Particulate matter (PM) can cause various negative acute and chronic diseases of the respiratory system, including the upper airways. Curcumin has been reported to have anti-inflammatory and anti-oxidative effects; therefore, we investigated the effects of curcumin on nasal fibroblasts exposed to urban PM (UPM). Methods: Samples of inferior turbinate tissue were obtained from six patients. Flow cytometry was used to assess the levels of reactive oxygen species (ROS) following the treatment of nasal fibroblasts with UPM and/or curcumin. We evaluated the effects of UPM and/or curcumin on the expression of phosphorylated ERK, Nrf2, HO-1, and SOD2 in fibroblasts by Western blotting. Results: When UPM was applied to nasal fibroblasts, ROS production was significantly increased in a dose-dependent manner. UPM-exposed fibroblasts caused the activation of ERK to increase HO-1 expression and decrease SOD2 expression. Treatment with curcumin reduced the UPM-mediated increase in ROS; this decrease in ROS occurred in a dose-dependent manner. The UPM-induced activation of ERK was inhibited by curcumin. Nrf2 production was also promoted to increase the expression of HO-1 and SOD2 by curcumin. Conclusion: Curcumin reduced ROS production caused by UPM in human nasal fibroblasts in a dose-dependent manner, suggesting that curcumin has anti-oxidative effects and may be useful in the treatment of nasal diseases caused by UPM, such as allergic and chronic rhinitis.

Background: Eupatilin is an active flavon extracted from the Artemisia species and has properties such as antioxidant, anti-inflammatory, and anti-cancer. We examined the effect of eupatilin using fine particulate matter (FPM) and human bronchial epithelial cell line (BEAS-2B) to confirm the potential of eupatilin as a therapeutic agent for respiratory diseases caused by FPM. Methods: Reactive oxygen species (ROS) levels were checked by flow cytometry to identify if FPM and eupatilin affect ROS production. Western blotting was performed to identify the mechanism of action of eupatilin in FPM-exposed BEAS-2B cells. Results: When cells were exposed to FPM above 12.5 μg/mL concentration for 24 h, ROS production increased significantly compared to the control. When eupatilin was added to cells exposed to FPM, the ROS level decreased proportionally with the eupatilin dose. The phosphorylation of Akt, NF-κB p65, and p38 MAPK induced by FPM was significantly reduced by eupatilin, respectively. Conclusion: FPM cause respiratory disease by producing ROS in bronchial epithelial cells. Eupatilin has been shown to inhibit ROS production through altering signaling pathways. The ROS inhibiting property of eupatilin can be exploited in FPM induced respiratory disorders.

Background: To evaluate the diagnostic performance of ultrasound risk-stratification systems for the discrimination of benign and malignant thyroid nodules and to determine the optimal cutoff values of individual risk-stratification systems. Methods: PubMed, Embase, SCOPUS, Web of Science, and Cochrane library databases were searched up to August 2022. Sensitivity and specificity data were collected along with the characteristics of each study related to ultrasound risk stratification systems. Results: Sixty-seven studies involving 76,512 thyroid nodules were included in this research. The sensitivity, specificity, diagnostic odds ratios, and area under the curves by K-TIRADS (4), ACR-TIRADS (TR5), ATA (high suspicion), EU-TIRADS (5), and Kwak-TIRADS (4b) for malignancy risk stratification of thyroid nodules were 92.5%, 63.5%, 69.8%, 70.6%, and 95.8%, respectively; 62.8%, 89.6%, 87.2%, 83.9%, and 63.8%, respectively; 20.7111, 16.8442, 15.7398, 12.2986, and 38.0578, respectively; and 0.792, 0.882, 0.859, 0.843, and 0.929, respectively. Conclusion: All ultrasound-based risk-stratification systems had good diagnostic performance. Although this study determined the best cutoff values in individual risk-stratification systems based on statistical assessment, clinicians could adjust or alter cutoff values based on the clinical purpose of the ultrasound and the reciprocal changes in sensitivity and specificity.