Oral Submucous Fibrosis (OSMF) is a chronic debilitating disease more frequently encountered in the South-East Asian population. This disease represents a public health priority as it is grouped within oral potentially malignant disorders, with malignant transformation rates of around 7–19%. Hence, early identification of high-risk OSMF patients is of the utmost importance to prevent malignant transformation. Among various biomarkers, EGFR overexpression has an unfavorable clinical outcome, poor prognosis, and low survival rates in Oral Squamous Cell Carcinoma (OSCC). The current study aimed to evaluate the expression of EGFR in saliva and exfoliated buccal cells of OSMF. Immunoexpression of EGFR was observed in healthy controls (n = 11), OSCC (n = 106), and OPMD with dysplasia (n = 56), which showed significant expression with increasing grades of dysplasia and OSCC. EGFR expression was evaluated in saliva and exfoliated buccal cells of healthy controls (n = 15), OSMF (n = 24), and OSCC (n = 10) patients using ELISA, which revealed significant expression in OSMF and OSCC. Validation studies were also performed using real-time PCR (RT-PCR) to compare gene expression in healthy controls (n = 9), OSMF (n = 9), and OSCC (n = 25), which showed significant 18-fold upregulation in OSCC and three-fold upregulation in OSMF when compared to healthy controls. Hence, saliva and exfoliated buccal cells could be considered as potential non-invasive diagnostic samples for the evaluation of high-risk patients of OSMF using EGFR as a biomarker.

Introduction Taste perception influences food choices and may contribute to the development and progression of metabolic disorders. Altered taste sensitivity has been reported in individuals with impaired glucose regulation, but comparative data across stages of dysglycemia remain limited. The present study aimed to compare taste sensitivity for sweet, sour, salty, and bitter modalities among healthy controls, pre-diabetic individuals, and patients with type 2 diabetes mellitus (T2DM). Methodology A cross-sectional study was conducted in 45 participants divided into three groups: healthy controls (n = 15), pre-diabetics (n = 15), and T2DM subjects (n = 15). Taste thresholds were assessed using standardized solutions of sucrose (sweet), citric acid (sour), sodium chloride (salty), and quinine hydrochloride (bitter). Data were analyzed using ANOVA to compare taste thresholds across groups and Pearson correlation to evaluate associations with HbA1c levels. Results Sensitivities to sweet and sour tastes decreased significantly from controls to pre-diabetic and T2DM participants (p < 0.001). No significant differences were observed for salty or bitter taste sensitivity (p > 0.05). Higher HbA1c levels showed strong negative correlations with sweet (r = -0.89) and sour (r = -0.85) taste sensitivity (p < 0.001). Conclusions Sweet and sour taste perception declines progressively with worsening glycemic status. Taste testing may serve as a simple, non-invasive adjunct tool for the early detection of dysglycemia and for individualized dietary counseling in diabetes management.

Advances in artificial intelligence have transformed the approach to volumetric segmentation of dental anatomical structures in cone-beam computed tomography (CBCT) and dental CT images. This review explores and compares the performance, applications, and limitations of traditional convolutional neural network (CNN) architectures and the U-Net family for segmentation tasks in dental imaging. Current literature demonstrates that U-Net models consistently outperform classical CNNs in accuracy, efficiency, and reliability for semantic and volumetric segmentation, owing to their unique encoder-decoder structure and skip connections. The manuscript discusses key findings, methodological developments, and future directions for the automated analysis of dental anatomy.