Clinicopathological characteristics and diagnostic accuracy of BRAF mutations in ameloblastoma: A Bayesian network analysis.

OBJECTIVE: This Bayesian network meta-analysis was performed to analyze the associations between clinicopathological characteristics and BRAF mutations in ameloblastoma (AM) patients and to evaluate the diagnostic accuracy. MATERIALS AND METHODS: Four electronic databases were searched from 2010 to 2024. The search terms used were specific to BRAF and AM. Observational studies or randomized controlled trials were considered eligible. The incidence of BRAF mutation and corresponding clinicopathological features in AM patients were subjected to Bayesian network analyses and diagnostic accuracy evaluation. RESULTS: A total of 937 AM patients from 20 studies were included. The pooled prevalence of BRAF mutations in AM patients was 72%. According to the Bayesian network analysis, BRAF mutations are more likely to occur in younger (odds ratio [OR], 2.3; credible interval [CrI]: 1.2-4.5), mandible site (OR, 3.6; 95% CrI: 2.7-5.2), and unicystic (OR, 1.6; 95% CrI: 1.1-2.4) AM patients. Similarly, higher diagnostic accuracy was found in the younger, mandible, and unicystic AM groups. CONCLUSIONS: The incidence, risk, and diagnostic accuracy of BRAF mutation in AM were greater in younger patients, those with mandible involvement, and those with unicystic AM than in patients with other clinicopathological features. In addition, there was a strong concordance in the diagnostic accuracy between molecular tests and immunohistochemical analysis.

CT-based radiomics analysis of different machine learning models for differentiating gnathic fibrous dysplasia and ossifying fibroma.

OBJECTIVE: In this study, our aim was to develop and validate the effectiveness of diverse radiomic models for distinguishing between gnathic fibrous dysplasia (FD) and ossifying fibroma (OF) before surgery. MATERIALS AND METHODS: We enrolled 220 patients with confirmed FD or OF. We extracted radiomic features from nonenhanced CT images. Following dimensionality reduction and feature selection, we constructed radiomic models using logistic regression, support vector machine, random forest, light gradient boosting machine, and eXtreme gradient boosting. We then identified the best radiomic model using receiver operating characteristic (ROC) curve analysis. After combining radiomics features with clinical features, we developed a comprehensive model. ROC curve and decision curve analysis (DCA) demonstrated the models' robustness and clinical value. RESULTS: We extracted 1834 radiomic features from CT images, reduced them to eight valuable features, and achieved high predictive efficiency, with area under curves (AUC) exceeding 0.95 for all the models. Ultimately, our combined model, which integrates radiomic and clinical data, displayed superior discriminatory ability (AUC: training cohort 0.970; test cohort 0.967). DCA highlighted its optimal clinical efficacy. CONCLUSION: Our combined model effectively differentiates between FD and OF, offering a noninvasive and efficient approach to clinical decision-making.

Can botulinum toxin injection alleviate the pain of bruxism? A Bayesian network analysis and a single-arm analysis.

Background/purpose: There is inconsistent evidence regarding whether the botulinum toxin A (BTA) injection can relieve pain caused by bruxism. This study aimed to estimate the efficiency of BTA injection in relieving pain caused by bruxism at different follow-up periods. Materials and methods: Five electronic databases were searched from 2005 to 2022 using search terms related to botulinum toxin and bruxism. Only controlled clinical trials were included. Two investigators reviewed each article and discussed any disagreements until a consensus was reached. Pain outcomes as evaluated by the visual analogue scale (VAS) were subjected to single-arm and Bayesian network meta-analyses. Pooling data were measured by a random-effects model. Results: Eleven studies with a total of 365 bruxism patients were included. According to the single-arm analyses of the pooled data, the reduction in bruxism-related pain after BTA injection measured 4.06 points (95% CI = 3.37 to 4.75) on the VAS, and the pain relief was significant in the first 6 months after treatment (P < 0.01). According to the Bayesian analysis, BTA also resulted in significantly greater pain relief than oral splinting (mean difference (MD), -1.5; 95% credible interval (CrI) = -2.7 to -0.19) or saline injection (MD, -3.3; 95% CrI = -6.2 to -0.32). Conclusion: BTA significantly relieves the pain of bruxism for 6 months after injection, and its therapeutic efficacy was higher than that of oral splinting. Nevertheless, further long-term follow-up randomized controlled trials comparing BTA with other management or drugs are warranted.

High-Performance Tin Oxide Thin-Film Transistors Realized by Codoping and Their Application in Logic Circuits.

Tin oxide is a promising channel material, offering the advantages of being low-cost and environmentally friendly and having a wide band gap. However, despite the high electron mobility of SnO2 in bulk, the corresponding thin-film transistors (TFTs) generally exhibit moderate performance, hindering their widespread application. Herein, we proposed a codoping strategy to improve both the electrical property and the stability of SnO2 TFTs. A comparative analysis between doped and undoped SnO2 was conducted. It is observed that taking advantage of the difference in ionic radii between two dopants (indium and gallium) and the tin ions in the host lattice can effectively reduce impurity-induced strain. Additionally, we investigated the effect of codoping content on SnO2 TFTs. The optimal codoped SnO2 (TIGO) TFTs demonstrate high performance, featuring a field-effect mobility of 15.9 cm2/V·s, a threshold voltage of 0.2 V, a subthreshold swing of 0.5 V/decade, and an on-to-off current ratio of 2.2 × 107. Furthermore, the devices show high stability under both positive and negative bias stress conditions with a small threshold voltage shift of 1.8 and -1.2 V, respectively. Utilizing the TIGO TFTs, we successfully constructed a resistor-loaded unipolar inverter with a high gain of 10.76. This study highlights the potential of codoped SnO2 TFTs for advanced applications in electronic devices.

PON3::LCN1 and HTN3::MSANTD3 Gene Fusions With NR4A3/NR4A2 Expression in Salivary Acinic Cell Carcinoma.

Acinic cell carcinoma of the salivary gland (AciCC) is a low-grade carcinoma characterized by the overexpression of the transcription factor nuclear receptor subfamily 4 group A member 3 (NR4A3). AciCC has been the subject of a few molecular research projects. This study delves into AciCC's molecular landscape to identify additional alterations and explore their clinical implications. RNA sequencing and immunohistochemical staining for markers NR4A3/NR4A2, DOG-1, S100, and mammaglobin were utilized on 41 AciCCs and 11 secretory carcinoma (SC) samples. NR4A3 was evident in 35 AciCCs, while the residual 6 were NR4A3-negative and NR4A2-positive; SC samples were consistently NR4A3-negative. A novel fusion, PON3 exon 1- LCN1 exon 5, was detected in 9/41 (21.9%) AciCCs, exhibiting a classical histologic pattern with serous cell components growing in solid sheets alongside the intercalated duct-like component. Clinical follow-up of 39 patients over a median of 59 months revealed diverse prognostic outcomes: 34 patients exhibited no disease evidence, whereas the remaining 5 experienced poorer prognosis, involving local recurrence, lymph node, and distant metastasis, and disease-associated death, 4 of which harbored the PON3::LCN1 fusion. In addition, the HTN3::MSANTD3 fusion was recurrently identified in 7/41 AciCC cases. SC patients lacked both fusions. Immunohistochemistry uncovered differential expression of DOG-1, S100, and mammaglobin across samples, providing nuanced insights into their roles in AciCC. This study accentuates PON3::LCN1 and HTN3::MSANTD3 fusions as recurrent molecular events in AciCC, offering potential diagnostic and prognostic utility and propelling further research into targeted therapeutic strategies.

Mast Cell Infiltration and Subtype Promote Malignant Transformation of Oral Precancer and Progression of Oral Cancer.

The role of mast cell (MC), a common myeloid-derived immune cell, in the development of oral squamous cell carcinoma (OSCC) is unclear. The aim of this study was to investigate MC infiltration in oral precancer and oral cancer. The evaluation of immune cell infiltration and its association with prognosis in OSCC used RNA sequencing and multiple public datasets. Multiplex immunofluorescence was used to explore the infiltration of MC in the microenvironment of OSCC and oral precancer and the interaction with CD8+ cells. The role of MC in OSCC progression was verified by in vivo experiments. The resting MC infiltration was mainly present in oral precancer, whereas activated MC infiltration was significantly higher in OSCC. Activated MC was associated with malignant transformation of oral precancer and poor prognosis of OSCC. In vivo studies showed that MC promoted the growth of OSCC. The infiltration of activated MC was negatively correlated with the infiltration of CD8+ T cells. The subtype of MC containing tryptase without chymase (MCT) was significantly higher in OSCC compared with oral precancer and was associated with poor survival. Furthermore, spatial distance analysis revealed a greater distance between MCT and CD8+ cells, which was also linked to poor prognosis in OSCC. Cox regression analysis showed that MCT could be a potential diagnostic and prognostic biomarker. This study provides new insights into the role of MC in the immune microenvironment of OSCC. It might enhance the immunotherapeutic efficacy of OSCC by developing targeted therapies against MC. SIGNIFICANCE: In this study, we investigated the role of mast cells (MC) in oral precancer and oral cancer and demonstrated that MCs are involved in oral cancer progression and may serve as a potential diagnostic and prognostic marker. It might improve the immunotherapeutic efficacy through developing targeted therapies against MCs.

The prevalence, diagnostic accuracy and genotype-phenotype correlation of GNAS mutations in fibrous dysplasia: a meta-analysis.

Background: There is inconsistent evidence regarding the accuracy of GNAS mutations identification for the diagnosis of FD/MAS. This study was performed to estimate the prevalence and diagnostic accuracy of GNAS mutations detection and to preliminarily investigate the genotype-phenotype correlation in FD patients. Methods: Five electronic databases were searched from 1995 to 2024 using search terms related to GNAS and fibrous dysplasia. Observational studies of FD patients undergoing GNAS mutation detection in FD were included. Results: A total of 878 FD patients were included. The pooled prevalence of GNAS mutations in FD based on the random effects model was 74% (95% CI = 64%-83%). Regarding diagnostic accuracy, a sensitivity of 0.83 (95% CI, 0.65-0.96), specificity of 0.99 (95% CI, 0.98-1.00) and the area under the receiver operating characteristic curve of 98.38% were found. Additionally, meta-analysis and Fisher's test showed the GNAS mutation types were significantly associated with FD types (OR = 3.51, 95% CI = 1.05 to 11.72; p < 0.05). Conclusion: A high detection rate of GNAS mutations occurred in FD, and its detection is reliable for diagnosing FD. Additionally, GNAS mutation type was types were significantly associated with FD type. Systematic Review Registration: Identifier CRD42024553469.