OBJECTIVES: This study aims to compare the effects of two orthodontic treatment modalities for skeletal class Ⅲ malocclusion on specific changes in airway volume, morphology, palatal angle, mandibular rotation, and bone displacement. Results provide scientific evidence for the selection of orthodontic treatment plans and reduce the risk of developing obstructive sleep apnea hypopnea syndrome (OSAHS). METHODS: Thirty-six patients diagnosed with skeletal class Ⅲ malocclusion at the Department of Orthodontics, the Affiliated Stomatological Hospital of Nanjing Medical University from September 2018 to December 2023 were divided into two groups: orthodontic-orthognathic treatment group (18 patients) and camouflage orthodontic treatment group (18 patients). Changes in airway volume, cross-sectional area, palatal angle, mandibular, and tongue positions were observed through pre- and post-operative cone beam computed tomography and 3D cephalometric measurements. RESULTS: In the camouflage orthodontic treatment group, nasopharyngeal volume and oropharyngeal volume statistically increased after treatment (P<0.05). In the orthodontic-orthognathic treatment group, changes in nasopharyngeal volume, nasopharyngeal airway, distance from posterior tongue to pharyngeal wall, palatal angle, mandibular rotation, and hyoid bone displacement were statistically significant after surgery (P<0.05). In the comparison between the two groups after treatment, changes in the distance from posterior tongue to pharyngeal wall, palatal angle, and distance from hyoid bone to sella turcica point were statistically significant (P<0.05). CONCLUSIONS Patients in the orthodontic-orthognathic treatment group showed significantly greater changes in oropharyngeal cross-sectional area, palate angle, and tongue position compared with patients in the camouflage orthodontic treatment group. As individuals susceptible to OSAHS often exhibit mandibular retrusion and decreased minimum airway cross-sectional area, special attention should be paid to airway morphology changes when adopting orthodontic-orthognathic treatment to avoid adverse consequences.
Humans ; Hyoid Bone/diagnostic imaging* ; Malocclusion, Angle Class III/therapy* ; Male ; Female ; Cone-Beam Computed Tomography ; Cephalometry ; Orthodontics, Corrective/methods* ; Adult ; Mandible ; Pharynx/diagnostic imaging* ; Sleep Apnea, Obstructive/etiology* ; Orthognathic Surgical Procedures

Objective:To investigate the regulatory effect of long non-coding RNA (lncRNA) FTX on gastric cancer cell proliferation through miR-22-3p/NOD-like receptor protein 3 (NLRP3) inflammasome pathway.Methods:The gastric cancer cell line NCI-N87 were divided into blank control group, si-FTX-NC group, si-FTX group, si-FTX+miR-22-3p inhibitor-NC group and si-FTX+miR-22-3p inhibitor group. Quantitative real-time fluorescent PCR was performed to analyze the expression levels of lncRNA FTX and miR-22-3p, clone formation assay was performed to analyze the proliferation ability of NCI-N87 cells, western blotting was performed to analyze the expressions of NLRP3 inflammasome pathway proteins, and dual-luciferase reporter assay was performed to analyze the targeting relationship between lncRNA FTX and miR-22-3p.Results:The relative expressions of lncRNA FTX in the blank control group, si-FTX-NC group, si-FTX group, si-FTX+miR-22-3p inhibitor-NC group and si-FTX+miR-22-3p inhibitor group were 1.03±0.09, 1.01±0.15, 0.42±0.08, 0.45±0.06 and 0.46±0.13 respectively, with a statistically significant difference ( F=52.19, P<0.001). The relative expressions of miR-22-3p were 1.04±0.12, 0.97±0.08, 2.26±0.15, 2.23±0.13 and 1.15±0.11 respectively, with a statistically significant difference ( F=178.53, P<0.001). Compared with the blank control group and si-FTX-NC group, the relative expressions of lncRNA FTX in the si-FTX group, si-FTX+miR-22-3p inhibitor-NC group and si-FTX+miR-22-3p inhibitor group decreased (all P<0.001). Compared with the blank control group, si-FTX-NC group and si-FTX+miR-22-3p inhibitor group, the relative expressions of miR-22-3p in the si-FTX group and si-FTX+miR-22-3p inhibitor-NC group increased (all P<0.001). The clones of the five groups were 115.50±7.25, 112.33±8.46, 54.83±5.17, 56.17±6.32 and 85.67±9.43, with a statistically significant difference ( F=91.67, P<0.001). The levels of NLRP3 protein in the five groups were 1.84±0.17, 1.86±0.12, 0.95±0.09, 0.97±0.11 and 1.28±0.19, with a statistically significant difference ( F=60.62, P<0.001). Compared with the blank control group and si-FTX-NC group, the number of clones and the level of NLRP3 protein of the si-FTX group, si-FTX+miR-22-3p inhibitor-NC group and si-FTX+miR-22-3p inhibitor group decreased (all P<0.05). Compared with the si-FTX+miR-22-3p inhibitor group, the number of clones and the level of NLRP3 protein in the si-FTX group and si-FTX+miR-22-3p inhibitor-NC group decreased (all P<0.05). The dual-luciferase reporter assay found that miR-22-3p was the target gene of lncRNA FTX. Conclusion:Silencing the expression of lncRNA FTX can inhibit the proliferation of gastric cancer cells, and the mechanism may be related to the regulation of lncRNA FTX on the miR-22-3p/NLRP3 inflammasome pathway.

Immune cell infiltration is of great significance for the diagnosis and prognosis of cancer. In this study, we collected gene expression data of non-small cell lung cancer (NSCLC) and normal tissues included in TCGA database, obtained the proportion of 22 immune cells by CIBERSORT tool, and then evaluated the infiltration of immune cells. Subsequently, based on the proportion of 22 immune cells, a classification model of NSCLC tissues and normal tissues was constructed using machine learning methods. The AUC, sensitivity and specificity of classification model built by random forest algorithm reached 0.987, 0.98 and 0.84, respectively. In addition, the AUC, sensitivity and specificity of classification model of lung adenocarcinoma and lung squamous carcinoma tissues constructed by random forest method 0.827, 0.75 and 0.77, respectively. Finally, we constructed a prognosis model of NSCLC by combining the immunocyte score composed of 8 strongly correlated features of 22 immunocyte features screened by LASSO regression with clinical features. After evaluation and verification, C-index reached 0.71 and the calibration curves of three years and five years were well fitted in the prognosis model, which could accurately predict the degree of prognostic risk. This study aims to provide a new strategy for the diagnosis and prognosis of NSCLC based on the classification model and prognosis model established by immune cell infiltration.
Algorithms ; Carcinoma, Non-Small-Cell Lung ; diagnosis ; physiopathology ; Humans ; Lung Neoplasms ; diagnosis ; physiopathology ; Machine Learning ; Prognosis