The homogeneous nanotubular surface regulates macrophage polarization for improving osseointegration.

Background: Periodontitis is a complex chronic inflammatory disease that is particularly associated with health-related conditions such as smoking, excessive drinking and depression. This research aimed to investigate the interaction between these lifestyles factors on periodontitis risk. Methods: This study included participants who participated in the National Health and Nutrition Examination Survey in the United States between 2009 and 2014. They had completed oral health-periodontal examination, Smoking-Cigarette Use Questionnaire, Alcohol Use Questionnaire, and Patient Health Questionnaire. Periodontal clinical attachment loss (CAL) of 3 mm or more and Patient Health Questionnaire-9 (PHQ-9) of 10 scores or more were used to identify periodontitis and depression, respectively. Daily alcohol consumption in the past year was classified into three levels: low (1 drink or less), moderate (between 1 and 3 drinks), and heavy drinking (4 drinks or more), while smoking was defined as having smoked at least 100 cigarettes in one's lifetime. Then, the logistic regression combined with interaction models were used to analyze the independent and combined effects of smoking, drinking and depression on periodontitis risk. Results: The results indicated a statistically significant multiplicative interaction between smoking and depression in relation to the development of periodontitis, both in the overall population (P = 0.03) and among male participants (P = 0.03). Furthermore, among individuals experiencing depression, smoking was found to significantly increase the prevalence of periodontitis by 129% in the younger age group compared to non-smokers (odds ratio [OR]: 2.29; 95% confidence interval [CI]: 1.10 to 4.76). However, the interaction between smoking and alcohol consumption was only significant among females (P < 0.05). There was a dose-dependent relationship between drinking frequency and smoking on periodontitis prevalence. In the smoking population, occasional drinking (OR: 1.70; 95% CI: 1.22 to 2.37) and regular drinking (OR: 2.28; 95% CI: 1.68 to 3.11) significantly increased the prevalence of periodontitis compared to individuals without these two factors. Conclusion: These results suggested that there were interactive effects between smoking, drinking and depression on periodontitis risk and policies aimed at healthy behaviours and mental health may be beneficial for our oral health.

Hypoxic deep-seated infections in refractory environments impede wound healing and exacerbate antibiotic resistance. Sonodynamic therapy (SDT) shows promise in combating pathogenic bacteria; however, the excessive reactive oxygen species (ROS) generated during the process often induce severe inflammatory responses, hindering tissue regeneration. To overcome these limitations, we have developed a multifunctional hydrogel, inspired by the dynamic regulatory mechanisms of rhizobia. GSH-SF/PeMA/MXene-TiO₂ (SP-MT) hydrogel was synthesized through the thiol-ene click chemistry mechanism. Methacrylated pectin (PeMA) and GSH-modified silk fibroin (GSH-SF) were combined with MXene-TiO₂ addition. This hydrogel exhibited favorable injectability, mechanical properties, swelling and degradation performance. In addition, this hydrogel can employ ultrasound-triggered dynamic ROS modulation to enable spatiotemporal regulation of antibacterial activity and promote tissue regeneration, effectively addressing the dual challenges of infection management and oxidative stress. Under ultrasound stimulation, SP-MT hydrogel can rapidly eradicate bacteria by disrupting membrane integrity and electron transport chains (ETCs) while simultaneously generating substantial ROS. Once the ultrasound stimulation ceased, the hydrogel and its degradation products eliminated residual ROS. In vivo studies further demonstrated that the nanohydrogel can accelerate soft tissue regeneration and periodontal bone regeneration by eradicating bacterial biofilms, promoting angiogenesis, and activating the TGF-β/SMAD signaling pathway. Therefore, this work introduces a novel strategy for equipping hydrogels with programmed antibacterial and anti-inflammatory functionalities, providing an innovative solution for treating deep-seated infections, particularly in periodontitis therapy.

This study has developed and optimized a machine learning model to accurately predict the final colors of CAD-CAM ceramics and determine their required minimum thicknesses to cover different clinical backgrounds. A total of 120 ceramic specimens (2 mm, 1 mm and 0.5 mm thickness; n = 10) of four CAD-CAM ceramics - IPS e.max, IPS ZirCAD, Upcera Li CAD and Upcera TT CAD - were studied. The CIELab coordinates (L*, a* and b*) of each specimen were obtained over seven different clinical backgrounds (A1, A2, A3.5, ND2, ND7, cobalt-chromium alloy (CC) and medium precious alloy (MPA)) using a digital spectrophotometer. The color difference (ΔE) and lightness difference (ΔL) results were submitted to 39 different models. The prediction results from the top-performing models were used to develop a fusion model via the Stacking integrated learning method for best-fitting prediction. The SHapley Additive exPlanation (SHAP) was performed to interpret the feature importance. The fusion model, which combined the ExtraTreesRegressor (ET) and XGBRegressor (XGB) models, demonstrated minimal prediction errors (R² = 0.9) in the external testing sets. Among the investigated variables, thickness and background colors (CC and MPA) majorly influenced the final color of restoration. To achieve perfect aesthetic restoration (ΔE<2.6), at least 1.9 mm IPS ZirCAD or 1.6 mm Upcera TT CAD were required to cover the CC background, while two tested glass-ceramics did not meet the requirements even with thicknesses over 2 mm. The fusion model provided a promising tool for automate decision-making in material selection with minimal thickness over various clinical background.