Journal of dental research最新文献

Harold (Hal) C. Slavkin, DDS, the 22nd president of the American Association for Dental, Oral, and Craniofacial Research (1993 to 1994), died on December 22, 2023. During a career that spanned almost 6 decades, Hal distinguished himself as an international authority on craniofacial biology and an advocate for oral health equity. He served as dean of the University of Southern California's dental school, founded the school's Center for Craniofacial Molecular Biology, created the nation's first PhD program in craniofacial biology, and served as the sixth director of the National Institute of Dental and Craniofacial Research. Hal's studies of the molecular and cellular underpinnings of craniofacial malformations prepared him to champion translational research later in his career, when his work with patient advocates revealed the importance of applying new discoveries to clinical practice. A visionary thinker, skilled administrator, progressive educator, compelling communicator, researcher, scholar, and mentor, Hal was known as a Renaissance leader. He rejoiced in fostering collaborative synergies among people and organizations. Throughout his life, family was his central grounding force. He and his wife, Lois, advanced a wide range of social and community initiatives and took great pride in their children, grandchildren, and great-grandchildren. We remember Hal for his indelible spirit, unflappable enthusiasm for science, fierce advocacy for social justice, and infectious zest for life. Here, we outline his multidimensional accomplishments through the lenses of academia, government, and nonprofit organizations. Although it is with heavy hearts that we bid goodbye to this remarkable man, our spirits are lightened by the many gifts he left behind.

Periodontal tissue destruction in periodontitis is a consequence of the host inflammatory response to periodontal pathogens, which could be aggravated in the presence of type 2 diabetes mellitus (T2DM). Accumulating evidence highlights the intricate involvement of macrophage-mediated inflammation in the pathogenesis of periodontitis under both normal and T2DM conditions. However, the underlying mechanism remains elusive. Alpha-2-glycoprotein 1 (AZGP1), a glycoprotein featuring an MHC-I domain, has been implicated in both inflammation and metabolic disorders. In this study, we found that AZGP1 was primarily colocalized with macrophages in periodontitis tissues. AZGP1 was increased in periodontitis compared with controls, which was further elevated when accompanied by T2DM. Adeno-associated virus-mediated overexpression of Azgp1 in the periodontium significantly enhanced periodontal inflammation and alveolar bone loss, accompanied by elevated M1 macrophages and pyroptosis in murine models of periodontitis and T2DM-associated periodontitis, while Azgp1^-/- mice exhibited opposite effects. In primary bone marrow-derived macrophages stimulated by lipopolysaccharide (LPS) or LPS and palmitic acid (PA), overexpression or knockout of Azgp1 markedly upregulated or suppressed, respectively, the expression of macrophage M1 markers and key components of the NLR Family Pyrin Domain Containing 3 (NLRP3)/caspase-1 signaling. Moreover, conditioned medium from Azgp1-overexpressed macrophages under LPS or LPS+PA stimulation induced higher inflammatory activation and lower osteogenic differentiation in human periodontal ligament stem cells (hPDLSCs). Furthermore, elevated M1 polarization and pyroptosis in macrophages and associated detrimental effects on hPDLSCs induced by Azgp1 overexpression could be rescued by NLRP3 or caspase-1 inhibition. Collectively, our study elucidated that AZGP1 could aggravate periodontitis by promoting macrophage M1 polarization and pyroptosis through the NLRP3/casapse-1 pathway, which was accentuated in T2DM-associated periodontitis. This finding deepens the understanding of AZGP1 in the pathogenesis of periodontitis and suggests AZGP1 as a crucial link mediating the adverse effects of diabetes on periodontal inflammation.

This study reviews and appraises the methodological and reporting quality of prediction models for tooth loss in periodontitis patients, including the use of regression and machine learning models. Studies involving prediction modeling for tooth loss in periodontitis patients were screened. A search was performed in MEDLINE via PubMed, Embase, and CENTRAL up to 12 February 2022, with citation chasing. Studies exploring model development or external validation studies for models assessing tooth loss in periodontitis patients for clinical use at any time point, with all prediction horizons in English, were considered. Studies were excluded if models were not developed for use in periodontitis patients, were not developed or validated on any data set, predicted outcomes other than tooth loss, or were prognostic factor studies. The CHARMS checklist was used for data extraction, TRIPOD to assess reporting quality, and PROBAST to assess the risk of bias. In total, 4,661 records were screened, and 45 studies were included. Only 26 studies reported any kind of performance measure. The median C-statistic reported was 0.671 (range, 0.57-0.97). All studies were at a high risk of bias due to inappropriate handling of missing data (96%), inappropriate evaluation of model performance (92%), and lack of accounting for model overfitting in evaluating model performance (68%). Many models predicting tooth loss in periodontitis are available, but studies evaluating these models are at a high risk of bias. Model performance measures are likely to be overly optimistic and might not be replicated in clinical use. While this review is unable to recommend any model for clinical practice, it has collated the existing models and their model performance at external validation and their associated sample sizes, which would be helpful to identify promising models for future external validation studies.

Dimethacrylate-based chemistries feature extensively as resin monomers in dental resin-based materials due to their distinguished overall performance. However, challenges endure, encompassing inadequate mechanical attributes, volumetric shrinkage, and estrogenicity. Herein, we first synthesized a novel resin monomer, 9-armed starburst polyurethane acrylate (NPUA), via the grafting-onto approach. Compared to the primary commercial dental monomer 2,2-bis [p-(2'-hydroxy-3'-methacryloxypropoxy) phenyl] propane (Bis-GMA) (with a viscosity of 1,174 ± 3 Pa·s and volumetric shrinkage of 4.7% ± 0.1%), the NPUA monomer achieves the lower viscosity (158 ± 1 Pa·s), volumetric shrinkage (2.5% ± 0.1%), and cytotoxicity (P < 0.05). The NPUA-based resins exhibit the higher flexural strength, flexural modulus, hardness, and hydrophobicity and lower volumetric shrinkage, water absorption, and solubility compared to the Bis-GMA (70 wt%)/TEGDMA (30 wt%) resins. The NPUA-based composites exhibit significantly higher flexural strength, flexural modulus, and hardness and lower volumetric shrinkage (171.4 ± 3.0 MPa, 12.6 ± 0.5 GPa, 2.0 ± 0.2 GPa, and 3.4% ± 0.2%, respectively) compared to the Bis-GMA group (120.3 ± 4.7 MPa, 9.4 ± 0.7 GPa, 1.5 ± 0.1 GPa, and 4.7% ± 0.2%, respectively; P < 0.05). This work presents a viable avenue for augmenting the physicochemical attributes of dental resins.

Existing studies on multimorbidity have largely excluded oral diseases in multimorbidity prevalence estimates. The reason behind this is somewhat unclear, as chronic oral conditions are highly prevalent, affecting over half the global population. To address this gap, we examined the relationship between social disadvantage and multimorbidity, stratifying by the inclusion and exclusion of oral conditions. For participants aged 30 y and over (n = 3,693), cross-sectional analysis was carried out using the US National Health and Nutrition Survey (2013-2014). Multimorbidity was defined as having 2 or more chronic conditions. Five medical conditions were examined: diabetes, asthma, arthritis, cardiovascular disease, and depression, as well as 4 oral health conditions: caries, periodontal disease, number of teeth, and edentulousness. Education and income poverty ratio were selected as measures of social disadvantage. Multimorbidity prevalence estimates according to social disadvantage were analyzed on an absolute and relative scale using inverse probability treatment weighting (IPTW), adjusting for age, sex, and ethnicity. The inclusion of oral health conditions in the assessment of multimorbidity increased the overall prevalence of multimorbidity from 20.8% to 53.4%. Findings from IPTW analysis demonstrated clear social gradients for multimorbidity estimates stratified by the exclusion of oral conditions. Upon inclusion of oral conditions, the prevalence of multimorbidity was higher across all social groups for both education and income. Stratifying by the inclusion of oral conditions, the mean probability of multimorbidity was 27% (95% confidence interval [CI], 23%-30%) higher in the low-education group compared to the high-education group. Similarly, the mean probability of multimorbidity was 44% (95% CI, 40%-48%) higher in the low-income group. On a relative scale, low education was associated with a 1.52 times (95% CI, 1.44-1.61) higher prevalence of multimorbidity compared to high education. Low income was associated with a 2.18 (95% CI, 1.99-2.39) higher prevalence of multimorbidity. This novel study strongly supports the impact of chronic oral conditions on multimorbidity prevalence estimates.

Analyses of National Health and Nutrition Examination Survey (NHANES) data suggested a significant decrease in sealant prevalence among children between 2011 to 2014 and 2015 to 2018. We explore whether this decrease could be associated with possible changes in 1) clinical sealant delivery, 2) dental materials (i.e., increased use of glass ionomer [GI] sealants resulting in an inability to detect sealant fragments that still provide preventive benefits or increased use of composite restorations leading to misclassifying sealants as restorations), and 3) examination sensitivity and specificity. We used NHANES data to estimate the prevalences of sealants, untreated caries, and restorations in ≥1 first permanent molar among children aged 7 to 10 y and used Medical Expenditure Panel Survey data to estimate the annual clinical delivery of sealants and fluoride treatments. We examined changes in outcomes between 2 periods (P < 0.05) controlling for selected sociodemographic characteristics. NHANES sealant examination quality was based on the reference examiner's replicate examinations. The adjusted prevalence of sealants decreased relatively by 27.5% (46.6% vs. 33.8%). Overall, untreated caries decreased. Untreated caries and restoration decreased among children without sealants. Annual clinical sealant delivery did not change, whereas fluoride treatment delivery increased. The decrease in sealant prevalence held when assessed for various age ranges and NHANES cycle combinations. While sealant examination specificity remained similar between the periods, sensitivity (weighted by the proportion of exams by each examiner) decreased relatively by 17.4% (0.92 vs. 0.76). These findings suggest that decreased sealant prevalence was not supported by decreased clinical sealant delivery nor increased use of composite restorations. Decreased examination sensitivity, which could be due to an increased use of GI sealants, could contribute to the decrease in sealant prevalence. The decrease in caries among children without sealants could suggest the increased use of GI sealants. However, we could not rule out that the decrease in caries could be attributable to increased fluoride treatment delivery.

Research on 3-dimensional (3D) printed porous zirconia-based dental implants is still in its infancy. This study aimed to evaluate the biological responses of novel zirconia implants with p-cell structures fabricated by 3D printing. The solid zirconia samples exhibited comparable density, 3-point flexural strength, and accelerated aging properties compared to specimens prepared previously by conventional methods. Cell-based experiments showed that the p-cell structure promoted cell proliferation, adhesion, and osteogenesis-related protein expression. Mechanical tests showed that both p-cell and control implants could withstand a torque of 35 Ncm without breaking. The mean maximum breaking loads of p-cell and control implants were 1,222.429 ± 115.591 N and 1,903.857 ± 250.673 N, respectively, which were much higher than the human physiological chewing force and human mean maximum occlusal force. An animal experiment showed that the bone trabeculae around the implants were significantly thicker, more numerous, and denser in the p-cell group than in the control group. This work could provide promising guidance for further exploring 3D printing techniques for porous zirconia bionic implants in dentistry.

Quantitative analysis of irregular anatomical structures is crucial in oral medicine, but clinicians often typically measure only several representative indicators within the structure as references. Deep learning semantic segmentation offers the potential for entire quantitative analysis. However, challenges persist, including segmentation difficulties due to unclear boundaries and acquiring measurement landmarks for clinical needs in entire quantitative analysis. Taking the palatal alveolar bone as an example, we proposed an artificial intelligence measurement tool for the entire quantitative analysis of irregular dental structures. To expand the applicability, we have included lightweight networks with fewer parameters and lower computational demands. Our approach finally used the lightweight model LU-Net, addressing segmentation challenges caused by unclear boundaries through a compensation module. Additional enamel segmentation was conducted to establish a measurement coordinate system. Ultimately, we presented the entire quantitative information within the structure in a manner that meets clinical needs. The tool achieved excellent segmentation results, manifested by high Dice coefficients (0.934 and 0.949), intersection over union (0.888 and 0.907), and area under the curve (0.943 and 0.949) for palatal alveolar bone and enamel in the test set. In subsequent measurements, the tool visualizes the quantitative information within the target structure by scatter plots. When comparing the measurements against representative indicators, the tool's measurement results show no statistically significant difference from the ground truth, with small mean absolute error, root mean squared error, and errors interval. Bland-Altman plots and intraclass correlation coefficients indicate the satisfactory agreement compared with manual measurements. We proposed a novel intelligent approach to address the entire quantitative analysis of irregular image structures in the clinical setting. This contributes to enabling clinicians to swiftly and comprehensively grasp structural features, facilitating the design of more personalized treatment plans for different patients, enhancing clinical efficiency and treatment success rates in turn.

The phosphate ester monomer 10-methacryloyloxydecyl dihydrogen phosphate (10-MDP) is capable of bonding to hydroxyapatite and, for this reason, is a key component of several self-etch adhesives. In this study, dicalcium phosphate dihydrate particles (DCPD; CaHPO₄.2H₂O) were functionalized with 10-MDP and used to formulate an experimental composite with 50 vol% inorganic content (3:1 DCPD:silanated barium glass ratio) dispersed in a BisGMA/TEGDMA matrix. The tested hypothesis was that DCPD functionalization would improve the composite's mechanical performance without compromising Ca²⁺ release. Composites containing nonfunctionalized DCPD or only reinforcing glass (in both cases, with or without 10-MDP mixed in the resin phase) were used as controls. Materials were tested for degree of conversion (DC; by Fourier transform infrared spectroscopy), water sorption (WS) and solubility (SL; according to ISO 4049), biaxial flexural strength (BFS)/modulus (FM) after 24 h and 5 mo in water, and 28-d Ca²⁺ release in water (by plasma-coupled optical emission spectroscopy). Data were analyzed using analysis of variance/Tukey test (alpha: 5%). DCPD functionalization did not interfere with DC. The composite containing functionalized DCPD showed significantly lower WS and SL in comparison with the material formulated with nonfunctionalized particles. The presence of 10-MDP (as a functionalizing agent or dispersed in the resin phase) reduced the composite's initial BFS and FM. After 5 mo in water, the composite with functionalized DCPD and both glass-only composites were able to maintain their mechanical properties at levels statistically similar to what was observed after 24 h. Ca²⁺ release was significantly reduced in both formulations containing 10-MDP. In conclusion, DCPD functionalization with 10-MDP increased the composite's resistance to hydrolytic degradation, improving its mechanical stability after prolonged water storage. However, the impaired water transit at the particle-matrix interface led to a reduction in Ca²⁺ release.