Journal of dental research最新文献

Behavioral interventions can improve children's oral hygiene practices. The multiphase optimization strategy (MOST) offers a framework to prepare, optimize, and evaluate behavioral interventions. This optimization trial tested 3 intervention components-brief motivational interviewing (MI), storytelling videos (STVs), and oral health promotion messages (OHPMs)-in enhancing mother's self-reported brushing of their preschool children's teeth. A total of 128 mothers with children <5 y old were included in a 2³ factorial trial. The primary outcome was children's plaque accumulation, assessed using the modified Plaque Index of Silness and Löe, with scores ranging from 0 to 3. The secondary outcome was mothers' self-reported frequency of brushing their children's teeth, categorized as at least once daily or less than once daily. Mothers were randomized to 8 experimental conditions based on combinations of on-off levels of the 3 components. Linear regression and generalized linear regression with logit link function were used to assess the impact of the components and their interactions on plaque score and daily toothbrushing after 3 mo. Multiple imputation was used for missing values. The principle of effect hierarchy guided the selection of components for inclusion in the optimized package, giving priority to main effects and 2-way over 3-way interactions. Plaque was reduced from mean = 1.8 at baseline to mean = 1.5 and daily toothbrushing increased from 50.8% to 69.5% after 3 mo. MI led to non-significantly less plaque and non-significantly more daily toothbrushing. Combining OHPMs and STVs together without MI canceled each other. Neither the main effects nor the 2- or 3-way interactions significantly affected the 2 outcomes. Individual or combined components did not significantly reduce plaque or increase daily toothbrushing. MI had the greatest promise for behavior change, and the m-oral health components need modification before they can be combined with MI in a health promotion package.

Big data has emerged as a pivotal asset in addressing oral health disparities in recent years. Big data encompasses the vast pool of health care-related biomedical information sourced from diverse channels, such as claims data, patient registries, and electronic health records (EHRs). This study is a critical review that synthesizes the evidence, identifies gaps in knowledge, and discusses future implications regarding big data analytics and oral health disparities. Published reports from 2014 to 2023 that studied associations between big data, social determinants of oral health, and oral health disparities, published in English and available in electronic databases, were included. Search engines were MEDLINE via PubMed, Google Scholar, and Web of Science. A total of 23 studies were included in the review, and all were retrospective data analytics. Studies have used a variety of big data sources, including EHRs, claims, and national or regional registries. This study used a framework of data quality dimensions with intrinsic (data attributes) and contextual values (information provided by the data, in this case, oral health disparities) to critically appraise the included studies. Big data revealed disparities in oral health outcomes and dental care utilization based on race, ethnicity, socioeconomic status, geographical location, insurance category, access to care, and other barriers to care. For the intrinsic data dimension, none of the studies addressed or reported data missingness or consistency of the data. The studies clearly provided contextual data dimensions. From a value-added perspective, several studies provided novel and new information related to racial oral health inequities. Several studies used more than one oral health disparities variable or a composite variable. However, the conclusions from several studies were based on association-based analytics, and few studies used artificial intelligence approaches to understand the population's oral health inequities-gaps were seen in the study designs and causal analytics.

In dentistry, disinfection with antimicrobials is employed under different conditions and at different time points. During the COVID-19 pandemic, the use of disinfectant dental sprays was proposed, among other measures, to help prevent the transmission of infections during dental procedures that require highly effective antiseptics at particularly short contact times. The study aimed to evaluate the efficacy of electrolyzed saline (EOS) compared with other antiseptics in terms of the spread of enveloped and nonenveloped viruses by ultrasonic scaler (USS)-generated dental spray. Suspension tests were performed to evaluate the antiviral efficacy of EOS against herpes simplex virus 1 (HSV-1) and human adenovirus (HAdV), which served as models for enveloped and nonenveloped viruses, respectively. EOS, mostly composed of hypochlorous acid (HOCl), reduced the amount of both virus types in the presence or absence of artificial saliva by > 4 log₁₀ 50% tissue culture infectious dose (P < 0.001). In addition, the mechanism of virucidal effect was investigated using transmission electron microscopy. Following this assessment, a virus-laden dental spray transmission model was used to simulate virus-infected patients undergoing dental procedures with USS. Attenuation was achieved by substituting the USS coolant with one of the effective, pretested antiseptics. Due to safety concerns, nonhuman viral pathogens-equine arteritis virus (EAV) and feline calicivirus (FCV)-served as enveloped and nonenveloped virus models, respectively. Viral infection was evaluated by direct droplet/aerosol infection of RK-13 or CRFK cells. In addition, the biocompatibility of the antiseptics was tested with exposure to human oral keratinocytes. EOS demonstrated strong virucidal activity against both enveloped and nonenveloped viruses and was able to absolutely prevent airborne transmission of EAV and FCV through dental spray in the splatter and droplet/aerosol samples. The study emphasized that EOS, a chlorine-based antiseptic, is a promising, reasonably safe, broad-spectrum agent for preventing dental spray-mediated viral transmission.

The GLOBICS-Global Consortium of Oral Health Birth Cohort Studies (OHBCS)-is a long-lasting international collaborative research group among existing OHBCS, established in response to the Lancet Series on Oral Health, which pointed out the need to shift the global oral health agenda. This study aimed to identify priority research questions from OHBCS that can be leveraged to improve children's global oral health. A 2-phase online Delphi process sought consensus over research priorities for OHBCS. Participants were identified by mapping existing OHBCS. Fourteen research questions were grouped into 4 thematic areas. A 9-point Likert-type scale was applied. Consensus was achieved if the question had (1) at least 51% of participants scoring a research question as "high priority," (2) an interquartile range of <2.5, and (3) a standard deviation of <1.7 or 75% of responses falling between 2 points above and below the mean score. Forty-four of 114 participants completed the Delphi survey. The 8 research priorities identified included questions about the effect of childhood dental visits on oral health throughout life (n = 2), questions related to sugar consumption and dental caries in childhood and adolescence (n = 4), infant growth and dental diseases (n = 1), and whether socioeconomic inequalities in dental caries are mitigated by fluoride exposure (n = 1). Guided by expert insight, the priorities identified for future OHBCS research should leverage a life course perspective to address knowledge gaps in children's oral health and oral health equity.

The colonization of dental implants by oral biofilms causes inflammatory reactions that can ultimately lead to implant loss. Therefore, safety-integrated implant surfaces are under development that aim to detect bacterial attachment at an early stage and subsequently release antibacterial compounds to prevent their accumulation. Since primary oral colonizers ferment carbohydrates leading to local acidification, pH is considered a promising trigger for these surfaces. As a prerequisite for such systems, the present study aimed at specifically analyzing the pH at the interface between implant material and oral biofilms. For this purpose, in vitro-grown Streptococcus oralis monospecies biofilms and an established multispecies biofilm on titanium discs as well as in situ-grown biofilms from orally exposed titanium-equipped splints were used. Mature biofilm morphology was characterized by live/dead fluorescence staining, revealing improved growth from in vitro to in situ biofilms as well as a general decreasing membrane permeability over time due to the static incubation conditions. For pH analysis, the pH-sensitive dye C-SNARF-4 combined with 3-dimensional imaging by confocal laser-scanning microscopy and digital image analysis were used to detect extracellular pH values in different biofilm layers. All mature biofilms showed a pH gradient, with the lowest values at the material interface. Interestingly, the exact values depicted a time- and nutrient-dependent gradual acidification independently of the biofilm source and for in situ biofilms also independently of the sample donor. After short incubation times, a mild acidification to approximately pH 6.3 could be observed. But when sufficient nutrients were processed for a longer period of time, acidification intensified, leading to approximately pH 5.0. This not only defines the required turning point of pH-triggered implant release systems but also reveals the opportunity for a tailored release at different stages of biofilm formation.

H₂S, as a typical metabolite of periodontal pathogens, exhibits a clear positive correlation with the occurrence and development of periodontitis. H₂S at physiological concentrations can regulate many biological processes. However, excess H₂S in the periodontal pocket can trigger secretion of proinflammatory cytokines, cause oxidative stress, and result in mitochondrial damage and cell death in human gingival fibroblasts, exacerbating periodontitis development and periodontal tissue destruction. Worse, H₂S facilitates bacteria survival and proliferation by maintaining bacterial redox balance and enhancing antibiotic resistance. Unfortunately, scavenging H₂S during periodontitis treatment is usually ignored. Herein, a kind of hyaluronic acid methacryloyl/ZnO (HMZ) composite hydrogel with an H₂S-scavenging ability was prepared to enhance periodontitis treatment. The HMZ hydrogel possessed good injectability and cytocompatibility and was able to remove H₂S by a reaction with ZnO. As a result, the HMZ hydrogel was able to increase cell viability from 13% to 120% for human gingival fibroblasts and 22% to 94% for human periodontal ligament fibroblasts at 48 h, restore mitochondrial homeostasis, and alleviate cGAS-STING signaling pathway-mediated inflammation. Meanwhile, the HMZ hydrogel showed satisfactory antibacterial properties and efficiency of plaque biofilm removal. The in vivo results further confirmed that HMZ hydrogel decreased the concentration of H₂S within the periodontal pocket from 0.7 to 0.8 mM to the normal level (0.3 to 0.4 mM), killed the bacteria in the periodontal tissues, inhibited osteoclast activity, relieved excess inflammation, and decreased the vertical distance between the cementoenamel junction and the alveolar bone crest from 1,175 µm to 798 µm on the 7th day and from 1,075 µm to 693 µm on the 14th day, achieving efficient periodontal bone regeneration. In brief, an H₂S scavenging-based promising strategy was developed to enhance the therapeutic efficiency of periodontitis.

Cementum, a bone-like tissue, is an essential component of periodontium, and periodontitis can lead to degenerative changes in the cementum, eventually resulting in tooth loss. The therapeutic strategy for advanced periodontitis is to achieve periodontal regeneration, of which cementum regeneration is a key criterion. Cementoblasts are responsible for cementogenesis, and their mineralization counts in cementum regeneration. However, research is still limited. Thus, novel treatment targets are required. The expression levels of lysine (K)-specific demethylase 6B (KDM6B), fatty acid oxidation (FAO), and cementogenic markers were detected by quantitative polymerase chain reaction, Western blot, immunofluorescence, and immunohistochemical assays. FAO levels were analyzed by assay kit. In vivo, injection of GSK-J4 into mice detected the influence of KDM6B on cementum formation. Chromatin immunoprecipitation sequencing, transcriptomic RNA sequencing, subsequent chromatin immunoprecipitation-quantitative polymerase chain reaction and overexpression of HADHA (hydroxyacyl-coA dehydrogenase trifunctional multienzyme complex subunit alpha) elucidated the KDM6B-Hadha axis. Global lactylation was detected by Western blot. Lactylation proteomics clarified the modified sites of HADHA. Mutating these sites and applying coimmunoprecipitation confirmed their significance. Knockdown of Kdm6b was utilized to assess its regulation on the lactylation of HADHA, FAO, and mineralization levels. FAO and KDM6B expression was elevated during cementoblast mineralization. KDM6B targeted Hadha and activated its transcription, thereby increasing FAO levels and promoting mineralization. Lactylation occurred in the process of mineralization, and KDM6B could regulate the lactylation of HADHA to promote FAO and mineralization. Overexpression of Hadha and the addition of lactate sodium could rescue the inhibition of mineralization by knockdown of Kdm6b. In summary, during cementoblast mineralization, KDM6B regulates HADHA by mediating histone demethylation and lactylation, thereby upregulating FAO and thus promoting mineralization.

Dental caries among long-term care (LTC) residents is a persistent and complex problem driven by social and structural factors. Systems thinking may be useful in considering novel approaches to reducing disease. This study aimed to develop a system dynamics model to simulate the progression of dentate older adults in LTC through caries severity states and estimate the effects of 3 intervention scenarios on the progression of caries: preventive topical fluoride (TF), arrest of caries with silver diamine fluoride (SDF), and a combination of TF and SDF. Dentate older adults in LTC were categorized into 4 caries severity states by their number of untreated carious lesions. The model assumed that changes in severity states were consistent with incidence rates reported in the literature and available billing data for dental care and that individuals move in and out of the system by entering and exiting the facility or experiencing edentulism. For all scenarios, the proportion of dentate older adults in LTC with 1 or more untreated lesions stays stable, the distribution of disease shifts from a high severity state, and the system approaches equilibrium after 4 y. The TF intervention predicts minimal impacts on decreasing the proportion of dentate older adults with 1 or more untreated lesions (2.5% decrease), while the SDF intervention and the combination interventions were most disruptive. There was a 29.6% and 33.6% decrease, respectively. Given the specific population dynamics in LTC, these findings suggest that long-term (greater than 4 y) interventions should be designed to address both the management of existing lesions and their incidence. This system dynamics model allows researchers to render institution-specific data points from LTCs to estimate the effects of proposed interventions at the respective site.

Several pieces of evidence have been reported regarding the association between periodontitis and systemic diseases. Despite the emphasized significance of prevention and early diagnosis of periodontitis, there is still a lack of a clinical tool for early screening of this condition. Therefore, this study aims to use explainable artificial intelligence (XAI) technology to facilitate early screening of periodontitis. This is achieved by analyzing various clinical features and providing individualized risk assessment using XAI. We used 1,012 variables for a total of 30,465 participants data from National Health and Nutrition Examination Survey (NHANES). After preprocessing, 9,632 and 5,601 participants were left for all age groups and the over 50 y age group, respectively. They were used to train deep learning and machine learning models optimized for opportunistic screening and diagnosis analysis of periodontitis based on Centers for Disease Control and Prevention/ American Academy of Pediatrics case definition. Local interpretable model-agnostic explanations (LIME) were applied to evaluate potential associated factors, including demographic, lifestyle, medical, and biochemical factors. The deep learning models showed area under the curve values of 0.858 ± 0.011 for the opportunistic screening and 0.865 ± 0.008 for the diagnostic dataset, outperforming baselines. By using LIME, we elicited important features and assessed the combined impact and interpretation of each feature on individual risk. Associated factors such as age, sex, diabetes status, tissue transglutaminase, and smoking status have emerged as crucial features that are about twice as important than other features, while arthritis, sleep disorders, high blood pressure, cholesterol levels, and overweight have also been identified as contributing factors to periodontitis. The feature contribution rankings generated with XAI offered insights that align well with clinically recognized associated factors for periodontitis. These results highlight the utility of XAI in deep learning-based associated factor analysis for detecting clinically associated factors and the assistance of XAI in developing early detection and prevention strategies for periodontitis in medical checkups.

Wound healing in the oral mucosa is superior to that in the skin, with faster wound closure accompanied by reduced inflammation, less angiogenesis, and minimal scar formation. A well-characterized oral wound model is critical to investigating the mechanisms of oral wound closure and the efficacy of various clinical interventions. Currently, there are a few human oral wound models, although none of them are well characterized. In the present study, we describe and characterize a human hard palate wound healing model. A 3.5-mm circular and two 1 × 5-mm rectangular full-thickness wounds were made in the first and second molar region, 5 mm from the gingival margin, on the hard palate of human subjects. The circular wound was used to monitor wound closure and collect swabs for a microbiome analysis via 16s rRNA sequencing. The rectangular wounds were biopsied and the tissue was used to evaluate the gene expression of wound healing-related mediators by real-time polymerase chain reaction. Saliva was also collected to examine the protein levels of similar molecules by enzyme-linked immunosorbent assays. Circular wounds were nearly closed on day 7 after wounding. Significant changes in the gene expression of inflammatory cytokines, growth factors, antimicrobial peptides, and extracellular matrix-related molecules were identified in day 1 and day 3 wound tissue and compared with unwounded tissue on day 0. Changes in the protein levels of various mediators were limited in the saliva. In addition, alpha diversity, beta diversity, and differential microbiome analysis demonstrated significant changes in bacterial colonization of the wound surface over time compared with unwounded mucosa. In summary, we comprehensively characterize a human hard palate wound-healing model that details the dynamic changes of wound closure, levels of wound healing-related mediators in the wound and saliva, and the oral wound microbiome.