Journal of Dental Research最新文献

{"title":"Unraveling the Microbial Mosaic and Inflammatory Core of Peri-implantitis.","authors":"R C V Casarin,G M Bonilha,H Paz,T B Cerquera,C S Stolf,S P Pimentel,W A M Fernandes,M F Noronha,L M Carvalho,M Z Casati,L M Shaddox,M P Santamaria,M F Monteiro","doi":"10.1177/00220345251344585","DOIUrl":"https://doi.org/10.1177/00220345251344585","url":null,"abstract":"This study investigated the distinct microbiological and immunologic characteristics of peri-implantitis as compared with periodontitis. Both diseases are biofilm-driven inflammatory conditions affecting supportive tissues around teeth or implants, but their specific causes remain not fully understood. A cross-sectional study was carried out to compare the microbial profiles (i.e., composition and functional activity), the inflammatory mediators in crevicular fluid, and the potential impact of titanium particles in peri-implantitis. Twenty patients with moderate to severe periodontitis and 20 with peri-implantitis were included. Clinical assessments were performed, and biofilms were collected for 16S rRNA gene sequencing and metatranscriptomic analysis. Gingival crevicular fluid and peri-implant crevicular fluid were obtained to measure inflammatory markers and titanium levels (peri-implantitis group only). Results showed significant differences in microbial diversity between peri-implantitis and periodontitis. Specifically, peri-implantitis displayed enrichment of species such as Streptococcus parasanguinis, Streptococcus mutans, Cutibacterium acnes, and Aerococcus viridans. Additionally, the immune response in peri-implantitis appeared skewed toward a Th2/Th17 dominance. Analysis of the biofilm's functional activity presented heightened expression of genes associated with flagella, bacterial chemotaxis, and various metabolic pathways in the peri-implantitis group. Interestingly, titanium levels modulate the overall microbial community structure, are associated with the abundance of certain peri-implantitis-associated species, and are positively correlated with Th17 levels in PICF. Peri-implantitis harbors distinct microbial communities and inflammatory patterns, potentially influenced by titanium particles. These findings suggest a unique environment driving tissue destruction in peri-implantitis as compared with periodontitis.","PeriodicalId":15596,"journal":{"name":"Journal of Dental Research","volume":"73 1","pages":"220345251344585"},"PeriodicalIF":7.6,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144652730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Periodontitis and Systemic Disease: The Impact of Covariate Selection.","authors":"N Z Bashir,B A R Woolf,S Burgess,E Bernabé","doi":"10.1177/00220345251356469","DOIUrl":"https://doi.org/10.1177/00220345251356469","url":null,"abstract":"Most evidence implicating periodontitis as a causal agent in systemic disease comes from observational research, where confounding is ubiquitous. There are substantial methodological differences among observational studies, of which an important one is the choice of covariates used to adjust for confounding. The present study assesses the impact of covariate selection on the association between periodontitis and systemic disease, using cardiovascular disease and cognitive function as examples. Data were taken from the National Health and Nutrition Examination Survey, where periodontal status was assessed by full-mouth examination. Nineteen covariates were available for selection, including sociodemographic factors, health behaviors, and physiologic measures. Multiverse analysis and specification curves were used to visualize how the distribution of estimated associations between periodontitis and systemic disease vary across 393,216 models, depending on the selection of covariates. The findings show that estimates of the association between periodontitis and systemic disease are sensitive to the choice of covariates included within models, in some cases spanning positive and negative directions (i.e., Janus effect). Depending on the covariates included in the adjustment set, the odds ratio for the association of severe periodontitis with cardiovascular disease ranged from 0.81 to 1.51, while the linear regression coefficient for the association with cognitive function ranged from -1.56 to 0.50. Our study makes 2 important contributions. First, we introduce the idea of multiverse analysis to periodontal research and show that it can be a valuable tool for understanding challenges around model selection and misspecification. Second, we use rigorous quantitative methods to highlight the importance of careful covariate selection in determining our understanding of the relationship between periodontitis and systemic disease.","PeriodicalId":15596,"journal":{"name":"Journal of Dental Research","volume":"3 1","pages":"220345251356469"},"PeriodicalIF":7.6,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144652707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Culturomics: Deciphering the Microbial Dark Matter in the Oral Cavity.","authors":"S Bartsch,C Kreutz,K J Scholz,E Kohnert,J Hertel,M Wolf,N Jakubovics,A Al-Ahmad,F Cieplik","doi":"10.1177/00220345251346781","DOIUrl":"https://doi.org/10.1177/00220345251346781","url":null,"abstract":"The idea of the tree of life originated in the 19th century and has steadily evolved since then. In the last 20 y, high-throughput sequencing methods have revolutionized microbial ecology and expanded our understanding of this tree of life tremendously. However, this has led to a sharp increase in what is known as microbial dark matter, consisting of bacterial and archaeal taxa that are only known by sequencing and have not yet been cultivated. The lack of ecologic information about these species poses a major challenge. This has led to the need for other approaches to supplement the DNA sequence-based findings. The term \"culturomics\"-which describes the large-scale isolation, culture, and identification of species from an environment-was introduced in 2012 with a focus on the human gut microbiota. The cultivation of new species, which had been neglected for many years, is now firmly back in the spotlight since strains are required for experimental studies to complement the knowledge obtained from microbial DNA sequences. Laboratory culture is essential to gain knowledge of microbial physiology, assign functions to novel genes and proteins, identify resistance profiles, and better understand the impact of different microorganisms on human health. While many culturomics studies have focused on gut microbiota, significant progress has been made in oral microbiology, with the enrichment of Candidatus Nanosynbacter lyticus representing one of the greatest achievements. This review gives a comprehensive overview of the oral microbial community regarding the microbial dark matter and summarizes the work carried out to date on the oral microbiota using culturomics. The capability and challenges of metagenomics and culturomics and the potential use of artificial intelligence are examined, with insights from extensive culturomics research on gut microbiota, which promises applicability to the field of oral microbiology.","PeriodicalId":15596,"journal":{"name":"Journal of Dental Research","volume":"29 1","pages":"220345251346781"},"PeriodicalIF":7.6,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144645926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning Photo Processing for Periodontitis Screening","authors":"L.-R. Tao, Y. Li, X.-Y. Wu, Y. Gu, Y. Xie, X.-Y. Yu, H.-C. Lai, M.S. Tonetti","doi":"10.1177/00220345251347508","DOIUrl":"https://doi.org/10.1177/00220345251347508","url":null,"abstract":"Late detection of periodontitis has significant health implications. Screening via oral images may serve as an accessible nonclinical method. This study tested the hypothesis that diagnostic information in oral images can aid a deep learning algorithm in detecting periodontitis cases. This cross-sectional diagnostic accuracy study involved consecutive subjects seeking care at Shanghai Ninth People’s Hospital, China, and their oral digital twins. The index test was a global activation pooling-based multi-instance deep learning model (DLM) based on pretrained ResNet50, developed and tested in 2 independent samples to identify stage II to IV periodontitis. The model did not use annotated landmarks on images but labeled cases based on a reference consisting of a periodontal clinical examination. The external testing dataset included oral images of subjects diagnosed based on panoramic radiographs. The performance was assessed by the area under the receiver-operating curve (AUROC), sensitivity, and specificity. A total of 387 subjects participated in the internal development and testing. The external testing dataset consisted of 183 subjects. DLM processing of a single frontal view oral image accurately identified stage II to IV periodontitis in the internal (AUROC = 0.93, 95% confidence interval [CI] 0.85–0.98) and external dataset (AUROC = 0.93, 95% CI 0.88–0.96). High consistency was observed between the regions of interest identified in the class activation heat maps and a periodontist (internal test: 99.66%; external test: 99.45%). DLM showed better sensitivity and specificity than clinicians with different skill levels. The multimodal combination of images and other nonclinical parameters led to only marginal improvements in accuracy. DLM processing of oral images shows potential for periodontal health screening. Artificial intelligence focuses on the important image areas but seems to capture features that are not apparent to clinicians. More development and validation are needed to introduce this approach as a screening tool to multiple populations worldwide.","PeriodicalId":15596,"journal":{"name":"Journal of Dental Research","volume":"37 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144611273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling the Transcription Factor Code of Odontoblast Differentiation","authors":"J. Lavický, M. Gonzalez Lopez, V. Chochola, P. Kompaníková, V. Rakultsev, J. Raška, E. Wentworth Winchester, H. Tuaima, L. Englmaier, J. Verner, E. Švandová, M. Buchtová, J. Cotney, V. Bryja, D. Bohačiaková, T. Bárta, J. Krivanek","doi":"10.1177/00220345251348148","DOIUrl":"https://doi.org/10.1177/00220345251348148","url":null,"abstract":"The molecular mechanisms controlling the differentiation of stem cells into specialized cells and tissues are enormously complex. Deciphering the mechanisms behind this precisely regulated process is essential not only for understanding ontogenesis but also for interpretations of evolutionary dynamics. A deep understanding of differentiation processes in various cell types would open the way for safe and targeted tissue engineering. This was previously limited by technical constraints, but the recent development of multiomic approaches has overcome these barriers, providing unprecedented insight into the intricate workings of this molecular machinery. Based on single-cell RNA-seq analyses of continuously growing mouse teeth, 4 transcription factors ( <jats:italic>Etv4</jats:italic> , <jats:italic>Gsc</jats:italic> , <jats:italic>Sall1</jats:italic> , and <jats:italic>Nupr1</jats:italic> ) were selected. Their role during tooth development has not been previously evaluated. Here, we provide evidence about their function in the differentiation of odontoblasts—dental cells responsible for dentin production. Our results revealed that controlled overexpression of specific transcription factors directly in mouse-induced pluripotent stem cells is sufficient to guide their differentiation into cells with an odontoblast-like phenotype, both in vitro and in vivo. The differentiated cells exhibited upregulated expression of odontoblast-specific molecular markers (DMP1 and DSP) as well as production of collagenous and mineralized tissue. We demonstrate that a deep insight into fundamental developmental events can provide a powerful basis for innovative cell differentiation approaches. Taken together, this research might serve as a proof of concept for using large-omics data in the generation of specific, differentiated cell types by controlled expression of a particular transcription factor code. This may represent a turning point in both developmental biology and regenerative medicine fields.","PeriodicalId":15596,"journal":{"name":"Journal of Dental Research","volume":"12 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144611230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Areca Nut Production, Imports, and Their Impact on Oral Cancer Incidence","authors":"L.-M. Cao, B. Zhang, H.-Y. Luo, K. Zhou, Y.-F. Yu, Z.-Z. Li, G.-R. Wang, Y. Xiao, Z.-Q. Zhu, B. Cai, Z. Bian, B. Liu, L.-L. Bu","doi":"10.1177/00220345251344895","DOIUrl":"https://doi.org/10.1177/00220345251344895","url":null,"abstract":"Approximately one-third of global lip and oral cavity cancer (LOC) cases are linked to smokeless tobacco or areca nut (AN) consumption. Over the past 32 y, AN production has significantly increased, accompanied by rising international trade. This study explores the relationship between changes in AN production/import quantities and LOC incidence in regions where consumption is prevalent. LOC incidence rates were obtained from the Global Burden of Disease and GLOBOCAN databases, while AN production and import data were sourced from the Food and Agriculture Organization Corporate Statistical Database and Hainan province’s statistical yearbook. Spearman’s correlation analysis was used to evaluated the relationship between AN production or AN imports and LOC incidence rate in AN-producing/importing regions. Descriptive statistics were used to describe the trends of AN production, AN imports, and LOC incidence in AN-producing/importing regions. In 2021, the total AN production of 12 regions (Bangladesh, Bhutan, China mainland, Taiwan, India, Indonesia, Malaysia, Maldives, Myanmar, Nepal, Sri Lanka, Thailand) was 5.4 times that of 1990, with an average annual production of 1,177,926 tons. A strong positive correlation ( <jats:italic>R</jats:italic> ≥ 0.8, <jats:italic>P</jats:italic> &lt; 0.001) was observed between increased production and LOC incidence in Bangladesh, Bhutan, China mainland, India, Myanmar, Nepal, Sri Lanka, Thailand, and the combined data for all 12 regions. Additionally, among the top 10 countries by average annual AN imports from 2012 to 2021, a positive correlation was observed between their average annual imports and the incidence of LOC in 2022. The findings highlight a positive correlation between large-scale AN production and a rising LOC incidence rate, and AN imports may be associated with a higher incidence of LOC. These results support the need for regulatory measures on AN similar to those used for tobacco to address this growing public health concern.","PeriodicalId":15596,"journal":{"name":"Journal of Dental Research","volume":"3 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144586249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI in Learning Anatomy and Restoring Central Incisors: A Comparative Study.","authors":"P Binvignat,S Valette,A T Hara,P Lahoud,R Jacobs,A Chaurasia,M Ducret,R Richert","doi":"10.1177/00220345251344548","DOIUrl":"https://doi.org/10.1177/00220345251344548","url":null,"abstract":"More than 1 billion individuals worldwide have experienced dental trauma, particularly children aged 7 to 12 y, predominantly affecting the anterior teeth, which has a significant impact on oral health and esthetics. Rapid emergency restorations using composite resin are followed by medium-term lab-fabricated mock-ups. Recent advancements in artificial intelligence (AI) assist dental restorations, and the objective of this study was to compare the performances of different AI approaches for the learning and reconstruction of central incisors. The study was approved by ethical committees and followed AI in dentistry recommendations. STL files of mature permanent maxillary incisors without severe wear were collected from 3 universities. Principal component analysis (PCA) and Deep Learning of Signed Distance Functions (DeepSDF) models were trained using these files. The learning of PCA and DeepSDF approaches were 3-fold cross-validated, and their performances were assessed using the following metrics to measure the reconstruction accuracy: the difference of surfaces, volumes, lengths, average Euclidian distance, Hausdorff distance, and crown-root angulations. Explainability was assessed using feature contribution analysis for PCA and Stochastic Neighbor Embedding (t-SNE) for DeepSDF. DeepSDF showed significantly better precision in surface, volume, and Hausdorff distance metrics compared with PCA. For reconstructions, the lower size of the latent code of the DeepSDF model demonstrated lower performances compared with higher sizes. In addition, DeepSDF raised concerns about explainability. This study demonstrates the potential of PCA and DeepSDF approaches, particularly DeepSDF, for the learning and reconstruction of the anatomy of upper central incisors. To foster trust and acceptance, future research should, however, focus on improving the explainability of DeepSDF models and considering a broader range of factors that influence smile design. These high performances suggest potential clinical applications, such as assisting practitioners in future smile designs and oral rehabilitation using AI approaches.","PeriodicalId":15596,"journal":{"name":"Journal of Dental Research","volume":"11 1","pages":"220345251344548"},"PeriodicalIF":7.6,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144533299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Materials Informatics Opens the Door for Dental Materials Development","authors":"S. Yamaguchi, H. Li, A. Tichy, F. Schwendicke, S. Imazato","doi":"10.1177/00220345251343610","DOIUrl":"https://doi.org/10.1177/00220345251343610","url":null,"abstract":"Materials informatics (MI) has gained attention as a data-driven approach to accelerating material optimization in several fields. By leveraging computational methods, recent advancements in artificial intelligence, and large datasets, MI is poised to significantly accelerate the development of various materials. This approach drives innovative solutions, offers new insights into composition–property relationships, and potentially redefines the standards for material testing and selection. Consequently, MI has become a powerful alternative to traditional experimentation, offering more systematic and efficient pathways for materials innovation. Despite its success in other domains, only a handful of studies have used MI in dental materials research, which has long relied on iterative, labor-intensive empirical testing to make incremental improvements. This narrative review summarizes the fundamental principles of MI while showcasing its emerging role in dental materials research. We also discuss advantages of MI compared with traditional pipelines; current limitations, such as data scarcity and the challenges of translating in vitro findings to clinical outcomes; and future perspectives.","PeriodicalId":15596,"journal":{"name":"Journal of Dental Research","volume":"7 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Randomized Controlled Trial of Silver Diamine Fluoride Application Time","authors":"I.G. Yan, F.M. Zheng, I.G. Sun, E.C.M. Lo, D. Duangthip, C.H. Chu","doi":"10.1177/00220345251345801","DOIUrl":"https://doi.org/10.1177/00220345251345801","url":null,"abstract":"Clinicians have recommended, with no scientific evidence, increasing the application times of 38% silver diamine fluoride (SDF) to foster caries arrest. The current study determined the rate of carious lesion activity in response to topical 38% SDF with increasing treatment application time. A 6-mo, stratified-randomized, double-blind, active-controlled, parallel-group trial compared 9 treatment arms. The primary outcome was carious lesion activity at the tooth-surface level 6 mo after initial treatment. Participants included 665 children aged 3 to 4 y with 2,106 carious teeth (234 teeth/group) with 3,024 active carious tooth surfaces. The carious teeth were block randomized into 9 groups with SDF application times of 3, 5, 10, 15, 30, 45, 60, 120, and 180 s. The dose (SDF application time) and response (proportion of active carious tooth surfaces becoming arrested) were modeled using multiple dose-response models. At the 6-mo examination, 642 children with 2,038 SDF-treated carious teeth and 2,939 SDF-treated carious tooth surfaces were evaluated. The estimated proportion of inactive (arrested) lesions (%) increased over time from 75% at 4 s, to 80% at 16 s, and 84% at 60 s. Among the multiple dose-response models, the Emax model provided the best fit. The estimated rate of the proportion of arrested lesions (%s <jats:sup>−1</jats:sup> ) reduced over time from 0.1%s <jats:sup>−1</jats:sup> at 30 s to 0.05%s <jats:sup>−1</jats:sup> at 43 s. An estimated 16-s application time was required to arrest 80% of caries lesions. The proportion of arrested lesions was associated with lesion-surface type (single/multiple) and tooth location (anterior/posterior). A 16-s application time was estimated to arrest 88% of single tooth-surface lesions in anterior teeth, compared with 66% of multiple tooth-surface lesions in posterior teeth. In conclusion, the trial found an increase in the proportion of arrested lesions with increasing SDF application time, although the rate of the proportion of arrested lesions decreased over application time. (ClinicalTrials.gov NCT04655430)","PeriodicalId":15596,"journal":{"name":"Journal of Dental Research","volume":"18 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The NLRP3 Mediates Masticatory Muscle Atrophy by Pyroptosis and Mitophagy","authors":"Q. Li, A. Gao, C. Wu, X. Song, W. Liu, Y. Cheng, T. Li, K. Zhang, Y. Chen, X. Liu, Y. Hong, T. Wu","doi":"10.1177/00220345251344295","DOIUrl":"https://doi.org/10.1177/00220345251344295","url":null,"abstract":"Masticatory muscle atrophy is relatively common and affects occlusal function, facial appearance, and even quality of life. The molecular mechanisms underlying changes in the masticatory muscles remain largely unknown. The Nod-like receptor protein 3 (NLRP3) inflammasome has been extensively reported to be associated with various myopathies; however, little is known about its role in masticatory muscle atrophy. Here, we investigated the function and underlying mechanisms of NLRP3 inflammasome activation in muscle atrophy models both in vitro and in vivo. First, significant atrophy of the masticatory muscles was observed after excessive orthodontic traction in rats, with NLRP3 inflammasome activation leading to increased myocyte pyroptosis. Further observations in the atrophied masticatory muscles revealed a significant reduction in mitochondrial number and overactivation of mitophagy. Conversely, inhibiting NLRP3 suppressed the expression of pyroptosis-related proteins and alleviated muscle atrophy. Moreover, blocking the activation of the NLRP3 inflammasome considerably alleviated mitochondrial dysfunction in the atrophied masticatory muscles and reduced excessive mitophagy, thereby maintaining intracellular homeostasis and preserving muscle mass. In addition, the results of the in vitro experiments confirmed that knocking down NLRP3 significantly alleviated NLRP3 agonist-induced pyroptosis and atrophy in the myotubes, improved mitochondrial damage, maintained mitochondrial membrane potential (Δψm), and decreased reactive oxygen species production. In summary, this study demonstrates that the NLRP3 inflammasome induces pyroptosis, mitochondrial dysfunction, and mitophagy, thereby becoming an important regulatory factor for masticatory muscle atrophy. Our research provides new insights into the mechanism of masticatory muscle atrophy.","PeriodicalId":15596,"journal":{"name":"Journal of Dental Research","volume":"18 1","pages":""},"PeriodicalIF":7.6,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}