Yulong Zhang, Tingxi Wu, Erica Dorigatti de Avila, Renate Lux, Wenyuan Shi, Benjamin M Wu
{"title":"Engineering bio-selectivity: Novel denture coatings for targeted inhibition of denture-associated pathogens.","authors":"Yulong Zhang, Tingxi Wu, Erica Dorigatti de Avila, Renate Lux, Wenyuan Shi, Benjamin M Wu","doi":"10.4012/dmj.2026-037","DOIUrl":null,"url":null,"abstract":"<p><p>The increasing prevalence of denture use, particularly among the elderly population, necessitates effective strategies against Candida-containing polymicrobial biofilms. This study investigated novel temporary (biocompatible hydrogel) and permanent (sealant) denture coatings designed to selectively inhibit associated pathogens. Seven biomaterials were screened using minimum inhibitory concentration (MIC) assays against Candida albicans, Fusobacterium nucleatum, and Streptococcus mutans. Coatings were applied to acrylic surfaces and evaluated for physicochemical properties and antimicrobial efficacy using biofilm models and colony-forming unit (CFU) counting. Results demonstrated that poly(ethylene glycol) diacrylate / titanium dioxide (PEGDA/TiO<sub>2</sub>) and Sealant/TiO<sub>2</sub> formulations exhibited significant, selective antimicrobial activity. This efficacy is attributed to altered surface hydrophilicity and the specific mechanisms of incorporated agents. These findings underscore the potential of biocompatible, bio-selective coatings in preventing denture-associated infections. Additional research involving a broader spectrum of oral microbes is required to further validate these preventive applications.</p>","PeriodicalId":11065,"journal":{"name":"Dental materials journal","volume":" ","pages":"481-490"},"PeriodicalIF":1.8000,"publicationDate":"2026-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dental materials journal","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.4012/dmj.2026-037","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/7/1 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"DENTISTRY, ORAL SURGERY & MEDICINE","Score":null,"Total":0}
引用次数: 0
Abstract
The increasing prevalence of denture use, particularly among the elderly population, necessitates effective strategies against Candida-containing polymicrobial biofilms. This study investigated novel temporary (biocompatible hydrogel) and permanent (sealant) denture coatings designed to selectively inhibit associated pathogens. Seven biomaterials were screened using minimum inhibitory concentration (MIC) assays against Candida albicans, Fusobacterium nucleatum, and Streptococcus mutans. Coatings were applied to acrylic surfaces and evaluated for physicochemical properties and antimicrobial efficacy using biofilm models and colony-forming unit (CFU) counting. Results demonstrated that poly(ethylene glycol) diacrylate / titanium dioxide (PEGDA/TiO2) and Sealant/TiO2 formulations exhibited significant, selective antimicrobial activity. This efficacy is attributed to altered surface hydrophilicity and the specific mechanisms of incorporated agents. These findings underscore the potential of biocompatible, bio-selective coatings in preventing denture-associated infections. Additional research involving a broader spectrum of oral microbes is required to further validate these preventive applications.
期刊介绍:
Dental Materials Journal is a peer review journal published by the Japanese Society for Dental Materials and Devises aiming to introduce the progress of the basic and applied sciences in dental materials and biomaterials. The dental materials-related clinical science and instrumental technologies are also within the scope of this journal. The materials dealt include synthetic polymers, ceramics, metals and tissue-derived biomaterials. Forefront dental materials and biomaterials used in developing filed, such as tissue engineering, bioengineering and artificial intelligence, are positively considered for the review as well. Recent acceptance rate of the submitted manuscript in the journal is around 30%.