Dental Caries Management with Antibacterial Silver-Doped Prussian Blue Hydrogel by the Combined Effects of Photothermal Response and Ion Discharge.
Sijie LiQing LiHeng ZhangFang LiJinming HuJunchao QianYuanyin WangJia ZhangZhengyan WuPublished in: ACS applied materials & interfaces (2024)
Caries is a destructive condition caused by bacterial infection that affects the hard tissues of the teeth, significantly reducing the quality of life for individuals. Photothermal therapy (PTT) offers a noninvasive and painless treatment for caries, but the use of unsafe laser irradiance limits its application. To address this challenge, we prepared nanoparticles of silver ion-doped Prussian blue (AgPB), which was encased within cationic guar gum (CG) to form the antibacterial PTT hydrogel CG-AgPB with a photothermal conversion efficiency of 34.4%. When exposed to an 808 nm laser at a power density of 0.4 W/cm 2 , the hydrogel readily reached a temperature of over 50 °C in just 3 min, synchronized by the discharge of Ag + ions from the interstitial sites of AgPB crystals, resulting in broad-spectrum and synergistic antibacterial activities (>99%) against individual oral pathogens ( Streptococcus sanguinis , Streptococcus mutans , and Streptococcus sobrinus ) and pathogen-induced biofilms. In vivo, CG-AgPB-mediated PTT demonstrated a capability to profoundly reduce the terminal number of cariogenic bacteria to below 1% in a rat model of caries. Given the outstanding biocompatibility, injectability, and flushability, this CG-AgPB hydrogel may hold promise as a next-generation oral hygiene adjunct for caries management in a clinical setting.
Keyphrases
- candida albicans
- drug delivery
- silver nanoparticles
- quantum dots
- wound healing
- biofilm formation
- oral health
- cancer therapy
- tissue engineering
- hyaluronic acid
- photodynamic therapy
- drug release
- highly efficient
- gold nanoparticles
- light emitting
- pseudomonas aeruginosa
- gene expression
- staphylococcus aureus
- escherichia coli
- anti inflammatory
- big data
- oxidative stress
- deep learning
- machine learning
- high resolution
- gram negative
- water soluble