Archives of oral biology最新文献

Objectives: Streptococcus mutans, a causative organism of dental caries, has also been implicated in the pathogenesis of cardiovascular disease (CVD). Substance P (SP) involvement in physiological and pathological processes within the cardiovascular system is currently the foci of research. The role of SP in modulating the human aortic endothelial cells (HAECs) response to S. mutans within the context of CVD pathogenesis has not been examined. This study aimed to investigate SP expression in S. mutans-stimulated HAECs and to clarify the role of SP in the interaction between S. mutans and HAECs, considering its cooperative action with an innate immune factor DMBT1.

Design: HAECs were stimulated with S. mutans strains. SP expression was analyzed by dot blot assay and RT-PCR. S. mutans binding to SP was determined using ELISA. S. mutans aggregation was evaluated by monitoring decrease in optical density and phase-contrast microscopy. Effects of SP and/or DMBT1 on the interaction between S. mutans and HAECs were examined by invasion assay, cytokine assay, and cytotoxicity assay.

Results: All tested S. mutans strains induced SP production in HAECs. S. mutans bound directly to SP. SP agglutinated S. mutans and pronounced aggregation was induced by SP when used with DMBT1. SP reduced S. mutans invasion of HAECs, suppressed S. mutans-induced cytokine production in HAECs, and decreased S. mutans-mediated cytotoxicity to HAECs. These inhibitory effects of SP were further enhanced by DMBT1.

Conclusion: These findings suggest that SP, acting in concert with DMBT1, exerts a protective role against S. mutans-induced CVD processes in HAECs.

Objectives: This study aimed to evaluate salivary monoacetylated polyamines as noninvasive biomarkers for the detection and staging of oral squamous cell carcinoma (OSCC).

Design: Unstimulated saliva samples were collected from healthy controls (n = 15), oral leukoplakia (OLK) patients (n = 15), and OSCC patients stratified into early (n = 28) and advanced stages (n = 46). Seven polyamines were quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Diagnostic performance was assessed via receiver operating characteristic (ROC) analysis, logistic regression modeling, and multivariate clustering.

Results: N¹-acetylspermidine and N¹-acetylspermine showed progressive elevation from OLK to advanced OSCC, with AUCs of 0.87 and 0.81, respectively. A two-marker logistic model achieved a cross-validated AUC of 0.85, demonstrating good discriminatory performance between malignant and non-malignant states. Multivariate analysis confirmed their contribution to disease stratification, while calibration plots supported model reliability.

Conclusions: Salivary N¹-acetylspermidine and N¹-acetylspermine are promising biomarkers for noninvasive OSCC detection and staging.

Background: Exosomes and lactylation modification have been increasingly recognized as key regulators of diseases, yet their integrative role in periodontitis remains unclear. No diagnostic model based on exosome-related lactylation genes (ERLGs) has been previously established for periodontitis. This study aimed to explore ERLGs as potential diagnostic biomarkers for periodontitis.

Methods: Integration of bulk and single-cell RNA sequencing (scRNA-seq) datasets, machine learning modeling, and experimental validation were employed to identify ERLG signatures and dissect their cellular context in periodontitis.

Result: We identified 53 ERLGs that were significantly dysregulated in periodontitis and closely linked to metabolic reprogramming and immune regulation. ERLG-based clustering robustly distinguished periodontitis from healthy tissues and revealed distinct immune infiltration patterns. A machine learning-based diagnostic model using eight core ERLGs (AK3, CHST1, CHST2, MERTK, EGLN3, CXCR4, DSC2, KCNN4) achieved excellent predictive performance (AUC=0.938 in training cohort; validated in two independent cohorts). scRNA-seq uncovered heterogeneous lactylation modification patterns across major cell populations. Fibroblast subclustering revealed three disease-sensitive subsets (Fib_NTRK3, Fib_TNXB, Fib_MFAP5) that were reduced in periodontitis and exhibited reduced lactylation scores. Endothelial cell subclustering identified a disease-enriched Endo_TGM2 population characterized by high lactylation scores, activation of TGF-β, PI3K-AKT-mTOR, and TNFα/NF-κB signaling, and dynamic differentiation trajectories, and strong interactions with fibroblasts. Inflammatory stimulation enhanced exosomal lactylation and derived ERLG dysregulation in human gingival fibroblasts.

Conclusion: This study establishes the first ERLG-based diagnostic model for periodontitis, demonstrates its robust predictive capability and delineates cell type-specific lactylation remodeling, which providing mechanistic insights and potential signature for diagnosis.

Objective: This study aimed to clarify the antibacterial and antibiofilm effects of ferulic acid against periodontal pathogenic bacteria.

Design: The cytotoxicity of ferulic acid was examined using the MTT assay on the human oral epithelial cell line Ca9-22. To determine the minimum inhibitory concentration (MIC) and minimum bactericidal concentration, Porphyromonas gingivalis ATCC 33277, Fusobacterium nucleatum ATCC 25586, Prevotella intermedia ATCC 25611, Aggregatibacter actinomycetemcomitans JP2, and Streptococcus mitis ATCC 903 were treated with ferulic acid. The inhibition of biofilm formation was evaluated by crystal violet staining. The inhibition of P. gingivalis autoinducer-2 (AI-2) production and receptor activity was evaluated by luminescence measurements using the sensor strain Vibrio harveyi BB170.

Results: Ferulic acid did not exhibit any cytotoxicity on human oral epithelial cells. The MICs of ferulic acid against P. gingivalis and A. actinomycetemcomitans were 1000 and 500 µg/mL, respectively. It did not show antibacterial activity against F. nucleatum, P. intermedia, and S. mitis, indicating the weak antibacterial activity of ferulic acid. However, ferulic acid significantly inhibited P. gingivalis biofilm formation at low concentrations below 1/8 MIC. It specifically inhibited AI-2 production from P. gingivalis below 1/8 MIC and suppressed the receptor activity of AI-2.

Conclusions: Although ferulic acid showed weak antibacterial activity against periodontopathogenic bacteria, it had low cytotoxicity and inhibited P. gingivalis biofilm formation. Ferulic acid inhibited AI-2 production and receptor activity, suggesting that ferulic acid is an efficient quorum-sensing inhibitor for controlling P. gingivalis biofilm formation.