Abstract Objective: The aim of this study was to investigate the association between defensin beta 1 ( DEFB1 ) rs11362 polymorphism and susceptibility to periodontitis and to evaluate its influence on clinical outcomes following nonsurgical periodontal therapy. Methods: The prospective case-control study included 95 participants (65 patients with periodontitis and 30 healthy controls). Rs11362 polymorphism was genotyped using Tetra-amplification refractory mutation system polymerase chain reaction. Hardy-Weinberg equilibrium was confirmed in controls ( P = 0.674). Genotype distribution were compared using Pearson’s chi-square or Fisher’s exact test. Multivariable logistic regression under the dominant model (heterozygous genotype [CT] + homozygous genotypes [TT] vs. [CC]), adjusted for body mass index, hypertension, type 2 diabetes mellitus, and smoking and followed by false discovery rate correction, was performed to evaluate periodontitis susceptibility. Clinical attachment loss (CAL), probing pocket depth (PPD), gingival index, and plaque index were evaluated at baseline and after 3 months; treatment-related changes and differences among genotypes were assessed using the Wilcoxon signed-rank test and one-way analysis of variance or Kruskal-Wallis test. Results: No significant differences in genotype or allele distributions were observed between groups. Logistic regression showed no significant association between rs11362 and periodontitis susceptibility (odds ratio = 0.781, 95% confidence interval [CI]: 0.313-1.951). Following treatment, CAL and PPD decreased by 1.11 mm (95% CI: 0.91-1.31) and 1.91 mm (95% CI: 1.66-2.15). Although the CC genotype showed greater mean improvements than the CT and TT genotypes, the between genotype differences were not statistically significant. The absence of a significant association may partly reflect the limited statistical power of this study. Conclusion: DEFB1 rs11362 polymorphism was not significantly associated with periodontitis susceptibility in this cohort. Nonsurgical periodontal therapy significantly improved periodontal outcomes. Larger longitudinal studies are warranted to determine whether DEFB1 rs11362 influences periodontal treatment.
Abstract Objective: To critically analyze the biological basis of enamel biomineralization and evaluate contemporary and emerging strategies for enamel remineralization and regeneration. Methods: A comprehensive narrative review was conducted using literature from major electronic databases, focusing on studies related to amelogenesis, enamel matrix proteins, biomimetic remineralization, and advanced material-based strategies. Relevant articles from the past decade were prioritized, alongside foundational studies. Results: Enamel biomineralization is a highly regulated process involving coordinated protein–mineral interactions. Conventional ion-based remineralization strategies effectively arrest early lesions but fail to replicate the enamel microarchitecture. Advanced approaches, including protein-guided systems, hydrogels, and hybrid biomimetic platforms, demonstrate improved control over crystal orientation and structural integration, though clinical translation remains limited. Conclusion: Current remineralization strategies are predominantly reparative rather than regenerative. Biomimetic approaches show promise in replicating enamel structure; however, significant translational challenges persist. Future clinical success depends on integrating biological principles with material science to achieve functional enamel regeneration.
Abstract Objective: Pro-inflammatory cytokine release and their stimulated bone resorption are regulated by nuclear factor kappa B (NF-κB), which plays an important role in the etiopathogenesis of periodontitis and rheumatoid arthritis (RA). This study assessed if adjunctive therapy with omega-3 fatty acids after scaling and root planing has a role to play in improving the clinical and biochemical parameters (NF-κB levels), compared to scaling and root planing (SRP) alone. Methods: This prospective, double-blind trial (Clinical Trials Registry of India registered: February 2023; trial start: March 2023) enrolled systemically diagnosed RA patients (American College of Rheumatology/European Alliance of Associations for Rheumatology 2010 criteria) exhibiting severe periodontitis (Stage IV, Grade B under the 2017/2018 American Academy of Periodontology/European Federation of Periodontology classification). Active smokers were excluded. Participants were allocated via a computer-generated randomization sequence into treatment arms receiving either SRP alone or SRP with adjunctive dietary omega-3 polyunsaturated fatty acids (PUFAs). The clinical and biochemical variables were assessed at baseline and 3 months postoperatively. The allocation protocol was masked to the investigators and laboratory personnel. Compliance and gastrointestinal tolerability were verified monthly. Results: Baseline demographic characteristics, disease duration, and clinical parameters were homogeneous across groups ( P > 0.05). Adjunctive omega-3 supplementation yielded a statistically significant down-regulation of NF-κB levels compared to SRP alone ( P < 0.05). While clinical variables improved, the magnitude of change did not reach statistical superiority in proportion to the biochemical reduction. This highlights a distinct temporal kinetics gap, where cellular transcription factor suppression precedes macroscopic soft-tissue reattachment and extracellular matrix remodeling. No adverse events were reported. Conclusions: Adjunctive dietary omega-3 PUFA therapy effectively attenuates NF-κB-driven inflammation in patients co-managed for RA and periodontitis. The pronounced biochemical suppression demonstrates rapid anti-inflammatory efficacy, establishing a favorable cellular environment prior to clinical structural healing.
Abstract Objective: Education regarding oral health is essential for improving oral hygiene and is a vital component of dental care services. Mobile applications are effective resources for improving knowledge and skills among healthcare practitioners. This scoping review aimed to critically evaluate and summarize current research on the effectiveness of mobile applications in oral health care. Methods: Evidence documenting the reported effectiveness of mobile applications in dental education and therapeutic interventions among patients seeking dental treatment was included. A literature search of PubMed Central, Cochrane Library, Google Scholar, Scopus, and Web of Science was carried out for the period between 2015 and 2025, yielding 20,183 articles. Based on the inclusion and exclusion criteria, 26 articles were considered for the final review process. Results: On analysis of the included studies, mobile applications were reported as a useful additional tool in medical and dental education because they were cost-effective, adaptable, largely location-independent, and supported learning through online, offline, and simulation methods. The research evaluation indicated that digital applications have improved dental health knowledge, behavioral outcomes, and clinical assessment metrics across various age groups and genders. However, the strength of the evidence supporting these benefits varied across studies. Conclusion: Mobile applications used to provide oral healthcare demonstrated superior effectiveness in influencing patient behavior by enhancing oral hygiene awareness and compliance. Additional studies with detailed and broader clinical parameters are essential to validate the current use and effectiveness of mobile applications in dentistry.
Abstract Objective: Oral potentially malignant disorders (OPMDs) are associated with an increased risk of progression to oral squamous cell carcinoma (OSCC), making early and accurate risk prediction essential for improving patient outcomes. While clinical examination and histopathological assessment remain the standard diagnostic approaches, predicting which lesions will undergo malignant transformation continues to be challenging. In recent years, artificial intelligence (AI) has emerged as a promising adjunctive tool for enhancing diagnostic precision and prognostic assessment. This systematic review and independent quantitative synthesis evaluates and compares contemporary AI-based algorithms used for early detection and prediction of OPMDs and OSCC. Methods: A comprehensive search of PubMed, Scopus, Google Scholar, Cochrane Central Register of Controlled Trials, and Web of Science was conducted for the studies published between 2015 and 2025. Studies assessing AI models for the diagnosis or prediction of malignant transformation were included. Of the 1909 records identified, 7 unique studies (yielding 8 independent datasets) met the eligibility criteria and were included in the qualitative and independent quantitative synthesis. Results: The included studies reported improvement in the diagnostic accuracy and predictive performance of AI-based tools such as random survival forest, DeepSurv, and convolutional neural network in identifying high-risk lesions. Among the evaluated models, DeepSurv demonstrated comparatively stronger prognostic capability for predicting lesion progression. However, variability in datasets, validation strategies, and outcome measures were noted across several studies. Conclusion: AI-based predictive models show meaningful potential in supporting early detection and risk stratification of OPMDs and OSCC. However, further standardized, large-scale studies are necessary to establish their reliability and facilitate integration into routine clinical practice. PROSPERO registry number: CRD420251236709.
