The periodontal condition has a reciprocal relationship with rheumatoid arthritis (RA). Rheumatoid arthritis patients are reported to present with more serious periodontal disease (PD) as compared to non-RA patients. This study aimed to evaluate the effects of non-surgical periodontal treatment on Vietnamese patients with active RA and PD, where the clinical characteristics and serum indices of the patients were of interest. We conducted a randomized clinical trial (RCT) on 82 RA patients with PD. The patients were randomly divided into 2 groups: the intervention group, consisting of patients who received oral hygiene instructions, scaling and root planing; and the control group, consisting of patients who received oral hygiene instructions only. Both groups received the same treatment plan for RA. The Disease Activity Score 28 based on C-reactive protein (DAS28-CRP), disease activity classification, rheumatoid factor (RF), erythrocyte sedimentation rate (ESR), anti-citrullinated protein autoantibodies (ACPAs), and C-reactive protein (CRP) were monitored, with the measurements taken at 3 months and 6 months following the treatment. The 2 groups exhibited similar parameters at baseline. In the intervention group, DAS28-CRP and disease activity classification were significantly reduced at 3 months after treatment as compared to the baseline data. At 6 months following the treatment there was a significant decrease in ESR, ACPAs and DAS28-CRP in the intervention group, while the control group showed a decrease only in ACPAs. Further, when comparing the intervention and control groups at 6 months following the treatment, there were no differences between the groups in the ACPAs, RF and CRP serum levels. Non-surgical periodontal treatment can significantly reduce DAS28-CRP, disease activity classification, ESR, and the ACPAs level in serum, and can be applied to reduce RA severity in RA patients with PD.

To evaluate and compare the oral neutrophil numbers (ONN) in saliva, the level of matrix metalloproteinase-8 (MMP-8) in gingival crevicular fluid (GCF) and the periodontal parameters in smokers versus non-smokers with periodontitis, before and after nonsurgical periodontal treatment (NSPT). 40 chronic periodontitis patients including 20 smokers and 20 non-smokers were enrolled in this quasi-experimental study. All patients were received the NSPT included instructing oral hygiene, scaling and root planing. At baseline (T0) and after NSPT 1 month (T1) and 3 months (T3), all patients were assessed for salivary ONN, GCF MMP-8, and clinical parameters like plaque index (PlI), gingival index (GI), bleeding on probing (BOP), probing pocket depth (PPD) and clinical attachment loss (CAL). The differences between the two groups were analyzed using the independent sample t-test and the Mann-Whitney U test; and the differences between T0, T1 and T3 of each group were analyzed with paired-samples t-test and Wilcoxon signed-rank test. The level of significance was set at 0.05. The ONN was significantly less in smokers than in non-smokers although there was no significant difference in other parameters between the two groups at baseline (p > 0.05). All clinical periodontal parameters reduced significantly after 1 month and 3 months of NSPT in both groups (p < 0.01). PPD of non-smokers was significantly lower than those of smokers at T1 and T3. ONN and MMP-8 level showed a significant decrease in non-smoking subjects, while there was no significant difference in smoking ones after NSPT (T1 and T3). At 1 month after treatment, ONN tended to reduce in non-smokers whereas to increase in smokers significantly. Smoking reduced ONN, impaired treatment effect in reducing PPD, and changed the MMP-8 level in gingival crevicular fluid to NSPT. Identifier NCT04974502 in CLinicalTrials.gov

Objectives: In this study, we aimed to investigate the effects of a mixture of advanced platelet‐rich fibrin (A‐PRF) and xenogenic bone substitute material (XBSM) on the proliferation and migration of human periodontal ligament stem cells (hPDLSCs) based on the in vitro release of growth factors.Material and Methods: The concentrations of platelet‐derived growth factor‐AB (PDGF‐AB) and vascular endothelial growth factor (VEGF) released by the A‐PRF‐XBSM mixture were estimated using enzyme‐linked immunoassay for up to 7 d. The A‐PRF‐XBSM mixture exudate was incubated with hPDLSCs. At Days 1, 3, 5, and 7, cell proliferation and migration were investigated by cell counting and wound‐healing assays.Results: PDGD‐AB and VEGF were released from the A‐PRF‐XBSM mixture exudate for up to 7 days. hPDLSCs were cultured in media with various concentrations of the A‐PRF‐XBSM mixture exudate and exhibited their proliferation and migration ability. Furthermore, the factors released from the 100% A‐PRF‐XBSM mixture exudate had a substantial effect on cell migration, whereas those released from 4% and 20% A‐PRF‐XBSM mixture exudates stimulated hPDLSC proliferation.Conclusions: A‐PRF‐XBSM mixture continuously released growth factors over 7 days and enhanced hPDLSC proliferation and migration. Therefore, A‐PRF in combination with XBSM might provide potential advantages for periodontal tissue regeneration.

Background: Periodontal diseases are common chronic conditions that can lead to tooth loss and systemic complications if not diagnosed and treated promptly. The 2017 classification by the American Academy of Periodontology highlights the need for effective, accurate diagnostic tools. This study aimed to develop and validate an AI-driven system for automated staging and grading periodontitis from panoramic radiographs using the YOLOv8 architecture. Methods: A total of five hundred panoramic radiographs from patients diagnosed with periodontitis were included. Radiographs were labeled and split into training (75%), validation (15%), and testing (10%) sets. Three specialized YOLOv8-based models were trained to segment the alveolar bone level, the cemento-enamel junction (CEJ), and tooth axes. Image augmentations were applied to enhance model robustness. The resulting measurements of radiographic bone loss were combined with patient information (age, smoking status, diabetes) to identify periodontitis stage and grade following the 2017 guidelines. Results: The bone level and CEJ detection models achieved high precision (0.95–0.97) and recall (0.94–0.96), reflecting strong segmentation performance. The tooth detection model achieved a precision of approximately 0.82 and a recall of 0.81. Integrating all three models enabled automated determination of periodontal stage (I–IV) and grade (A–C), with an interactive interface allowing clinicians to review and adjust outputs if necessary. Conclusion: The proposed YOLOv8-based framework accurately detects key periodontal landmarks and automates disease staging and grading. Future work should expand the dataset, refine the tooth detection model, and validate the system in clinical settings to support large-scale periodontal screening and improved patient care.

Recently, methods of quantifying total oxidant status (TOS) and total antioxidant capacity (TAOC) were developed to investigate periodontitis. This study was performed to evaluate the salivary TOS and TAOC levels of patients with chronic periodontitis (CP) and investigating the association between periodontal clinical parameters and these oxidative stress biomarkers. 40 participants (23-65 years old) were classified into two groups of 20 each, namely the CP group (participants with CP) and the control group (periodontally healthy controls). Clinical periodontal parameters were monitored, and TOS and TAOC levels were measured using laboratory assays. TOS level increased in the saliva of patients with CP and the salivary TAOC in patients with CP was significantly lower than that of the control group. The TOS had a positive moderate correlation with the plaque index and clinical attachment loss (r=0.32 and 0.37, respectively) while TAOC was negatively and moderately correlated with clinical attachment loss (r=-0.35). Salivary TOS and TAOC were distinguished in healthy and chronic PD patients. Further studies are required to comprehensively evaluate the potential role of these biomarkers in diagnosis and treatment evaluation of CP.