Aim: This study aimed to assess and compare the sociodemographic characteristics, oral health behaviors, knowledge, and attitudes of first- and second-year students from the Faculty of Dentistry and the Nursing Department. Methods: In the study, a 26-item questionnaire, consisting of the "Hiroshima University Dental Behavioral Inventory (HU-DBI)" and an additional six questions, was distributed to the dental and nursing students of Burdur Mehmet Akif Ersoy University. Students were requested to voluntarily complete the questionnaire. Results: Total HU-DBI scores were analyzed based on participants' gender and year of education. No statistically significant difference was found in the total HU-DBI scores with respect to gender or year of education. However, it was observed that first-year nursing students had the highest HU-DBI scores (5.85 ± 1.46). The percentage of nursing students who agreed with the statements “I brush each of my teeth carefully” (p = 0.006) and “I put off going to a dentist until I have a toothache” (p = 0.002) was statistically higher than that of dental students. The percentage of second-year dental students (9.1%) who agreed with the statement “My gums tend to bleed when I brush my teeth” was lower than that of second-year nursing students (42.0%). Conclusion: The results of this study show that the behaviors and attitudes of dental and nursing students, who would guide and contribute to the future oral health of the society, should be enhanced.

Methotrexate (MTX) commonly causes oral mucositis by inducing epithelial cytotoxicity and inflammation, leading to functional impairment and treatment limi

Bu çalışmanın amacı; implant yuvasının preparasyonunda düşük devirli irrigasyonsuz frezlemenin implant etrafındaki marjinal kemik kaybına ve implantların kaybedilme oranına etkilerinin değerlendirilmesidir. Çalışmaya parsiyel ve total dişsizliğe sahip toplam 23 hasta dahil edildi. Çalışma grubundaki 44 implantın frezlemesi 50rpm düşük devirli irrigasyonsuz şekilde yapılırken, kontrol grubundaki 30 implantın frezlemesi 600rpm devirli ve irrigasyonlu bir şekilde yapıldı. Marjinal kemik seviyelerini belirlemek için tüm implantlardan, yerleştirildikten hemen sonra ve postoperatif 3. ayda periapikal radyografiler alındı. Ayrıca, çalışmada implantların kaybedilme oranı, yerleştirme tork değerleri, implant yerleştirilen bölgedeki kemik kalitesi, frezleme ve toplam ameliyat süreleri kaydedildi. Bu çalışmada; düşük devirli irrigasyonsuz frezleme (DDİF) ile standart frezleme (SF) protokolü arasında mesial, distal ve ortalama marjinal kemik kaybı düzeyleri açısından istatistiksel olarak anlamlı bir farklılık görülmedi (p>0.05). İmplantların kaybedilme oranları da gruplar arasında benzerdi (p>0.05). Ayrıca, implant yerleştirme tork değerleri, frezleme ve toplam ameliyat sürelerinde de gruplar arasında farklılık gözlenmedi (p>0.05). Bu çalışmanın bulguları, DDİF’nin cerrahi sonrası iyileşme dönemindeki marjinal kemik kaybı, implant kaybı ve başlangıç tork değerlerine etkilerinin SF ile benzer olduğunu işaret etmektedir. Ancak, tekniğin güvenilirliği açısından daha ileri ve uzun hasta takipli çalışmalara ihtiyaç vardır.

Background/Objectives: To evaluate the concordance of three general-purpose large language models (LLMs), ChatGPT, Claude, and Gemini, with an adjudicated expert consensus classification of Stage, Grade, and Extent in Stage III–IV periodontitis when applying the 2018 American Academy of Periodontology/European Federation of Periodontology (AAP/EFP) rules to clinician-prepared, standardized case summaries. Methods: In this multicenter retrospective concordance study (two centers, 105 patients), two periodontologists independently classified each case from complete charts and radiographs; discordant cases were adjudicated. De-identified summaries containing pre-extracted clinical, radiographic, and modifier variables were presented to each LLM in three independent sessions per case; the modal decision was the primary index result, and single-session performance was also reported. Stage and Grade concordance (Cohen’s/weighted kappa) were co-primary endpoints; Extent and full concordance were secondary. Results: Modal Stage concordance was almost perfect for ChatGPT (κ = 0.98) and Gemini (κ = 0.92) and substantial for Claude (κ = 0.73); single-session Stage κ ranged from 0.73 to 0.98. Grade (weighted κ = 0.97–1.00) and Extent (κ = 0.93–1.00) concordance were almost perfect. Full concordance ranged from 85.7% (Claude) to 99.0% (ChatGPT). Every classifiable modal Stage discordance understated severity: Claude and Gemini assigned Stage II or I to 14 Stage III cases in which attachment loss met the Stage III threshold but radiographic bone loss was below 33%. Conclusions: Given pre-extracted variables and explicit instructions, the LLMs applied the classification rules with substantial to almost perfect concordance; this reflects rule application, not independent diagnosis. Performance was model-specific, Gemini showed greater session-to-session variability, and two models systematically understaged borderline Stage III cases. The findings support only clinician-supervised, educational use with local validation.