Oral leukoplakia (OL) is the most common oral potentially malignant disorder and carries a risk of malignant transformation. Cryotherapy is a minimally invasive treatment option for OL, but its efficacy and optimal dose-response remain inconsistent among various studies. This systematic review evaluated the clinical efficacy and safety of cryotherapy for OL lesions and explored whether the characteristics of the lesions and treatment parameters influenced clinical outcomes. Electronic searches were performed in Embase, PubMed, and the Cochrane Central Register of Controlled Trials according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Seven studies reporting original clinical outcomes of cryotherapy for OL lesions were included. Data on cryotherapy dose, number and frequency of sessions, complete regression rates, and recurrence rates were extracted. Seven studies comprised 357 patients and approximately 360 OL lesions. Complete regression rates ranged from 77.8% to 100%. Cryogun cryotherapy needed a mean of 3.1 ± 1.3 treatment sessions to achieve complete regression of the OL lesions, compared to 6.3 sessions by cotton-swab cryotherapy. OL lesions smaller than 2 cm2, located outside the tongue, with epithelial dysplasia, or with a surface keratin layer <55 μm required significantly fewer cryotherapy sessions to achieve a complete regression. Reported recurrence rates were 8-34%, and continued tobacco use was the most consistent risk factor for recurrence. Malignant transformation was observed in 6.6% of OL patients in a long-term cohort. We conclude that cryotherapy is a simple, safe, and effective treatment for OL. Cryogun cryotherapy is more efficient than cotton-swab cryotherapy.
Alveolar ridge remodeling following tooth extraction remains a clinical challenge in implant dentistry, particularly in the esthetic zone where dimensional stability of hard and soft tissues is critical for subsequent implant placement. This short communication describes a simplified clinical workflow for socket regeneration using a composite regenerative matrix (CRM) composed of concentrated growth factor (CGF), autologous fibrinogen glue (AFG), and freeze-dried bone allograft (FDBA). The technique was applied following atraumatic extraction in a single maxillary esthetic-zone case. Clinical and radiographic observations were documented for up to 5 years. Healing was uneventful, and cone-beam computed tomography performed at 3 months demonstrated qualitative socket fill and preservation of ridge contour. Implant placement was subsequently performed using a digitally guided approach. Radiographic follow-up at 1 and 5 years demonstrated stable peri-implant bone levels and maintained buccal plate morphology. The results suggest that CRM provides a simplified, biologically integrated, and predictable workflow for socket regeneration, particularly suitable for esthetic-zone applications requiring long-term dimensional stability.
This narrative review explores the "Leeuwenhoek Paradox," a metaphorical and conceptual challenge that arises when artificial intelligence (AI) detects subtle periapical radiological changes that are not visible to human observers. Drawing on evidence from studies using two-dimensional and cone-beam computed tomography (CBCT) imaging, this review critically examined the limitations of human-centered reference standards and recurrent discrepancies in AI-based periapical detection. The literature shows that AI systems frequently detect more periapical alterations than human experts. These findings may reflect early bone changes, as indicated by CBCT-based analyses of bone density and longitudinal observations. The paradox arises because AI identifies subclinical radiographic changes (AI-SRCs) that fall below the threshold of human visual perception, leading to their classification as false positives by humans owing to the limitations of human vision. Framed within the Leeuwenhoek Paradox, this article highlighted the constraints of equating diagnostic truth exclusively with human visual perception. Finally, the review outlined conceptual pathways for validating AISRCs, including longitudinal clinical studies, standardized visualization tools such as heatmaps, and the definition of new diagnostic thresholds, with the aim of supporting the safe integration of AI into dental diagnostics while mitigating the risks of overdiagnosis.
Background/purpose:Substantial evidence demonstrates that diabetes is associated with periodontal disease. The purpose of this study was to analyze the scientometric characteristics and research trends of diabetes-associated periodontal disease (DAPD). Materials and methods:All the papers on DAPD were comprehensively retrieved from the Scopus database. The years of publication were divided into before 2019 and after 2019 in the analysis of research trends. Results:There were 2466 papers on DAPD, with total citations of 73,553 and the h index of 120. The trend of clinical investigations has highlighted periodontal examination, bone development, micro-computed tomography, tooth brushing, cardiovascular disease, hypertension, diabetic complication, diabetic periodontitis, drug therapy, fasting blood glucose level, gingival index, and questionnaire. The trend of laboratory investigations has changed to gene expression, macrophage, signal transduction, microbiota, microflora, RNA 16s, in vitro study, immune response, antioxidant, reactive oxygen metabolite, and interleukin (IL)-17 after 2019. There have always been common keywords such as tumor necrosis factor alpha, IL-1beta, IL-6, insulin resistance, C-reactive protein, osteolysis, Porphyromonas gingivalis, genetics, advanced glycation end-products, oxidative stress, and saliva. Conclusion:This scientometric study elucidated the current scenario and research trends of DAPD, particularly the comprehensive identification and recognition of the important research topics concerned. A better understanding of diabetic-periodontal relationship supports interdisciplinary approaches and points toward novel preventive and therapeutic strategies.
Background /purpose:Large language models (LLMs) have shown potential in answering professional examination questions. This study evaluated the performance of ChatGPT-4, Gemini, and DeepSeek-V3 in answering English-translated questions from the 2023 Taiwan National Dental Technician Licensing Examination (TNDTLE) over a three-week period. Materials and methods:A total of 194 English-translated, text-based multiple-choice questions were selected from the 2023 TNDTLE. ChatGPT-4, Gemini, and DeepSeek-V3 were used to answer the same set of English-translated questions at four time points: baseline and one-, two-, and three-week follow-ups. Accuracy rates (ARs) were calculated and compared to evaluate changes over time and differences among the three LLMs, between basic and clinical subjects, and between English-translated and original Chinese-language questions. Results:The baseline ARs were 69.1% for ChatGPT-4, 75.8% for Gemini, and 69.6% for DeepSeek- V3. Among the three LLMs, only ChatGPT-4 demonstrated a statistically significant improvement at the three-week follow-up (P = 0.029). No significant differences were observed among the three LLMs at most time points, except that Gemini achieved a significantly higher AR than Deep-Seek-V3 at the three-week follow-up (78.4% vs. 68.6%, P = 0.039). ARs were generally higher for basic subjects than for clinical subjects. ChatGPT-4 and Gemini achieved significantly higher ARs for English-translated questions than for original Chinese-language questions, whereas DeepSeek- V3 showed no significant language-related difference. Conclusion:ChatGPT-4, Gemini, and DeepSeek-V3 demonstrate moderate capability in answering dental technician examination questions but generally show no significant improvement over a three-week period. Translating Chinese-language questions into English may improve the performance of ChatGPT-4 and Gemini.
Background/purpose:Diagnosing periapical cysts and granulomas using periapical radiographs is challenging due to subtle radiographic differences. This study aimed to develop a machine learning-based diagnostic framework to improve lesion classification through ensemble learning and dentin standardization. Materials and methods:Five models-Support Vector Classifier (SVC), Nu-SVC, K-Nearest Neighbors (KNN) and Decision Tree-were trained on 144 pre-treatment periapical radiographs (70 cysts and 74 granulomas). Dentin standardization normalized grayscale values to ensure feature consistency. A weighted soft voting strategy was employed to integrate predictions, with model weights derived from individual diagnostic performance. Model performance was evaluated via five-fold cross-validation. Statistical significance among models was assessed using the Friedman test, followed by Wilcoxon signed-rank tests for pairwise comparisons (α = 0.05). Results:The ensemble method achieved a precision of 0.83 and a sensitivity of 0.83, demonstrating robust diagnostic performance. Statistical analysis revealed significant differences among models in specificity (P = 0.001) and negative predictive value (P = 0.044), with the ensemble method reaching a peak specificity of 0.83. Although numerous improvements were observed in precision and sensitivity compared to several base models, these differences did not reach statistical significance (P > 0.05). Overall, the ensemble method demonstrated balanced performance across metrics, although its improvements over individual models were not statistically significant. Conclusion:By integrating dentin standardization with a weighted ensemble approach, the proposed method provides a reliable, non-invasive tool for improving radiographic differentiation of periapical cysts and granulomas. These results support the potential of intelligent diagnostic systems in dental radiology.
Background/purpose:Our previous studies found the serum gastric parietal cell antibody (GPCA) positivity in 12.3%-26.7% of atrophic glossitis (AG), burning mouth syndrome (BMS), and oral lichen planus (OLP) patients. This study assessed whether GPCA-positive oral mucosal disease (GPCA+OMD) patients (including 284 AG, 109 BMS, and 139 OLP patients) had significantly higher frequencies of microcytosis, macrocytosis, anemia, serum iron and vitamin B12 deficiencies, and hyperhomocysteinemia than healthy control subjects (HCSs) or GPCA-negative OMD (GPCA-OMD) patients. Materials and methods:The mean corpuscular volume, blood Hb, and serum iron, vitamin B12, homocysteine, and GPCA levels were measured and compared between any two of three groups of 532 GPCA+OMD patients, 532 disease-, age- and sex-matched GPCA-OMD patients, and 532 age- and sex-matched HCSs. Results:We found that 532 GPCA+OMD patients had significantly higher frequencies of microcytosis, macrocytosis, anemia, serum iron and vitamin B12 deficiencies, and hyperhomocysteinemia than 532 HCSs (all P-values <0.001) and significantly higher frequencies of macrocytosis, macrocytic anemia including pernicious anemia (PA), serum vitamin B12 deficiency, and hyperhomocysteinemia than 532 GPCA-OMD patients (all P-values <0.001). Moreover, 532 GPCA-OMD patients also had significantly higher frequencies of microcytosis, macrocytosis, anemia, serum iron and vitamin B12 deficiencies, and hyperhomocysteinemia than 532 HCSs (all P-values <0.001). PA (39.4%) and normocytic anemia (34.3%) were the two most common types of anemia in 137 anemic GPCA+OMD patients. Conclusion:GPCA+OMD patients have significantly higher frequencies of macrocytosis, macrocytic anemia including PA, serum vitamin B12 deficiency, and hyperhomocysteinemia than HCSs or GPCA-OMD patients.
Background/purpose:Large language models (LLMs) have shown promise in answering professional examination questions. This study evaluated the performance of ChatGPT-4, Gemini, and DeepSeek-V3 in answering prompt-engineered questions selected from the 2023 Taiwan National Dental Technician Licensing Examination (TNDTLE) over a three-week period. Materials and methods:A total of 194 Chinese-language text-based multiple-choice questions were selected from the 2023 TNDTLE. The three LLMs answered these questions using a standardized prompt referring to 17 dental technology textbooks. Accuracy rates (ARs) were recorded at baseline and after one, two, and three weeks. Comparisons of ARs over time, among three LLMs, between basic and clinical subjects, and between Chinese-language questions with and without a prompt were performed by McNemar's or chi-square test, where appropriate. Results:Baseline ARs ranged from 70.1% to 75.3% across the three LLMs. None of the three LLMs demonstrated significant improvement over a three-week period. Overall performance was comparable among models, with only one significant difference observed (Gemini outperforming ChatGPT-4 at one week, P = 0.033). ARs were generally higher for basic subjects than for clinical subjects, although most differences were not statistically significant. The prompt-engineering significantly improved the performance of ChatGPT-4 and Gemini at several time points (P < 0.05), whereas DeepSeek-V3 showed no significant improvement over a three-week period. Conclusion:ChatGPT-4, Gemini, and DeepSeek-V3 achieve moderate accuracy in answering prompt-engineered dental technician examination questions but do not exhibit significant improvement over a three-week period. The prompt-engineering can enhance performance for ChatGPT-4 and Gemini but not for DeepSeek-V3.
Background/purpose:Adequate polymerization of resin luting cements is essential for durable bonding in zirconia restorations. However, variations in zirconia microstructure and composition may influence translucency and light transmittance, thereby affecting resin cement polymerization. This study aimed to investigate the optical properties of conventional and high-translucency zirconia ceramics and their effects on resin cement polymerization. Materials and methods:Six zirconia ceramics were evaluated: CerconBase, CerconHT, and VitaHT (3Y-TZP); VitaST (4Y-PSZ); and CerconXT and VitaXT (5Y-PSZ). Disk specimens (0.5 and 1.0 mm thick) were fabricated and sintered. Grain size and elemental compositions were analyzed using scanning electron microscopy and energy-dispersive X-ray spectroscopy, and phase composition was assessed by X-ray diffraction. Optical properties, including light transmittance, translucency parameter (TP), and contrast ratio (CR), were measured using a UV-NIR spectrophotometer. A light-curable resin cement (Variolink N base) was polymerized through zirconia disks, and surface microhardness was measured immediately and after 24 h. Results:Two 5Y-PSZ ceramics (CerconXT, VitaXT) exhibited the highest cubic-phase fractions (48.66-54.36%), and larger grain sizes, whereas 3Y-TZP showed finer grains. Light transmittance at 468 nm was lowest for CerconBase (15.52% and 10.33% at 0.5 and 1.0 mm, respectively), while other zirconia exhibited higher and comparable values (24.63-31.41%). TP and CR followed similar trends. Although immediate microhardness values were comparable, resin cement polymerized through 1.0-mm-thick CerconBase exhibited significantly lower microhardness after 24 h. Conclusion:Optical behaviors of zirconia ceramics are governed by composition and microstructure. Opaque zirconia, particularly at greater thickness, significantly impairs post-curing polymerization of resin cement.
Background/purpose:In skeletal Class III malocclusion, evaluation of mandibular third molar development is clinically important for orthodontic treatment planning, particularly in relation to posterior space conditions. This study aimed to assess the association between dental age of mandibular third molars and retromolar morphological characteristics in skeletal Class III patients. Materials and methods:This retrospective cross-sectional study included panoramic radiographs from 157 patients diagnosed with skeletal Class III malocclusion based on clinical examination and lateral cephalometric analysis. Mandibular third molar development was evaluated using Demirjian mineralization stages (D-H), representing stages from crown completion to root maturation. Retromolar morphology was evaluated using retromolar space (RMS), the RMS-to-crown width ratio (Ganss ratio), and the mesiodistal angulation between the second and third molars (Beta angle). Correlations between dental age and these morphological parameters were analyzed. Results:As dental age progressed, RMS increased from 5.59 mm to 9.18 mm and the Ganss ratio from 0.45 to 0.70, whereas the Beta angle decreased from 35.82° to 24.80°. Dental age showed moderate positive associations with RMS and the Ganss ratio (P < 0.001), but no significant association with the Beta angle (P = 0.479). These findings indicate coordinated changes between third molar development and retromolar morphology in skeletal Class III patients. Conclusion:Dental age-related changes in retromolar morphology may provide useful radiographic information for describing posterior space conditions in skeletal Class III patients.
Background/purpose:Intentional replantation is regarded as a final strategy to preserve natural teeth affected by inaccessible endodontic and periodontal disease. The purpose of this study was to analyze the scientometric characteristics and research trends of tooth intentional replantation. Materials and methods:All the papers on intentional replantation were comprehensively retrieved from the Scopus database. The years of publication were divided into before 2017 and after 2017 in the analysis of research trends. Results:There were 356 papers on intentional replantation, with total citations of 5562 and the h index of 42. The trend of bone substitutes, boron compounds, and boron derivative before 2017, has changed to aluminum compounds, aluminum derivative, and silicate after 2017. The trend of treatment keywords such as anti-bacterial agents, antiinfective agent, curettage, guided tissue regeneration, post and core technique, and retrograde obturation before 2017, has changed to apical surgery, endodontic surgery, surgical extrusion, periodontal regeneration, treatment failure, and platelet-rich fibrin after 2017. Besides, there were more systematic review and/or meta-analyses of the effectiveness and outcome of intentional replantation after 2017. There have always been common keywords such as root canal therapy, cone beam computed tomography, tooth extraction, diagnostic imaging, apicoectomy, root resorption, tooth ankylosis, tooth avulsion, periodontal ligament, periodontal pocket, auto-transplantation, alveolar bone loss, and bone regeneration. Conclusion:This scientometric study elucidated the current scenario and research trends of tooth intentional replantation, particularly the comprehensive identification and recognition of the important research topics concerned.
Background/purpose:Amelogenesis imperfecta (AI) is a group of rare, inherited disorders characterized by abnormal enamel formation. While identifying the genes and mutations that cause the disease is important, understanding its molecular pathogenesis is essential to developing precision and personalized medicine, which aim to stop disease onset, slow its progression, and provide a range of treatment options. Previously, we identified mutations that affect the conserved alternative splicing of the AMELX gene, leading to the inclusion of normally skipped exon 4 and resulting in a characteristic AI phenotype. Materials and methods:HEK293 cells were grown on cell culture dishes for an in vitro splicing assay, and transiently transfected with the wild-type, c.120T>C, or c.143T>C AMELX expression vector. Morpholino antisense oligonucleotides (ASO) were designed and tested for correction of the altered splicing pattern. The test was performed with ASO concentrations of 1, 2 and 4 μM. Total RNA was isolated for splicing analysis, and the cells and culture media were harvested for Western blot analyses. Results:The altered splicing pattern was corrected by applying antisense oligonucleotides in vitro. The exon 4-included mutant mRNA was successfully eliminated, and the expression pattern of AMELX protein was restored. Conclusion:To the best of our knowledge, this is the first report to use ASO to silence mutant transcripts to correct splicing mutations confirmed to be disease-causing. This study represents a small step towards genetic interventions for AI and may serve as a basis for regulating the expression of mutant transcripts in developing teeth for future human studies.
Background/purpose:Although risk factors for medication-related osteonecrosis of the jaw (MRONJ) are known, clinical assessment prior to dental extraction remains largely subjective. We aimed to develop and externally validate a simple clinical risk scoring system to predict post-extraction MRONJ in osteoporotic patients receiving antiresorptive therapy (ART) and support evidence-based clinical decision-making. Materials and methods:This retrospective cohort study used a derivation cohort (N = 1067 extractions, 2003-2022) to develop a 5- to 16-point risk score system based on five predictors (age ≥75, ART duration ≥24 months, bisphosphonate use, drug interruption <3 months, and extraction site). The model was validated in an independent cohort (N = 928 extractions, 2022-2024) using a pre-defined ≥12 cut-off. Performance metrics included the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results:MRONJ prevalence was lower in the validation cohort (2.2% vs. 24.5%; P< 0.001), reflecting stricter drug interruption adherence (90.0% vs. 71.5%). The AUC was 0.86 and 0.75 in derivation and validation cohorts, respectively. At the ≥12 cut-off, sensitivity was 65.0%, specificity 67.5%, PPV 4.2%, and NPV 98.9%. Conclusion:The model demonstrates good discrimination and excellent "rule-out" utility in a real-world, low-prevalence setting, identifying low-risk patients (<12 points) for safe dental extraction, thereby facilitating evidence-based clinical decision-making.
Background/purpose:Implant osseointegration depends not only on osteogenesis but also on coordinated bone remodeling. Our previous study demonstrated that epigallocatechin-3-gallate (EGCG)/type I collagen-coated titanium (Ti) surfaces enhance angiogenesis and osteogenic differentiation in vitro. However, their influence on osteoclast differentiation remains unclear. This study evaluated the modulatory effects of this coating on osteoclast responses in vitro. Materials and methods:Sandblasted and acid-etched (SLA) Ti surfaces followed by alkaline treatment (SLAA) were prepared. Type I collagen was immobilized onto SLAA surfaces using the natural crosslinker EGCG (10 or 50 μg/mL). Surface morphology, roughness, hydrophilicity, and functional groups were characterized. RAW 264.7 macrophages were used to assess cell adhesion, proliferation, viability, tartrate-resistant acid phosphatase (TRAP) expression, and F-actin ring formation. Osteoclast differentiation was induced using receptor activator of nuclear factor kappa-B ligand (RANKL). Statistical analysis was performed using one-way ANOVA with Dunnett's test. Results:Surface characterization confirmed successful coating without compromising surface stability. Compared with SLA surfaces, collagen-coated surfaces with or without EGCG enhanced initial cell spreading while showing less increase in metabolic activity without cytotoxicity. EGCG- and EGCG/type I collagen-coated surfaces significantly reduced TRAP expression and F-actin ring size relative to SLA surfaces. Although the 50 μg/mL EGCG groups showed lower TRAP expression and smaller F-actin rings than the 10 μg/mL groups, the differences were not statistically significant. Conclusion:EGCG/type I collagen surface modification may modulate osteoclast-related cellular responses in RAW 264.7 cells without affecting cell viability, suggesting a potential strategy to modulate peri-implant bone resorption and support long-term implant stability.
Delayed tooth eruption is frequently considered a benign developmental variation but may represent an early sign of genetically driven tooth agenesis. We evaluated a 22-month-old female presenting with markedly delayed eruption (only eight primary teeth) and a positive family history of ectodermal features. Given the inconclusive early radiographic findings, whole-exome sequencing (WES) was utilized. WES revealed the proband carried a heterozygous EDARADD variant (NM_080738:c.328G > T; p. Asp110Tyr). Subsequent familial segregation analysis identified an additional heterozygous WNT10A variant (NM_025216:c.637G > A; p. Gly213Ser) within the broader family. The EDARADD variant alone was associated with varying presentations from normal dentition to delayed eruption. Furthermore, the WNT10A variant alone correlated with distinct tooth agenesis, whereas their coexistence exacerbated the phenotype, resulting in severe agenesis and ectodermal features. This case demonstrates WES provides critical diagnostic insight when radiographic evaluation is inconclusive in young patients, facilitating precision dentistry.
