Search Results (346)

Background: Early childhood caries (ECC) affects a substantial proportion of young children worldwide, and timely screening is essential for early intervention and referral. While deep learning has shown promise for automated dental diagnostics, many existing approaches rely on computationally heavy models that limit deployment in community and mobile settings. This study investigates whether compact convolutional neural networks can achieve clinically meaningful performance for screening dental caries from oral photographs. Methods: We curated a dataset of 435 intraoral images from children aged 3–14 years, annotated by licensed dentists, and performed patient-level stratified splitting to prevent data leakage. Three convolutional neural networks (ResNet-18, MobileNetV3-Small, and EfficientNet-B0) were fine-tuned using ImageNet-pretrained weights and comparatively evaluated for the detection of dental caries from oral photographs. Models were trained with class-weighted cross-entropy loss and evaluated on a held-out test set using sensitivity, specificity, balanced accuracy, ROC-AUC, and PR-AUC with bootstrap 95% confidence intervals. Results: ResNet-18 achieved the highest balanced accuracy (0.929), weighted F1-score (0.954), and perfect sensitivity (1.00), while EfficientNet-B0 achieved the strongest threshold-independent discrimination with the highest ROC-AUC (0.978) and PR-AUC (0.990). MobileNetV3-Small maintained competitive performance (ROC-AUC 0.952; PR-AUC 0.976) with substantially lower computational complexity. Conclusions: In addition to performance evaluation, we incorporated an interpretability analysis using Grad-CAM to examine model decision behavior. The resulting attribution maps predominantly highlighted clinically relevant tooth regions associated with caries, providing evidence that the models rely on meaningful dental features rather than background artifacts. These results demonstrate that compact, deployment-friendly architectures can achieve clinically meaningful performance for ECC detection, supporting their suitability for scalable, real-world screening applications. Full article

Objectives: Oral leukoplakia (OL) is the most prevalent oral potentially malignant disorder and requires accurate diagnosis, safe excision, and reliable margin evaluation to minimize recurrence and malignant transformation. Diode laser excision is increasingly adopted due to its precision and favorable clinical outcomes; however, laser-induced thermal effects at surgical margins raise concerns regarding tissue integrity and histopathological reliability. This study aimed to evaluate optical coherence tomography (OCT) as a real-time, high-resolution, non-invasive imaging modality for assessing peri-incisional thermal effects during diode laser excision of non-dysplastic OL. The primary objective was to validate OCT for ultrastructural and morphometric tissue analysis while ensuring preservation of diagnostic readability. Methods: A single-center observational case series was conducted at the University of Turin. Thirty patients with clinically and histopathologically confirmed oral leukoplakia without epithelial dysplasia were enrolled and allocated to two groups: 15 lesions excised using a 980 nm diode laser in continuous-wave contact mode (laser group) and 15 lesions removed by conventional scalpel biopsy (control group). Laser excisions were performed with standardized parameters and a circumferential safety margin of 5 mm. Immediately after excision, specimens underwent ex vivo spectral-domain OCT (SD-OCT) imaging to evaluate the epithelial and connective tissue microarchitecture at surgical margins and central lesion areas. OCT acquisition sites were precisely correlated with histological sections. Quantitative OCT measurements of epithelial thickness, lamina propria thickness, and laser-induced thermal alterations were compared with corresponding histological findings. Results: OCT consistently provided high-resolution visualization of oral mucosal microarchitecture in both groups, allowing clear identification of epithelial stratification, basement membrane continuity, and lamina propria organization. In the laser group, OCT detected superficial optical alterations at the surgical margins consistent with laser-induced thermal effects, while deeper tissue layers remained structurally readable. Histological analysis revealed mean epithelial and connective tissue thermal alterations of 288.9 μm and 430.3 μm, respectively. OCT-derived measurements showed high concordance with histology, with an overall agreement of 88.5% and no statistically significant differences between OCT and histological assessments. Importantly, laser-induced thermal effects did not impair definitive histopathological diagnosis in any specimen. Comparison with the control group confirmed preserved tissue architecture in scalpel-excised samples and highlighted OCT sensitivity in detecting laser-related structural remodeling. Conclusions: OCT proved to be a reliable, non-invasive imaging technique for real-time assessment of diode laser-induced thermal effects during OL excision. The technique accurately delineated tissue microstructure and surgical margins without compromising histopathological interpretation. Integration of OCT into the laser-assisted management of oral potentially malignant disorders may enhance surgical precision, optimize margin control, reduce diagnostic uncertainty, and support individualized follow-up strategies. Full article

Background: Myricetin (MYR) is a natural flavonol with antioxidant, neuroprotective, anti-inflammatory, antidiabetic, and cardioprotective activities. Still, its pharmaceutical use is limited by very low aqueous solubility (~16.6 µg/mL) and poor oral bioavailability (<10%). This study aimed to enhance the solubility and potentially improve the bioavailability of MYR by developing an amorphous nanofibrous delivery system. Methods: Electrospinning was applied to fabricate MYR-loaded nanofibers using polyvinylpyrrolidone K30 (PVP30), and the influence of key processing parameters on MYR solubility was evaluated. Nanofibers produced under selected electrospinning conditions were characterized in terms of morphology, encapsulation efficiency, and physicochemical properties. Results: X-ray powder diffraction confirmed complete amorphization of MYR within the BB5 fiber structure (distance: 12 cm, voltage: 25 kV, flow rate: 1.5 mL/h). FTIR analysis indicated hydrogen-bonding interactions between MYR hydroxyl groups and PVP30 carbonyl groups, contributing to stabilization of the amorphous form. SEM images revealed homogeneous, defect-free fibers with diameters below 400 nm, although localized MYR agglomerates were observed. Solubility and release studies demonstrated a characteristic spring-and-parachute effect, enabling rapid MYR release and maintenance of a supersaturated state. Enhanced solubility resulted in significantly improved antioxidant activity in DPPH and CUPRAC assays compared with crystalline MYR. Conclusions: Electrospun PVP30 nanofibers represent a promising platform for improving the solubility, dissolution behavior, and functional activity of poorly soluble bioactive compounds such as myricetin, supporting their potential application in pharmaceutical formulations. Full article

Background: Atrial fibrillation (AF) is consistently associated with cognitive impairment and dementia through mechanisms that extend beyond classical cardioembolic stroke. However, the relative contribution of these pathways and the effectiveness of available therapeutic strategies for preserving cognition remain uncertain, as most data come from observational studies with a substantial risk of bias. Objectives: This review narratively synthesizes contemporary evidence on epidemiology, pathophysiological mechanisms, therapeutic strategies—including anticoagulation, rhythm control, and comprehensive risk-factor management—and the role of digital health technologies in the relationship between AF and cognitive decline. Methods: We performed a narrative, PRISMA-informed scoping review of observational cohorts, mechanistic studies, randomized clinical trials, systematic reviews, and meta-analyses published up to January 2026, identified through structured searches in MEDLINE/PubMed and complementary sources. Studies were selected if they examined (i) associations between AF and cognitive impairment or dementia, (ii) mechanistic pathways linking AF to brain injury, (iii) therapeutic interventions with cognitive or brain imaging outcomes, or (iv) digital health technologies applied to AF management. Heterogeneity in study design and outcome assessment precluded meta-analysis; therefore, we provide a qualitative synthesis, explicitly distinguishing observational evidence from randomized data and discussing key sources of confounding. Risk of bias was evaluated using validated tools: ROBINS-I for non-randomized studies, RoB 2.0 for RCTs, Newcastle–Ottawa Scale for observational cohorts, and AMSTAR-2 for systematic reviews. Results: Large population-based cohorts and meta-analyses indicate that AF is associated with a 1.4–2.2-fold higher risk of cognitive impairment or incident dementia, even after adjustment for shared vascular risk factors and exclusion of patients with prior stroke; nevertheless, residual confounding and selection bias cannot be excluded. Silent cerebral infarcts are detected in roughly one-quarter to two-fifths of AF patients without clinical stroke and are themselves associated with cognitive deficits, suggesting that subclinical embolism represents one important, but not exclusive, pathway. Additional mechanisms include chronic cerebral hypoperfusion, neuroinflammation, small vessel disease, and structural brain atrophy, all of which are incompletely disentangled from comorbidities. Observational data suggest that oral anticoagulation, particularly with direct oral anticoagulants (DOACs), is associated with lower rates of dementia compared with no anticoagulation or warfarin, but randomized trials such as BRAIN-AF and GIRAF have not demonstrated a clear cognitive benefit, underlining the low-to-moderate certainty of this evidence. Rhythm-control interventions, especially catheter ablation, are associated with lower dementia incidence in registry studies, yet strong selection effects and short follow-up limit causal inference. Digital health tools and ABC-pathway mobile applications improve cardiovascular outcomes and adherence, although cognitive endpoints remain largely unexplored. Conclusions: AF should be conceptualized as a neurovascular condition with important implications for brain health, rather than a purely cardiac rhythm disorder confined to stroke prevention. A comprehensive heart–brain management strategy that combines optimal anticoagulation, individualized rhythm control, aggressive vascular risk factor modification, routine cognitive screening in older or high-risk patients, and judicious use of digital health technologies may offer the best opportunity for preserving cognition, although rigorous trials with cognitive endpoints are still needed to establish causality. Full article

Background/Objectives: Extranodal NK/T-cell lymphoma, nasal type (ENKTCL-NT), is a rare and extremely aggressive subtype of non-Hodgkin lymphoma that most frequently involves the nasal cavity and upper aerodigestive tract. Primary isolated oral manifestation is exceptionally uncommon and may mimic odontogenic or infectious diseases, delaying diagnosis. We report a case of ENKTCL-NT presenting initially as a destructive oral lesion without sinonasal involvement at diagnosis. Methods: A 32-year-old man with progressive palatal ulceration underwent clinical and imaging assessment (panoramic radiography and staging ^18F-FDG PET–CT) and repeated biopsies. Diagnosis was established using histopathology (H&E), immunohistochemistry (T-cell markers and cytotoxic profile), EBV detection by EBER in situ hybridization, and T-cell receptor gamma (TCRG) gene rearrangement analysis. Results: The lesion presented as a hemorrhagic, ulcerative palatal destruction covered by pseudomembranous exudate and was complicated by fungal infection, periostitis, and severe dental inflammatory foci, contributing to diagnostic delay. Histopathological examination revealed extensive necrosis with a dense atypical lymphoid infiltrate; angiocentric and angiodestructive growth was identified in one biopsy specimen. Tumor cells expressed T-cell markers (CD2, CD3, CD5, CD7; heterogeneous) and cytotoxic markers (TIA-1) and showed CD30 and CD56 positivity, with EBV positivity confirmed by EBER in situ hybridization. Molecular analysis demonstrated monoclonal TCRG rearrangement, and Ki-67 indicated high proliferative activity. Initial PET–CT demonstrated an intensely FDG-avid, locally invasive lesion without distant organ involvement. The patient was treated with L-asparaginase-based SMILE chemotherapy followed by radiotherapy (50 Gy), achieving marked initial clinical improvement and partial metabolic response; however, systemic relapse subsequently occurred with refractory disease despite salvage therapy and immunotherapy. Conclusions: This case highlights the substantial diagnostic challenge posed by isolated oral extranodal NK/T-cell lymphoma, nasal type, which may closely mimic benign inflammatory or infectious conditions and lead to significant diagnostic delay. Persistent, progressive, or therapy-resistant oral ulcerations should prompt early consideration of hematologic malignancy. Timely biopsy with comprehensive immunophenotyping, EBV testing, and close multidisciplinary collaboration are essential for accurate diagnosis and may contribute to earlier diagnosis and improved patient outcomes in these rare and atypical presentations. Full article

Background: Extranodal extension (ENE) is a critical prognostic factor in head and neck squamous cell carcinoma (HNSCC) and was incorporated into the AJCC eighth-edition staging system. However, the concordance between clinical (cENE) and pathological (pENE) ENE remains poorly understood in real-world practice. Methods: We conducted a retrospective analysis using Taiwan Cancer Registry (TCR) long-form data from 2018 to 2022, focusing on four major HNSCC sites (oral cavity, oropharynx, hypopharynx, and larynx). The diagnostic gap was defined as the difference between pENE and cENE positivity rates. Results: Among 29,830 patients, a persistent diagnostic gap was observed across all sites: laryngeal (20.8%), hypopharyngeal (20.4%), oropharyngeal (11.5%), and oral cavity (9.9%). For oral cavity cancer, the gap did not narrow over the 5-year period (p = 0.9788). Furthermore, in oral cavity cancer, medical centers demonstrated a larger gap than non-medical centers (10.5% vs. 8.4%), a phenomenon we term the “Quality-Gap Paradox”. Conclusions: A significant diagnostic gap persists in HNSCC, highlighting the limitations of current imaging. The Quality-Gap Paradox, observed in oral cavity cancer, suggests this is driven by a complex interplay of factors including superior pathological detection in high-volume centers. Our findings underscore the need for advanced, personalized risk-stratification tools to bridge this gap and improve patient management. Full article

Objective: This study aimed to evaluate and compare the diagnostic performance of computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography-computed tomography (PET-CT) in detecting metastatic cervical lymph nodes in patients with oral squamous cell carcinoma (OSCC), with a particular focus on radiologically indeterminate lymph nodes. Materials and Methods: A retrospective analysis was conducted on OSCC patients who underwent CT, MRI, and PET-CT imaging prior to surgery, followed by histopathologic confirmation. Lymph nodes were categorized as metastatic, indeterminate, or benign based on imaging criteria specific to each modality. Diagnostic accuracy, sensitivity, and specificity were calculated using histopathology as the reference standard. Results: After excluding lymph nodes classified as indeterminate on preoperative imaging, CT demonstrated an accuracy of 83.6%, sensitivity of 51.9%, and specificity of 92.4% for metastatic lymph node detection. MRI and PET-CT showed comparable accuracies (81.6% and 80.8%, respectively) and identical sensitivities (53.9%). In contrast, among radiologically indeterminate lymph nodes, most lesions identified on CT and MRI were histopathologically benign, whereas PET-CT yielded very few indeterminate nodes, all of which were benign. For benign node identification, PET-CT exhibited the highest sensitivity (86.8%) but lower specificity (55.8%), while CT and MRI demonstrated more balanced specificity (73.1%) with lower sensitivity. Logistic regression confirmed SUVmax as a significant predictor of malignancy (p < 0.001; odds ratio 1.71, 95% CI: 1.48–2.35), and ROC analysis demonstrated strong discriminative performance (AUC = 0.88), with an optimal SUVmax cutoff of 3.6. Conclusion: While CT remains highly specific, PET-CT offers greater sensitivity in detecting benign and indeterminate lymph nodes, making it a valuable adjunct in preoperative assessment. SUVmax serves as a strong quantitative indicator for metastatic involvement. A multimodal imaging approach may enhance diagnostic accuracy, particularly in cases where lymph nodes lack definitive radiologic features. Full article

Background: Periapical pathosis in periapical radiographs must be properly diagnosed for the success of endodontic treatment but is often muddled by 2D imaging limitations and subjective interpretation. Artificial intelligence (AI) offers a solution, but whether the diagnostic granularity of AI versus human clinicians in everyday clinical practice has been adequately explored remains to be addressed. The purpose of this study was to evaluate the diagnostic accuracy of ChatGPT-5 in detecting periapical radiographic abnormalities compared with the three-expert consensus reference standard. Methods: In this diagnostic accuracy retrospective study, 270 periapical radiographs were independently read by a large language model (ChatGPT-5) and a three-board-certified oral radiologist consensus. The AI was given a standardized prompt to label radiographic features, like the presence of periapical radiolucency, border, shape, and integrity of lamina dura. Diagnostic accuracy, agreement (Cohen’s κ), and predictors of correct AI classification were compared with the expert consensus reference standard. Results: ChatGPT-5 demonstrated high sensitivity (87.5%) but low specificity (12.5%), resulting in an overall diagnostic accuracy of 50.0%. This performance profile reflects a tendency toward over-identification of pathology, with the model classifying 87.5% of radiographs as abnormal compared with 50.0% by expert consensus. Agreement was almost perfect for anatomical localization (arch, κ = 0.857) but poor for binary abnormality detection (κ = 0.000). For morphological descriptors, statistically significant disagreement was observed for lesion border characterization (κ = 0.127; p < 0.001), whereas lesion shape demonstrated only descriptive divergence without reaching statistical significance (κ = 0.359). Root resorption assessment also differed significantly between evaluators (p = 0.046). Regression analysis showed that well-defined corticated borders (OR = 60.25, p < 0.001) and first molar-associated lesions (OR = 32.55, p < 0.001) were significant predictors of correct AI classification. Conclusions: This study demonstrates that while ChatGPT-5 Vision can visually interpret periapical radiographs with high sensitivity, limited specificity and inconsistent morphological feature characterization restrict its reliability for independent clinical diagnosis. The AI system tends to over-diagnose systematically and categorizes lesions more structurally and defined compared to dental experts. AI has the potential for being optimized as a sensitive first-screening test, but its findings must be validated by dental professionals to avoid false positives and ensure proper characterization. Full article

Epstein–Barr virus (EBV) is an oncogenic virus implicated in several epithelial malignancies; however, its role in the tumor microenvironment of oral squamous cell carcinoma (OSCC) remains unclear. This study investigated the association between EBV infection and clinicopathological and microenvironmental features of OSCC. A cross-sectional analysis was conducted on 62 archived OSCC biopsy specimens. EBV was detected using polymerase chain reaction (PCR), and clinical data were obtained from medical records. Tumor–stroma ratio (TSR), perineural invasion (PNI), lymphovascular invasion (LVI), and histological differentiation were assessed microscopically, while tumor-infiltrating lymphocytes (TILs) were quantified using ImageJ software version 1.54j (National Institutes of Health, Bethesda, MD, USA). EBV DNA was identified in 43.5% of cases. EBV positivity was significantly associated with older age (p = 0.046), especially among patients aged 60 years or older. All EBV-positive tumors exhibited a high tumor–stroma ratio, which was significantly associated with EBV status (p = 0.031). No significant associations were observed between EBV status and sex, tumor site, clinical stage, TILs, PNI, LVI, or histological differentiation. These findings indicate that EBV-positive OSCC is characterized by distinct microenvironmental features, particularly an elevated tumor–stroma ratio, and suggest a potential role for EBV status in microenvironmental profiling and prognostic stratification. Full article

A supplemental description of Lamproglena barbicola Fryer, 1961 is provided based on specimens collected from the gills of Labeobarbus altianalis (Boulenger, 1900) from the Nyando River, Lake Victoria Basin, Kenya, using an integrated approach of scanning electron microscopy (SEM) and molecular analysis (18S, 28S rDNA, and cox1 gene regions). Morphologically, the specimens conform to L. barbicola and closely resemble Lamproglena hoi Dippenaar, Luus-Powell & Roux, 2001; however, SEM revealed a previously undescribed feature on the uniramous antennule in L. barbicola, namely indistinctly three-segmented, tapering from a broad base to the apex, basal segment much longer than distal, comprising 14 setae of varying sizes, ventral laterally, absence of distinctive anterior fringe of setae on the antennule, as well as several characters that differentiate L. barbicola from L. hoi, including 5 setae at the basal endopod of leg one, five cuticular protuberances in the oral region, 19 setae on the basal antennular segment, and 10 setae on the distal segment, with 1 seta on each ramus. The phylogenetic analysis confirms L. barbicola as a sister taxon of L. hoi, supporting their close relationship. The genetic divergence presented as the uncorrected genetic p-distances between L. barbicola and L. hoi are 23.1% and 0.45% for cox1 and 28S rDNA regions, respectively, with observed nucleotide differences of 145 and 3 bp between the sequences, respectively. There was no interspecific variability detected in the 18S rDNA sequences. This study provides novel molecular sequences and the first high-resolution SEM images, which reveal additional taxonomic features for L. barbicola, establishing a robust reference for future identification. Full article

This in vitro study compared the antimicrobial and antibiofilm efficacy of four commercially available chlorhexidine (CHX)-based mouthwashes, with different nominal CHX concentrations, against clinically relevant postoperative oral pathogens, including Staphylococcus aureus, Streptococcus mutans, Escherichia coli, Pseudomonas aeruginosa, Candida albicans, and Candida auris. Antimicrobial potency was evaluated using MIC and CEMIC indices, while biofilm thickness reduction was quantified using 3D digital microscopy and custom image analysis software. Among the tested formulations, the excipient-enriched formulation exhibited the lowest MIC values and the most significant reduction in biofilm thickness, particularly against Gram-negative bacteria and Candida species. All mouthwashes achieved CEMIC < 0.1, confirming high theoretical applicability margins; however, CEMIC reflects potential clinical usefulness rather than clinical superiority. The findings demonstrate that the antimicrobial and antibiofilm activity of CHX rinses is formulation-dependent and cannot be predicted solely by CHX concentration. The influence of excipients is discussed as a possible contributing factor, but related mechanisms remain speculative and require direct validation in future studies. This work supports a formulation-driven, evidence-based approach to antiseptic comparison in postoperative dentistry, without assessing clinical wound-healing outcomes. Full article

Artificial Intelligence (AI) is a computer science that focuses on developing systems and machines capable of performing tasks that typically require human cognitive abilities. It has widespread applications in medical diagnostics. Its use has led to rapid advancements in diagnostic methodology, enabling the analysis of large datasets. The major applications of AI in medical diagnostics include personalized treatment based on patient genetics, preventive measures, and medical image analysis. AI is employed to analyse genomic data and biomarkers, aiding in the precise tailoring of therapies to individual patient needs. It could also be employed in modern dentistry in the near future, helping to achieve higher efficiency and accuracy in diagnosis and treatment planning. AI may be utilized in screening for oral mucosa lesions and to discriminate between oral potentially malignant disorders and cancers from benign lesions. The potential advantages of AI include high speed and accuracy in the diagnostic process, as well as relatively low costs. The aim of this review was to present the potential applications of AI methods in the diagnosis of selected mucocutaneous diseases. A literature review focuses on oral lichen planus, recurrent aphthous stomatitis, and oral and laryngeal leukoplakia. Full article

Background/Objectives: Preoperative differentiation between oral squamous cell carcinoma (SCC) and minor salivary gland carcinoma (SGC) remains clinically challenging due to overlapping imaging characteristics. This study aimed to develop a diagnostic model based on quantitative dynamic contrast-enhanced MRI (qDCE-MRI) parameters to distinguish SCC from SGC prior to surgery. Methods: Patients with histopathologic confirmed SCC or minor SGC who underwent preoperative 3.0T qDCE-MRI were recruited. Clinical characteristics and pharmacokinetic parameters, including volume transfer constant (K^trans), reverse reflux rate constant (K_ep), volume fraction of extravascular extracellular space (V_e), plasma volume fraction (V_p), time to peak (TTP), maximum concentration (MAXConc), maximal slope (MAXSlope), and area under the concentration-time curve (AUCt), along with the apparent diffusion coefficient (ADC), were extracted. Univariate and multivariable logistic regression analyses were performed to identify independent discriminators. Diagnostic performance was assessed using receiver operating characteristic analysis, and model comparisons were conducted with the DeLong test. Interobserver agreement was evaluated using intraclass correlation coefficients (ICC). Results: All qDCE-MRI parameters demonstrated excellent interobserver agreement (ICC range, 0.82–0.94). Multivariable analysis identified K_ep (OR = 2620.172, p = 0.001), maximal slope (OR = 1.715, p = 0.024), and tumor location (OR = 5.561, p = 0.027) as independent predictors. The qDCE-MRI model achieved superior diagnostic performance compared with the clinical model (AUC: 0.945 vs. 0.747; p = 0.012). Conclusions: A qDCE-MRI–based model incorporating K_ep and MAXSlope was shown to provide excellent accuracy for preoperative differentiation between oral SCC and minor SGC. Full article

Urethral stricture is a disease of fibrotic narrowing that compromises the urethral mucosa and spongiosum. Oral mucosal graft urethroplasty delivers excellent outcomes in complex cases, yet its procedural demands restrict availability beyond specialized centers. Endoscopic transplantation of oral mucosa has been proposed; while feasibility is shown, clinical efficacy remains suboptimal. We asked whether extracellular vesicles from stem cells of human exfoliated deciduous teeth (SHED-EVs) promote oral mucosa fibroblast (OMF) growth under urethra-mimetic paracrine conditions and whether culture growth phase tunes EV function. SHED-EVs were collected during logarithmic (SHED-EV-L) or stationary (SHED-EV-S) phases under xeno-free conditions, isolated by a standardized workflow, and characterized by nanoparticle tracking analysis. miRNA cargo was profiled with a human miRNA microarray platform and normalized for comparative analyses. OMF proliferation was quantified in a horizontal indirect co-culture with urethral epithelial cells using incubator-based time-lapse imaging. SHED-EV-L produced a sustained pro-proliferative effect across 24–96 h, whereas SHED-EV-S showed a weaker early effect with a late catch-up; both exceeded vehicle at 96 h. Fibrosis-related miRNA heat maps showed culture growth phase-dependent patterns: SHED-EV-L displayed relatively higher signals for miR-31-3p, miR-146b-3p, several let-7 members, and selected miR-181 isoforms, whereas SHED-EV-S showed a marked relative increase of miR-486-3p; miR-21, miR-99/100, and miR-205 were broadly comparable between phases. These findings indicate that culture growth phase is a practical design lever that orients SHED-EV cargo and function, supporting phase-matched formulations for adjunctive transurethral applications and motivating in vivo validation and manufacturing-oriented quality controls. Full article

Background/Objectives: Artificial intelligence (AI) has rapidly evolved from experimental algorithms to transformative tools in clinical dentistry. Between 2020 and 2025, advances in machine learning (ML) and deep learning (DL) have reshaped diagnostic imaging, caries detection, prosthodontic design, and teledentistry, while raising new ethical and regulatory challenges. This study aimed to provide a comprehensive bibliometric and conceptual review of AI applications in dental care, highlighting research trends, thematic clusters, and future directions for equitable and responsible integration of AI technologies. In addition, the review further considers the implications of AI adoption for patient-centered care, including its potential role in supporting shared decision-making processes in oral healthcare. Methods: A comprehensive search was conducted in PubMed, Scopus and Embase for articles published between January 2020 and October 2025 using AI-related keywords in dentistry. Eligible records were analyzed using VOSviewer (v.1.6.20) to map co-occurrence networks of keywords, authors, and citations. A narrative synthesis complemented the bibliometric mapping, emphasizing conceptual and ethical dimensions of AI adoption in oral health care. Results: A total of 50 documents met the inclusion criteria. Bibliometric network visualization identified that the largest and most interconnected clusters were centered around the keywords “artificial intelligence,” “machine learning,” and “deep learning,” reflecting the technological backbone of AI-based applications in dentistry. Thematic evolution analysis indicated increasing interest in generative and multimodal AI models, explainability, and fairness in clinical deployment. Conclusions: AI has become a core driver of innovation in dentistry, enabling precision diagnostics and personalized care. However, responsible translation requires robust validation, transparency, and ethical oversight. Future research should integrate interdisciplinary approaches linking AI performance, patient outcomes, and equity in oral health. Full article