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关键词： CAD-CAM resin   color stability   composite materials   flexural strength   surface roughness   thermocycling  

摘要： This in vitro study investigated the effect of thermocycling on the physicochemical properties of a conventional light-cured nanohybrid resin composite (ATOS, Smart Dent) and a CAD/CAM resin composite (ATOS BLOCK, Smart Dent). A total of 30 specimens (n = 10 per group and per time point) were prepared and evaluated after 24 h, 5,000 and 10,000 thermal cycles (5 degrees C/55 degrees C) for flexural strength (FS), elastic modulus (EM), and solvent softening (Delta KHN%), while color stability (Delta E-00 and Delta WID) was assessed only for nonaged specimens after immersion in black tea. Data were analyzed using two-way ANOVA followed by Tukey's post hoc test (alpha = 0.05), except for color stability, which was analyzed using one-way ANOVA. The CAD/CAM composite (BLOCK) exhibited significantly higher FS values than the conventional resin at all time points (p = 0.002). After 10,000 cycles, FS decreased to 105.0 +/- 7.2 MPa (BLOCK) and 70.0 +/- 6.9 MPa (ATOS) (p < 0.0001). EM values ranged from 980.0 +/- 85 to 1380.0 +/- 100 MPa, with no significant differences between groups (p = 0.072). Delta KHN% remained higher for BLOCK (33.0% +/- 2.0%-18.0% +/- 1.0%) than for ATOS (21.0% +/- 1.8%-9.0% +/- 1.1%) (p < 0.001). No statistically significant differences in Delta E-00 Delta WID were observed between materials (p > 0.05). Overall, CAD/CAM composites demonstrated superior physicochemical stability and surface preservation compared with conventional light-cured composites.

关键词： Geospatial network analysis   GIS-CAD integration   Transportation planning   Road network dataset   Spatial data interoperability  

摘要： The transportation system depends on existing road networks that connect destinations, forming the backbone of urban mobility. This study focuses on the creation and analysis of a road network dataset (ND) designed for spatial network analysis, with an emphasis on route optimization within urban areas and support for sustainable urban planning and smart infrastructure. The methodology includes data acquisition and digitization using geographic information system (GIS) technologies, specifically OpenStreetMap and Google MyMaps, followed by CAD-to-GIS format conversion to ensure precise spatial alignment. This process yields a comprehensive ND that enables shortest path analysis and optimized route planning. Validation showed distance discrepancies under +/- 0.52% between ArcMap and QGIS tools, with GPS error within +/- 2.09%, confirming high spatial accuracy. Well-connected nodes contribute to a robust geospatial network foundation. The final dataset supports transportation planning in academic environments and demonstrates potential for broader urban deployment. It enhances traffic flow, connectivity, and environmental outcomes through improved route strategies. The study offers a transferable framework applicable across cities, addressing infrastructure challenges and advancing smart, resilient, and sustainable urban growth. These findings contribute to spatial information science through practical methods that improve data reliability and decision-making.

关键词： acute coronary syndrome   coronary artery bypass   complication   CABG   coronary artery bypass graft   CAD   coronary artery disease   IVUS   intravascular ultrasound   LAD   left anterior descending   LIMA   left internal mammary artery   NSTEMI   non-ST-elevation myocardial infarction   PCI   percutaneous intervention   PDA   posterior descending artery   RIMA   right internal mammary artery   SVG   saphenous vein graft  

摘要： Arterial conduits improve long-term outcomes in coronary bypass surgery, but persistent right internal mammary artery (RIMA) side branches can cause ischemia via coronary steal.

关键词： CAD/CAM   fiber reinforced CAD composite   shear bond strength   luting resin  

摘要： The aim was to evaluate the shear-bond strength (SBS) of experimental short fiber-reinforced CAD/CAM composites (SFRC-CAD) and commercial CAD/CAM composites (Cerasmart 270) to different luting resin composites before and after hydrothermal aging. Discs (2 mm) obtained from SFRC-CAD and Cerasmart 270 were air-particle abraded and treated with a primer (G-CEM One Enhancing Primer) with or without universal adhesive (G2 Bond). A fiber-reinforced flowable composite (everX Flow) and a self-adhesive resin cement (G-CEM One) were used as luting materials under direct or indirect curing conditions. Thirty-two experimental groups were determined based on restorative material, bonding protocol, luting resin, curing technique, and aging procedure (n = 8/group). SBS was measured after 24 h of water storage or following hydrothermal aging. Data were analyzed using nonparametric statistical tests (p < 0.05). No statistically significant differences in SBS were observed between everX Flow and G-CEM One regardless of the bond application (p > 0.05). SFRC-CAD bonded with everX Flow and universal adhesive demonstrated significantly higher SBS than the corresponding Cerasmart groups (p < 0.05), whereas no significant differences were observed between comparable groups when G-CEM One was used. Failure mode analysis showed predominantly adhesive and mixed failures, with no cohesive failures within SFRC-CAD. Overall, the everX Flow proved to be an effective luting material, indicating that this material may be suitable for luting CAD/CAM indirect restorations.

关键词： aorta   aortic valve   autoimmune   cardiovascular disease   echocardiography   three-dimensional imaging   valve replacement   AGS   alpha-gal syndrome   CAD   coronary artery disease   RCA   right coronary artery  

摘要： Alpha-gal syndrome (AGS) is a delayed allergic reaction to galactose-α-1,3-galactose, a carbohydrate in nonprimate mammalian tissue. Reactions can occur in individuals exposed to lone star ticks after consuming red meat and dairy products and/or exposure to mammal-derived medications or bioprosthetic materials.

摘要： Objective To evaluate the effect of deep margin elevation (DME) with four different injectable restorative materials on the three-year clinical performance of nanoceramic-resin CAD/CAM onlay restorations. Materials and methods Sixty-four adult patients with subgingival, broad Class II carious molars indicated for onlay restorations were randomly assigned to four groups according to the injectable DME materials used: highly viscous glass ionomer (HVGI), high-filled injectable composite resin (ICR), resin-modified glass ionomer (RMGI), and bioactive ionic resin (BAIR). The proximal subgingival margins were repositioned to a supragingival level using the assigned materials;subsequently, all groups received nanoceramic-resin CAD/CAM onlay restorations. Gingival health and restorative performance were assessed over a three-year evaluation period using the Gingival Index (GI) and modified World Dental Federation (FDI) criteria. The collected data were statistically analyzed. Results All restorations were evaluated with a 100% recall rate and a 100% survival rate. For GI, assessment of scores across various evaluation periods within each group revealed a significant increase over time. Nevertheless, no significant differences were found among the tested groups at each evaluation period. Additionally, FDI evaluation criteria showed no significant differences. Conclusions After three years, nanoceramic-resin CAD/CAM onlay restorations following deep margin elevation with injectable restorative materials demonstrated acceptable clinical behavior, with only a slight increase in gingival bleeding.

关键词： cervical cancer   L1CAM   CD171   biomarker   immunohistochemistry   prognosis  

摘要： Cervical cancer remains a major contributor to cancer-related mortality among women worldwide, despite substantial progress in prevention and treatment strategies. While established prognostic factors such as tumor size, lymphovascular space invasion, and nodal status guide clinical decision-making, they lack sufficient specificity for individualized risk stratification. Consequently, there remains an unmet need for robust biomarkers capable of reliably predicting recurrence and treatment response. L1 cell adhesion molecule (L1CAM), a neural adhesion protein implicated in epithelial-mesenchymal transition (EMT), tumor invasion, and metastasis, has emerged as a candidate prognostic marker in several solid tumors, including gynecologic malignancies. Its role in cervical cancer, however, remains insufficiently defined. This narrative review synthesizes preclinical evidence and clinical studies evaluating L1CAM expression in cervical cancer, with an emphasis on its biological rationale, methodological challenges, and prognostic significance across different disease contexts. Data from early-stage and from locally advanced disease were critically appraised. Most early-stage studies have not demonstrated an independent prognostic effect of L1CAM, although associations with adverse histopathological features have been reported. In contrast, recent multicenter evidence suggests that high-level L1CAM expression (>= 50%) may predict inferior pelvic control in patients undergoing chemoradiotherapy, underscoring a potential context-dependent prognostic role. Current evidence emphasizes the need for standardized immunohistochemistry protocols, prespecified positivity thresholds, and integration of L1CAM assessment with other. Prospective, adequately powered studies are essential to validate L1CAM as a clinically actionable biomarker and to determine whether its incorporation into prognostic models can enhance treatment personalization in cervical cancer.

关键词： Tongue cancer   Glossectomy   CAD/CAM   Palatal augmentation prostheses (PAPs)   Tongue pressure  

摘要： Purpose This prospective study evaluated the impact of computer-aided design/manufacturing (CAD/CAM) palatal augmentation prostheses (PAPs) rehabilitation on maximum tongue pressure in tongue cancer patients underwent glossectomy. Methods Twelve patients (7 men, 5 women;mean age 53.2 years) with T1N0M0 or T2N0M0 tongue cancer that had undergone a type IIIa glossectomy without radiotherapy or chemotherapy were enrolled. All the participants had intact palates for good retention of PAP. Six weeks postoperatively, maxillary arches were scanned with an intraoral scanner;PAPs were digitally designed to lower the palatal vault utilizing CAD and then were fabricated from biocompatible PMMA via 3D printing and delivered. Patients wore the PAP daily and performed tongue-PAP contact exercises for at least four hours per day over six months. Maximum tongue pressure was measured using the Iowa Oral Performance Instrument before PAP delivery and after six months of rehabilitation. Statistical analysis was conducted using ANOVA with p < 0.05 considered significant. Results Mean maximum tongue pressure increased from 16.93 +/- 13.16 kPa pre-rehabilitation to 26.93 +/- 15.60 kPa post-rehabilitation (median: 11.9 to 21.9 kPa). ANOVA showed a significant improvement (F = 5.31, p = 0.0038). Conclusion CAD/CAM PAP rehabilitation significantly improved the maximum tongue pressure in glossectomy patients, suggesting potential benefits for oral-phase swallowing efficiency. Early postoperative delivery through a digital workflow minimized tongue-palate distance, enabling prompt exercises, and accelerating functional recovery. This approach represents an innovative rehabilitation strategy. Integration of pressure sensors into PAPs could enable real-time monitoring of tongue activity, expanding their role as dynamic training devices.

关键词： CAD-CAM ceramics   Gastric reflux   Color   Hardness   Solubility  

摘要： Purpose: To investigate the effects of coffee and orange juice on 3 different esthetic ceramic materials regarding color changes, Vickers microhardness, and solubility & sorption changes among patients with reflux. Methods: A glass-ceramic material (IPS Emax CAD), a polymer-infiltrated ceramic material (Vita Enamic), and a nano-hybrid ceramic material (Cerasmart) were selected for this study (n=32/group). Following the polishing procedure, all the samples were immersed in artificial saliva for 21 days. Half the samples were assigned to the control group and exposed only to artificial saliva (pH 7.3). The remaining 16 samples were exposed to saliva or simulated gastric acid. Sixteen samples from each group were exposed to gastric acid 3 times daily for 30 seconds. The color, Vickers microhardness, and solubility & sorption were then measured. Following this procedure, the samples were exposed to coffee and orange juice (n=8/per group). The samples were exposed to the solutions for 16 hours and 48 minutes to simulate 21 days of consumption. Final measurements were then obtained. Statistical significance was determined using Levene's test to compare variances, and three-way analysis of variance (ANOVA) followed by Tukey's post-hoc test, Welch's ANOVA, and Games-Howell's test were applied to reveal differences between groups. Results: According to ANOVA, restorative material type and immersion media had a significant effect on color change (P < 0.001), microhardness (P < 0.001), and solubility & sorption (P < 0.001). Conclusions: The choice of material is crucial for erosion-prone patients.

关键词： Artificial intelligence   Computer vision   Feature extraction   Art detection   Content authenticity  

摘要： This study presents a strong framework for the detection of artificial intelligence-generated artwork using digital imaging and deep learning-based transformers models, which helps in art community to distinguish the authenticity of human-created art from highly fascinated machine-generated content. Art holds reflection of deep cultural, historical, and social significance, however, due to rapid advancements in artificial intelligence, particularly in generative adversarial networks and diffusion models, have enabled the production of visually creating artworks that blur the boundaries between originality and synthesis. Traditional methods relying on conventional features and statistical analysis are increasingly lower performance against such advance transformation, highlighting the need for more advanced detection mechanisms. To address this challenge, the proposed approach employs Distillation with No Labels (DINO) v2, a self-distilled transformer model that excels in extracting discriminative features by capturing both global structures and fine-grained visual cues. The model was trained and evaluated on a balanced dataset of real and AI-generated art images, with results benchmarked against strong baselines. Experimental findings demonstrate that the proposed framework achieves 99.01% accuracy, 95.29% precision, 94.58% recall, 94.93% F1-score, and an AUC of 99%, outperforming all baselines with superior generalization. Furthermore, interpretability methods along with statistical validation based on log of p-values, confirmed that predictions are both dependable and transparent.