Static guided surgery for dental implant insertion is a well-documented procedure requiring the manufacturing of a custom-made surgical guide, either teeth-supported, mucosal-supported, bone-supported, or mixed (teeth-mucosal-supported), depending on the clinical situation. The guidance of the surgical drills during implant bed preparation could be undertaken using a sequence of different diameters of metal drill sleeves or, with the sleeves incorporated in the surgical guide, shank-modified drills, both clinically accepted and used with good results. Despite the great number of advantages associated with the use of guided surgery, one of the major risks is guide fracture during drilling for implant bed preparation. Therefore, the aim of the present study was to evaluate the surgical guides without metal sleeves and to simulate, with the aid of Finite Element Analysis (FEA), the use of such dentally supported guides for implant insertion. The FEA is performed in CATIA v5 software after defining the surgical guide mesh material and bone properties. A maximum stress of 6.92 MPa appeared on the guide at the special built-in window meant to allow cooling during drilling, and the maximum value of the guide displacement during drilling simulation was 0.002 mm. Taking into consideration the limits of the current research, the designed tooth-supported surgical guide can withstand the forces occurring during the surgery, even in denser bone, without the risk of fracture.

Objective: This systematic review and meta-analysis aimed to evaluate the effects of moisture control strategies (including wet-bonding techniques, universal adhesives, and etching type) on dentin bonding performance in restorative dentistry. Methods: A comprehensive literature search was conducted across PubMed, Scopus, and Google Scholar, following PRISMA guidelines. Only in vitro and ex vivo studies comparing wet- and dry-bonding protocols, using human dentin substrates, and reporting microtensile bond strength (μTBS) were included. The data were synthesized using a random-effects meta-analysis and the methodological quality was assessed using the MINORS tool. Certainty of evidence was evaluated using the GRADE framework. Results: Nine studies met the inclusion criteria, eight of which were included in this meta-analysis. The moisture control strategies significantly influenced the bonding outcomes, with ethanol and acetone wet bonding yielding higher μTBS and enhanced hybrid layer morphology. The universal adhesives performed effectively under both moist and dry conditions, although their performance varied by the adhesive composition and solvent system. The meta-analysis revealed a statistically significant advantage for hydrated dentin (SMD = +1.20; 95% CI: 0.52 to 1.86; p < 0.001), with the moist and ethanol-treated substrates outperforming the dry and over-wet surfaces. The long-term durability was better preserved with ethanol and acetone pretreatments and the adjunctive use of chlorhexidine. Conclusions: Moisture conditions influence dentin bond strength, but modern universal adhesives show consistent bonding performance across different moisture conditions. Solvent-wet-bonding protocols, particularly with ethanol or acetone, enhance the immediate and long-term performance. While the current evidence is limited by the in vitro designs and heterogeneity, the findings demonstrate protocol flexibility and highlight strategies to optimize adhesion in clinical practice. Future clinical trials are necessary to validate these approaches under real-world conditions.

Objectives: To compare artificial intelligence (AI) crown design with expert or non-AI computer-aided (CAD) design for single-unit tooth and implant-supported crowns across efficiency, marginal and internal fit, morphology and occlusion, and mechanical performance. Materials and Methods: This systematic review was conducted and reported in accordance with PRISMA 2020. PubMed MEDLINE, Scopus, Web of Science, IEEE Xplore, and Dentistry and Oral Sciences Source were searched from 2016 to 2025 with citation chasing. Eligible studies directly contrasted artificial intelligence-generated or artificial intelligence-assisted crown designs with human design in clinical, ex vivo, or in silico settings. Primary outcomes were design time, marginal and internal fit, morphology and occlusion, and mechanical performance. Risk of bias was assessed with ROBINS-I for non-randomized clinical studies, QUIN for bench studies, and PROBAST + AI for computational investigations, with TRIPOD + AI items mapped descriptively. Given heterogeneity in settings and endpoints, a narrative synthesis was used. Results: A total of 14 studies met inclusion criteria, including a clinical patient study, multiple ex vivo experiments, and in silico evaluations. Artificial intelligence design reduced design time by between 40% and 90% relative to expert computer-aided design or manual workflows. Marginal and internal fit for artificial intelligence and human designs were statistically equivalent in multiple comparisons. Mechanical performance matched technician designs in load-to-fracture testing, and modeling indicated stress distributions similar to natural teeth. Overall risk of bias was judged as some concerns across tiers. Conclusions: Artificial intelligence crown design delivers efficiency gains while showing short-term technical comparability across fit, morphology, occlusion, and strength for single-unit crowns in predominantly bench and in silico evidence, with limited patient-level feasibility data. Prospective clinical trials with standardized, preregistered endpoints are needed to confirm durability, generalizability, and patient-relevant outcomes, and to establish whether short-term technical advantages translate into clinical benefit.

Background: Whether nanoengineered titanium surfaces confer superior implant stability beyond modern microrough controls remains uncertain. Methods: This systematic review followed PRISMA 2020 guidance: comprehensive multi-database searching with de-duplication; dual independent screening, full-text assessment, and standardized data extraction for predefined outcomes (implant stability quotient [ISQ], mechanical anchorage by removal/push-out/pull-out torque, and histologic bone-to-implant contact). Risk of bias was appraised with RoB 2 for randomized trials, ROBINS-I for non-randomized clinical studies, and CAMARADES (animal experimentation). The certainty of clinical evidence was summarized using GRADE. Results: Across animal models, nanoengineered surfaces consistently improved early osseointegration indices (higher removal torque and bone-to-implant contact at initial healing). In clinical comparative studies, nanoengineered implants showed modest, time-limited gains in early stability (ISQ) versus microrough titanium. By 3–6 months, between-group differences typically diminished, and no consistent advantages were demonstrated for survival or marginal bone outcomes at later follow-up. Methodologic heterogeneity (surface chemistries, timepoints, outcome definitions) and small clinical samples limited quantitative synthesis. Overall, risk-of-bias concerns ranged from some concerns to high in non-randomized studies; the certainty of clinical evidence was low. Conclusions: Nanofeatured titanium surfaces improve early osseointegration but do not demonstrate a consistent long-term advantage over modern microrough implants. Current evidence supports an early osseointegration benefit without clear long-term clinical advantage over contemporary microrough implants. Adequately powered, head-to-head trials with standardized stability endpoints and ≥12-month follow-up are needed to determine whether early gains translate into patient-important outcomes.

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Digital technologies represent new alternatives in prosthetic rehabilitation of all kind of maxillary or mandibular spans. This article is composed of two parts, in which different technological aspects will be presented regarding the prosthetic restoration of frontal maxillary areas using the CAD-CAM technology, but using different material for resistance framework, both veneered with ceramic materials to restore the aesthetics. The main material that will be used are: Co-Cr dental alloy and zirconium dioxide (zirconia).