The cementation of indirect restoration is one of the most important steps in prosthetic and restorative dentistry. Cementation aims to bond the prosthetic restoration to the prepared enamel or enamel and dentine. Successful cementation protocols prevent biofilm formation at the margin between tooth and restoration and minimize mechanical and biological complications. With the advancements in dental cements, they have been modified to be versatile in terms of handling, curing, and bond strengths. This review presents updates on dental cements, focusing on the composition, properties, advantages, limitations, and indications of the various cements available. Currently, dental restorations are made from various biomaterials, and depending on each clinical case, an appropriate luting material will be selected. There is no luting material that can be universally used. Therefore, it is important to distinguish the physical, mechanical, and biological properties of luting materials in order to identify the best options for each case. Nowadays, the most commonly used dental cements are glass-ionomer and resin cement. The type, shade, thickness of resin cement and the shade of the ceramic, all together, have a tangible influence on the final restoration color. Surface treatments of the restoration increase the microtensile bond strength. Hence, the proper surface treatment protocol of both the substrate and restoration surfaces is needed before cementation. Additionally, the manufacturer’s instructions for the thin cement-layer thickness are important for the long-term success of the restoration.

Aim. This comprehensive review is aimed at evaluating the diagnostic and prognostic accuracy of artificial intelligence in endodontic dentistry. Introduction. Artificial intelligence (AI) is a relatively new technology that has widespread use in dentistry. The AI technologies have primarily been used in dentistry to diagnose dental diseases, plan treatment, make clinical decisions, and predict the prognosis. AI models like convolutional neural networks (CNN) and artificial neural networks (ANN) have been used in endodontics to study root canal system anatomy, determine working length measurements, detect periapical lesions and root fractures, predict the success of retreatment procedures, and predict the viability of dental pulp stem cells. Methodology. The literature was searched in electronic databases such as Google Scholar, Medline, PubMed, Embase, Web of Science, and Scopus, published over the last four decades (January 1980 to September 15, 2021) by using keywords such as artificial intelligence, machine learning, deep learning, application, endodontics, and dentistry. Results. The preliminary search yielded 2560 articles relevant enough to the paper’s purpose. A total of 88 articles met the eligibility criteria. The majority of research on AI application in endodontics has concentrated on tracing apical foramen, verifying the working length, projection of periapical pathologies, root morphologies, and retreatment predictions and discovering the vertical root fractures. Conclusion. In endodontics, AI displayed accuracy in terms of diagnostic and prognostic evaluations. The use of AI can help enhance the treatment plan, which in turn can lead to an increase in the success rate of endodontic treatment outcomes. The AI is used extensively in endodontics and could help in clinical applications, such as detecting root fractures, periapical pathologies, determining working length, tracing apical foramen, the morphology of root, and disease prediction.

Antibiotic resistance rate is rising worldwide. Silver nanoparticles (AgNPs) are potent for fighting antimicrobial resistance (AMR), independently or synergistically. The purpose of this study was to prepare AgNPs using wild ginger extracts and to evaluate the antibacterial efficacy of these AgNPs against multidrug-resistant (MDR) Staphylococcus aureus, Streptococcus mutans, and Enterococcus faecalis. AgNPs were synthesized using wild ginger extracts at room temperature through different parameters for optimization, i.e., pH and variable molar concentration. Synthesis of AgNPs was confirmed by UV/visible spectroscopy and further characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy analysis (EDXA), and Fourier-transform infrared spectroscopy (FTIR). Disc and agar well diffusion techniques were utilized to determine the in vitro antibacterial activity of plant extracts and AgNPs. The surface plasmon resonance peaks in absorption spectra for silver suspension showed the absorption maxima in the range of 400–420 nm. Functional biomolecules such as N–H, C–H, O–H, C–O, and C–O–C were present in Zingiber zerumbet (Z. zerumbet) (aqueous and organic extracts) responsible for the AgNP formation characterized by FTIR. The crystalline structure of ZZAE-AgCl-NPs and ZZEE-AgCl-NPs was displayed in the XRD analysis. SEM analysis revealed the surface morphology. The EDXA analysis also confirmed the element of silver. It was revealed that AgNPs were seemingly spherical in morphology. The biosynthesized AgNPs exhibited complete antibacterial activity against the tested MDR bacterial strains. This study indicates that AgNPs of wild ginger extracts exhibit potent antibacterial activity against MDR bacterial strains.

The aim is to assess the influence of fabrication techniques—conventional (CN), CAD-CAM (CC), and 3D printing (3D)—on the marginal fit, adaptation, surface roughness, and wear of interim restorations of crowns. Thirty interim crowns were fabricated using CN, CC, and 3D techniques. Sixty discs were fabricated to evaluate surface wear and surface roughness properties, with 10 disc samples in each group (n = 10). Internal adaptation and marginal integrity of interim crowns were analyzed with micro CT to detect microgaps at selected points. Average surface micro-roughness (Ra) was calculated in micrometers (μm) using an optical non-contact surface microscope under cyclic loading. Surface wear was evaluated by surface area measurements (mm³) using a micro CT. Analysis of variance (ANOVA) and Tukey’s post hoc comparison tests with Pearson correlation were performed for data analysis. The highest adaptation means were for CN (269.94 ± 64 μm), and the lowest mean value was observed for 3D (197.82 ± 11.72 μm) crowns. CN and CC specimens showed comparable adaptation (p > 0.05), which were significantly higher (p < 0.05) than 3D crowns. CN crowns showed significantly higher marginal misfit compared to 3D (p < 0.05) and CC (p < 0.05) crowns. The highest mean surface roughness was observed in the 3D crowns (5.61 ± 0.33 µm), whereas the lowest was found in CC crowns (3.28 ± 0.34 µm). Better restoration Ra was observed using the CC method followed by CN. CN had the highest wear (17.79 ± 2.78 mm³), and the lowest wear was observed in the 3D (10.81 ± 2.00 mm³) specimen. Low surface wear was observed using 3D printing, followed by CN and CC techniques. The printed specimen showed comparable outcomes to CAD-CAM restoration; however, they were better than CN restoration. A positive correlation between adaptation and surface roughness was observed, indicating an effect of the fabrication technique on material physical property.

Antimicrobial resistance (AMR) is a global health issue that plays a significant role in morbidity and mortality, especially in immunocompromised patients. It also becomes a serious threat to the successful treatment of many bacterial infections. The widespread and irrelevant use of antibiotics in hospitals and local clinics is the leading cause of AMR. Under this scenario, the study was conducted in a tertiary care hospital in Lahore, Pakistan, from 2 August 2021 to 31 October 2021 to discover the prevalence of bacterial infections and AMR rates in COVID-19 patients admitted in surgical intensive care units (SICUs). Clinical samples were collected from the patients and we proceeded to identify bacterial isolates, followed by antibiotic susceptibility testing (AST) using the Kirby Bauer disk diffusion method and minimum inhibitory concentration (MIC). The data of other comorbidities were also collected from the patient’s medical record. The current study showed that the most common pathogens were E. coli (32%) and Klebsiella pneumoniae (17%). Most E. coli were resistant to ciprofloxacin (16.8%) and ampicillin (19.8%). Klebsiella pneumoniae were more resistant to ampicillin (13.3%) and amoxycillin (12.0%). The most common comorbidity was chronic kidney disease (CKD) and urinary tract infections (UTIs). Around 17 different types of antibiotic, the carbapenem, fluoroquinolones, aminoglycoside, and quinolones, were highly prevalent in ICU patients. The current study provides valuable data on the clinical implication of antibiotics consumed by COVID-19 patients in SICUs and the AMR rates, especially with different comorbidities.

Background: Dental implants emerge as a dependable and efficacious alternative for patients experiencing partial or complete tooth loss. The stability of these implants is influenced by surface topography and macro-level design. In cases where the height of the maxillary posterior region is diminished, employing short implants can prove advantageous. With the aim of examining the distribution of von Mises stress, strain, and micromovement in D4 bone quality surrounding platform-switched short implants, measuring 6 mm in length and featuring diameters ranging from 4 to 6 mm, as well as different thread designs, an in-depth finite element analysis was conducted under immediate loading conditions. Methodology: A 3D finite element model was constructed to simulate maxillary molar crowns, incorporating an implant with a length of 6 mm and varying diameters and thread designs. The diameters utilized were 4/3.6 mm, 5/4 mm, and 6/4.8 mm, while the thread designs included buttress, square, and triangle patterns. Each model underwent analysis with a 100 N force applied in two directions: vertical and oblique, relative to the long axis of the implant. Stress, strain, and micromovement in the peri-implant region were recorded, employing the Ansys Workbench R v.18.1 software for modelling and analysis. Results: When comparing all three diameters, the wide diameter (6 mm threads) exhibited the lowest values of peri-implant von Mises stresses (3.3 MPa and 35.1 MPa), strains (194 Ɛ and 484 Ɛ), and micromovements (0.7 μm and 1.3 Ɛ) subjected to axial and non-axial loading of a 100 N force. Notably, square microthreads yielded the most favorable stress parameters among the different thread shapes, manifesting the minimum values of stress, strains, and micromovements in their vicinity. Conclusion: For the treatment of atrophic ridges or in scenarios necessitating extensive surgical preparation of the implant site, a combination of short implants, wide diameters, and platform switching can be employed. In situations with reduced bone height and the requirement for an implant-supported prosthesis to replace a missing permanent maxillary molar, the utilization of wide-diameter platform-switched short implants measuring 6 mm in length, featuring a square thread design, should be taken into consideration.