Methods: One hundred and eighty standardized disc samples were prepared, of which ninety samples each were used for surface roughness and microhardness test, respectively. They were divided equally into: Group 1 (Filtek-Z350-XT), Group 2 (Zmack-Comp), and Group 3 (Zr-Hybrid). For surface roughness test, all samples were polished with aluminium oxide discs and further subdivided into aged and unaged subgroups, in which composite samples in aged subgroups were subjected to 2500 thermal cycles. Next, all the samples were subjected to surface roughness test using a contact stylus profilometer. As for microhardness test, all the aged and unaged samples were tested using a Vickers hardness machine with a load of 300 kgf for 10 s and viewed under a digital microscope to obtain microhardness value. Data were analyzed using two-way ANOVA followed by post hoc Tukey's honestly significant difference and paired sample t-test with significance level set at P = 0.05.
Results: In both the aged and unaged groups, Zr-Hybrid showed statistically significantly lower surface roughness (P < 0.05) than Filtek-Z350-XT and Zmack-Comp, but no statistically significant difference was noted between Filtek-Z350-XT and Zmack-Comp (P > 0.05). A similar pattern was noted in microhardness test, whereby Zr-Hybrid showed the highest value (P < 0.05) followed by Filtek-Z350-XT and lastly Zmack-Comp. Besides, significant differences in surface roughness and microhardness were noted between the aged and unaged groups.
Conclusion: Zr-Hybrid seems to demonstrate better surface roughness and microhardness value before and after artificial ageing.
MATERIAL AND METHODS: A search of English peer-reviewed literature (January 1960-February 2021) was conducted from electronic databases (PubMed Central, Cochrane, LILACS, Science Direct, Web of Science, SIGLE, EMBASE, EBSCO, Medline, and Google Scholar).
RESULTS: 11 articles and a book section were finally selected for qualitative analysis. Studies concluded that the physicomechanical properties and the color stability of rice husk dental composites showed comparable results to conventional dental composites. Incorporation of zirconia nanopowder into rice husk dental composite increased the compressive strength and hardness values, associated with lower shrinkage, a high degree of conversion, and improved fracture strength when applied on root canal treated teeth.
CONCLUSIONS: Due to its low cost, eco-friendliness, and acceptable clinical performances, rice husk dental composite resin can be considered as an alternative to conventional composites.
CLINICAL SIGNIFICANCE: Dental composite resin derived from rice husk silica demonstrated excellent performance, which could potentially substitute currently available composite resins. This review will give new insight to clinicians and researchers on the usage of natural biowaste mass in the field of dental restorative materials.
METHODS: Twelve dental technicians with at least five years of professional experience and currently working in Malaysia agreed to participate in the one-to-one in-depth online interviews. Interviews were recorded, transcribed verbatim and translated. Thematic analysis was conducted to identify patterns, themes, and categories within the interview transcripts.
RESULTS: The analysis revealed two key themes: "Perceived Benefits of AI" and "Concerns and Challenges". Dental technicians recognised the enhanced efficiency, productivity, accuracy, and precision that AI can bring to dental laboratories. They also acknowledged the streamlined workflow and improved communication facilitated by AI systems. However, concerns were raised regarding job security, professional identity, ethical considerations, and the need for adequate training and support.
CONCLUSION: This research sheds light on the potential benefits and challenges associated with the integration of AI in dental laboratory practices. Understanding these perceptions and addressing the challenges can support the effective integration of AI in dental laboratories and contribute to the growing body of literature on AI in healthcare.
METHODS: Recently extracted lower first premolars were randomly categorized into three experimental groups (n = 15 samples), positive control (n = 5 samples), and negative control group (n = 5 sample). Samples from the experimental groups and positive control group were subject to cavity Class I occlusal preparation followed by modified coronal pulpotomy. Different types of bioceramic dressing material were placed in 3 mm thickness accordingly, group 1 (Biodentine), group 2 (MTA Angelus), and group 3 (ProRoot MTA). No dressing material was placed in the positive control group (group 4). All samples were placed in the incubator for 24 h at 37℃, 100% humidity, for the materials to be completely set. The final restoration was placed using the Z350 resin composite. A double layer of nail varnish was applied over all the sample surfaces except the occlusal site. Whereas the samples' surfaces in the negative control, were completely covered. A 3 mm length was measured from the root apex of the samples from each group, before proceeding with the resection. The bacterial leakage test was performed using Enterococcus faecalis TCC 23,125, and a sample from each experimental group was randomly chosen for SEM. Data analysis was conducted under the One-way ANOVA test, completed by Tukey's post hoc test.
RESULTS: There is a significant difference in sealing ability and marginal adaptation between the groups. (p