MATERIALS AND METHODS: Using a stainless-steel mold, disc-shaped wax patterns with dimensions of 10 mm in diameter and 2 mm thick (in accordance with ADA Specification No. 12) were created and prepared for a total of 75 acrylic samples. Dimensions of all 75 acrylic samples were checked with a digital Vernier caliper. About 25 samples of denture base material were immersed in three different chemical disinfectants: Group I: immersed in chlorhexidine gluconate solution, group II: immersed in sodium hypochlorite solution, and group III: immersed in glutaraldehyde solution. All samples were scrubbed daily for 1 minute with the appropriate disinfectant and submerged for 10 minutes in the same disinfectant. Between disinfection cycles, samples were kept in distilled water at 37°C. Color stability was measured using a reflection spectrophotometer. Surface roughness values were measured by a profilometer at baseline following 15 days and 30 days.
RESULTS: After 15 days, the color stability was better in chlorhexidine gluconate solution group (4.88 ± 0.24) than sodium hypochlorite solution (4.74 ± 0.18) and glutaraldehyde solution group (4.46 ± 0.16). The mean surface roughness was less in glutaraldehyde solution group (2.10 ± 0.19), followed by chlorhexidine gluconate solution group (2.48 ± 0.09) and sodium hypochlorite solution group (2.64 ± 0.03). After 30 days, the color stability was significantly better in chlorhexidine gluconate solution group (4.40 ± 0.02), followed by sodium hypochlorite solution (4.06 ± 0.16) and glutaraldehyde solution group (3.87 ± 0.17). The mean surface roughness was significantly lesser in glutaraldehyde solution group (2.41 ± 0.14), followed by chlorhexidine gluconate solution group (2.94 ± 0.08) and sodium hypochlorite solution group (3.02 ± 0.13).
CONCLUSION: In conclusion, the color stability was significantly better in chlorhexidine gluconate solution group than sodium hypochlorite solution and glutaraldehyde solution group. But the surface roughness was significantly lesser in the glutaraldehyde solution group, followed by the chlorhexidine gluconate and sodium hypochlorite solution group.
CLINICAL SIGNIFICANCE: The maintenance of the prosthesis requires the use of a denture disinfectant; therefore, it is crucial to select one that is effective but would not have a negative impact on the denture base resin's inherent characteristics over time. How to cite this article: Kannaiyan K, Rakshit P, Bhat MPS, et al. Effect of Different Disinfecting Agents on Surface Roughness and Color Stability of Heat-cure Acrylic Denture Material: An In Vitro Study. J Contemp Dent Pract 2023;24(11):891-894.
Materials and methods: Sixty (60) extracted sound Maxilla (Mx) and Mandibular (Mn) premolars were randomly divided into 2 groups (test and control). Artificial WSLs were produced on buccal surface of teeth and were immersed in artificial saliva for 8 weeks. Colour components (L∗, a∗, b∗) and surface roughness (Sa∗) were assessed on 40 teeth using colour difference meter RD-100 and Alicona® Infinite Focus profilometer respectively. The measurements were done at baseline (T1), directly after artificial WSLs (T2), after 24 hours immersed in saliva and application of resin (T3) and immersion in artificial saliva for 1 (T4), 2 (T5), 4 (T6), 6 (T7) and 8 (T8) weeks. SEM images analysis were carried out on 20 teeth in four time points.
Results: The values of L∗ (lightness), b∗ (yellow/blue) and Sa∗ (surface roughness) are gradually reduced to the baseline value. Whereas, the value of a∗ gradually increased with distinct treatment time to achieve the baseline value. The higher value of L∗ and Sa∗, the whiter the lesion suggesting higher degree of enamel demineralization and surface roughness. Lower L∗ values suggest a masking colour effect.
Conclusion: The material produced favorable esthetics on colour and the surface roughness of teeth at distinct treatment times. It is recommended to be used to improve WSL post orthodontic treatment.
MATERIALS AND METHODS: The ethanolic extract was used to synthesise copper nanoparticles. The copper nanoparticles were successfully synthesised from copper sulphate solution which was identified by the colour change from dark green colour of the extract. Thus the B.oleracea var acephala is a good source to synthesis copper nanoparticles. The synthesised copper nanoparticles were characterised using Scanning Electron Microscope (SEM) analysis. The SEM image displayed the high-density nanoparticles synthesised by leaf extracts and that the nanoparticles were crystals in shape.
RESULTS: The copper nanoparticles (CNP) bind to the leaf extract. B.oleracea var acephala also has shown the antimicrobial and antioxidant activity. A comparative study was done between ethanolic its crude extract and nanoparticles. Both extracts exhibited zone of inhibition and better antioxidant potential but the CuNPs shows major zone of inhibition and showed more antioxidant activity. Anticancer activity of B.oleracea var acephala against Cervical HeLa cell line was confirmed using ethanolic crude extract and CNP. The results showed that HeLa cells proliferation was inhibited with increasing concentration of ethanolic crude extract and copper nanoparticles. From the results, it was seen that percentage viability of the cancer cells decreased with increased concentration of the samples whereas cytotoxicity against HeLa cell lines increased with the increased concentration of the samples.
CONCLUSION: Thus B.oleracea var acephala possesses anticancer activity against HeLa cell lines.
METHOD: Categorisation was a surgical judgment call after thorough clinical assessment. There were 4 levels of urgency with their respective TTT; Red (2 hours), Yellow (8 hours), Green (24 hours), Blue (72 hours). Caesarean cases were excluded in colour coding due to pre - existing classification. The data for mean TTT was collected 4 weeks before the implementation (Stage 1), and another 4 weeks after implementation (Stage II). As there was a violation in the assumption for parametric test, Mann Whitney U test was used to compare the means between these two groups. Using logarithmic (Ln) transformation for TTT, Analysis of Covariance (ANCOVA) was conducted for multivariate analysis to adjust the effect of various departments. The mean TTT for each colour coding classification was also calculated.
RESULTS: The mean TTT was reduced from 13 hours 48 min to 10 hours, although more cases were completed in Stage II (428 vs 481 cases). Based on Mann-Whitney U test, the difference in TTT for Stage I (Median=6.0, /IQR=18.9) and Stage II (Median=4.2, IQR=11.5) was significantly different (p=0.023). The result remained significant (p=0.039) even after controlled for various department in the analysis. The mean/median TTT after colour coding was Red- 2h 24min/1h, Yellow- 8h 26min/3h 45 min, Green- 15h 8min/8h 15min, and Blue- 13h 46min/13h 5min.
CONCLUSION: Colour coding classification in emergency Operation (OT) was effective in reducing TTT of patients for non-caesarean section cases.