To establish efficient methods for selfprevention of oral diseases, assessment of dental health behavior and knowledge in various social classes is necessary. The main purpose of this study was to determine the major differences in oral health knowledge and behavior in a group of Iranian preuniversity students. In this cross-sectional study, 591 pre-university students from different regions of Mashhad, Iran were randomly selected to complete a questionnaire consisting of two parts including dental health behavior and knowledge. Scores were recorded and statistical analyses performed to determine the correlation between dental health behavior and knowledge. Data was analyzed with Student's t-test, oneway analysis of variance and Pearson correlation. The mean score of dental health knowledge was significantly lower than the dental health behavior (2.95 ± 0.02 vs. 3.31 ± 0.05, P < 0.001). This difference was observed with gender, birth location and major subject of study. The dental health behavior of Iranian pre-university students was inadequate and their dental health knowledge was at a lower level compared to their behavior. Experimental science students had better oral health behavior compared to other students. (J Oral Sci 53, 177-184, 2011)

The aim of this study was to develop a novel hybrid genetic algorithm and artificial neural network (GA-ANN) system for predicting the sizes of unerupted canines and premolars during the mixed dentition period. This study was performed on 106 untreated subjects (52 girls, 54 boys, aged 13-15 years). Data were obtained from dental cast measurements. A hybrid GA-ANN algorithm was developed to find the best reference teeth and the most accurate mapping function. Based on a regression analysis, the strongest correlation was observed between the sum of the mesiodistal widths of the mandibular canines and premolars and the mesiodistal widths of the mandibular first molars and incisors (r = 0.697). In the maxilla, the highest correlation was observed between the sum of the mesiodistal widths of the canines and premolars and the mesiodistal widths of the mandibular first molars and maxillary central incisors (0.742). The hybrid GA-ANN algorithm selected the mandibular first molars and incisors and the maxillary central incisors as the reference teeth for predicting the sum of the mesiodistal widths of the canines and premolars. The prediction error rates and maximum rates of over/underestimation using the hybrid GA-ANN algorithm were smaller than those using linear regression analyses.

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Ham's F-10 is capable of preserving PDL cells viable and reproducible better than milk and tap water and similar to HBSS.

Aim The aim of this pilot study was to evaluate equations for predicting the size of unerupted canines and premolars during the mixed dentition period in an Iranian population. Methods and Materials This cross-sectional analysis was performed on 106 subjects (52 girls, 54 boys, aged 13–15 years). Data were obtained from dental cast by making direct measurements of the maximum mesiodistal widths of all mandibular and maxillary incisors, canines, premolars, and first molars with an electronic digital sliding caliper, with an accuracy of ±0.02 mm and repeatability of ±0.01 mm. The results were statistically analyzed using Student t tests, Pearson product-moment coefficients, and ANOVA tests. Correlation coefficients (r) and error variance of estimates were determined using a significance level of p<0.05. Results No significant differences were found between the mesiodistal tooth widths of males and females in this Iranian population. The highest correlation was between the sum of the mesiodistal width of canines and premolars in the maxilla with the mesiodistal width of the mandibular first molars and maxillary central incisors (r=0.742). A moderate correlation was obtained in the mandible (r=0.665). Approximations were developed to predict the size of the unerupted canines and premolars in both jaws (in the maxilla, Y = 0.740X + 14.271, or the simplified formula, Y = 3/4X + 14; for the mandibular arch, Y = 0.658X + 16.353, or the simplified formula, Y = 2/3 X + 16). Conclusion The strongest correlation was found for the sum of the mesiodistal width of canines and premolars in the maxilla with the mesiodistal width of the mandibular first molars and maxillary central incisors in the maxillary analysis (r=0.742). A moderate correlation was found in the mandible for the sum of the mesiodistal width of canines and premolars with the mesiodistal width of the mandibular first molars and maxillary central incisors (r=0.665). Clinical Significance The simplified equations proposed for the maxillary arch (Y = 3/4 X + 14) and for the mandibular arch (Y = 2/3 X + 16) offer an easy and practical way to predict the size of unerupted canines and premolars in the maxillary and mandibular arches of Iranian children. Citation Talebi M, Parisay I, Sarraf A, Mazhari F. Regression equations for predicting the size of unerupted canines and premolars in an Iranian population: A pilot study. J Contemp Dent Pract [Internet], 2010 October; 11(5):033-040. Available from http://www.thejcdp.com/journal/view/ volume11-issue5-talebi