Streptococcus mutans is the microorganism mostly responsible for initiation of tooth decay and also for the progression of an established lesion. Silver has been used for its antibacterial properties for many years, in different forms: ionised and elementary forms, as silver zeolites or as nanoparticles. The purpose of this study was to evaluate the antibacterial activity of three dental cements modified by nanosilver. Three cements were used: Sealapex, RelyX ARC, and Vitrebond. The cements were incorporated with 0.05 mL of silver nanoparticles solution. Control groups were prepared without silver. Six Petri plates with BHI were inoculated with S. mutans using sterile swabs. Three cavities were made in each agar plate (total = 18) and filled with the manipulated cements. They were incubated at 37• C for 48 h, and the inhibition halos were measured. The paired t-Test was used for statistical analysis (P < 0.05). No inhibition halos were obtained for Sealapex and Rely X, but Vitrebond showed bactericidal activity without silver and enhanced effect with silver incorporation.
BackgroundFollow-up studies of former students are an efficient way to organize the entire process of professional training and curriculum evaluation. The aim of this study was to identify professional profile subgroups based on job-related variables in a sample of former students of a Brazilian public dental school.MethodsA web-based password-protected questionnaire was sent to 633 registered dentists who graduated from the Federal University of Goias between 1988 and 2007. Job-related information was retrieved from 14 closed questions, on subjects such as gender, occupational routine, training, profits, income status, and self-perception of professional career, generating an automatic database for analysis. The two-step cluster method was used for dividing dentists into groups on the basis of minimal within-group and maximal between-group variation, using job-related variables to represent attributes upon which the clustering was based.ResultsThere were 322 respondents (50.9%), predominantly female (64.9%) and the mean age was 34 years (SD = 6.0). The automatic selection of an optimal number of clusters included 289 cases (89.8%) in 3 natural clusters. Clusters 1, 2 and 3 included 52.2%, 30.8% and 17.0% of the sample respectively. Interpretation of within-group rank of variable importance for cluster segmentation resulted in the following characterization of clusters: Cluster 1 - specialist dentists with higher profits and positive views of the profession; Cluster 2 - general dental practitioners in small cities; Cluster 3 - underpaid and less motivated dentists with negative views of the profession. Male dentists were predominant in cluster 1 and females in cluster 3. One-way Anova showed that age and time since graduation were significantly lower in Cluster 2 (P < 0.001). Alternative solutions with 4 and 5 clusters revealed specific discrimination of Cluster 1 by gender and dental education professionals.ConclusionsCluster analysis was a valuable method for identifying natural grouping with relatively homogeneous cases, providing potentially meaningful information for professional orientation in dentistry in a variety of professional situations and environments.
The use of the self-etching adhesive system, even after intracoronal bleaching, presented satisfactory adhesive strength for the bonding of brackets.
The recognition of the student profile provides strategic information for planning educational policies in the university environment. The aims of this study were to identify natural segmentation of freshman undergraduate dental students based on demographic, socioeconomic and educational variables, and to subsequently investigate their impact on academic performance of Brazilian undergraduate students. Cluster analysis (two‐step algorithm) was used to segment students who entered dental school in the time period from 1999 to 2001 (n = 158) into groups based on responses to a questionnaire completed by students at the time of the admission examination. Clustering analysis revealed three natural groups. Age, the parents’ level of education, and performance on the first admission test were the most important variables for cluster segmentation. Cluster 1 (n = 42; 26.6%) was characterized by female students with higher socioeconomic status and better previous educational indicators. Cluster 2 (n = 62; 39.2%) represented disadvantaged socioeconomic profiles, with a predominance of females and older students. Cluster 3 (n = 54; 34.2%) showed similar socioeconomic characteristics to cluster 1, except for male prevalence, higher age, and experiencing difficulty in the admission test. Clusters’ academic performance was satisfactory in both overall course and course groups (grade point average of at least 7.0), with average ranging from 7.89 (SD = 0.44) to 8.13 (SD = 0.31) and 7.37 (SD = 0.75) to 8.31(SD = 0.26), respectively. Our findings provide encouraging evidence for the current context of equality of access to education and reveal the importance of financial support to maximize successful educational experiences of socioeconomically disadvantaged dental students.
-In this paper, an aerosol-based process is shown for
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