Evaluation of Complete Denture Quality and Masticatory Efficiency in Denture Wearers

Purpose: This study aimed to investigate (1) the influence of complete denture quality and years of denture use on masticatory efficiency and (2) the relationship between complete denture quality and years of use. Materials and Methods: A cross-sectional study was conducted with 93 edentulous patients (mean age: 65.6 years) wearing both mandibular and maxillary dentures. Patients were classified into two categories according to years of denture use: <= 2 years and >= 5 years. Masticatory efficiency was evaluated via the colorimetric method with beads as the artificial test food. A reproducible method for objective evaluation of the technical quality of complete dentures was employed. The association between denture quality and years of denture use was analyzed using chi-square and Fisher exact tests. The results of masticatory efficiency testing were analyzed using two-way analysis of variance (with the Tukey post hoc test) in terms of years of denture use <= 2 years, >= 5 years) and denture quality (poor, average, good). Results: A significant relationship was found between denture quality and years of denture use (P < .05). Masticatory efficiency differed significantly (P < .05) between patients with <= 2 years of denture use (0.101 +/- 0.076 absorbance) and >= 5 years of use (0.068 +/- 0.076 absorbance). Masticatory efficiency was not influenced by denture quality. Conclusions: Complete denture quality and masticatory efficiency significantly decreased over time. However, complete denture quality did not influence masticatory efficiency. Int J Prosthodont 2012;25:625-630.

Structure- and Ligand-Based Structure-Activity Relationships for a Series of Inhibitors of Aldolase

Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r(2) = 0.98 and q(2) = 0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pK(i) values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.