0000000000136099
AUTHOR
Hai Pham-the
Radicular cyst in a primary molar following pulp therapy with gutta percha : a case report and literature review
A radicular cyst (RC) in deciduous dentition is relatively rare. This clinical report presents a case of RC that condition derived from a primary molar undergone an endodontic treatment with gutta-percha approximately one year ago. In addition, we also considered whether intracanal medicaments and gutta-percha filling material related to the formation and development of the cyst or not. Key words:Primary tooth, radicular cyst, pulp therapy, gutta-percha filling material, intracanal medicament.
Computational identification of chemical compounds with potential anti-Chagas activity using a classification tree
Chagas disease is endemic to 21 Latin American countries and is a great public health problem in that region. Current chemotherapy remains unsatisfactory; consequently the need to search for new drugs persists. Here we present a new approach to identify novel compounds with potential anti-chagasic action. A large dataset of 584 compounds, obtained from the Drugs for Neglected Diseases initiative, was selected to develop the computational model. Dragon software was used to calculate the molecular descriptors and WEKA software to obtain the classification tree. The best model shows accuracy greater than 93.4% for the training set; the tree was also validated using a 10-fold cross-validation p…
MOESM1 of QuBiLS-MAS, open source multi-platform software for atom- and bond-based topological (2D) and chiral (2.5D) algebraic molecular descriptors computations
Additional file 1. The mathematical definitions of the norms, means and statistical invariants as generalizations of the linear combination of LOVIs as global (and/or local) MDs aggregation operator, as well as classical algorithms which generalize the first three groups are presented as Figure SI1-Table S12. The UML diagram (Figure SI3), a debug report file content (Figure SI4), a batch process manager dialog window (Figure SI5) are also listed. Some results of the factor analysis by the principal component method are shown as Table SI6-Table SI8, and finally, the names of structures for Cramer’s steroid database and their corresponding values for the binding affinity to the corticosteroid…
Machine learning-based models to predict modes of toxic action of phenols to Tetrahymena pyriformis.
The phenols are structurally heterogeneous pollutants and they present a variety of modes of toxic action (MOA), including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles, and soft electrophiles. Because it is often difficult to determine correctly the mechanism of action of a compound, quantitative structure-activity relationship (QSAR) methods, which have proved their interest in toxicity prediction, can be used. In this work, several QSAR models for the prediction of MOA of 221 phenols to the ciliated protozoan Tetrahymena pyriformis, using Chemistry Development Kit descriptors, are reported. Four machine learning techniques (ML), k-nearest neighbours, support vector…