Inhibitory effect of Taraxacum officinale L (Compositae) aqueous root extract on spermatogenesis

Purpose: To investigate if T. officinale root aqueous extract has anti-spermatogenic activity similar to that of the whole plant which was shown previously to inhibit spermatogenesis.Methods: T. officinale aqueous extract was prepared by soaking 100 g of dried materials in 1 L distilled water for two days at 45 oC. Fifty adult male rats were divided into five groups and treated for 60 days. Four groups were gavaged with the whole plant or root aqueous extract in low or high doses. The male rat rats were allowed to mate with female rats. The control group received distilled water. Sperm count, motility and morphology as well as chromatin integrity were evaluated.Results: Serum testosterone level, sperm parameters, pregnancy rate and average number of fetuses per pregnant females decreased significantly in the treated groups compared to control and in the rootreceiving rats compared to the whole plant-receiving rats. Female rats which were mated with high dose root-receiving males did not deliver fetuses. Cross sections of seminiferous tubules of T. officinale treated rats showed lesions and disorganized germinal epithelium. Late spermatogenesis maturation arrest (spermatid stage) was observed in all of the treated groups except the high dose root-receiving group which showed early maturation arrest (spermatocyte stage). In addition, the mRNA level of two spermatogonial stem cell markers responsible for self-renewal and proliferation of spermatogonia increased in high dose-receiving rats.Conclusion: T. officinale root aqueous extract has inhibitory effects on spermatogenesis. Further studies are required to identify specific ingredient(s) in T. officinale that may be useful as male contraceptive(s).Keywords: Taraxacum officinale, Dandelion, GDNF family receptor alpha 1, Macrophage Colony- Stimulating Factor, Promyelocytic Leukaemia Zinc-Finger, Testosterone, Sperm coun

Artificial neural networks for dihedral angles prediction in enzyme loops: a novel approach

Structure prediction of proteins is considered a limiting step and determining factor in drug development and in the introduction of new therapies. Since the 3D structures of proteins determine their functionalities, prediction of dihedral angles remains an open and important problem in bioinformatics, as well as a major step in discovering tertiary structures. This work presents a method that predicts values of the dihedral angles φ and ψ for enzyme loops based on data derived from amino acid sequences. The prediction of dihedral angles is implemented through a neural network based mining mechanism. The amino acid sequence data represents 6342 enzyme loop chains with 18,882 residues. The initial neural network input was a selection of 115 features and the outputs were the predicted dihedral angles φ and ψ. The simulation results yielded a 0.64 Pearson\u27s correlation coefficient. After feature selection through determining insignificant features, the input feature vector size was reduced to 45, while maintaining close to identical performance