Antibacterial activity of Hibiscus rosa-sinensis L. red flower against antibiotic-resistant strains of Helicobacter pylori and identification of the flower constituents.

Utilization of plant resources for treatment of Helicobacter pylori infections is one of the appealing approaches as rapid emergence of antibiotic-resistant strains is occurring throughout the world. Ethanol extract and its fractions from Hibiscus rosa-sinensis red flower were assessed for antibacterial and urease inhibitory activities towards forty-three clinical strains and two reference strains of H. pylori. The ethyl acetate fraction exhibited the most potent bacteriostatic activity with minimum inhibitory concentrations (MICs) of 0.2-0.25 mg/mL and minimum bactericidal concentrations (MBCs) of 1.25-1.5 mg/mL against all test strains, including forty-three strains resistant to one to four antibiotics, azithromycin (MICs, 8-256 µg/mL), erythromycin (MICs, 8-128 µg/mL), levofloxacin (MICs, 8-256 µg/mL), and/or metronidazole (MICs, 8-256 µg/mL). The fraction had similar antibacterial activities toward these test strains suggesting the preparation and the antibiotics do not have a common mechanism of anti-H. pylori activity. The fraction also had stronger effects on biofilm formation, morphological conversion, and urease activity of H. pylori than the other fractions and the ethanol extract. These flower preparations were non-toxic to three human cell lines, and nine compounds were also isolated and identified from the ethyl acetate fraction. In vivo research needs to be conducted to confirm the potential usefulness of H. rosa-sinensis flower and its constituents for effective prevention and treatment of H. pylori disease.

Antibacterial activity of Hibiscus rosa-sinensis L. red flower against antibiotic-resistant strains of Helicobacter pylori and identification of the flower constituents

Utilization of plant resources for treatment of Helicobacter pylori infections is one of the appealing approaches as rapid emergence of antibiotic-resistant strains is occurring throughout the world. Ethanol extract and its fractions from Hibiscus rosa-sinensis red flower were assessed for antibacterial and urease inhibitory activities towards forty-three clinical strains and two reference strains of H. pylori. The ethyl acetate fraction exhibited the most potent bacteriostatic activity with minimum inhibitory concentrations (MICs) of 0.2-0.25 mg/mL and minimum bactericidal concentrations (MBCs) of 1.25-1.5 mg/mL against all test strains, including forty-three strains resistant to one to four antibiotics, azithromycin (MICs, 8-256 µg/mL), erythromycin (MICs, 8-128 µg/mL), levofloxacin (MICs, 8-256 µg/mL), and/or metronidazole (MICs, 8-256 µg/mL). The fraction had similar antibacterial activities toward these test strains suggesting the preparation and the antibiotics do not have a common mechanism of anti-H. pylori activity. The fraction also had stronger effects on biofilm formation, morphological conversion, and urease activity of H. pylori than the other fractions and the ethanol extract. These flower preparations were non-toxic to three human cell lines, and nine compounds were also isolated and identified from the ethyl acetate fraction. In vivo research needs to be conducted to confirm the potential usefulness of H. rosa-sinensis flower and its constituents for effective prevention and treatment of H. pylori disease.

Modified feed-forward neural network structures and combined-function-derivative approximations incorporating exchange symmetry for potential energy surface fitting.

The classical interchange (permutation) of atoms of similar identity does not have an effect on the overall potential energy. In this study, we present feed-forward neural network structures that provide permutation symmetry to the potential energy surfaces of molecules. The new feed-forward neural network structures are employed to fit the potential energy surfaces for two illustrative molecules, which are H(2)O and ClOOCl. Modifications are made to describe the symmetric interchange (permutation) of atoms of similar identity (or mathematically, the permutation of symmetric input parameters). The combined-function-derivative approximation algorithm (J. Chem. Phys. 2009, 130, 134101) is also implemented to fit the neural-network potential energy surfaces accurately. The combination of our symmetric neural networks and the function-derivative fitting effectively produces PES fits using fewer numbers of training data points. For H(2)O, only 282 configurations are employed as the training set; the testing root-mean-squared and mean-absolute energy errors are respectively reported as 0.0103 eV (0.236 kcal/mol) and 0.0078 eV (0.179 kcal/mol). In the ClOOCl case, 1693 configurations are required to construct the training set; the root-mean-squared and mean-absolute energy errors for the ClOOCl testing set are 0.0409 eV (0.943 kcal/mol) and 0.0269 eV (0.620 kcal/mol), respectively. Overall, we find good agreements between ab initio and NN prediction in term of energy and gradient errors, and conclude that the new feed-forward neural-network models advantageously describe the molecules with excellent accuracy.