Determination of neuroprotective oxysterols in Calculus bovis , human gallstones, and traditional Chinese medicine preparations by liquid chromatography with mass spectrometry

Shexiang Baoxin Pill, a Formulated Chinese Herbal Mixture, Induces Neuronal Differentiation of PC12 Cells: A Signaling Triggered by Activation of Protein Kinase A

Background: Shexiang Baoxin Pill (SBP) is a well-known composite formula of traditional Chinese medicine (TCM), which is commonly used today in treating cardiovascular diseases. SBP consists of seven materials thereof, including Moschus, extract of Ginseng Radix et Rhizoma, Bovis Calculus Artifactus, Cinnamomi Cortex, Styrax, Bufonis Venenum, and Borneolum Syntheticum. Here, we are investigating the potential roles of SBP in inducing neuron differentiation, i.e., seeking possible application in neurodegenerative diseases.

Methods: Water and ethanol extracts of SBP, denoted as SBP_water and SBP_EtOH, respectively, as well as its individual herbal materials, were standardized and applied onto cultured rat pheochromocytoma PC12 cells. The potential effect of SBP extracts in neuronal differentiation was suggested by following parameters: (i) induction of neurite outgrowth of PC12 cells, (ii) increase of neurofilament expression, and (iii) activation of transcription of neurofilament.

Results: The treatments of SBP_water and SBP_EtOH, or extracts from individual herbal materials, with or without low concentration of nerve growth factor (NGF), could potentiate the differentiation of cultured PC12 cells. The differentiation was indicated by increase of neurite outgrowth, as well as expression of neurofilaments. In addition, application of H89, a protein kinase A (PKA) inhibitor, suppressed the SBP-induced neurofilament expressions, as well as the phosphorylation of cAMP-responsive element binding protein (CREB) in cultures.

Conclusion: SBP is proposed to possess trophic activity in modulating neuronal differentiation of PC12 cells, and this induction is shown to be mediated partly by a cAMP-PKA signaling pathway. These results indicate the neurite-promoting SBP could be useful in developing potential drug in treating or preventing neurodegenerative diseases.

Efficient discovery and capture of new neuronal nitric oxide synthase-postsynaptic density protein-95 uncouplers from herbal medicines using magnetic molecularly imprinted polymers as artificial antibodies

In the scope of stroke treatment, new neuronal nitric oxide synthase-postsynaptic density protein-95 uncouplers from herbal medicines were discovered and captured. To do so, highly selective magnetic molecularly imprinted polymers with a core-shell structure were prepared as artificial antibodies. According to the results of computational simulations, we designed and synthesized various polymers with varying amounts and types of template, functional monomer, cross-linker, and solvent. Characterization and performance tests revealed that the most appropriate artificial antibodies showed uniform spherical morphologies, large adsorption capacities, fast-binding kinetics, high selectivity, and quick separation. These artificial antibodies were then used as sorbents for dispersive magnetic solid-phase extraction coupled with high-performance liquid chromatography and mass spectrometry to capture and identify structural analogs to ZL006 from extracts of Scutellariae radix, Psoraleae fructus, and Trifolium pratense. Furthermore, according to the neuroprotective effect and coimmunoprecipitation test, Baicalein, Neobavaisoflavone, Corylifol A, and Biochanin A can be the potential uncouplers of neuronal nitric oxide synthase-postsynaptic density protein-95. Therefore, this present study contributes valuable information for the discovery of neuronal nitric oxide synthase-postsynaptic density protein-95 uncouplers from herbal medicines.

Five-descriptor model to predict the chromatographic sequence of natural compounds

Despite the recent introduction of mass detection techniques, ultraviolet detection is still widely applied in the field of the chromatographic analysis of natural medicines. Here, a neural network cascade model consisting of nine small artificial neural network units was innovatively developed to predict the chromatographic sequence of natural compounds by integrating five molecular descriptors as the input. A total of 117 compounds of known structure were collected for model building. The order of appearance of each compound was determined in gradient chromatography. Strong linear correlation was found between the predicted and actual chromatographic position orders (Spearman's rho = 0.883, p < 0.0001). Application of the model to the external validation set of nine natural compounds was shown to dramatically increase the prediction accuracy of the real chromatographic order of multiple compounds. A case study shows that chromatographic sequence prediction based on a neural network cascade facilitated compound identification in the chromatographic fingerprint of Radix Salvia miltiorrhiza. For natural medicines of known compound composition, our method provides a feasible means for identifying the constituents of interest when only ultraviolet detection is available.