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Objective:To establish the quality evaluation method of Astmgali Radix based on three-dimensional fluorescence spectroscopy. Methods:The three-dimensional fluorescence spectra of Astmgali Radix extract was measured by fluorescence spectrum analysis technology, and the characteristics of fluorescence components of three-dimensional fluorescence spectrum of Astmgali Radix were analyzed by parallel factor analysis. The three-dimensional fluorescence spectra of Astmgali Radix samples from 23 different places were measured for quality discriminant analysis. Results:After the optimization, the three-dimensional fluorescence spectrum of 80% ethanol extract of Astmgali Radix showed that three groups of characteristic excitation/emission (λex/λem) peak, which located at 305 nm/420 nm (Peak 1), 280 nm/315 nm (Peak 2) and 265 nm/475 nm (Peak 3), respectively. The results of parallel factor analysis showed that Peak 1 and Peak 3 both contained one isoflavones fluorescent component, and Peak 2 contained two amino acid fluorescent components. There were differences in the number of characteristic peaks and fluorescence intensity of three-dimensional fluorescence spectra of Astmgali Radix samples from different origins. Conclusion:The three-dimensional fluorescence spectrum could evaluate the consistency of Astmgali Radix from different places. The method is simple, fast, and efficient. This method is accurate, which could provide reference for the quality evaluation of Astmgali Radix.
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PURPOSE: To explore spatial and temporal characteristics of glaucomatous visual field (VF) progression through multi-way decomposition of data. METHODS: Six serial VF exams with intervals of 6.0 ± 1.0 months in 121 pre-perimetric glaucoma eyes and 80 perimetric glaucoma eyes were arranged into a three-dimensional cube. The data were decomposed using parallel factor analysis. RESULTS: Three tri-linear components (i.e., spatial scores, temporal loadings, and subject-specific loadings) were identified. Component 1 clearly showed differences between superior and inferior hemispheres, linear trends over time, and wide variability in perimetric glaucoma. Findings were compatible with well-known characteristics of glaucomatous VF defects. Component 2 showed nasal and central areas in contrast with superior, inferior, and temporal peripheral locations, whereas component 3 showed a contrast between nasal and temporal hemispheres. Both components 2 and 3 failed to show clear temporal trends. CONCLUSIONS: Identification of spatio-temporal patterns shows new possibilities for a multi-way decomposition methodology for earlier diagnosis and prediction of glaucomatous VF progression.