Three new triterpenoid saponins, acanthopanaxosides A (1), B (7), and C (13), were isolated from the leaves of Acanthopanax senticosus, together with 12 known saponins. The structures of these new saponins were established as 3-O-beta-D-glucopyranosyl-(1-->2)-alpha-L-arabinopyranosyl-30-nor-olean-12,20(29)-dien-28-oic acid 28-O-alpha-L-rhamnopyranosyl-(1-->4)-6-O-acetyl-beta-D-glucopyranosyl-(1-->6)-beta-D-glucopyranosyl ester (1), 3-O-beta-D-glucopyranosyl-(1-->2)-alpha-L-arabinopyranosyl oleanolic acid 28-O-alpha-L-rhamnopyranosyl-(1-->4)-6-O-acetyl-beta-D-glucopyranosyl-(1-->6)-beta-D-glucopyranosyl ester (7), and 3-O-alpha-L-rhamnopyranosyl-(1-->2)-alpha-L-arabinopyranosyl-3beta-hydroxyolean-12-ene-28,29-dioic acid (13), on the basis of spectroscopic analysis and chemical degradation. Among the known compounds, sessiloside and tauroside H1 are reported for the first time from A. senticosus. The biological activity of compounds 1-15 was examined against pancreatic lipase. Ciwujianoside C1 (6), tauroside H1 (11), 3-O-alpha-rhamnopyranosyl-(1-->2)-alpha-arabinopyranosyl mesembryanthemoidigenic acid (12), acanthopanaxoside C (13), sessiloside (14), and chiisanoside (15) inhibited pancreatic lipase activity in vitro. In turn, ciwujianosides C2 (3), D2 (5), C4 (8), and C3 (10) and hederasaponin B (9) enhanced this enzyme.

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Fourier Ptychographic Microscopy (FPM) is a newly proposed computational imaging method aimed at reconstructing a high-resolution wide-field image from a sequence of low-resolution images. These lowresolution images are captured under varied illumination angles and the FPM recovery routine then stitches them together in the Fourier domain iteratively. Although FPM has achieved success with static sample reconstructions, the long acquisition time inhibits real-time application. To address this problem, we propose here a self-learning based FPM which accelerates the acquisition and reconstruction procedure. We first capture a single image under normally incident illumination, and then use it to simulate the corresponding low-resolution images under other illumination angles. The simulation is based on the relationship between the illumination angles and the shift of the sample's spectrum. We analyze the importance of the simulated low-resolution images in order to devise a selection scheme which only collects the ones with higher importance. The measurements are then captured with the selection scheme and employed to perform the FPM reconstruction. Since only measurements of high importance are captured, the time requirements of data collection as well as image reconstruction can be greatly reduced. We validate the effectiveness of the proposed method with simulation and experimental results showing that the reduction ratio of data size requirements can reach over 70%, without sacrificing image reconstruction quality.

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