434 research outputs found

    Seasonal variation of phytoplankton community assembly processes in Tibetan Plateau floodplain

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    Uncovering the mechanisms underlying phytoplankton community assembly remains a major challenge in freshwater ecology. The roles of environmental filtering and spatial processes in shaping phytoplankton metacommunity in Tibetan floodplain ecosystems under various hydrological conditions are still unclear. Here, multivariate statistics and a null model approach were used to compare the spatiotemporal patterns and assembly processes of phytoplankton communities in the river-oxbow lake system of Tibetan Plateau floodplain between non-flood and flood periods. The results showed that phytoplankton communities had significant seasonal and habitat variations, with the seasonal variations being more remarkable. Phytoplankton density, biomass, and alpha diversity were distinctly lower in the flood than non-flood period. The habitat differences (rivers vs. oxbow lakes) in phytoplankton community were less pronounced during the flood than non-flood period, most likely due to the increased hydrological connectivity. There was a significant distance-decay relationship only in lotic phytoplankton communities, and such relationship was stronger in the non-flood than flood period. Variation partitioning and PER-SIMPER analysis showed that the relative role of environmental filtering and spatial processes affecting phytoplankton assemblages varied across hydrological periods, with environmental filtering dominating in the non-flood period and spatial processes in the flood period. These results suggest that the flow regime plays a key role in balancing environmental and spatial factors in shaping phytoplankton communities. This study contributes to a deeper understanding of ecological phenomena in highland floodplains and provides a theoretical basis for floodplain ecosystem maintenance and ecological health management.Peer reviewe

    Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network

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    In the past decade, the heterogeneous information network (HIN) has become an important methodology for modern recommender systems. To fully leverage its power, manually designed network templates, i.e., meta-structures, are introduced to filter out semantic-aware information. The hand-crafted meta-structure rely on intense expert knowledge, which is both laborious and data-dependent. On the other hand, the number of meta-structures grows exponentially with its size and the number of node types, which prohibits brute-force search. To address these challenges, we propose Genetic Meta-Structure Search (GEMS) to automatically optimize meta-structure designs for recommendation on HINs. Specifically, GEMS adopts a parallel genetic algorithm to search meaningful meta-structures for recommendation, and designs dedicated rules and a meta-structure predictor to efficiently explore the search space. Finally, we propose an attention based multi-view graph convolutional network module to dynamically fuse information from different meta-structures. Extensive experiments on three real-world datasets suggest the effectiveness of GEMS, which consistently outperforms all baseline methods in HIN recommendation. Compared with simplified GEMS which utilizes hand-crafted meta-paths, GEMS achieves over 6%6\% performance gain on most evaluation metrics. More importantly, we conduct an in-depth analysis on the identified meta-structures, which sheds light on the HIN based recommender system design.Comment: Published in Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM '20

    Interaction of Flavonoids from Woodwardia unigemmata with Bovine Serum Albumin (BSA): Application of Spectroscopic Techniques and Molecular Modeling Methods

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    Phytochemical investigation on the methanol extract of Woodwardia unigemmata resulted in the isolation of seven flavonoids, including one new flavonol acylglycoside (1). The structures of these compounds were elucidated on the basis of extensive spectroscopic analysis and comparison of literature data. The multidrug resistance (MDR) reversing activity was evaluated for the isolated compounds using doxorubicin-resistant K562/A02 cells model. Compound 6 showed comparable MDR reversing effect to verapamil. Furthermore, the interaction between compounds and bovine serum albumin (BSA) was investigated by spectroscopic methods, including steady-state fluorescence, synchronous fluorescence, circular dichroism (CD) spectroscopies, and molecular docking approach. The experimental results indicated that the seven flavonoids bind to BSA by static quenching mechanisms. The negative ∆H and ∆S values indicated that van der Waals interactions and hydrogen bonds contributed in the binding of compounds 2–6 to BSA. In the case of compounds 1 and 7 systems, the hydrophobic interactions play a major role. The binding of compounds to BSA causes slight changes in the secondary structure of BSA. There are two binding sites of compound 6 on BSA and site I is the main site according to the molecular docking studies and the site marker competitive binding assayThis work was supported by the Natural Science Foundation of China (81502921) and the Young Scholars Program of Shandong University (2015WLJH50).Peer Reviewe
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