@article{chen_neuropeptide_2022, title = {A {Neuropeptide} {Y}/{F}-like {Polypeptide} {Derived} from the {Transcriptome} of {Turbinaria} peltata {Suppresses} {LPS}-{Induced} {Astrocytic} {Inflammation}}, volume = {85}, issn = {0163-3864}, url = {https://doi.org/10.1021/acs.jnatprod.2c00158}, doi = {10.1021/acs.jnatprod.2c00158}, abstract = {Neuropeptides are a group of neuronal signaling molecules that regulate physiological and behavioral processes in animals. Here, we used in silico mining to predict the polypeptide composition of available transcriptomic data of Turbinaria peltata. In total, 118 transcripts encoding putative peptide precursors were discovered. One neuropeptide Y/F-like peptide, named TpNPY, was identified and selected for in silico structural, in silico binding, and pharmacological studies. In our study, the anti-inflammation effect of TpNPY was evaluated using an LPS-stimulated C8-D1A astrocyte cell model. Our results demonstrated that TpNPY, at 0.75–3 μM, inhibited LPS-induced NO production and reduced the expression of iNOS in a dose-dependent manner. Furthermore, TpNPY reduced the secretion of proinflammatory cytokines. Additionally, treatment with TpNPY reduced LPS-mediated elevation of ROS production and the intracellular calcium concentration. Further investigation revealed that TpNPY downregulated the IKK/IκB/NF-κB signaling pathway and inhibited expression of the NLRP3 inflammasome. Through molecular docking and using an NPY receptor antagonist, TpNPY was shown to have the ability to interact with the NPY Y1 receptor. On the basis of these findings, we concluded that TpNPY might prevent LPS-induced injury in astrocytes through activation of the NPY-Y1R.}, number = {6}, urldate = {2022-09-21}, journal = {Journal of Natural Products}, author = {Chen, Qian and Liang, Zirong and Yue, Qian and Wang, Xiufen and Siu, Shirley Weng In and Pui-Man Hoi, Maggie and Lee, Simon Ming-Yuen}, month = jun, year = {2022}, note = {0 citations (Crossref) [2022-09-21] Publisher: American Chemical Society}, pages = {1569--1580}, } @article{chen_use_2017, title = {Use of stable isotopes to understand food webs in {Macao} wetlands}, volume = {25}, issn = {1572-9834}, url = {https://doi.org/10.1007/s11273-016-9502-2}, doi = {10.1007/s11273-016-9502-2}, abstract = {In this study, components of the food-web in Macao wetlands were quantified using stable isotope ratio techniques based on carbon and nitrogen values. The δ13C and δ15N values of particulate organic matter (δ13CPOM and δ15NPOM, respectively) ranged from −30.64 ± 1.0 to −28.1 ± 0.7 ‰, and from −1.11 ± 0.8 to 3.98 ± 0.7 ‰, respectively. The δ13C values of consumer species ranged from −33.94 to −16.92 ‰, showing a wide range from lower values in a freshwater lake and inner bay to higher values in a mangrove forest. The distinct dietary habits of consumer species and the location-specific food source composition were the main factors affecting the δ13C values. The consumer 15N-isotope enrichment values suggested that there were three trophic levels; primary, secondary, and tertiary. The primary consumer trophic level was represented by freshwater herbivorous gastropods, filter-feeding bivalves, and plankton-feeding fish, with a mean δ15N value of 5.052 ‰. The secondary consumer level included four deposit-feeding fish species distributed in Fai Chi Kei Bay and deposit-feeding gastropods in the Lotus Flower Bridge flat, with a mean δ15N value of 6.794 ‰. The tertiary consumers group consisted of four crab species, one shrimp species, and four fish species in the Lotus Flower Bridge Flat, with a mean δ15N value of 13.473 ‰. Their diet mainly comprised organic debris, bottom fauna, and rotten animal tissues. This study confirms the applicability of the isotopic approach in food web studies.}, language = {en}, number = {1}, urldate = {2021-02-10}, journal = {Wetlands Ecology and Management}, author = {Chen, Qian and Liu, Yang and Ho, Wei-Tim and Chan, Shek Kiu and Li, Qiu-hua and Huang, Jian-Rong}, month = feb, year = {2017}, note = {8 citations (Crossref) [2022-09-21]}, pages = {59--66}, }