1.Changes of intestinal flora and the mechanism of NLRP3 inflammasome in elderly mice with cognitive dysfunction induced by sevoflurane anesthesia
Shanshan HAN ; Junjie LIANG ; Ruxi BIAN ; Chao YE ; Peng ZHAO ; Wentao SHI ; Dengxin ZHANG
Chinese Journal of Behavioral Medicine and Brain Science 2023;32(10):879-885
Objective:To investigate changes of intestinal flora and the mechanism of NLRP3 inflammasome in elderly mice with cognitive dysfunction induced by sevoflurane anesthesia.Methods:Eighteen fourteen-month-old male SPF grade C57BL/6J mice were randomly divided into control and sevoflurane groups, with 9 mice in each group. The mice of sevoflurane group inhaled 3% sevoflurane for 2 hours daily for three days. Fecal samples were collected post-exposure 24 hours for 16S rRNA sequencing. Morris water maze was then used to test the cognitive ability. Western blot was used to detect the expressions of synapse-associated proteins, NLRP3 inflammasome-related proteins of hippocampus, and NLRP3 inflammasome-related proteins of colon. Golgi staining was used to observe the number of dendritic spines in the hippocampus. qPCR was used to detect the expression of inflammatory cytokines IL-1β, IL-18, TNF-α mRNA in mice colon and hippocampal tissues.Results:(1) The Morris water maze test showed that the escape latency of the sevoflurane group was longer than the control group, but there was statistical difference only on the fifth day ( P<0.05). In the spatial exploration test, escape latency of the sevoflurane group was higher than that of the control group((49.50±9.99)s, (18.67±7.63)s, t=6.005, P<0.001), and platform crossing frequency was less than that of the control group((0.83±0.75)times, (2.33±1.03)times, t=2.87, P=0.017). (2) Western blot and Golgi staining results showed that the expression of hippocampal synaptic-related proteins and the number of dendritic spines in the sevoflurane group were significantly reduced compared with those in control group (all P<0.05). (3) 16S rRNA sequencing showed significant β-diversity difference between the two groups ( P<0.05). Compared with the control group, potential pathogens that p_Desulfobacterota and g_Desulfovibrio increased significantly in the sevoflurane group (both P<0.05), and beneficial bacteria that p_Verrucomicrobiota and g_Akkermansia decreased significantly (both P<0.05). (4) Compared with the control group, the results of qPCR showed increased expression of inflammatory cytokines TNF-α, IL-1β mRNA in the colon and hippocampal tissues of the sevoflurane group (all P<0.05). Western blot results showed increased expression of NLRP3 inflammasome-related proteins in the colon and hippocampal tissues of the sevoflurane group (both P<0.05). Immunofluorescence results showed the higher fluorescence intensity of ASC in the DG region of the hippocampus of the sevoflurane group compared with the control group ( P<0.01). Conclusion:The cognitive dysfunction model induced by sevoflurane in elderly mice shows neuroinflammatory reactions and synaptic damage, which may be related to intestinal microbiota imbalance and activation of NLRP3 inflammasome.
2.Application of Multi-element Fingerprints in the Study of Origin Traceability of Anemarrhenae Rhizoma
Hongkun ZHANG ; Yuyao HUANG ; Linyan PAN ; Ruxi PENG ; Jinsong ZHOU ; Changda GUO
China Pharmacist 2018;21(1):61-65
Objective:To study the origin traceability of anemarrhenae rhizoma from Bozhou and Hebei based on multi-element fingerprints technology , and establish a discrimination model .Methods:The contents of 48 elements were determined by using induc-tively coupled plasma mass spectrometry ( ICP-MS) for 44 samples of anemarrhenae rhizome from Bozhou and Hebei province .Princi-pal component analysis ( PCA) and orthogonal partial least squares discrimination analysis ( OPLS-DA) were applied in the data analy-sis to screen out the significant elements .And then Fisher linear discrimination analysis was used to determine the origin of anemarrhe-nae rhizoma and the discrimination models were developed .Results:Two discrimination models were developed by the discrimination a-nalysis of the whole model method with nine significant elements identified by PCA and OPLS -DA, and 100%correct classification and 95.5%cross validation were achieved by the models .Conclusion: It is a promising approach to classify the geographical origin of anemarrhenae rhizome based on multi-element fingerprints analysis combined with multivariate statistical analysis .The discrimination models are good enough to be applied in the origin traceability of anemarrhenae rhizome.