1.Stress distribution and deformation of uterosacral ligament and cardinal ligament under different working conditions simulated by the finite element model
Xinxin MA ; Shiyao SHANG ; Bing XIE ; Yue CHANG ; Xiuli SUN ; Xin YANG ; Jing WU ; Nan HONG ; Jianliu WANG
Chinese Journal of Obstetrics and Gynecology 2016;(2):114-119
Objective To establish the finite element model of uterosacral ligament (USL) and cardinal ligament (CL) and analyze the stress distribution and deformation with USL and CL under different working conditions. Methods Patients with stage Ⅲ-Ⅳpelvic organ prolapse (POP) and healthy female volunteers were selected for research subject, and divided into anterior uterus group and posterior uterus group. Two POP patients and two volunteers were selectd into the anterior uterus group and posterior uterine group respectively. Pelvic MRI scan was performed in two groups. Based on the original MRI data sets, the finite element model of USL and CL was constructed by using the software such as the Mimics, and the stress distribution and deformation of USL and CL were simulated. Results Under the premise of the elastic modulus fixed and three different working conditions such as 60 cmH2O, 99 cmH2O and 168 cmH2O (1 cmH2O=0.098 kPa) with abdominal pressure generated by maximum Valsalva maneuver, according to the present conditions and the simulation, the trend was analyzed: the stress and deformation of the uterus, anterior vaginal wall, USL and CL in two groups were mainly distributed in the middle and lower part of the anterior vaginal wall or the ligament and the cervix-vagina junction, the maximum stress and the maximum displacement were mainly concentrated in the lower region of the anterior vaginal wall. With increasing of abdominal pressure generated by the maximum Valsalva maneuver, the maximum stress values of the POP patient in anterior uterus group under three different working conditions were: 0.027 9, 0.046 0, 0.078 0 MPa, and the maximum displacement values were: 9.145 5, 15.090 0, 25.607 0 mm. The maximum stress values of the volunteer in anterior uterus group under three different working conditions were:0.012 6, 0.020 8, 0.035 3 MPa, and the maximum displacement values were: 1.816 7, 2.997 5, 5.086 7 mm. The maximum stress values of the POP patient in posterior uterine group under three different conditions were: 0.069 4, 0.114 6, 0.194 5 MPa, and the maximum displacement values were:11.658 0, 19.236 0, 32.643 0 mm. The maximum stress values of the volunteer in posterior uterus group under three different working conditions were:0.009 1, 0.015 1, 0.025 6 MPa, and the maximum displacement values were:2.581 6, 4.259 6, 7.228 4 mm. The maximum stress values and the maximum displacement values were all increased with increasing of abdominal pressure in the two groups. The maximum stress values and the maximum displacement values of the POP patients were greater than those of volunteers. Under different working conditions, the maximum stress values and maximum displacement values of the posterior uterus POP patient were all greater than those of the anterior uterus POP patient. Conclusions The finite element model of USL and CL is completely based on the MRI technology and the model is real and reliable. The increase of abdominal pressure will produce a larger stress and deformation of USL and CL, which is one of the reasons causing the injury of the ligament.
2.Mechanism of Buyang Huanwutang in Regulating Macrophage Cell Polarization Based on TLR4/NF-κB/NLRP3 Pathway
Yuting LI ; Zhiqiang LEI ; Yu YOU ; Hongyang ZHU ; Ziling RONG ; Shiyao CHANG ; Yuhui LIU
Chinese Journal of Experimental Traditional Medical Formulae 2023;29(19):18-25
ObjectiveTo explore the mechanism of Buyang Huanwutang in regulating macrophage polarization based on the Toll-like receptor 4 (TLR4) / nuclear factor-κB (NF-κB) / nucleotide-binding oligomerization domain-like receptor 3 (NLRP3) pathway. MethodRAW264.7 macrophages were intervened with lipopolysaccharide (LPS) of different concentrations (0, 1.25, 2.5, 5, 10, 20, 40, and 80 mg·L-1) for 24 hours. Cell Counting Kit-8 (CCK-8) assay was used to determine the cell viability of RAW264.7 macrophages. The optimal concentration was chosen to establish an in vitro inflammation model induced by LPS. Cells were divided into a blank group (20% blank serum), a model group (20% blank serum + 10 mg·L-1 LPS), a model control group (20% FBS + 10 mg·L-1 LPS), low-, medium-, and high-dose (5%, 10%, and 20%) Buyang Huanwutang-containing serum groups, a high-dose (20%) Buyang Huanwutang combined with NLRP3 inhibitor MCC950 (50 μmol·L-1) group, a high-dose (20%) Buyang Huanwutang combined with reactive oxygen species (ROS) inhibitor NAC (10 μmol·L-1) group, and a high-dose (20%) Buyang Huanwutang combined with NF-κB inhibitor PDTC (10 μmol·L-1) group. Enzyme-linked immunosorbent assay (ELISA) was used to detect the expression of interleukin-1β (IL-1β), interleukin-18 (IL-18), and tumor necrosis factor-α (TNF-α) in RAW264.7 macrophages. Flow cytometry was employed to measure ROS levels in macrophages. Western blot was used to determine the protein expression of M1-type macrophage-related factors inducible nitric oxide synthase (iNOS) and TNF-α, M2-type macrophage-related factors arginase-1 (Arg-1) and interleukin-10 (IL-10), as well as the proteins in the TLR4/NF-κB/NLRP3 pathway. ResultCCK-8 results indicated that under 10 mg·L-1 LPS stimulation, RAW264.7 macrophages exhibited the highest cell viability (P<0.01). Compared with the blank group, the model group showed significantly increased levels of IL-1β, IL-18, and TNF-α (P<0.05,P<0.01), increased ROS expression (P<0.05,P<0.01), increased protein expression of M1-type macrophage factors iNOS and TNF-α (P<0.01), decreased protein expression of M2-type macrophage factors Arg-1 and IL-10 (P<0.05,P<0.01), and upregulated expression levels of TLR4, myeloid differentiation factor 88 (MyD88), phosphorylated inhibitor of NF-κB (p-IκB)/NF-κB inhibitor (IκB), phosphorylated NF-κB (p-NF-κB) p65/NF-κB p65, NLRP3, apoptosis-associated speck-like protein containing a CARD (ASC), and pro-Caspase-1 (P<0.05, P<0.01). Compared with the model group, all Buyang Huanwutang-treated groups and inhibitor groups significantly reduced levels of IL-1β, IL-18, and TNF-α (P<0.01), suppressed the expression of inflammatory factors in RAW264.7 macrophages, decreased cellular ROS expression levels (P<0.01), downregulated M1-type macrophages iNOS and TNF-α protein expression (P<0.01), upregulated M2-type macrophages Arg-1 and IL-10 protein expression (P<0.01), and lowered protein expression levels of TLR4, MyD88, p-IκB/IκB, p-NF-κB p65/NF-κB p65, NLRP3, ASC, and pro-Caspase-1 (P<0.05, P<0.01). ConclusionBuyang Huanwutang can improve macrophage inflammation, potentially by reducing macrophage ROS levels, inhibiting RAW264.7 macrophage polarization, and downregulating the protein expression levels of the TLR4/NF-κB/NLRP3 pathway.
3.Progress in the regulation of energy metabolic homeostasis by the SWI/SNF complex subunit Baf60a.
Mengyi XU ; Shiyao ZHANG ; Wenxiang ZHANG ; Chang LIU ; Siyu CHEN
Chinese Journal of Biotechnology 2021;37(2):500-512
Metabolic syndrome is a global chronic epidemic. Its pathogenesis is determined by genetic and environmental factors. Epigenetic modification is reported to regulate gene expression without altering its nucleotide sequences. In recent years, epigenetic modification is sensitively responded to environmental signals, further affecting the gene expression and signaling transduction. Among these regulators, chromatin remodeling SWI/SNF (SWItch/Sucrose non fermentable, SWI/SNF) complex subunit Baf60a plays an important role in maintaining energy homeostasis in mammals. In this paper, we described the pathophysiological roles of Baf60a in maintaining the balance of energy metabolism, including lipid metabolism, cholesterol metabolism, urea metabolism, as well as their rhythmicity. Therefore, in-depth understanding of Baf60a-orchestrated transcriptional network of energy metabolism will provide potential therapeutic targets and reliable theoretical supports for the treatment of metabolic syndrome.
Animals
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Energy Metabolism/genetics*
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Homeostasis
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Lipid Metabolism
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Signal Transduction
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Transcription Factors/metabolism*