1.Carvedilol to prevent hepatic decompensation of cirrhosis in patients with clinically significant portal hypertension stratified by new non-invasive model (CHESS2306)
Chuan LIU ; Hong YOU ; Qing-Lei ZENG ; Yu Jun WONG ; Bingqiong WANG ; Ivica GRGUREVIC ; Chenghai LIU ; Hyung Joon YIM ; Wei GOU ; Bingtian DONG ; Shenghong JU ; Yanan GUO ; Qian YU ; Masashi HIROOKA ; Hirayuki ENOMOTO ; Amr Shaaban HANAFY ; Zhujun CAO ; Xiemin DONG ; Jing LV ; Tae Hyung KIM ; Yohei KOIZUMI ; Yoichi HIASA ; Takashi NISHIMURA ; Hiroko IIJIMA ; Chuanjun XU ; Erhei DAI ; Xiaoling LAN ; Changxiang LAI ; Shirong LIU ; Fang WANG ; Ying GUO ; Jiaojian LV ; Liting ZHANG ; Yuqing WANG ; Qing XIE ; Chuxiao SHAO ; Zhensheng LIU ; Federico RAVAIOLI ; Antonio COLECCHIA ; Jie LI ; Gao-Jun TENG ; Xiaolong QI
Clinical and Molecular Hepatology 2025;31(1):105-118
Background:
s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model.
Methods:
Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort.
Results:
In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM).
Conclusions
Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.
2.Carvedilol to prevent hepatic decompensation of cirrhosis in patients with clinically significant portal hypertension stratified by new non-invasive model (CHESS2306)
Chuan LIU ; Hong YOU ; Qing-Lei ZENG ; Yu Jun WONG ; Bingqiong WANG ; Ivica GRGUREVIC ; Chenghai LIU ; Hyung Joon YIM ; Wei GOU ; Bingtian DONG ; Shenghong JU ; Yanan GUO ; Qian YU ; Masashi HIROOKA ; Hirayuki ENOMOTO ; Amr Shaaban HANAFY ; Zhujun CAO ; Xiemin DONG ; Jing LV ; Tae Hyung KIM ; Yohei KOIZUMI ; Yoichi HIASA ; Takashi NISHIMURA ; Hiroko IIJIMA ; Chuanjun XU ; Erhei DAI ; Xiaoling LAN ; Changxiang LAI ; Shirong LIU ; Fang WANG ; Ying GUO ; Jiaojian LV ; Liting ZHANG ; Yuqing WANG ; Qing XIE ; Chuxiao SHAO ; Zhensheng LIU ; Federico RAVAIOLI ; Antonio COLECCHIA ; Jie LI ; Gao-Jun TENG ; Xiaolong QI
Clinical and Molecular Hepatology 2025;31(1):105-118
Background:
s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model.
Methods:
Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort.
Results:
In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM).
Conclusions
Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.
3.Carvedilol to prevent hepatic decompensation of cirrhosis in patients with clinically significant portal hypertension stratified by new non-invasive model (CHESS2306)
Chuan LIU ; Hong YOU ; Qing-Lei ZENG ; Yu Jun WONG ; Bingqiong WANG ; Ivica GRGUREVIC ; Chenghai LIU ; Hyung Joon YIM ; Wei GOU ; Bingtian DONG ; Shenghong JU ; Yanan GUO ; Qian YU ; Masashi HIROOKA ; Hirayuki ENOMOTO ; Amr Shaaban HANAFY ; Zhujun CAO ; Xiemin DONG ; Jing LV ; Tae Hyung KIM ; Yohei KOIZUMI ; Yoichi HIASA ; Takashi NISHIMURA ; Hiroko IIJIMA ; Chuanjun XU ; Erhei DAI ; Xiaoling LAN ; Changxiang LAI ; Shirong LIU ; Fang WANG ; Ying GUO ; Jiaojian LV ; Liting ZHANG ; Yuqing WANG ; Qing XIE ; Chuxiao SHAO ; Zhensheng LIU ; Federico RAVAIOLI ; Antonio COLECCHIA ; Jie LI ; Gao-Jun TENG ; Xiaolong QI
Clinical and Molecular Hepatology 2025;31(1):105-118
Background:
s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model.
Methods:
Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort.
Results:
In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM).
Conclusions
Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.
4.Development and multicenter validation of machine learning models for predicting postoperative pulmonary complications after neurosurgery.
Ming XU ; Wenhao ZHU ; Siyu HOU ; Hongzhi XU ; Jingwen XIA ; Liyu LIN ; Hao FU ; Mingyu YOU ; Jiafeng WANG ; Zhi XIE ; Xiaohong WEN ; Yingwei WANG
Chinese Medical Journal 2025;138(17):2170-2179
BACKGROUND:
Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery.
METHODS:
PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed.
RESULTS:
PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model.
CONCLUSIONS:
The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes.
TRIAL REGISTRATION
ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult
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Aged
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Female
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Humans
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Male
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Middle Aged
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Algorithms
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Lung Diseases/etiology*
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Machine Learning
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Neurosurgical Procedures/adverse effects*
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Postoperative Complications/diagnosis*
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Risk Factors
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ROC Curve
5.ADAR1 Regulates the ERK/c-FOS/MMP-9 Pathway to Drive the Proliferation and Migration of Non-small Cell Lung Cancer Cells.
Li ZHANG ; Xue PAN ; Wenqing YAN ; Shuilian ZHANG ; Chiyu MA ; Chenpeng LI ; Kexin ZHU ; Nijia LI ; Zizhong YOU ; Xueying ZHONG ; Zhi XIE ; Zhiyi LV ; Weibang GUO ; Yu CHEN ; Danxia LU ; Xuchao ZHANG
Chinese Journal of Lung Cancer 2025;28(9):647-657
BACKGROUND:
Double-stranded RNA-specific adenosine deaminase 1 (ADAR1) binds to double-stranded RNA and catalyzes the deamination of adenosine (A) to inosine (I). The functional mechanism of ADAR1 in non-small cell lung cancer (NSCLC) remains incompletely understood. This study aimed to investigate the prognostic significance of ADAR1 in NSCLC and to elucidate its potential role in regulating tumor cell proliferation and migration.
METHODS:
Data from The Cancer Genome Atlas (TCGA) and cBioPortal were analyzed to assess the correlation between high ADAR1 expression and clinicopathological features as well as prognosis in lung cancer. We performed Western blot (WB), cell proliferation assays, Transwell invasion/migration assays, and nude mouse xenograft modeling to examine the phenotypic changes and molecular mechanisms induced by ADAR1 knockdown. Furthermore, the ADAR1 p150 overexpression model was utilized to validate the proposed mechanism.
RESULTS:
ADAR1 expression was significantly elevated in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tissues compared with adjacent non-tumor tissues (LUAD: P=3.70×10-15, LUSC: P=0.016). High ADAR1 expression was associated with poor prognosis (LUAD: P=2.03×10-2, LUSC: P=2.81×10-2) and distant metastasis (P=0.003). Gene Set Enrichment Analysis (GSEA) indicated that elevated ADAR1 was associated with mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathway activation, matrix metalloproteinase-9 (MMP-9) expression, and cell adhesion. ADAR1 and MMP-9 levels showed a strongly positive correlation (P=6.45×10-34) in 10 lung cancer cell lines, highest in H1581. Knockdown of ADAR1 in H1581 cells induced a rounded cellular morphology with reduced pseudopodia. Concomitantly, it suppressed cell proliferation, invasion, migration, and in vivo tumorigenesis. It also suppressed ERK phosphorylation and downregulated cellular Finkel-Biskis-Jinkins murine osteosarcoma viral oncogene homolog (c-FOS), MMP-9, N-cadherin, and Vimentin. Conversely, ADAR1 p150 overexpression in PC9 cells enhanced ERK phosphorylation and increased c-FOS and MMP-9 expression.
CONCLUSIONS
High ADAR1 expression is closely associated with poor prognosis and distant metastasis in NSCLC patients. Mechanistically, ADAR1 may promote proliferation, invasion, migration, and tumorigenesis in lung cancer cells via the ERK/c-FOS/MMP-9 axis.
Humans
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Lung Neoplasms/physiopathology*
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Adenosine Deaminase/genetics*
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Matrix Metalloproteinase 9/genetics*
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Cell Proliferation
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Carcinoma, Non-Small-Cell Lung/physiopathology*
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Cell Movement
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Animals
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Mice
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RNA-Binding Proteins/genetics*
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Female
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Male
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Cell Line, Tumor
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Proto-Oncogene Proteins c-fos/genetics*
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Middle Aged
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MAP Kinase Signaling System
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Gene Expression Regulation, Neoplastic
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Mice, Nude
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Extracellular Signal-Regulated MAP Kinases/genetics*
6.Pien Tze Huang Attenuates Cell Proliferation and Stemness Promoted by miR-483-5p in Hepatocellular Carcinoma Cells.
Li-Hui WEI ; Xi CHEN ; A-Ling SHEN ; Yi FANG ; Qiu-Rong XIE ; Zhi GUO ; Thomas J SFERRA ; You-Qin CHEN ; Jun PENG
Chinese journal of integrative medicine 2025;31(9):782-791
OBJECTIVE:
To investigate the effect of miR-483-5p on hepatocellular carcinoma (HCC) cells proliferation and stemness, as well as the attenuating effect of Pien Tze Huang (PZH).
METHODS:
Differentially expressed miRNA between HepG2 cells and hepatic cancer stem-like cells (HCSCs) were identified by a miRNA microarray assay. miR-483-5p mimics were transfected into HepG2 cells to explore the effects of miR-483-5p on cell proliferation and stemness. HepG2 cells and HCSCs were treated with PZH (0, 0.25, 0.50 and 0.75 mg/mL) to explore the effects of PZH on the proliferation and stemness, both in non-induced state and the state induced by miR-483-5p mimics.
RESULTS:
miR-483-5p was significantly up-regulated in HCSCs and its overexpression increased cell proliferation and stemness in HepG2 cells (P<0.05). PZH not only significantly inhibited proliferation in HepG2 cells, but also significantly suppressed the cell proliferation and self-renewal of HCSCs (P<0.05). The effects of miR-483-5p mimics on proliferation and stemness of HepG2 cells were partially abolished by PZH.
CONCLUSIONS
miR-483-5p promotes proliferation and enhances stemness of HepG2 cells, which were attenuated by PZH, demonstrating that miR-483-5p is a potential molecular target for the treatment of HCC and provide experimental evidence to support clinical use of PZH for patients with HCC.
Humans
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MicroRNAs/metabolism*
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Cell Proliferation/drug effects*
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Liver Neoplasms/drug therapy*
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Carcinoma, Hepatocellular/drug therapy*
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Hep G2 Cells
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Neoplastic Stem Cells/metabolism*
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Drugs, Chinese Herbal/therapeutic use*
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Gene Expression Regulation, Neoplastic/drug effects*
7.Silent or low expression of bla TEM and bla SHV suggests potential for targeted proteomics in clinical detection of β-lactamase-related antimicrobial resistance.
Huige WU ; Wenting DONG ; Xinxin HU ; Chunyang XIE ; Xinyi YANG ; Congran LI ; Guoqing LI ; Yun LU ; Xuefu YOU
Journal of Pharmaceutical Analysis 2025;15(7):101220-101220
Image 1.
8.Research progress of mitophagy in asthma
Yingzhi He ; You Wang ; Xuemei Chen ; Yuwei Xie ; Dang Ao ; Chuanghong Ke ; Wen Li
Acta Universitatis Medicinalis Anhui 2025;60(4):766-771
Abstract
Asthma is a well-characterized heterogeneous disease marked by airway remodeling and chronic airway inflammation. Clinically, the treatment of asthma primarily relies on hormonal drugs. However, the long-term use of these medications can lead to significant side effects. Mitophagy is a biological process that selectively transports damaged mitochondria to lysosomes for degradation. Recent research has revealed the crosstalk between mitophagy and asthma. Accordingly, taking mitophagy as an entry point, summarizing the key molecular mechanisms and regulators of mitophagy in asthma will facilitate the development of novel intervention targets and strategies for asthmatic treatment.
9.LONP1 ameliorates liver injury and improves gluconeogenesis dysfunction in acute-on-chronic liver failure
Muchen WU ; Jing WU ; Kai LIU ; Minjie JIANG ; Fang XIE ; Xuehong YIN ; Jushan WU ; Qinghua MENG
Chinese Medical Journal 2024;137(2):190-199
Background::Acute-on-chronic liver failure (ACLF) is a severe liver disease with complex pathogenesis. Clinical hypoglycemia is common in patients with ACLF and often predicts a worse prognosis. Accumulating evidence suggests that glucose metabolic disturbance, especially gluconeogenesis dysfunction, plays a critical role in the disease progression of ACLF. Lon protease-1 (LONP1) is a novel mediator of energy and glucose metabolism. However, whether gluconeogenesis is a potential mechanism through which LONP1 modulates ACLF remains unknown.Methods::In this study, we collected liver tissues from ACLF patients, established an ACLF mouse model with carbon tetrachloride (CCl 4), lipopolysaccharide (LPS), and D-galactose (D-gal), and constructed an in vitro hypoxia and hyperammonemia-triggered hepatocyte injury model. LONP1 overexpression and knockdown adenovirus were used to assess the protective effect of LONP1 on liver injury and gluconeogenesis regulation. Liver histopathology, biochemical index, mitochondrial morphology, cell viability and apoptosis, and the expression and activity of key gluconeogenic enzymes were detected to explore the underlying protective mechanisms of LONP1 in ACLF. Results::We found that LONP1 and the expressions of gluconeogenic enzymes were downregulated in clinical ACLF liver tissues. Furthermore, LONP1 overexpression remarkably attenuated liver injury, which was characterized by improved liver histopathological lesions and decreased serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in ACLF mice. Moreover, mitochondrial morphology was improved upon overexpression of LONP1. Meanwhile, the expression and activity of the key gluconeogenic enzymes were restored by LONP1 overexpression. Similarly, the hepatoprotective effect was also observed in the hepatocyte injury model, as evidenced by improved cell viability, reduced cell apoptosis, and improved gluconeogenesis level and activity, while LONP1 knockdown worsened liver injury and gluconeogenesis disorders.Conclusion::We demonstrated that gluconeogenesis dysfunction exists in ACLF, and LONP1 could ameliorate liver injury and improve gluconeogenic dysfunction, which would provide a promising therapeutic target for patients with ACLF.
10.Effect of Ginkgo biloba extract in post-stroke depression model rats
Si-Min XIE ; You-Qiong WANG ; Miao-Miao MO ; Dong-Yi WANG ; Hai-Lan CHEN ; Bin YANG
The Chinese Journal of Clinical Pharmacology 2024;40(13):1933-1937
Objective To observe the effect of Ginkgo biloba extract(GBE)on depression like behavior in post stroke depression(PSD)model rats,and explore the mechanism of regulating Toll like receptor 4/nuclear factor-κ B(TLR4/NF-κB)pathway to inhibit neuroinflammation.Methods Rats were randomly divided into 6 groups,sham,cerebral ischemia,PSD,paroxetine,low-dose Ginkgo biloba extract(GBE-L)and high-dose Ginkgo biloba extract(GBE-H)groups,10 rats in each group.Except for the sham group,middle cerebral artery occlusion(MCAO)was performed to prepare a left focal cerebral ischemia model.Except for the sham group and cerebral ischemia group,other groups were subjected to chronic unpredictable mild stress(CUMS)to establish PSD rat model for 8 weeks.After 4 weeks of CUMS,the paroxetine group,GBE-L,and GBE-H were treated with paroxetine 5 mg·kg-1,GBE 50 mg·kg-1,and GBE 100 mg·kg-1,respectively.The sham group,cerebral ischemia group,and PSD group were treated with the same volume of 0.9%NaCl and continuously administered by gavage for 28 d.After 4 weeks and 8 weeks of CUMS,the body weight and sugar preference test were measured.Levels of serum tumor necrosis factor-α(TNF-α),interleukin-1 β(IL-1 β)and levels of norepinephrine(NE),serotonin(5-HT),and dopamine(DA)in the cerebral cortex were measured by enzyme-linked immunosorbent assay(ELISA).The mRNA levels of Tlr4,Nfkb1,and nuclear factor κ B-kinase subunit β inhibitory factor(Ikbkb)in the hippocampus of rats were detected by polymerase chain reaction.The protein levels of NF-κB,nuclear factor κB inhibitory protein α(IKBα)and phosphorylation nuclear factor κB inhibitory protein α(p-IKB)in hippocampal tissue were detected by Western blot.Results The body weights of rats in the sham group,cerebral ischemia group,PSD group,paroxetine group,GBE-L group and GBE-H group were(427.10±6.36),(403.10±7.37),(310.10±9.71),(355.00±4.03),(347.90±9.88)and(391.90±5.07)g;sugar preference rate were(93.93±1.78)%,(91.57±1.03)%,(54.72±7.34)%,(88.35±4.36)%,(63.55±12.73)%and(81.04±4.31)%;the levels of NE in the cerebral cortex were(1 951.14±52.86),(1 827.27±23.63),(1 662.12±35.92),(2 033.58±72.28),(1 887.31±33.07)and(2 175.00±42.54)pg·mL-1;the levels of 5-HT in the cerebral cortex were(237.07±8.86),(226.15±10.27),(214.51±3.46),(297.13±5.79),(274.14±7.63)and(285.34±8.72)ng·mL-1;the levels of DA in the cerebral cortex were(1 531.11±47.26),(1 209.89±58.09),(1 143.15±36.31),(1 812.67±51.28),(1 651.56±31.82)and(1 853.33±20.42)pg·mL-1.Compared with the PSD group,GBE significantly increased the body weight of rats(P<0.01)and increased the preference rate of sugar water in rats,showing the antidepressant like behavioral.GBE significantly reduced the levels of serum TNF-α,IL-1 β(all P<0.01),increased the levels of NE,5-HT,and DA in the cerebral cortex(all P<0.01),down regulate the mRNA levels of Tlr4,Nfkb1 and Ikbkb(P<0.05,P<0.01),reduced the expression of NF-κB(P<0.01),and reduced the phosphorylation of IKBα(P<0.01).Conclusion Ginkgo biloba extract can improve depression-like behavior in PSD model rats,and has antidepressant effect.Its mechanism is related to the inhibition of TLR4/NF-κB pathway,thus reducing neuroinflammation.


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