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Antagonism of Protease-Activated Receptor 4 Protects Against Traumatic Brain Injury by Suppressing Neuroinflammation via Inhibition of Tab2/NF-κB Signaling 被引量:5
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作者 Jianing Luo Xun Wu +11 位作者 Haixiao Liu wenxing cui Wei Guo Kang Guo Hao Guo Kai Tao Fei Li Yingwu Shi Dayun Feng Hao Yan Guodong Gao Yan Qu 《Neuroscience Bulletin》 SCIE CAS CSCD 2021年第2期242-254,共13页
Traumatic brain injury(TBI)triggers the activation of the endogenous coagulation mechanism,and a large amount of thrombin is released to curb uncontrollable bleeding through thrombin receptors,also known as protease-a... Traumatic brain injury(TBI)triggers the activation of the endogenous coagulation mechanism,and a large amount of thrombin is released to curb uncontrollable bleeding through thrombin receptors,also known as protease-activated receptors(PARs).However,thrombin is one of the most critical factors in secondary brain injury.Thus,the PARs may be effective targets against hemorrhagic brain injury.Since the PAR1 antagonist has an increased bleeding risk in clinical practice,PAR4 blockade has been suggested as a more promising treatment.Here,we explored the expression pattern of PAR4 in the brain of mice after TBI,and explored the effect and possible mechanism of BMS-986120(BMS),a novel selective and reversible PAR4 antagonist on secondary brain injury.Treatment with BMS protected against TBI in mice.mRNA-seq analysis,Western blot,and qRT-PCR verification in vitro showed that BMS significantly inhibited thrombin-induced inflammation in astrocytes,and suggested that the Tab2/ERK/NF-κB signaling pathway plays a key role in this process.Our findings provide reliable evidence that blocking PAR4 is a safe and effective intervention for TBI,and suggest that BMS has a potential clinical application in the management of TBI. 展开更多
关键词 Protease-activated receptors BMS Traumatic brain injury Inflammation ASTROCYTE Tab2
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Acrolein Induces Systemic Coagulopathy via Autophagy-dependent Secretion of von Willebrand Factor in Mice after Traumatic Brain Injury 被引量:3
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作者 wenxing cui Xun Wu +8 位作者 Dayun Feng Jianing Luo Yingwu Shi Wei Guo Haixiao Liu Qiang Wang Liang Wang Shunnan Ge Yan Qu 《Neuroscience Bulletin》 SCIE CAS CSCD 2021年第8期1160-1175,共16页
Traumatic brain injury(TBI)-induced coagulopathy has increasingly been recognized as a significant risk factor for poor outcomes,but the pathogenesis remains poorly understood.In this study,we aimed to investigate the... Traumatic brain injury(TBI)-induced coagulopathy has increasingly been recognized as a significant risk factor for poor outcomes,but the pathogenesis remains poorly understood.In this study,we aimed to investigate the causal role of acrolein,a typical lipid peroxidation product,in TBI-induced coagulopathy,and further explore the underlying molecular mechanisms.We found that the level of plasma acrolein in TBI patients suffering from coagulopathy was higher than that in those without coagulopathy.Using a controlled cortical impact mouse model,we demonstrated that the acrolein scavenger phenelzine prevented TBI-induced coagulopathy and recombinant ADAMTS-13 prevented acrolein-induced coagulopathy by cleaving von Willebrand factor(VWF).Our results showed that acrolein may contribute to an early hypercoagulable state after TBI by regulating VWF secretion.mRNA sequencing(mRNA-seq)and transcriptome analysis indicated that acrolein over-activated autophagy,and subsequent experiments revealed that acrolein activated autophagy partly by regulating the Akt/mTOR pathway.In addition,we demonstrated that acrolein was produced in the perilesional cortex,affected endothelial cell integrity,and disrupted the blood-brain barrier.In conclusion,in this study we uncovered a novel pro-coagulant effect of acrolein that may contribute to TBI-induced coagulopathy and vascular leakage,providing an alternative therapeutic target. 展开更多
关键词 Traumatic brain injury COAGULOPATHY AUTOPHAGY ACROLEIN Von Willebrand factor
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Acrolein Aggravates Secondary Brain Injury After Intracerebral Hemorrhage Through Drp1-Mediated Mitochondrial Oxidative Damage in Mice 被引量:3
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作者 Xun Wu wenxing cui +8 位作者 Wei Guo Haixiao Liu Jianing Luo Lei Zhao Hao Guo Longlong Zheng Hao Bai Dayun Feng Yan Qu 《Neuroscience Bulletin》 SCIE CAS CSCD 2020年第10期1158-1170,共13页
Clinical advances in the treatment of intracranial hemorrhage(ICH)are restricted by the incomplete understanding of the molecular mechanisms contributing to secondary brain injury.Acrolein is a highly active unsaturat... Clinical advances in the treatment of intracranial hemorrhage(ICH)are restricted by the incomplete understanding of the molecular mechanisms contributing to secondary brain injury.Acrolein is a highly active unsaturated aldehyde which has been implicated in many nervous system diseases.Our results indicated a significant increase in the level of acrolein after ICH in mouse brain.In primary neurons,acrolein induced an increase in mitochondrial fragmentation,loss of mitochondrial membrane potential,generation of reactive oxidative species,and release of mitochondrial cytochrome c.Mechanistically,acrolein facilitated the translocation of dynaminrelated protein 1(Drpl)from the cytoplasm onto the mitochondrial membrane and led to excessive mitochondrial fission.Further studies found that treatment with hydralazine(an acrolein scavenger)significantly reversed Drpl translocation and the morphological damage of mitochondria after ICH.In parallel,the neural apoptosis,brain edema,and neurological functional deficits induced by ICH were also remarkably alleviated.In conclusion,our results identify acrolein as an important contributor to the secondary brain injury following ICH.Meanwhile,we uncovered a novel mechanism by which Drpl-mediated mitochondrial oxidative damage is involved in acroleininduced brain injury. 展开更多
关键词 Intracerebral hemorrhage Secondary brain injury ACROLEIN Drp1 Mitochondrial oxidative damage
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Death after discharge:prognostic model of 1-year mortality in traumatic brain injury patients undergoing decompressive craniectomy
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作者 wenxing cui Shunnan Ge +7 位作者 Yingwu Shi Xun Wu Jianing Luo Haixiao Lui Gang Zhu Hao Guo Dayun Feng Yan Qu 《Chinese Neurosurgical Journal》 CSCD 2022年第1期36-44,共9页
Background:Despite advances in decompressive craniectomy(DC)for the treatment of traumatic brain injury(TBI),these patients are at risk of having a poor long-term prognosis.The aim of this study was to predict 1-year ... Background:Despite advances in decompressive craniectomy(DC)for the treatment of traumatic brain injury(TBI),these patients are at risk of having a poor long-term prognosis.The aim of this study was to predict 1-year mortality in TBI patients undergoing DC using logistic regression and random tree models.Methods:This was a retrospective analysis of TBI patients undergoing DC from January 1,2015,to April 25,2019.Patient demographic characteristics,biochemical tests,and intraoperative factors were collected.One-year mortality prognostic models were developed using multivariate logistic regression and random tree algorithms.The overall accuracy,sensitivity,specificity,and area under the receiver operating characteristic curves(AUCs)were used to evaluate model performance.Results:Of the 230 patients,70(30.4%)died within 1 year.Older age(OR,1.066;95%CI,1.045-1.087;P<0.001),higher Glasgow Coma Score(GCS)(OR,0.737;95%CI,0.660-0.824;P<0.001),higherD-dimer(OR,1.005;95%CI,1.001-1.009;P=0.015),coagulopathy(OR,2.965;95%CI,1.808-4.864;P<0.001),hypotension(OR,3.862;95%CI,2.176-6.855;P<0.001),and completely effaced basal cisterns(OR,3.766;95%CI,2.255-6.290;P<0.001)were independent predictors of 1-year mortality.Random forest demonstrated better performance for 1-year mortality prediction,which achieved an overall accuracy of 0.810,sensitivity of 0.833,specificity of 0.800,and AUC of 0.830 on the testing data compared to the logistic regression model.Conclusions:The random forest model showed relatively good predictive performance for 1-year mortality in TBI patients undergoing DC.Further external tests are required to verify our prognostic model. 展开更多
关键词 Decompressive craniectomy Traumatic brain injury One-year mortality Prognostic model Random forest
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