Evidence map›Paper›PMID 39444013›Full record

ArticleCell & bioscience2024

Revisiting Virchow's triad: exploring the cellular and molecular alterations in cerebral venous congestion.

Chen Zhou, Yifan Zhou, Wei Ma, Lu Liu, Weiyue Zhang, Hui Li, Chuanjie Wu, Jian Chen, Di Wu, Huimin Jiang and 1 more

Abstract read
In one paragraph

Article in Cell & bioscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Chen ZhouBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Capital Medical University, Beijing, 100069, China.
Yifan ZhouBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Capital Medical University, Beijing, 100069, China.
Wei MaBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Capital Medical University, Beijing, 100069, China.
Lu LiuDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Weiyue ZhangBeijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China.
Hui LiDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Chuanjie WuDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Jian ChenDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Di WuDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China. seadi-wu@163.com.
Huimin JiangBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Capital Medical University, Beijing, 100069, China. jianghuimin06@163.com.
Xunming JiBeijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Capital Medical University, Beijing, 100069, China. jixm@ccmu.edu.cn.ORCID http://orcid.org/0000-0002-0527-2852

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCerebral venous thrombosis (CVT) is a rare but serious condition that can lead to significant morbidity and mortality. Virchow's triad elucidates the role of blood hypercoagulability, blood flow dynamics, and endothelial damage in the pathogenesis of CVT. Cerebral venous congestion (CVC) increases the risk of cerebral venous sinus thrombosis and can lead to recurrent episodes and residual symptoms. However, the precise mechanism by which blood congestion leads to thrombosis remains unclear. Our objective was to investigate the cellular and molecular alterations linked to CVC through analysis of the pathological morphology of venous sinus endothelial cells and transcriptomic profiling.

resultsThis study demonstrated a remarkable correlation between CVC and the phenotypic transformation of endothelial cells from an anticoagulant to a procoagulant state. The findings revealed that cerebral venous stasis results in tortuous dilatation of the venous sinuses, with slow blood flow and elevated pressure in the sinuses and damaged endothelial cells of the retroglenoid and internal jugular vein ligation (JVL) rat model. Mechanistically, analysis of transcriptomic results of cerebral venous sinus endothelial cells showed significant activation of platelet activation, complement and coagulation cascades pathway in the JVL rats. Furthermore, the expression of von Willebrand factor (vWF) and coagulation factor VIII (F8) in the complement and coagulation cascades and Fgg and F2 in the platelet activation was increased in the cerebral venous sinuses of JVL rats than in sham rats, suggesting that endothelial cell injury in the venous sinus induced by CVC has a prothrombotic effect. In addition, endothelial cell damage accelerates coagulation and promotes platelet activation. Significantly, the concentrations of vWF, F2 and F8 in venous sinus blood of patients with internal jugular vein stenosis were higher than in their peripheral blood.

conclusionCollectively, our data suggest that CVC can induce endothelial cell damage, which then exhibits a procoagulant phenotype and ultimately increases the risk of CVT. This research contributes to our understanding of the pathophysiology of CVC associated with procoagulant factors and reexamines the components of Virchow's triad in the context of CVC.

Indexed as

Cerebral venous congestionCVTEndothelial injuryStrokeVirchow’s triad

Identifiers

PMID39444013
PMCPMC11515517

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.