ArticleFrontiers in neurology2023
Biomarker study of symptomatic intracranial atherosclerotic stenosis in patients with acute ischemic stroke.
Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed, 2 citations in OpenAlex.
- Non-invasive assessment of glymphatic dysfunction in middle cerebral artery stenosis based on DTI-ALPS and ro-ALPS.Frontiers in neurology · 2026Article
- A model based on high-resolution magnetic resonance vessel wall imaging for predicting stroke recurrence in patients with symptomatic intracranial atherosclerosis.Quantitative imaging in medicine and surgery · 2025Article
- Baicalin Inhibits FIPV Infection In Vitro by Modulating the PI3K-AKT Pathway and Apoptosis Pathway.International journal of molecular sciences · 2024Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Acute ischemic stroke (AIS) is characterized by high rates of morbidity, disability, mortality, and recurrence, often leaving patients with varying degrees of sequelae. Symptomatic intracranial atherosclerotic stenosis (sICAS) is a significant contributor to AIS pathogenesis and recurrence. The formation and progression of sICAS are influenced by pathways such as lipid metabolism and inflammatory response. Given its high risk of clinical recurrence, timely assessment of intracranial vascular stenosis in AIS is crucial for diagnosing sICAS, treating stroke, and preventing stroke recurrence. Methods: Fourteen AIS patients were divided into stenosis and control groups based on the presence or absence of intracranial vessel stenosis. Initially, 4D Label-free proteome quantification technology was employed for mass spectrometry analysis to identify differential proteins between the groups. Subsequently, functional enrichment analysis, including GO classification, KEGG pathway, and Domain, revealed trends related to differential proteins. The STRING (v.11.5) protein interaction network database was used to identify differential protein interactions and target proteins. Finally, parallel reaction monitoring (PRM) validated the selected target proteins. Results: Mass spectrometry identified 1,096 proteins, with 991 being quantitatively comparable. Using a Conclusion: The detection of changes in these five proteins in AIS patients can aid in the diagnosis of sICAS, inform stroke treatment, and assist in preventing stroke recurrence. Moreover, it can contribute to the development of drugs for preventing AIS recurrence by integrating traditional Chinese and Western medicine.
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