ReviewTranslational stroke research2025
Animal Models of Intracranial Aneurysms: History, Advances, and Future Perspectives.
Review in Translational stroke research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Characterizing Infiltrating Macrophages in Intracranial Aneurysm with IA Animal Models and Spatial Transcriptomics.Translational stroke research · 2026Review
- MRI Visibility and MR-DSA Concordance of the Nuvascular Harbor Intrasaccular Occlusion Device: A Preclinical Study.Brain sciences · 2026Article
- Subarachnoid hemorrhage mediates human neocortical network, membrane potential, and action potential bursting via glutamate receptors.Communications biology · 2025Article
- Multifunctional nanoparticles in abdominal aortic aneurysm management: from basic research to clinical transformation.Journal of nanobiotechnology · 2025Review
- High wall shear stress-dependent podosome formation in a novel murine model of intracranial aneurysm.Frontiers in stroke · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Intracranial aneurysms (IA) are a disease process with potentially devastating outcomes, particularly when rupture occurs leading to subarachnoid hemorrhage. While some candidates exist, there is currently no established pharmacological prevention of growth and rupture. The development of prophylactic treatments is a critical area of research, and preclinical models using animals play a pivotal role. These models, which utilize various species and induction methods, each possess unique characteristics that can be leveraged depending on the specific aim of the study. A comprehensive understanding of these models, including their historical development, is crucial for appreciating the advantages and limitations of aneurysm research in animal models.We summarize the significant roles of animal models in IA research, with a particular focus on rats, mice, and large animals. We discuss the pros and cons of each model, providing insights into their unique characteristics and contributions to our understanding of IA. These models have been instrumental in elucidating the pathophysiology of IA and in the development of potential therapeutic strategies.A deep understanding of these models is essential for advancing research on preventive treatments for IA. By leveraging the unique strengths of each model and acknowledging their limitations, researchers can conduct more effective and targeted studies. This, in turn, can accelerate the development of novel therapeutic strategies, bringing us closer to the goal of establishing an effective prophylactic treatment for IA. This review aims to provide a comprehensive view of the current state of animal models in IA research.
Indexed as
Identifiers
39060663What OpenQuestion holds
Registered trials
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 OpenQuestion graph.