ReviewFrontiers in immunology2021
Quantitative Assessment of Experimental Ocular Inflammatory Disease.
Review in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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
8 citing papers in PubMed, 13 citations in OpenAlex.
- Qualitative and Quantitative Assessment of Vitreous Inflammation in Uveitis: Current Limitations and Emerging Diagnostic Approaches.Diagnostics (Basel, Switzerland) · 2026Review
- Nanomaterial-enabled delivery of plant-derived bioactive metabolites for diabetic retinopathy: from evidence appraisal to preclinical translation.Frontiers in pharmacology · 2026Review
- A pathogenic CD4 T cell phenotype in experimental uveitis shares common features with other immune mediated inflammatory diseases.Discovery immunology · 2026Article
- Comparative models of uveitis.Eye (London, England) · 2025Review
- Comparative Efficacy of Interleukin-7 and -15 Blockade in Alleviating Experimental Chronic Uveitis and Suppressing Pathogenic Memory CD4+ T Cells.Investigative ophthalmology & visual science · 2025Article
- Comprehensive Grading System for Experimental Autoimmune Uveitis in Mice.Biomedicines · 2023Article
- A machine learning framework for the quantification of experimental uveitis in murine OCT.Biomedical optics express · 2023Article
- Long-lived autoreactive memory CD4FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ocular inflammation imposes a high medical burden on patients and substantial costs on the health-care systems that mange these often chronic and debilitating diseases. Many clinical phenotypes are recognized and classifying the severity of inflammation in an eye with uveitis is an ongoing challenge. With the widespread application of optical coherence tomography in the clinic has come the impetus for more robust methods to compare disease between different patients and different treatment centers. Models can recapitulate many of the features seen in the clinic, but until recently the quality of imaging available has lagged that applied in humans. In the model experimental autoimmune uveitis (EAU), we highlight three linked clinical states that produce retinal vulnerability to inflammation, all different from healthy tissue, but distinct from each other. Deploying longitudinal, multimodal imaging approaches can be coupled to analysis in the tissue of changes in architecture, cell content and function. This can enrich our understanding of pathology, increase the sensitivity with which the impacts of therapeutic interventions are assessed and address questions of tissue regeneration and repair. Modern image processing, including the application of artificial intelligence, in the context of such models of disease can lay a foundation for new approaches to monitoring tissue health.
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What 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.