ArticleJournal of visualized experiments : JoVE2021
An Epithelial Abrasion Model for Studying Corneal Wound Healing.
Article in Journal of visualized experiments : JoVE, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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.
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Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Review
- V-Cornea: A computational model of corneal epithelium homeostasis, injury, and recovery.PLoS computational biology · 2025Article
- Corneal Myofibroblasts Suppress T-Cell Immunity in Corneal Transplantation.Investigative ophthalmology & visual science · 2025Article
- CALR promotes corneal epithelial cell proliferation and migration through Wnt7a.Molecular biology reports · 2025Article
- Alpha-1 antitrypsin promotes re-epithelialization by regulating inflammation and migration.Frontiers in immunology · 2025Article
- Large corneal epithelial detachment as a complication of wound burping to release aqueous humor for elevated intraocular pressure following cataract surgery.Journal of surgical case reports · 2024Article
- Regenerated Corneal Epithelium Expresses More βIII-Tubulin After Chemical Injuries Compared to Mechanical Injuries.Translational vision science & technology · 2023Article
- Role of aquaporins in corneal healing post chemical injury.Experimental eye research · 2023Review
- A Low-Fat/Sucrose Diet Rich in Complex Carbohydrates Reverses High-Fat/Sucrose Diet-Induced Corneal Dysregulation.International journal of molecular sciences · 2023Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
The cornea is critical for vision, accounting for about two-thirds of the refractive power of the eye. Crucial to the role of the cornea in vision is its transparency. However, due to its external position, the cornea is highly susceptible to a wide variety of injuries that can lead to the loss of corneal transparency and eventual blindness. Efficient corneal wound healing in response to these injuries is pivotal for maintaining corneal homeostasis and preservation of corneal transparency and refractive capabilities. In events of compromised corneal wound healing, the cornea becomes vulnerable to infections, ulcerations, and scarring. Given the fundamental importance of corneal wound healing to the preservation of corneal transparency and vision, a better understanding of the normal corneal wound healing process is a prerequisite to understanding impaired corneal wound healing associated with infection and disease. Toward this goal, murine models of corneal wounding have proven useful in furthering our understanding of the corneal wound healing mechanisms operating under normal physiological conditions. Here, a protocol for creating a central corneal epithelial abrasion in mouse using a trephine and a blunt golf club spud is described. In this model, a 2 mm diameter circular trephine, centered over the cornea, is used to demarcate the wound area. The golf club spud is used with care to debride the epithelium and create a circular wound without damaging the corneal epithelial basement membrane. The resulting inflammatory response proceeds as a well-characterized cascade of cellular and molecular events that are critical for efficient wound healing. This simple corneal wound healing model is highly reproducible and well-published and is now being used to evaluate compromised corneal wound healing in the context of disease.
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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.