Excessive corneal endothelial single-cell loss following endothelial injuries

We identified accelerated stochastic single-cell loss in the corneal endothelium following primary injuries, persisting well beyond the expected wound healing period, a phenomenon that has not been previously highlighted. This finding offers a potential explanation for the chronic endothelial cell loss following a primary injury.

Authors

Institutions

Publication Details

Journal
Taiwan Journal of Ophthalmology
Published
2025-05-30
DOI
https://doi.org/10.4103/tjo.tjo-d-24-00118
Primary Topic
Corneal surgery and disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Excessive corneal endothelial single-cell loss following endothelial injuries

Matthew Lin, Lung‐Kun Yeh, Hsin‐Yuan Tan, Kuo-Hsuan Hung et al.
Taiwan Journal of Ophthalmology
Corneal surgery and disorders
article

Excessive corneal endothelial single-cell loss following endothelial injuries

Matthew Lin, Lung‐Kun Yeh, Hsin‐Yuan Tan, Kuo-Hsuan Hung, Yuan-Kai Fu
article en

Abstract

We identified accelerated stochastic single-cell loss in the corneal endothelium following primary injuries, persisting well beyond the expected wound healing period, a phenomenon that has not been previously highlighted. This finding offers a potential explanation for the chronic endothelial cell loss following a primary injury.

Taiwan Journal of OphthalmologyVol. 15(3)
Chang Gung University (TW), Chang Gung Memorial Hospital (TW)
Openalex Percentile: Top 81%
Corneal surgery and disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.