Evidence map›Paper›PMID 40682461›Full record

ArticleActa ophthalmologica2026

Secretory autophagy and epithelial-to-mesenchymal transition in cadaveric AMD samples: Novel pathways in disease progression.

Iswariyaraja Sridevi Gurubaran, Ali Koskela, Hanna Heloterä, Kai Kaarniranta

Abstract read
In one paragraph

Article in Acta ophthalmologica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Iswariyaraja Sridevi GurubaranDepartment of Ophthalmology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.ORCID https://orcid.org/0000-0003-1863-9550
Ali KoskelaDepartment of Ophthalmology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.ORCID https://orcid.org/0000-0003-1194-275X
Hanna HeloteräDepartment of Ophthalmology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.
Kai KaarnirantaDepartment of Ophthalmology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.ORCID https://orcid.org/0000-0003-2600-8679

Funding

the Academy of Finland 333302the Eye and Tissue Bank Foundationthe Finnish Cultural Foundationthe Finnish Eye Foundationthe Kuopio University Hospital VTR grant 5503770the Päivikki and Sakari Sohlberg Foundationthe Sigrid Juselius Foundationthe Sokeain Ystävät ry - De Blindas Vänner sr
6 · The paper itself

Abstract

purposeTo examine the presence of secretory autophagy and epithelial-mesenchymal transition (EMT) in the macular retinal pigment epithelium (RPE) of human cadaver eyes with different forms of age-related macular degeneration (AMD).

methodsHuman cadaver macula samples representing dry and wet AMD, as well as age-matched controls, were analyzed using immunohistochemistry. Markers of secretory autophagy, EMT, and inflammation were evaluated in RPE cells.

resultsIncreased expression of proteins associated with secretory autophagy and EMT was detected in the RPE of AMD samples compared to controls. These changes were observed in both dry and wet AMD forms.

conclusionSecretory autophagy and EMT are elevated in the macular RPE of AMD-affected eyes. These observations offer novel insight into AMD progression and potential therapeutic approaches.

Indexed as

AutophagyEpithelial-Mesenchymal TransitionMacular DegenerationRetinal Pigment EpitheliumWet Macular DegenerationAgedAged, 80 and overBiomarkersCadaverDisease ProgressionFemaleHumansImmunohistochemistryMaleMiddle AgedBiomarkersagingdrusenepithelial degenerationepithelial‐mesenchymal transitionmaculasecretory autophagy

Identifiers

PMID40682461
PMCPMC12888955

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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.