Evidence map›Paper›PMID 42020902›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Quantification of Drusen-Like Deposits in Human Pluripotent Stem Cell-Derived Retinal Pigment Epithelium Cells Using Confocal Microscopy.

Jenna Hall, Shane Cheung, Kalyan Shobhana, Ellie Cho, Grace E Lidgerwood, Daniel Paull, Alice Pébay

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Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

7 authors.

Jenna HallDepartment of Anatomy and Physiology, The University of Melbourne, Melbourne, VIC, Australia.
Shane CheungBiological Optical Microscopy Platform, The University of Melbourne, Melbourne, VIC, Australia.
Kalyan ShobhanaBiological Optical Microscopy Platform, The University of Melbourne, Melbourne, VIC, Australia.
Ellie ChoBiological Optical Microscopy Platform, The University of Melbourne, Melbourne, VIC, Australia.
Grace E LidgerwoodDepartment of Anatomy and Physiology, The University of Melbourne, Melbourne, VIC, Australia.
Daniel PaullThe New York Stem Cell Foundation Research Institute, New York, NY, USA.
Alice PébayDepartment of Anatomy and Physiology, The University of Melbourne, Melbourne, VIC, Australia. apebay@unimelb.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accessing pathologically relevant models of human retinal degeneration is crucial for understanding, screening, and developing accurate treatment strategies that prevent or slow progression of blinding diseases. Human pluripotent stem cells (hPSCs) are a powerful tool to investigate retinal disease, as cells from selected individuals or specific genetic background can be differentiated into cell types of interest. hPSC-derived retinal pigment epithelium (RPE) cells can produce drusen-like deposits that accumulate between the RPE and the underlying Bruch's membrane. These key pathological markers of specific retinal disorders are detectable using simple microscopy techniques. However, quantification of these deposits often requires slow, low-throughput manual counting of images. This further lends itself to issues including sampling biases while ignoring critical data parameters such as deposit volume and precise localization. To overcome these issues, we developed two methods for quantifying the presence of drusen-like deposits in vitro, using hPSC-derived RPE cultures. Both methods accurately quantify drusen-like deposit numbers, and the mid-throughput pipeline allows for quantification of drusen-like deposit volume, as well as discerns their apical or basal localization on RPE cells. The platform's ability to track changes in drusen-like deposits supports screening experimentation and personalized medicine initiatives, including for gene therapy optimization.

Indexed as

Pluripotent Stem CellsRetinal DrusenRetinal Pigment EpitheliumCell DifferentiationHumansMicroscopy, ConfocalAge-related macular degenerationAutomationCell cultureConfocal microscopyHuman Pluripotent stem cellQuantificationRetinal pigment epithelium

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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.