ReviewInternational journal of molecular sciences2023
Establishing Functional Retina in a Dish: Progress and Promises of Induced Pluripotent Stem Cell-Based Retinal Neuron Differentiation.
Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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
7 citing papers in PubMed, 7 citations in OpenAlex.
- Human pluripotent stem cell-derived retinal ganglion cells: advances in differentiation and translational applications.Molecular medicine (Cambridge, Mass.) · 2025Review
- Magnetically guided neurite outgrowth modulated by PIEZO1 in hiPSC-derived retinal ganglion cells.Materials today. Bio · 2025Article
- Progress of iPSC-derived retinal organoids in the study of inherited retinal diseases.Orphanet journal of rare diseases · 2025Review
- Induced Pluripotent (iPSC) and Mesenchymal (MSC) Stem Cells for In Vitro Disease Modeling and Regenerative Medicine.International journal of molecular sciences · 2025Review
- Retinal Organoids: Innovative Tools for Understanding Retinal Degeneration.International journal of molecular sciences · 2025Review
- Glaucoma animal models in rabbits: State of the art and perspectives-A review.Animal models and experimental medicine · 2025Review
- Stem cell-based approaches for glaucoma treatment: a mini review.Open life sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The human eye plays a critical role in vision perception, but various retinal degenerative diseases such as retinitis pigmentosa (RP), glaucoma, and age-related macular degeneration (AMD) can lead to vision loss or blindness. Although progress has been made in understanding retinal development and in clinical research, current treatments remain inadequate for curing or reversing these degenerative conditions. Animal models have limited relevance to humans, and obtaining human eye tissue samples is challenging due to ethical and legal considerations. Consequently, researchers have turned to stem cell-based approaches, specifically induced pluripotent stem cells (iPSCs), to generate distinct retinal cell populations and develop cell replacement therapies. iPSCs offer a novel platform for studying the key stages of human retinogenesis and disease-specific mechanisms. Stem cell technology has facilitated the production of diverse retinal cell types, including retinal ganglion cells (RGCs) and photoreceptors, and the development of retinal organoids has emerged as a valuable in vitro tool for investigating retinal neuron differentiation and modeling retinal diseases. This review focuses on the protocols, culture conditions, and techniques employed in differentiating retinal neurons from iPSCs. Furthermore, it emphasizes the significance of molecular and functional validation of the differentiated cells.
Indexed as
Identifiers
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.