Hyaluronan improves photoreceptor differentiation and maturation in human retinal organoids
Bibliographic record
Abstract
Human stem cell-derived organoids enable both disease modeling and serve as a source of cells for transplantation. Human retinal organoids are particularly important as a source of human photoreceptors; however, the long differentiation period required and lack of vascularization in the organoid often results in a necrotic core and death of inner retinal cells before photoreceptors are fully mature. Manipulating the in vitro environment of differentiating retinal organoids through the incorporation of extracellular matrix components could influence retinal development. We investigated the addition of hyaluronan (HA), a component of the interphotoreceptor matrix, as an additive to promote long-term organoid survival and enhance retinal maturation. HA treatment had a significant reduction in the proportion of proliferating (Ki67+) cells and increase in the proportion of photoreceptors (CRX+), suggesting that HA accelerated photoreceptor commitment in vitro. HA significantly upregulated genes specific to photoreceptor maturation and outer segment development. Interestingly, prolonged HA-treatment significantly decreased the length of the brush border layer compared to those in control retinal organoids, where the photoreceptor outer segments reside; however, HA-treated organoids also had more mature outer segments with organized discs structures, as revealed by transmission electron microscopy. The brush border layer length was inversely proportional to the molar mass and viscosity of the hyaluronan added. This is the first study to investigate the role of exogenous HA, viscosity, and polymer molar mass on photoreceptor maturation, emphasizing the importance of material properties on organoid culture. STATEMENT OF SIGNIFICANCE: Retinal organoids are a powerful tool to study retinal development in vitro, though like many other organoid systems, can be highly variable. In this work, Shoichet and colleagues investigated the use of hyaluronan (HA), a native component of the interphotoreceptor matrix, to improve photoreceptor maturation in developing human retinal organoids. HA promoted human photoreceptor differentiation leading to mature outer segments with disc formation and more uniform and healthy retinal organoids. These findings highlight the importance of adding components native to the developing retina to generate more physiologically relevant photoreceptors for cell therapy and in vitro models to drive drug discovery and uncover novel disease mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".