Glucocorticoid agonists enhance retinal stem cell self-renewal and proliferation
Bibliographic record
Abstract
BACKGROUND: Adult mammalian retinal stem cells (RSCs) readily proliferate, self-renew, and generate progeny that differentiate into all retinal cell types in vitro. RSC-derived progeny can be induced to differentiate into photoreceptors, making them a potential source for retinal cell transplant therapies. Despite their proliferative propensity in vitro, RSCs in the adult mammalian eye do not proliferate and do not have a regenerative response to injury. Thus, identifying and modulating the mechanisms that regulate RSC proliferation may enhance the capacity to produce RSC-derived progeny in vitro and enable RSC activation in vivo. METHODS: Here, we used medium-throughput screening to identify small molecules that can expand the number of RSCs and their progeny in culture. In vitro differentiation assays were used to assess the effects of synthetic glucocorticoid agonist dexamethasone on RSC-derived progenitor cell fate. Intravitreal injections of dexamethasone into adult mouse eyes were used to investigate the effects on endogenous RSCs. RESULTS: We discovered that high-affinity synthetic glucocorticoid agonists increase RSC self-renewal and increase retinal progenitor proliferation up to 6-fold without influencing their differentiation in vitro. Intravitreal injection of synthetic glucocorticoid agonist dexamethasone induced in vivo proliferation in the ciliary epithelium-the niche in which adult RSCs reside. CONCLUSIONS: Together, our results identify glucocorticoids as novel regulators of retinal stem and progenitor cell proliferation in culture and provide evidence that GCs may activate endogenous RSCs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".