Modeling of Photoreceptor Donor-Host Interaction Following Transplantation Reveals a Role for Crx, Müller Glia, and Rho/ROCK Signaling in Neurite Outgrowth
Bibliographic record
Abstract
Abstract The goal of photoreceptor transplantation is to establish functional synaptic connectivity between donor cells and second-order neurons in the host retina. There is, however, limited evidence of donor-host photoreceptor connectivity post-transplant. In this report, we investigated the effect of the host retinal environment on donor photoreceptor neurite outgrowth in vivo and identified a neurite outgrowth-promoting effect of host Crx(−/−) retinas following transplantation of purified photoreceptors expressing green fluorescent protein (GFP). To investigate the noncell autonomous factors that influence donor cell neurite outgrowth in vitro, we established a donor-host coculture system using postnatal retinal aggregates. Retinal cell aggregation is sensitive to several factors, including plate coating substrate, cell density, and the presence of Müller glia. Donor photoreceptors exhibit motility in aggregate cultures and can engraft into established aggregate structures. The neurite outgrowth-promoting phenotype observed in Crx(−/−) recipients in vivo is recapitulated in donor-host aggregate cocultures, demonstrating the utility of this surrogate in vitro approach. The removal of Müller glia from host aggregates reduced donor cell neurite outgrowth, identifying a role for this cell type in donor-host signaling. Although disruption of chondroitin sulfate proteoglycans in aggregates had no effect on the neurite outgrowth of donor photoreceptors, disruption of Rho/ROCK signaling enhanced outgrowth. Collectively, these data show a novel role of Crx, Müller glia, and Rho/ROCK signaling in controlling neurite outgrowth and provide an accessible in vitro model that can be used to screen for factors that regulate donor-host connectivity. Stem Cells 2019;37:529–541
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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".