A Reinterpretation of Cell Transplantation: GFP Transfer From Donor to Host Photoreceptors
Bibliographic record
Abstract
Abstract The utilization of fluorescent reporter transgenes to discriminate donor versus host cells has been a mainstay of photoreceptor transplantation research, the assumption being that the presence of reporter+ cells in outer nuclear layer (ONL) of transplant recipients represents the integration of donor photoreceptors. We previously reported that GFP+ cells in the ONL of cone-GFP transplanted retinas exhibited rod-like characteristics, raising the possibility that GFP signal in recipient tissue may not be a consequence of donor cell integration. To investigate the basis for this mismatch, we performed a series of transplantations using multiple transgenic donor and recipient models, and assessed cell identity using nuclear architecture, immunocytochemistry, and DNA prelabeling. Our results indicate that GFP+ cells in the ONL fail to exhibit hallmark elements of donor cells, including nuclear hetero/euchromatin architecture. Furthermore, GFP signal does not appear to be a consequence of classic donor/host cell fusion or transfating post-transplant, but is most likely due to material exchange between donor and host photoreceptors. This transfer can be mediated by rods and cones, is bidirectional between donor and host cells, requires viable photoreceptors, occurs preferentially at sites of outer limiting membrane disruption and can be detected in second-order retinal neurons and Müller glia. Collectively, these data warrant re-evaluation of the use of lineage tracing fluorescent reporters in transplantation studies involving the retina and other CNS tissues. Furthermore, the reinterpretation of previous functional rescue data, based on material exchange, rather than cell integration, may offer a novel approach to vision rescue.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".