Transplanted Donor- or Stem Cell-Derived Cone Photoreceptors Can Both Integrate and Undergo Material Transfer in an Environment-Dependent Manner
Bibliographic record
Abstract
Human vision relies heavily upon cone photoreceptors, and their loss results in permanent visual impairment. Transplantation of healthy photoreceptors can restore visual function in models of inherited blindness, a process previously understood to arise by donor cell integration within the host retina. However, we and others recently demonstrated that donor rod photoreceptors engage in material transfer with host photoreceptors, leading to the host cells acquiring proteins otherwise expressed only by donor cells. We sought to determine whether stem cell- and donor-derived cones undergo integration and/or material transfer. We find that material transfer accounts for a significant proportion of rescued cells following cone transplantation into non-degenerative hosts. Strikingly, however, substantial numbers of cones integrated into the Nrl −/− and Prph2 rd2/rd2 , but not Nrl −/− ; RPE65 R91W/R91W , murine models of retinal degeneration. This confirms the occurrence of photoreceptor integration in certain models of retinal degeneration and demonstrates the importance of the host environment in determining transplantation outcome.
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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) | 0.001 | 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".