Bioactive Glial-Derived Neurotrophic Factor from a Safe Injectable Collagen–Alginate Composite Gel Rescues Retinal Photoreceptors from Retinal Degeneration in Rabbits
Bibliographic record
Abstract
The management of vision-threatening retinal diseases remains challenging due to the lack of an effective drug delivery system. Encapsulated cell therapy (ECT) offers a promising approach for the continuous delivery of therapeutic agents without the need for immunosuppressants. In this context, an injectable and terminable collagen-alginate composite (CAC) ECT gel, designed with a Tet-on pro-caspase-8 system, was developed as a safe intraocular drug delivery platform for the sustained release of glial-cell-line-derived neurotrophic factor (GDNF) to treat retinal degenerative diseases. This study examined the potential clinical application of the CAC ECT gel, focusing on its safety, performance, and termination through doxycycline (Dox) administration in the eyes of healthy New Zealand White rabbits, as well as its therapeutic efficacy in rabbits with sodium-iodate (SI)-induced retinal degeneration. The findings indicated that the CAC ECT gel can be safely implanted without harming the retina or lens, displaying resistance to degradation, facilitating cell attachment, and secreting bioactive GDNF. Furthermore, the GDNF levels could be modulated by the number of implants. Moreover, Dox administration was effective in terminating gel function without causing retinal damage. Notably, rabbits with retinal degeneration treated with the gels exhibited significant functional recovery in both a-wave and b-wave amplitudes and showed remarkable efficacy in reducing photoreceptor apoptosis. Given its biocompatibility, mechanical stability, controlled drug release, terminability, and therapeutic effectiveness, our CAC ECT gel presents a promising therapeutic strategy for various retinal diseases in a clinical setting, eliminating the need for immunosuppressants.
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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".