Plasticity of the human visual system after retinal gene therapy in patients with Leber’s congenital amaurosis
Bibliographic record
Abstract
Much of our knowledge of the mechanisms underlying plasticity in the visual cortex in response to visual impairment, vision restoration, and environmental interactions comes from animal studies. We evaluated human brain plasticity in a group of patients with Leber's congenital amaurosis (LCA), who regained vision through gene therapy. Using non-invasive multimodal neuroimaging methods, we demonstrated that reversing blindness with gene therapy promoted long-term structural plasticity in the visual pathways emanating from the treated retina of LCA patients. The data revealed improvements and normalization along the visual fibers corresponding to the site of retinal injection of the gene therapy vector carrying the therapeutic gene in the treated eye compared to the visual pathway for the untreated eye of LCA patients. After gene therapy, the primary visual pathways (for example, geniculostriate fibers) in the treated retina were similar to those of sighted control subjects, whereas the primary visual pathways of the untreated retina continued to deteriorate. Our results suggest that visual experience, enhanced by gene therapy, may be responsible for the reorganization and maturation of synaptic connectivity in the visual pathways of the treated eye in LCA patients. The interactions between the eye and the brain enabled improved and sustained long-term visual function in patients with LCA after gene therapy.
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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".