Retinal Blinding Disorders and Gene Therapy - Molecular and Clinical Aspects
Bibliographic record
Abstract
Retinal blinding disorders together have a prevalence of 1 in 2000 humans world wide and represent a significant impact on the quality of life as well as the possibility to attain personal achievements. Mutations in genes that are expressed either in RPE cells, photoreceptors or bipolar cells can cause varying forms of degenerative or stationary retinal disorders, as the presence of the encoded proteins is crucial for normal function, maintenance and synaptic interaction. The degree of damage caused by different mutations depends upon the type of mutation within the gene, resulting in either total absence or the presence of a non-functional or potentially toxic protein. Potential treatment strategies require the identification of the cell type, in which the mutated gene is expressed for later targeting by viral vector mediated gene transfer. In the first part of this review, the authors present different cellular pathways that take place either in the RPE, photoreceptors, or bipolar cells. Furthermore, the authors demonstrate why genetic and molecular testing methods, which clearly identify the disease causing mutations, are crucial for attaining the correct diagnosis in order to indentify patients suitable to be treated by upcoming new therapeutic methods. In the second part, a short clinical classification of the most important forms of retinal blinding disorders is given, together with clinical aspects concerning the problems that arise when facing low residual visual perception and the enormous heterogeneity of symptoms within these disorders. Keywords: Retina, LCA, EOSRD, retinitis pigmentosa, gene therapy, retinal degeneration, RPE, photoreceptors, Retinal blinding disorders, retinal pigment epithelium, apoptosis, adeno-associated viral (AAV) vec-tors, Leber congenital amaurosis, retinal dystrophy, RPE65 deficiency, phagocytosis, rhodopsin, congenital stationary night blindness, fundus albipunctatus, Bothnia dystrophy, Newfoundland rod-cone dys-trophy, MERTK, choroideremia, visual cycle, TYR, pink eye dilution gene, pigment epithelial growth factor, BEST1 gene, GNAT, RHOK, Bipolar Cell Signal-ing, Usher Syndrome, Bardet Biedl Syndrome, Missense Mutations, Null Mutations, Poly-morphisms, rod-cone dystrophies, cone-rod dystrophies, cone dystro-phies, uniparental isodisomy, non-Mendelian inheritance, Fundus autofluorescence, optical coherence tomography, electrooculo-gram, vitel-liforme macular dystrophy, autosomal dominant Vitreoretinochoroidopathy, auto-somal recessive Bestrophinopathy, funduscopy, fundus flavimaculatus, Stationary Cone Diseases/Achromatopsia, Stationary Rod Diseases/CSNB, Retinoschisis, Albinism
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".