Selective retinal ganglion cell loss and optic neuropathy in a humanized mouse model of familial dysautonomia
Bibliographic record
Abstract
Abstract Familial dysautonomia (FD) is an autosomal recessive neurodegenerative disease caused by a splicing mutation in the gene encoding Elongator complex protein 1 ( ELP1 , also known as IKBKAP ). This mutation results in tissue-specific skipping of exon 20 with a corresponding reduction of ELP1 protein, predominantly in the central and peripheral nervous system. Although FD patients have a complex neurological phenotype caused by continuous depletion of sensory and autonomic neurons, progressive visual decline leading to blindness is one of the most problematic aspect of the disease, as it severely affects their quality of life. To better understand the disease mechanism as well as to test the in vivo efficacy of targeted therapies for FD, we have recently generated a novel phenotypic mouse model, TgFD9; Elp1 ∆20/flox . This mouse exhibits most of the clinical features of the disease and accurately recapitulates the tissue-specific splicing defect observed in FD patients. Driven by the dire need to develop therapies targeting retinal degeneration in FD, herein, we comprehensively characterized the progression of the retinal phenotype in this mouse, and we demonstrated that it is possible to correct ELP1 splicing defect in the retina using the splicing modulator compound (SMC) BPN-15477.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".