Targeted next generation sequencing reveals genetic defects underlying inherited retinal disease in Iranian families.
Bibliographic record
Abstract
Purpose: Inherited retinal diseases (IRDs) are clinically and genetically heterogeneous showing progressive retinal cell death which results in vision loss. IRDs include a wide spectrum of disorders, such as retinitis pigmentosa (RP), Leber congenital amaurosis (LCA), cone-rod dystrophy (CRD), and Stargardt disease (STGD1). Methods: In this study, we performed targeted next-generation sequencing based on molecular inversion probes (MIPs) that allowed the sequence analysis of 108 IRD-associated genes in 50 Iranian IRD probands. Results: The sequencing and variant filtering led to the identification of putative pathogenic variants in 36 out of 50 (72%) probands. Among 36 unique variants, we identified 20 novel variants in 15 genes. Four out of 36 probands carry compound heterozygous variants, and 32 probands carry homozygous variants. Conclusions: Employing a cost-effective targeted next-generation sequencing procedure, we identified the genetic causes of different retinal disorders in the majority of Iranian families in this study.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".