Real-Time Detection of the Mutation Responsible for Progressive Rod-Cone Degeneration in Labrador Retriever Dogs Using Locked Nucleic Acid TaqMan Probes
Bibliographic record
Abstract
Progressive rod-cone degeneration (prcd) is a late onset, autosomal recessive, inherited disease in dogs caused by a G > A substitution in the PRCD locus. prcd has been reported in more than 18 breeds, including Labrador Retriever dogs. In this study, a real-time polymerase chain reaction (PCR) assay, exploiting the features of locked nucleic acid (LNA) fluorescent-labeled probes, was developed to genotype the sequence variants responsible for the disease. Two Labrador Retrievers were diagnosed with prcd by ophthalmological examination performed by a panelist of the Italian hereditary eye disease control program. The 2 dogs, as well as 8 related and 14 unrelated Labrador Retrievers, were genotyped with both direct sequencing of the disease locus and real-time LNA TaqMan PCR assay. Even though the region surrounding the mutation was predicted to be highly structured, making probe annealing difficult, the real-time PCR assay allowed researchers to correctly genotype the dogs in all cases with a sensitivity threshold of 4 ng/reaction of genomic DNA. A real-time PCR assay will allow a high-throughput analysis of a larger cohort of dogs, thereby enabling researchers to investigate the prevalence of the mutated allele in the affected breeds.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".