Bibliographic record
Abstract
The domestic dog, Canis familiaris, has a unique population structure that lends itself to the study of hereditary diseases. Purebred dogs populations are genetically isolated and as a result are affected by more than 400 naturally occurring diseases, many of which have human counterparts. In the last 15 years, dogs have emerged as a model for the study of human hereditary diseases, fueling the development of resources including a 7.6X coverage reference genome and single nucleotide polymorphism (SNP) genotyping arrays. Congenital myasthenic syndrome (CMS) is a neuromuscular disorder of both humans and dogs in which transmission across the neuromuscular junction is compromised. Affected individuals exhibit generalized muscle weakness that is exacerbated with exercise. To date, 18 genes are known to harbor mutations causative for CMS in humans. We characterized a novel CMS in a family of Labrador Retrievers. Using whole genome SNP profiles we identified COLQ as a candidate gene. In the neuromuscular junction, ColQ acts as an anchor for acetylcholinesterase, which is responsible for terminating the signal for muscle contraction. Sequencing revealed a missense mutation in exon 14 that predicts the substitution of a threonine for an isoleucine at a conserved position. The Jack Russell Terrier (JRT) is the first dog breed in which CMS was reported in the 1970s. Immunohistochemistry revealed an acetylcholine receptor (AChR) deficiency in affected dogs. Analysis of microsatellites flanking the five AChR subunit genes indicated that haplotypes encompassing CHRNB1 and CHRNE are consistent with inheritance identical by descent. Sequencing revealed a frameshift mutation in exon 7 of CHRNE (G193RfsX272) that is homozygous in recent CMS cases, as well as those from the 1970s. Congenital idiopathic megaesophagus (ME) is another neuromuscular condition observed in both humans and dogs characterized by an enlarged esophagus. Affected dogs are unable to move food into their stomachs, resulting in regurgitation and frequent aspiration pneumonia. ME is prevalent among German Shepherd Dogs (GSDs). We employed a genome-wide association study to identify genomic regions harboring genes underlying ME. Using 19 affected and 177 unaffected GSDs, we identified an associated region on chromosome 12.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".