First report of nt230(del4) mutation in the MDR1 gene in German Shepherds in Southern Brazil
Bibliographic record
Abstract
ABSTRACT: The P-glycoprotein (P-gp) is a transmembrane protein encoded by the MDR1 gene that functions as a biological barrier by extruding toxins and xenobiotics out of cells. The MDR1 gene can carry a mutation called nt230(del4), which is a deletion of four base pairs resulting in the formation of a non-functional protein that may predispose to severe toxicosis, as observed in dogs with sensitivity to ivermectin. Several breeds have been described as carriers of the mutation, including German Shepherds (GS). However, the presence of the mutant allele in this breed has not been described in Brazil. This study aimed to determine the genotypic and allelic frequency of the nt230(del4) mutation in the MDR1 gene in GS from Southern Brazil. Blood samples were collected from 79 GS in the state of Rio Grande do Sul and genotype for the MDR1 gene was performed. Seventy-eight (98.7%) dogs were dominant homozygous genotype (wild) and one (1.3%) was heterozygous. This study showed that there is a low frequency (0.6%) of the mutant allele while the frequency of the wild allele is high (99.4%) in this specific population. This is the first report of the presence of the nt230(del4) mutation in the MDR1 gene in GS in Brazil. This information is important for breeders to prevent dissemination of the mutant allele in the national breeding population and international exchange of animals for breeding; for owners and veterinarians to be aware when dispensing and administering medications for GS dogs in Brazil.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".