Occurrence of MDR1 1-delta mutation in herding dog breeds in Portugal
Bibliographic record
Abstract
The impact of drug transporters in veterinary medicine has been recognized in recent years. One of the most well-characterized is the product of the MDR1 gene, P-gp. A 4-bp deletion in the MDR1 gene known since 2001 has been described to affect herding dog breeds. Since many used drugs in veterinary medicine are substrates for P-gp, including the macrocyclic lactones, such as avermectins, this 4-bp deletion causes a pathological condition known as “ivermectin toxicosis.” For this reason, it is important to determine the animal status concerning this mutation. In Portugal, the information of the occurrence of this mutation in our breeds is limited. The aim of the present study was to determine the occurrence of this mutation and evaluate its association with Portuguese and non-Portuguese dog breeds in Portugal. To achieve this, a total of 105 animals were studied for the presence of the MDR1 4-bp deletion, 23 of which were from Barbado da Terceira, 10 from Cão da Serra d'Aires, 55 belonging to breeds known to carry the mutation (Australian Shepperd, Border Collie and others) and 17 to other breeds (Labrador Retriever, Jack Russel, and others). Despite the small sample size, we observed the presence of the MDR1 1—delta mutation in previously described breeds and identified this mutation in Barbado da Terceira breed for the first time.
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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 | 0.001 |
| 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".