Prevalence and Mode of Inheritance of the <i>Dal</i> Blood Group in Dogs in North America
Bibliographic record
Abstract
BACKGROUND: The Dal blood group system was identified a decade ago by the accidental sensitization of a Dal- Dalmatian with a Dal+ blood transfusion. Similar Dal-related blood incompatibilities have been suspected in other Dalmatians, Doberman Pinschers, and other breeds. OBJECTIVES: To determine the prevalence and mode of inheritance of the Dal antigen expression in dogs. ANIMALS: A total of 1130 dogs including 128 Dalmatians, 432 Doberman Pinschers, 21 Shih Tzus, and 549 dogs of other breeds including 228 blood donors were recruited from North America between 2008 and 2015. METHODS: Prospectively, dogs were blood typed for Dal applying a gel column technique using polyclonal canine anti-Dal sera. Pedigrees from 8 typed families were analyzed. RESULTS: The prevalence of the Dal+ blood type varied between 85.6 and 100% in Dalmatians and 43.3-78.6% in Doberman Pinschers depending on geographical area. Dal- dogs were identified mostly in Dalmatians (15/128; 11.7%), Doberman Pinschers (183/432; 42.4%), and Shih Tzus (12/21; 57.1%), and sporadically in mixed-breed dogs (3/122; 2.5%), Lhasa Apsos (1/6) and Bichon Frises (1/3). Only 6/245 (2.4%) blood donors were found to be Dal-, including 5 Doberman Pinschers. The mode of inheritance of the Dal+ phenotype was determined to be autosomal dominant. CONCLUSIONS AND CLINICAL IMPORTANCE: The high percentage of Dal- Doberman Pinchers, Dalmatians and Shih Tzus increases their risk of being sensitized by a blood transfusion from the common Dal+ donor. Extended Dal typing is recommended in those breeds and in dogs when blood incompatibility problems arise after initial transfusions.
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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 | 0.000 |
| 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".