Prevalence of the Mutations Responsible for Glanzmann Thrombasthenia in Horses in Brazil
Bibliographic record
Abstract
Glanzmann’s thrombasthenia (GT) is an autosomal recessive inherited disorder characterized by changes in platelet aggregation, leading to hemorrhage and epistaxis. To date, two independent mutations have been described in horses and associated with this disorder, a point mutation (c.122G > C) and a 10-base-pair deletion (g.1456_1466del) in the Integrin subunit alpha2β gene (ITGA2B) of horses of different breeds (Quarter Horse, Thoroughbred, Oldenburg, and Peruvian Paso). ITGA2B codifies the αIIb subunit of the αIIbβ3 integrin, also termed platelet fibrinogen receptor. Horses with GT have been diagnosed in the USA, Canada, Japan, and Australia. However, there are no studies on the prevalence of GT in horses. The aim of this study is to evaluate the prevalence of the mutations responsible for GT in horses in Brazil. A total of 1053 DNA samples of clinically healthy Quarter Horse (n = 679) and Warmblood horses (n = 374) were used. DNA fragments were amplified by PCR and sequenced. The genotype of each animal was analyzed and compared to the nucleotide sequence of the ITGA2B gene found on GenBankTM. There were no carriers in the analyzed samples, that is, all animals tested were wild type. Therefore, under the conditions in which this study was carried out, it can be inferred that GT seems to be extremely rare in the population of Quarter Horses and Warmbloods in Brazil, although it is not possible to affirm that there are no horses carrying mutated alleles 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 | 0.002 |
| 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 | 0.001 |
| 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".