Association Between the Canine Monoamine Oxidase B (MAOB)Gene Polymorphisms and Behavior of Puppies in Open-Field Test
Bibliographic record
Abstract
Excitability, activity and exploration behavior of puppies in a novel open-field were tested in a total of 204 two-month-old German shepherd dog, labrador retriever or English springer spaniel puppies. The polymorphisms of monoamine oxidase B gene (MAOB) were detected by PCR-RFLP. Statistics analysis indicated that genotype and allele frequencies of the polymorphisms were significantly different among three breeds (P < 0.01). With GLM analysis of SAS software, association analysis was conducted between MAOB gene polymorphisms and locomotion and vocalization behavior parameters in the open-field test. The results showed that MAOB gene polymorphisms had a significant effect on walking time, squares crossed, lying time, the times of standing up against walls(P < 0.01 or P < 0.05) and were associated with the times of posture change (P=0.064). Walking time and squares crossed were higher in TT genotype puppies than those in TC and CC puppies (P < 0.05) and the times of posture change and standing up against walls were also higher than those in CC (P < 0.05). In addition, lying time in CC genotype puppies were higher than that in TT (P < 0.05). MAOB had a positive effect on walking time, lying time, squares crossed, the times of posture change, the times of standing up against walls in the three dog breeds that was highly statistically significant (P < 0.01 or P < 0.05). Our results imply that MAOB gene significantly affects the excitability, activity and exploration behavior of puppies in open-field test and TT genotype has favorable effects in these behavior traits.
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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 | 0.000 | 0.000 |
| 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".