The genetic association study between polymorphisms in uncoupling protein 2 and uncoupling protein 3 and metabolic data in dogs
Bibliographic record
Abstract
BACKGROUND: The uncoupling proteins (UCPs) in the mitochondrial inner membrane are members of the mitochondrial anion carrier protein family that play an important role in energy homeostasis. Genetic association studies have shown that human UCP2 and UCP3 variants (SNPs and indels) are associated with obesity, insulin resistance, type 2 diabetes mellitus, and metabolic syndrome. The aim of this study was to examine the genetic association between polymorphisms in UCP2 and UCP3 and metabolic data in dogs. RESULTS: We identified 10 SNPs (9 intronic and 1 exonic) and 4 indels (intronic) in UCP2, and 13 SNPs (11 intronic and 2 exonic) and one indel (exonic) in UCP3, by DNA sequence analysis of 11 different dog breeds (n=119). An association study between these UCP2 and UCP3 variants and the biochemical parameters of glucose, total cholesterol, lactate dehydrogenase and triglyceride in Labrador Retrievers (n=50) showed that none of the UCP2 polymorphisms were significantly associated with the levels of these parameters. However, four UCP3 SNPs (intron 1) were significantly associated with total cholesterol levels. In addition, the allele frequencies of two of the four SNPs associated with higher total cholesterol levels in a breed that is susceptible to hypercholesterolemia (Shetland Sheepdogs, n=30), compared with the control breed (Shiba, n=30). CONCLUSION: The results obtained from a limited number of individuals suggest that the UCP3 gene in dogs may be associated with total cholesterol levels. The examination of larger sample sizes and further analysis will lead to increased precision of these results.
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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".