Preliminary insights into β-Amyloid, phospho-tau and inbreeding in Labrador Retriever dogs
Bibliographic record
Abstract
Serum concentrations of β-amyloid peptides (Aβ40 and Aβ42) and phosphorylated tau (p-tau) are emerging as potential biomarkers of age-related neurodegenerative processes in dogs, particularly in relation to ca- nine cognitive dysfunction. At the same time, the genetic background, especially inbreeding, may influence aging trajectories and brain pathology. This paper reports preliminary observations on the relationship between plasma Aβ40, Aβ42, and p-tau levels and the inbreeding coefficient in 24 healthy Labrador Retriever dogs. Blood samples were collected and analyzed using ELISA kits specific for canine Aβ and phosphorylated tau, and inbreeding coeffi- cients were calculated based on pedigree data. In addition, the Canine Dementia Scale (CADES) was administered. Although the small sample size limits the strength of statistical inference, initial findings suggest potential associ- ations between age, biomarker concentrations, and sex. However, the inbreeding coefficient was too low to detect possible correlations with biomarker levels. These results primarily provide preliminary insight into the effects of neurobiological aging in dogs, while the contribution of genetic factors remains to be clarified in larger cohorts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".