The Saliva Proteome of Dogs: Variations Within and Between Breeds and Between Species
Bibliographic record
Abstract
Saliva is a complex multifunctional fluid that bathes the oral cavity to assist in soft and hard tissue maintenance, lubrication, buffering, defense against microbes, and initiating digestion of foods. It has been extensively characterized in humans but its protein composition in dogs remains poorly characterized, yet saliva composition could explain (patho) physiological differences between individuals, breeds and with humans. This pilot discovery study aimed to characterize canine saliva from two breeds, Labrador retrievers and Beagles, and to compare this with human saliva using quantitative mass spectrometry. The analysis demonstrated considerable inter-individual variation and difference between breeds; however these were small in comparison to the differences between species. Functional mapping suggested roles of detected proteins similar to those found in human saliva with the exception of the initiation of digestion as salivary amylase was lacking or at very low abundance in canine saliva samples. Many potential anti-microbial proteins were detected agreeing with the notion that the oral cavity is under continuous microbial challenge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".