Evaluation of the impact of dental prophylaxis on the oral microbiota of dogs
Bibliographic record
Abstract
Periodontal disease is one of the most commonly diagnosed oral diseases in dogs and can result from undisturbed dental plaque. Dental prophylaxis is a routinely practiced veterinary procedure, but its effects on both the plaque and oral microbiota is not fully understood. The objectives of this study were to evaluate the impact of dental prophylaxis on the composition of the supragingival plaque and composite oral microbiota in clinically healthy dogs and to determine if composite sampling could be used in lieu of sampling the plaque microbiota directly. Thirty dogs received a dental prophylaxis. Supragingival plaque and composite oral samples were collected just prior to, and one week after dental prophylaxis. A subsample of 10 dogs was followed, and additional samples were collected two and five weeks post-prophylaxis. The V4 region of the 16S rRNA gene was used for Illumina MiSeq next-generation sequencing. Results demonstrate that decreases in Treponema as well as increases in Moraxella and Neisseria distinguished the plaque pre- and one week post-prophylaxis timepoints (all P<0.05). Within the oral microbiota, the initially dominant Psychrobacter (20% relative abundance) disappeared one week later (P<0.0001), and Pseudomonas became the dominant taxon one week after treatment (80% relative abundance, P<0.0001). A rapid transition back towards the pre-dental prophylaxis microbiota by five weeks post-treatment was seen for both niches, suggesting the canine oral microbiota is resilient. Direct comparison of the two environments yielded striking differences, with complete separation of groups. Firmicutes (40%) and Spirochaetes (22%) predominated in the plaque while Proteobacteria (58%) was predominant in the oral microbiota. Greater richness was also seen in the plaque microbiota. This study reveals that prophylaxis had a profound impact on both the plaque and oral microbiota, and the longitudinal results help elucidate the pathophysiology of periodontal disease. The results suggest that oral swabs are a poor proxy for plaque samples and highlight the need to study specific oral niches.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".