Bacterial microbiota and proinflammatory cytokines in the anal sacs of treated and untreated atopic dogs: Comparison with a healthy control group
Bibliographic record
Abstract
The pathogenesis of anal sacculitis has not been extensively investigated, although atopic dogs seem to be predisposed to the disease. The aim of this study was therefore to characterize and compare the bacterial microbiota and pro-inflammatory cytokines in the anal sacs of dogs from three groups (healthy dogs, untreated atopic dogs and atopic dogs receiving antipruritic treatment or allergen-specific immunotherapy) in order to determine whether changes could be at the origin of anal sacculitis in atopic dogs. Bacterial populations of anal sac secretions from fifteen healthy dogs, fourteen untreated and six treated atopic dogs were characterized by sequencing the V4 region of the 16S rRNA gene using Illumina technology. Proinflammatory cytokines were analyzed with the Luminex multiplex test. Community membership and structure were significantly different between the anal sacs of healthy and untreated atopic dogs (P = 0.002 and P = 0.003, respectively) and between those of untreated and treated atopic dogs (P = 0.012 and P = 0.017, respectively). However, the community structure was similar in healthy and treated atopic dogs (P = 0.332). Among the proinflammatory cytokines assessed, there was no significant difference between groups, except for interleukin 8 which was higher in the anal sacs of untreated atopic dogs compared to treated atopic dogs (P = 0.02), and tumor necrosis factor-alpha which was lower in the anal sacs of healthy dogs compared to treated atopic dogs (P = 0.04). These results reveal a dysbiosis in the anal sacs of atopic dogs, which may partially explain the predisposition of atopic dogs to develop bacterial anal sacculitis. Treatments received by atopic dogs (oclacitinib, desloratadine and allergen-specific immunotherapy) shift the microbiota of the anal sacs towards that of healthy dogs. Further studies are required to identify significant cytokines contributing to anal sacculitis in atopic dogs.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".