Gingival Toll‐like receptor and cytokine messenger <scp>RNA</scp> levels in equine periodontitis and oral health
Bibliographic record
Abstract
REASONS FOR PERFORMING STUDY: Equine periodontitis is a common and painful condition. However, the disease often goes unnoticed by owners and is thus a major welfare concern. The aetiopathogenesis of the condition remains poorly understood and has been investigated in few studies. The innate immune system is known to play an important role in human periodontitis, but its role in equine periodontitis has not been examined. OBJECTIVES: To quantify the messenger (m)RNA levels of Toll-like receptors (TLRs) and cytokines in gingival tissue from orally healthy horses and those affected by periodontitis. STUDY DESIGN: Observational study. METHODS: Gingival tissue samples were taken post-mortem from 13 horses with no clinical signs of oral disease and 20 horses with periodontitis. mRNA levels of TLR2, TLR4 and TLR9 and cytokines interleukin-1β (IL-1β), tumour necrosis factor-α (TNF-α), IL-4, IL-6, IL-10, IL-12, IL-17 and interferon-γ (IFN-γ) were determined using quantitative real-time PCR. The statistical significance of results was assessed using appropriate t tests. RESULTS: mRNA levels of all TLRs and cytokines were upregulated in equine periodontitis. Significant increases in mRNA levels of TLR2, TLR9, IL-4, IL-10, IL-12 (P≤0.05) and IFN-γ (P≤0.01) were observed for both unweighted and age-weighted analyses of diseased gingival tissue samples compared with healthy gingival samples. In comparisons of samples of periodontitis lesions with healthy gingival control samples from the same horse, significant increases in mRNA levels of TLR4, TLR9, IL-10, IFN-γ (P≤0.05), TLR2, IL-1β and IL-12p35 (P≤0.01) were observed. CONCLUSIONS: This study has provided an initial insight into the involvement of the immune system in equine periodontitis. Increased mRNA levels of TLR2, TLR4 and TLR9 indicate substantial microbial challenge in diseased gingival tissue. A mixed Th1/Th2/Th17 cytokine response is produced in equine periodontitis. Further studies are required to more fully characterise the role of the innate immune system in this disease.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".