Gingival Crevicular Fluid, Serum Levels of Receptor Activator of Nuclear Factor‐κB Ligand, Osteoprotegerin, and Interleukin‐17 in Patients With Rheumatoid Arthritis and Osteoporosis and With Periodontal Disease
Bibliographic record
Abstract
BACKGROUND: This study is performed to evaluate gingival crevicular fluid (GCF) and serum levels of soluble receptor activator of nuclear factor-κB ligand (sRANKL), interleukin (IL)-17A, IL-17E, IL-17F, IL-17A/F, and osteoprotegerin (OPG) in women with rheumatoid arthritis (RA), osteoporosis (OPR), and those who are systemically healthy (SH), all with periodontal disease. METHODS: GCF and serum samples were obtained before any periodontal intervention from 17 women with RA, 19 with OPR, and 13 who were SH with periodontitis. Full-mouth clinical periodontal measurements were recorded. sRANKL, OPG, and IL-17 levels were determined by enzyme-linked immunosorbent assay. RESULTS: Clinical periodontal measurements were similar in the three study groups. Although the total amounts of GCF albumin, OPG, IL-17A, and IL-17A/F were similar in the study groups, there were statistically significant differences in GCF concentrations of sRANKL, OPG, IL-17A, IL-17E, IL-17F, and IL-17A/F. The sRANKL/OPG ratios were significantly higher in the RA group than in the OPR and SH groups (P <0.05). Serum sRANKL, sRANKL/OPG, and IL-17A/IL-17E ratios were significantly higher, whereas OPG concentrations were significantly lower in the RA group compared to other groups (P <0.05). Serum IL-17A concentrations were significantly higher in the RA and OPR groups than in the SH group (P <0.05). CONCLUSION: Increased inflammatory mediator levels in patients with RA, despite the long-term use of various anti-inflammatory drugs, suggest that these patients may have a propensity to overproduce these inflammatory mediators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".