MMP-9 Levels in the Gingival Crevicular Fluid of Chilean Rosacea Patients
Bibliographic record
Abstract
Rosacea is a chronic inflammatory skin disease whose prevalence rates remain unknown in Chile. Laboratory benchmark testing for this disease is not useful, therefore, we aimed to evaluate the gingival crevicular fluid (GCF) levels of extracellular metalloproteinases (MMP)-2 and MMP-9 as novel rosacea biomarkers. We designed a cross-sectional study with a control group. Participants were systemically healthy adults (n = 20) and persons with rosacea (n = 18). We performed a periodontal evaluation and collected gingival crevicular fluid to measure MMP-2 and MMP-9 levels. Analysis showed mean and standard deviation of MMP-9 concentrations in the GCF for patients with rosacea was 764.52 ± 569.83 pg/mL; for healthy patients, it was 260.69 ± 170.43 pg/mL (p < 0.05). The diagnosis of rosacea was responsible for the levels of MMP-9 in the GCF (p < 0.05), as opposed to periodontitis, smoking, and age (p > 0.05). The Area under ROC for MMP-9 was 0.869 (95%, C.I: 0.719−0.956), with a sensitivity of 72.22% and specificity of 81.58% for the diagnosis of rosacea. We conclude that the quantification of MMP-9 in the GCF could be used as a biomarker of rosacea. Also, rosacea was responsible for increasing the levels of MMP-9 in the GCF independent of periodontal status.
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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) | 0.000 | 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) | 0.002 | 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".