Cyclosporine‐A inhibits MMP‐2 and ‐9 activities in the presence of <i>Porphyromonas gingivalis</i> lipopolysaccharide: an experiment in human gingival fibroblast and U937 macrophage co‐culture
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Studies have shown that bacterial plaque and the associated gingival inflammation increase the severity of gingival overgrowth induced by cyclosporine-A (CsA). This in vitro study aimed to evaluate the effect of CsA on the activities of MMPs from the co-culture of human gingival fibroblasts and U937 macrophages in the presence or absence of Porphyromonas gingivalis lipopolysaccharide (LPS). MATERIAL AND METHODS: Activities of pro-MMP-2, MMP-2 and pro-MMP-9 in the supernatants of independent cultures and co-cultures were examined by zymography. RT-PCR was selected to evaluate the expression of mRNA for membrane type-1 (MT1) MMP in the co-cultures. RESULTS: Activities of MMPs in the co-cultures were significantly greater when compared with any of the independent cultures. Lipopolysaccharide significantly increased the MMP activities in a dose-dependent manner in the co-cultures, whereas CsA inhibited these activities. In the presence of both CsA and LPS, the MMP activities inhibited by CsA could still be observed in the co-cultures. In the individual cultures, in contrast, the CsA-inhibited MMP activities, in the presence of LPS, were minimally detected. The mRNA expression of MT1-MMP was significantly enhanced after LPS treatment; however, this enhancement was inhibited by CsA. CONCLUSION: This study demonstrated that, in co-cultures of human gingival fibroblasts and U937 macrophages, CsA could inhibit MMP activities in the presence of P. gingivalis LPS. It might be part of the underlying reason for the persistent overgrowth of gingiva seen when bacterial plaque and local inflammation are present during CsA therapy.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".