Proinflammatory cytokines induce amelotin transcription in human gingival fibroblasts
Bibliographic record
Abstract
Amelotin (AMTN) is a secreted protein transcribed predominantly during the maturation stage of enamel formation and localized in the junctional epithelium. We investigated differences in the levels of AMTN gene expression between non-inflamed gingiva and inflamed gingiva from patients with chronic periodontitis. Total RNAs were isolated from these tissues and their gene expression profiles were monitored by DNA microarray. The observed induction of AMTN mRNA in inflamed gingiva and cultured human gingival fibroblasts (HGF) was confirmed by real-time PCR. Transient transfection assays were performed using chimeric constructs of mouse AMTN gene promoter fragments linked to a luciferase reporter gene. Immunohistochemical localization of AMTN in inflamed and non-inflamed gingiva was assessed by immunohistochemistry. Among many differentially expressed genes, the level of AMTN mRNA was significantly increased in inflamed gingiva. Treatment of HGF with interleukin-1β (IL-1β), IL-6 and tumor necrosis factor-α (TNF-α) induced the expression of AMTN mRNA, and increased the luciferase activities of the AMTN promoter constructs. AMTN protein was detected in inflamed gingival connective tissue and junctional epithelium. These findings demonstrate that proinflammatory cytokines induce AMTN gene expression in human gingival fibroblasts and suggest a role for AMTN in gingival inflammation.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".