C/<scp>EBP</scp>β and <scp>YY</scp>1 bind and interact with Smad3 to modulate lipopolysaccharide‐induced amelotin gene transcription in mouse gingival epithelial cells
Bibliographic record
Abstract
Junctional epithelium (JE) develops from reduced enamel epithelium during tooth formation and is critical for the maintenance of healthy periodontal tissue through ensuring appropriate immune responses and the rapid turnover of gingival epithelial cells. We have previously shown a relationship between inflammatory cytokines and expression of JE‐specific genes, such as amelotin (AMTN), in gingival epithelial cells. Here, we elucidated the effects of Porphyromonas gingivalis‐derived lipopolysaccharide (PgLPS) on Amtn gene transcription and the interaction of transcription factors. To determine the molecular basis of transcriptional regulation of the Amtn gene by PgLPS, we performed real‐time PCR and carried out luciferase assays using a mouse Amtn gene promoter linked to a luciferase reporter gene in mouse gingival epithelial GE1 cells. Gel mobility shift and chromatin immunoprecipitation assays were performed to identify response elements bound to LPS‐induced transcription factors. Next, we analyzed protein levels of the LPS‐induced transcription factors and the interaction of transcription factors by western blotting and immunoprecipitation. LPS increased Amtn mRNA levels and elevated luciferase activities of constructs containing regions between −116 and −238 of the mouse Amtn gene promoter. CCAAT/enhancer‐binding protein (C/EBP) 1–, C/EBP2– and Ying Yang 1 (YY1)–nuclear protein complexes were increased by LPS treatment. Furthermore, we identified LPS‐modulated interactions with C/EBPβ, YY1 and Smad3. These results demonstrate that PgLPS regulates Amtn gene transcription via binding of C/EBPβ–Smad3 and YY1–Smad3 complexes to C/EBP1, C/EBP2 and YY1 response elements in the mouse Amtn gene promoter.
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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) | 0.001 | 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) | 0.003 | 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".