Nicotine-upregulated miR-30a arrests cell cycle in G1 phase by directly targeting CCNE2 in human periodontal ligament cells
Bibliographic record
Abstract
The consumption of nicotine via smoking tobacco has been reported to stimulate the occurrence and progression of periodontitis. Many studies have demonstrated that nicotine prevents the regeneration of periodontal tissues primarily by inhibiting the proliferation of human periodontal ligament (PDL) cells. However, the mechanisms underlying this process are still unclear. Therefore, we investigated whether nicotine-upregulated miR-30a inhibited the proliferation of human PDL cells by downregulating cyclin E2 (CCNE2), in vitro. Quantitative real-time PCR analysis revealed that nicotine upregulated the expression of miR-30a in human PDL cells. In addition, nicotine inhibited the proliferation of human PDL cells by inducing cell cycle arrest. To support this hypothesis, we showed that nicotine downregulated the expression of CCNE2 in human PDL cells, whereas inhibition of miR-30a restored CCNE2 expression that had been downregulated by nicotine. Furthermore, using luciferase reporter assays, we found that miR-30a directly interacts with the CCNE2 3'UTR. In conclusion, these findings indicate that nicotine-upregulated miR-30a inhibits the proliferation of human PDL cells by downregulating the expression of CCNE2.
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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) | 0.001 | 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".