5Z-7-Oxozeanol Inhibits the Effects of TGFβ1 on Human Gingival Fibroblasts
Bibliographic record
Abstract
Transforming growth factor (TGF)β acts on fibroblasts to promote the production and remodeling of extracellular matrix (ECM). In adult humans, excessive action of TGFβ is associated with fibrotic disease and fibroproliferative conditions, including gingival hyperplasia. Understanding how the TGFβ1 signals in fibroblasts is therefore likely to result in valuable insights into the fundamental mechanisms underlying fibroproliferative disorders. Previously, we used the TAK1 inhibitor (5Z)-7-Oxozeaenol to show that, in dermal fibroblasts, the non-canonical TAK1 pathway mediates the ability of TGFβ1 to induce genes promoting tissue remodeling and repair. However, the extent to which TAK1 mediates fibroproliferative responses in fibroblasts in response to TGFβ1 remains unclear. Herein, we show that, in gingival fibroblasts, (5Z)-7-Oxozeaenol blocks the ability of TGFβ1 to induce expression of the pro-fibrotic mediator CCN2 (connective tissue growth factor, CTGF) and type I collagen protein. Moreover, genome-wide expression profiling revealed that, in gingival fibroblasts, (5Z)-7-Oxozeaenol reduces the ability of TGFβ1 to induce mRNA expression of essentially all TGFβ1-responsive genes (139/147), including those involved with a hyperproliferative response. Results from microarray analysis were confirmed using real time polymerase chain reaction analysis and a functional cell proliferation assay. Our results are consistent with the hypothesis that TAK1 inhibitors might be useful in treating fibroproliferative disorders, including that in the oral cavity.
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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 | 0.000 |
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".