Bibliographic record
Abstract
Activation of transforming growth factor-beta (TGF-beta) and activin receptors leads to phosphorylation of Sma- and Mad-related protein 2 (Smad2) and Smad3, which function as transcription factors to regulate gene expression. Smad7 is a regulatory protein which is able to inhibit TGF-beta and activin signalling in a negative-feedback loop, mediated by a direct regulation by Smad3 and Smad4 via a Smad-binding element (SBE) in the Smad7 promoter. Interestingly, we found that the Smad7 promoter was also regulated by nuclear factor kappaB (NF-kappaB), a transcription factor which plays an important role in inflammation and the immune response. Expression of NF-kappaB p65 subunit was able to inhibit the Smad7 promoter activity, and this inhibition could be reversed by co-expression of IkappaB, an inhibitor of NF-kappaB. In addition, the inhibitory activity of p65 was observed in a minimal promoter that contained only the Smad7 SBE and a TATA box, without any consensus NF-kappaB binding site. This inhibitory effect appeared to be common to other TGF-beta- and activin-responsive promoters, since p65 also inhibited the forkhead-activin-signal-transducer-2-mediated activation of a Xenopus Mix.2 promoter, as well as the Smad3-mediated activation of 3TP-lux which contains PMA-responsive elements and a plasminogen-activator-inhibitor-1 promoter. Activation of endogenous NF-kappaB by tumour necrosis factor-alpha (TNF-alpha) was also able to inhibit the Smad7 promoter in human embryonic kidney 293 cells. In human hepatoma HepG2 cells, TNF-alpha was able to inhibit TGF-beta- and activin-mediated transcriptional activation. Furthermore, overexpression of the transcription co-activator p300 could abrogate the inhibitory effect of NF-kappaB on the Smad7 promoter. Taken together, these data have indicated a novel mode of crosstalk between the Smad and the NF-kappaB signalling cascades at the transcriptional level by competing for a limiting pool of transcription co-activators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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; both teacher heads agree on what is shown here.
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".