The Role of SMAD4 in Human Embryonic Stem Cell Self-Renewal and Stem Cell Fate
Bibliographic record
Abstract
Transforming growth factor (TGF)-beta superfamily proteins play a key role in the regulation of human embryonic stem cells (hESCs). Those of the TGFbeta/activin/nodal branch seem to support self-renewal and pluripotency, whereas those of the bone morphogenic protein (BMP) branch induce differentiation. In contrast to this generalization, we found that hESC remained undifferentiated after knockdown of SMAD4 with inducible short hairpin RNA interference, although the knockdown inhibited TGFbeta signaling and rendered the cells nonresponsive to BMP-induced differentiation. Moreover, the rapid differentiation of hESC after pharmacological inhibition of TGFbeta/activin/nodal receptor signaling was restricted after SMAD4 knockdown. These results suggest that TGFbeta/activin/nodal signaling supports the undifferentiated phenotype of hESC by suppressing BMP activity. During long-term culture, SMAD4 knockdown cell populations became less stable and more permissive to neural induction, a situation that was rescued by re-establishment of SMAD4 expression. These results suggest that SMAD4 is not required for maintenance of the undifferentiated state of hESC, but rather to stabilize that state.
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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".