Induction of palate epithelial mesenchymal transition by transforming growth factor β3 signaling
Bibliographic record
Abstract
Transforming growth factor (TGFβ)3 is essential for palate development, particularly during the late phase of palatogenesis when the disintegration of the palatal medial edge seam (MES) occurs resulting in mesenchymal confluence. The MES is composed of medial-edge epithelium (MEE) of opposite palatal shelves; its complete disintegration is essential for mediating correct craniofacial morphogenesis. This phenomenon is initiated by TGFβ3 upon adherence of opposing palatal shelves, and subsequently epithelial-mesenchymal transition (EMT) instigates the loss of E-Cadherin, causing the MES to break into small epithelial islands forming confluent palatal mesenchyme; however, apoptosis and cell migration or in combination of all are other established mechanisms of seam disintegration. To investigate the molecular mechanisms that cause this E-Cadherin loss, we isolated and cultured murine embryonic primary MES cells from adhered palates and employed several biological approaches to explore the mechanism by which TGFβ3 facilitates palatal seam disintegration. Here, we demonstrate that TGFβ3 signals by activating both Smad-dependent and Smad-independent pathways. However, activation of the two most common EMT related transcription factors, Snail and SIP, was facilitated by Smad-independent pathways, contrary to the commonly accepted Smad-dependent pathway. Finally, we provide the first evidence that TGFβ3-activated Snail and SIP1, combined with Smad4, bind to the E-Cadherin promoter to repress its transcription in response to TGFβ3 signaling. These results suggest that TGFβ3 uses multiple pathways to activate Snail and SIP1 and these transcription factors repress the cell-cell adhesion protein, E-Cadherin, to induce palatal epithelial seam EMT. Manipulation and intervention of the pathways stimulated by TGFβ3 during palate development may have a significant therapeutic potential.
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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 | 0.001 |
| 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".