Palatal adhesion is dependent on Src family kinases and p38MAPK
Bibliographic record
Abstract
During secondary palate development, palatal shelves adhere to each other in the midline to form a midline epithelial seam leading to palatal closure. Cell-cell and cell-extracellular matrix adhesions, which are mediated by cell adhesion receptors, E-cadherin and integrins, are implicated in the process of adhesion of the palatal shelves. Src family kinases (SFK) function downstream of both receptors. In this study, we focused on the role of SFK in the process of palatal adhesion. During palatal adhesion, the expression of SFK mRNA, as well as localization and quantitation of the protein in the activated form, were examined by real-time qPCR and immunofluorescence. Palatal organ cultures were performed to identify the effect of pharmacological inhibition of SFK on palatal adhesion. Activated SFKs were found to be co-localized with adhesion receptors, E-cadherin and integrins in the palatal medial edge epithelium. Src, Fyn and Yes subfamily members were expressed in the palatal tissue. The expression of SFK mRNA and the quantity of the activated form of the protein were upregulated during palatal adhesion. An SFK inhibitor, PP2, blocked palatal adhesion, but another SFK inhibitor, SU6656 was not inhibitory. However, the combination of SU6656 and either of the p38MAPK inhibitors, SB203580 or BIRB0796, showed similar inhibitory effects on palatal adhesion compared to PP2 alone. The p38MAPK inhibitors alone did not alter palatal adhesion. Real-time qPCR revealed that p38MAPK alpha and delta were elevated during palatal adhesion. This study indicates that palatal cell adhesion is dependent on signaling from integrin receptors and E-cadherin through SFK and p38MAPK.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
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".