Qualitatively Monitoring Binding and Expression of the Transcription Factor Sp1 as a Useful Tool to Evaluate the Reliability of Primary Cultured Epithelial Stem Cells in Tissue Reconstruction
Bibliographic record
Abstract
Electrophoretic mobility shift assay and Western blot are simple, efficient, and rapid methods for the study of DNA-protein interactions and expression, respectively. Primary cultures and subcultures of epithelial cells are widely used for the production of tissue-engineered substitutes and are gaining popularity as a model for gene expression studies. The preservation of stem-cells through the culture process is essential to produce high quality substitutes. However as such cells are passaged in culture, they often lose their ability to proliferate, a process likely to be determined by the altered expression of nuclear-located transcription factors such as Sp1, whose expression has been documented to be required for cell adhesion, migration, and differentiation. Our recent studies demonstrated that reconstructed tissues exhibiting poor histological and structural characteristics are also those that were produced with epithelial cells in which expression and DNA binding of Sp1 was reduced in vitro. Therefore, monitoring both the expression and DNA binding of this transcription factor in human skin and corneal epithelial cells might prove a particularly useful tool for selecting which cells are to be used for tissue reconstruction.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".