Contribution of the Transcription Factors Sp1/Sp3 and AP-1 to Clusterin Gene Expression during Corneal Wound Healing of Tissue-Engineered Human Corneas
Bibliographic record
Abstract
In order to reduce the need for donor corneas, understanding of corneal wound healing and development of an entirely tissue-engineered human cornea (hTECs) is of prime importance. In this study, we exploited the hTEC to determine how deep wound healing affects the transcriptional pattern of corneal epithelial cells through microarray analyses. We demonstrated that the gene encoding clusterin (CLU) has its expression dramatically repressed during closure of hTEC wounds. Western blot analyses confirmed a strong reduction in the expression of the clusterin isoforms after corneal damage and suggest that repression of CLU gene expression might be a prerequisite to hTEC wound closure. Transfection with segments from the human CLU gene promoter revealed the presence of three regulatory regions: a basal promoter and two more distal negative regulatory regions. The basal promoter bears DNA binding sites for very potent transcription factors (TFs): Activator Protein-1 (AP-1) and Specificity protein-1 and 3 (Sp1/Sp3). By exploiting electrophoretic mobility shift assays (EMSA), we demonstrated that AP-1 and Sp1/Sp3 have their DNA binding site overlapping with one another in the basal promoter of the CLU gene in hCECs. Interestingly, expression of both these TFs is reduced (at the protein level) during hTEC wound healing, thereby contributing to the extinction of CLU gene expression during that process. The results of this study contribute to a better understanding of the molecular mechanisms accounting for the repression of CLU gene expression during corneal wound healing.
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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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".