Regulation of Human Clara Cell 10 kD Protein Expression by Chicken Ovalbumin Upstream Promoter Transcription Factors (COUP-TFs)
Bibliographic record
Abstract
Clara cell 10 kD protein (CC10) is expressed specifically in a portion of nonciliated airway epithelial cells. The molecular mechanisms that determine its high specificity are not clear. Transcription factors implicated in the regulation of CC10 in rodents do not show the same level of cell specificity. We report here that a 3.3 kb human CC10 DNA fragment, containing the 5' flanking region and promoter, directs lacZ reporter expression in a small portion of Clara cells of the airway epithelia of transgenic mice, indicating the requirement of additional regulatory elements for expression. Addition of an intron containing a transcription enhancer from the human cytokeratin 18 gene greatly enhances the level of transgene expression and broadens epithelial specificity. To gain insight into the mechanisms underlying the cell specificity of human CC10 expression, we performed a promoter analysis of the CC10 gene and a yeast one-hybrid screening to identify factors that regulate the promoter. We have found that chicken ovalbumin upstream promoter transcription factors (COUP-TFs) interact with a proximal promoter region and confirmed the interaction by gel-shift assays. Cotransfection analyses with reporter constructs in cultured cells indicated that COUP-TFs inhibit human CC10 expression. These experiments suggest that COUP-TFs may play a pivotal role in cell specificity of the human CC10 gene by inhibiting its expression in nonpermissive cells.
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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".